diff --git a/whisper_pipeline/HA1.wav b/whisper_pipeline/HA1.wav
new file mode 100644
index 0000000000000000000000000000000000000000..4bdd53010f4a2ae1b148e4b49baababf21180954
--- /dev/null
+++ b/whisper_pipeline/HA1.wav
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:87fd3e947f85de5aeeae4d2f34a4774370541acf92e0f3317686e3c70572aa6a
+size 1242438
diff --git a/whisper_pipeline/api.py b/whisper_pipeline/api.py
new file mode 100644
index 0000000000000000000000000000000000000000..d7ef9cfc09e72fdb316c07ebc32937709e634178
--- /dev/null
+++ b/whisper_pipeline/api.py
@@ -0,0 +1,42 @@
+from fastapi import FastAPI, UploadFile, File
+from fastapi.responses import JSONResponse
+from pathlib import Path
+import os
+from gector import GecBERTModel
+from faster_whisper import WhisperModel, BatchedInferencePipeline
+from transformers.models.whisper.english_normalizer import BasicTextNormalizer
+from text_processing.inverse_normalize import InverseNormalizer
+import shutil
+import uvicorn
+
+# Initialize the FastAPI app
+app = FastAPI()
+
+# Initialize models and normalizer
+current_dir = Path(__file__).parent.as_posix()
+inverse_normalizer = InverseNormalizer('vi')
+whisper_model = WhisperModel("pho_distill_q8", device="auto", compute_type="auto")
+batched_model = BatchedInferencePipeline(model=whisper_model, use_vad_model=True, chunk_length=15)
+gector_model = GecBERTModel(
+ vocab_path=os.path.join(current_dir, "gector/vocabulary"),
+ model_paths=[os.path.join(current_dir, "gector/Model_GECTOR")],
+ split_chunk=True
+)
+normalizer = BasicTextNormalizer()
+
+@app.post("/transcriptions")
+async def transcribe_audio(file: UploadFile = File(...)):
+ # Save the uploaded file temporarily
+ temp_file_path = Path(f"temp_{file.filename}")
+ with open(temp_file_path, "wb") as buffer:
+ shutil.copyfileobj(file.file, buffer)
+ segments, info = batched_model.transcribe(str(temp_file_path), language="vi", batch_size=32)
+ os.remove(temp_file_path)
+ transcriptions = [segment.text for segment in segments]
+ normalized_transcriptions = [inverse_normalizer.inverse_normalize(normalizer(text)) for text in transcriptions]
+ corrected_texts = gector_model(normalized_transcriptions)
+ return JSONResponse({"text": ' '.join(corrected_texts)})
+
+
+if __name__ == "__main__":
+ uvicorn.run("api:app", host="0.0.0.0", port=8000, reload=True)
\ No newline at end of file
diff --git a/whisper_pipeline/check.py b/whisper_pipeline/check.py
new file mode 100644
index 0000000000000000000000000000000000000000..f66823958bfcf03baa7514c1eff860ff79a6e41e
--- /dev/null
+++ b/whisper_pipeline/check.py
@@ -0,0 +1,6 @@
+from text_processing.inverse_normalize import InverseNormalizer
+import time
+normalizer = InverseNormalizer('vi')
+start = time.time()
+print(normalizer.inverse_normalize("mười hai ki lô gram"))
+print(time.time()- start)
\ No newline at end of file
diff --git a/whisper_pipeline/dockerfile b/whisper_pipeline/dockerfile
new file mode 100644
index 0000000000000000000000000000000000000000..a5b9934f7127f47d21269ce289becb21e9c29143
--- /dev/null
+++ b/whisper_pipeline/dockerfile
@@ -0,0 +1,56 @@
+# Use nvidia/cuda as base image with Python
+FROM nvidia/cuda:12.2.2-cudnn8-runtime-ubuntu22.04
+
+# Use args
+ARG USE_CUDA
+ARG USE_CUDA_VER
+
+## Basis ##
+ENV ENV=prod \
+ PORT=8000 \
+ USE_CUDA_DOCKER=${USE_CUDA} \
+ USE_CUDA_DOCKER_VER=${USE_CUDA_VER}
+
+# Install GCC and build tools
+RUN apt-get update && \
+ apt-get install -y gcc build-essential curl git pkg-config libicu-dev && \
+ apt-get clean && \
+ rm -rf /var/lib/apt/lists/*
+
+RUN apt-get update -y && apt-get install -y python3-pip
+
+
+
+# Set working directory
+WORKDIR /app
+
+# Copy the requirements.txt file and install dependencies
+COPY ./requirements.txt .
+
+# Install dependencies
+RUN pip install uv && \
+ if [ "$USE_CUDA" = "true" ]; then \
+ pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/$USE_CUDA_DOCKER_VER --no-cache-dir; \
+ else \
+ pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu --no-cache-dir; \
+ fi
+
+# Copy faster-whisper-main folder and install
+COPY ./faster-whisper-main ./faster-whisper-main
+RUN pip install ./faster-whisper-main --no-cache-dir
+
+RUN pip install --no-cache-dir -r requirements.txt
+
+
+# Copy the remaining application code
+COPY . .
+
+# Expose the API port
+EXPOSE 8000
+
+# Set the environment variables
+ENV HOST="0.0.0.0"
+ENV PORT="8000"
+
+# Set entrypoint to run the FastAPI server
+ENTRYPOINT ["bash", "start.sh"]
diff --git a/whisper_pipeline/faster-whisper-main/.github/workflows/ci.yml b/whisper_pipeline/faster-whisper-main/.github/workflows/ci.yml
new file mode 100644
index 0000000000000000000000000000000000000000..407661fd95398cffafac3e6f311729ddedec4766
--- /dev/null
+++ b/whisper_pipeline/faster-whisper-main/.github/workflows/ci.yml
@@ -0,0 +1,90 @@
+name: CI
+
+on:
+ push:
+ branches:
+ - master
+ tags:
+ - v*
+ pull_request:
+ branches:
+ - master
+
+jobs:
+ check-code-format:
+ runs-on: ubuntu-latest
+
+ steps:
+ - uses: actions/checkout@v3
+
+ - name: Set up Python 3.8
+ uses: actions/setup-python@v4
+ with:
+ python-version: 3.8
+
+ - name: Install module
+ run: |
+ pip install wheel
+ pip install -e .[dev]
+
+ - name: Check code format with Black
+ run: |
+ black --check .
+
+ - name: Check imports order with isort
+ run: |
+ isort --check-only .
+
+ - name: Check code style with Flake8
+ if: ${{ always() }}
+ run: |
+ flake8 .
+
+
+ run-tests:
+ runs-on: ubuntu-latest
+
+ steps:
+ - uses: actions/checkout@v3
+
+ - name: Set up Python 3.8
+ uses: actions/setup-python@v4
+ with:
+ python-version: 3.8
+
+ - name: Install module
+ run: |
+ pip install wheel
+ pip install -e .[dev]
+
+ - name: Run pytest
+ run: |
+ pytest -v tests/
+
+
+ build-and-push-package:
+ runs-on: ubuntu-latest
+ needs: [check-code-format, run-tests]
+
+ steps:
+ - uses: actions/checkout@v3
+
+ - name: Set up Python 3.8
+ uses: actions/setup-python@v4
+ with:
+ python-version: 3.8
+
+ - name: Install dependencies
+ run: |
+ pip install wheel
+
+ - name: Build package
+ run: |
+ python3 setup.py sdist bdist_wheel
+
+ - name: Push package on PyPI
+ if: github.event_name == 'push' && startsWith(github.ref, 'refs/tags')
+ uses: pypa/gh-action-pypi-publish@release/v1
+ with:
+ user: __token__
+ password: ${{ secrets.PYPI_API_TOKEN }}
diff --git a/whisper_pipeline/faster-whisper-main/.gitignore b/whisper_pipeline/faster-whisper-main/.gitignore
new file mode 100644
index 0000000000000000000000000000000000000000..8f634c289f61452594236f753e28066cf0ef2013
--- /dev/null
+++ b/whisper_pipeline/faster-whisper-main/.gitignore
@@ -0,0 +1,15 @@
+# Byte-compiled / Optimized / DLL Files
+*.pyc
+*.pyo
+*.pyd
+__pycache__/
+
+# Distribution / Packaging
+venv/
+
+# Unit Test
+.pytest_cache/
+
+# Ignore IDE, Editor Files
+.idea/
+.vscode/
diff --git a/whisper_pipeline/faster-whisper-main/CONTRIBUTING.md b/whisper_pipeline/faster-whisper-main/CONTRIBUTING.md
new file mode 100644
index 0000000000000000000000000000000000000000..8d6a9c244689ded701cad9aab99a234096008afc
--- /dev/null
+++ b/whisper_pipeline/faster-whisper-main/CONTRIBUTING.md
@@ -0,0 +1,31 @@
+# Contributing to faster-whisper
+
+Contributions are welcome! Here are some pointers to help you install the library for development and validate your changes before submitting a pull request.
+
+## Install the library for development
+
+We recommend installing the module in editable mode with the `dev` extra requirements:
+
+```bash
+git clone https://github.com/SYSTRAN/faster-whisper.git
+cd faster-whisper/
+pip install -e .[dev]
+```
+
+## Validate the changes before creating a pull request
+
+1. Make sure the existing tests are still passing (and consider adding new tests as well!):
+
+```bash
+pytest tests/
+```
+
+2. Reformat and validate the code with the following tools:
+
+```bash
+black .
+isort .
+flake8 .
+```
+
+These steps are also run automatically in the CI when you open the pull request.
diff --git a/whisper_pipeline/faster-whisper-main/LICENSE b/whisper_pipeline/faster-whisper-main/LICENSE
new file mode 100644
index 0000000000000000000000000000000000000000..2d92330dc294fea86caf785fa626d22917850141
--- /dev/null
+++ b/whisper_pipeline/faster-whisper-main/LICENSE
@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2023 SYSTRAN
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
diff --git a/whisper_pipeline/faster-whisper-main/MANIFEST.in b/whisper_pipeline/faster-whisper-main/MANIFEST.in
new file mode 100644
index 0000000000000000000000000000000000000000..8a103dd64eb1866fc9fce36e0e9c7d84e482f98b
--- /dev/null
+++ b/whisper_pipeline/faster-whisper-main/MANIFEST.in
@@ -0,0 +1,4 @@
+include faster_whisper/assets/silero_vad.onnx
+include requirements.txt
+include requirements.conversion.txt
+include faster_whisper/assets/pyannote_vad_model.bin
diff --git a/whisper_pipeline/faster-whisper-main/README.md b/whisper_pipeline/faster-whisper-main/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..f7d54ee45467a8fdf06d9e5fa77ab3d7c2184472
--- /dev/null
+++ b/whisper_pipeline/faster-whisper-main/README.md
@@ -0,0 +1,319 @@
+[](https://github.com/SYSTRAN/faster-whisper/actions?query=workflow%3ACI) [](https://badge.fury.io/py/faster-whisper)
+
+# Faster Whisper transcription with CTranslate2
+
+**faster-whisper** is a reimplementation of OpenAI's Whisper model using [CTranslate2](https://github.com/OpenNMT/CTranslate2/), which is a fast inference engine for Transformer models.
+
+This implementation is up to 4 times faster than [openai/whisper](https://github.com/openai/whisper) for the same accuracy while using less memory. The efficiency can be further improved with 8-bit quantization on both CPU and GPU.
+
+## Benchmark
+
+### Whisper
+
+For reference, here's the time and memory usage that are required to transcribe [**13 minutes**](https://www.youtube.com/watch?v=0u7tTptBo9I) of audio using different implementations:
+
+* [openai/whisper](https://github.com/openai/whisper)@[6dea21fd](https://github.com/openai/whisper/commit/6dea21fd7f7253bfe450f1e2512a0fe47ee2d258)
+* [whisper.cpp](https://github.com/ggerganov/whisper.cpp)@[3b010f9](https://github.com/ggerganov/whisper.cpp/commit/3b010f9bed9a6068609e9faf52383aea792b0362)
+* [faster-whisper](https://github.com/SYSTRAN/faster-whisper)@[cce6b53e](https://github.com/SYSTRAN/faster-whisper/commit/cce6b53e4554f71172dad188c45f10fb100f6e3e)
+
+### Large-v2 model on GPU
+
+| Implementation | Precision | Beam size | Time | Max. GPU memory | Max. CPU memory |
+| --- | --- | --- | --- | --- | --- |
+| openai/whisper | fp16 | 5 | 4m30s | 11325MB | 9439MB |
+| faster-whisper | fp16 | 5 | 54s | 4755MB | 3244MB |
+| faster-whisper | int8 | 5 | 59s | 3091MB | 3117MB |
+
+*Executed with CUDA 11.7.1 on a NVIDIA Tesla V100S.*
+
+### Small model on CPU
+
+| Implementation | Precision | Beam size | Time | Max. memory |
+| --- | --- | --- | --- | --- |
+| openai/whisper | fp32 | 5 | 10m31s | 3101MB |
+| whisper.cpp | fp32 | 5 | 17m42s | 1581MB |
+| whisper.cpp | fp16 | 5 | 12m39s | 873MB |
+| faster-whisper | fp32 | 5 | 2m44s | 1675MB |
+| faster-whisper | int8 | 5 | 2m04s | 995MB |
+
+*Executed with 8 threads on a Intel(R) Xeon(R) Gold 6226R.*
+
+
+### Distil-whisper
+
+| Implementation | Precision | Beam size | Time | Gigaspeech WER |
+| --- | --- | --- | --- | --- |
+| distil-whisper/distil-large-v2 | fp16 | 4 |- | 10.36 |
+| [faster-distil-large-v2](https://huggingface.co/Systran/faster-distil-whisper-large-v2) | fp16 | 5 | - | 10.28 |
+| distil-whisper/distil-medium.en | fp16 | 4 | - | 11.21 |
+| [faster-distil-medium.en](https://huggingface.co/Systran/faster-distil-whisper-medium.en) | fp16 | 5 | - | 11.21 |
+
+*Executed with CUDA 11.4 on a NVIDIA 3090.*
+
+
+testing details (click to expand)
+
+For `distil-whisper/distil-large-v2`, the WER is tested with code sample from [link](https://huggingface.co/distil-whisper/distil-large-v2#evaluation). for `faster-distil-whisper`, the WER is tested with setting:
+```python
+from faster_whisper import WhisperModel
+
+model_size = "distil-large-v2"
+# model_size = "distil-medium.en"
+# Run on GPU with FP16
+model = WhisperModel(model_size, device="cuda", compute_type="float16")
+segments, info = model.transcribe("audio.mp3", beam_size=5, language="en")
+```
+
+
+## Requirements
+
+* Python 3.8 or greater
+
+
+### GPU
+
+GPU execution requires the following NVIDIA libraries to be installed:
+
+* [cuBLAS for CUDA 12](https://developer.nvidia.com/cublas)
+* [cuDNN 8 for CUDA 12](https://developer.nvidia.com/cudnn)
+
+**Note**: Latest versions of `ctranslate2` support CUDA 12 only. For CUDA 11, the current workaround is downgrading to the `3.24.0` version of `ctranslate2` (This can be done with `pip install --force-reinstall ctranslate2==3.24.0` or specifying the version in a `requirements.txt`).
+
+There are multiple ways to install the NVIDIA libraries mentioned above. The recommended way is described in the official NVIDIA documentation, but we also suggest other installation methods below.
+
+
+Other installation methods (click to expand)
+
+
+**Note:** For all these methods below, keep in mind the above note regarding CUDA versions. Depending on your setup, you may need to install the _CUDA 11_ versions of libraries that correspond to the CUDA 12 libraries listed in the instructions below.
+
+#### Use Docker
+
+The libraries (cuBLAS, cuDNN) are installed in these official NVIDIA CUDA Docker images: `nvidia/cuda:12.0.0-runtime-ubuntu20.04` or `nvidia/cuda:12.0.0-runtime-ubuntu22.04`.
+
+#### Install with `pip` (Linux only)
+
+On Linux these libraries can be installed with `pip`. Note that `LD_LIBRARY_PATH` must be set before launching Python.
+
+```bash
+pip install nvidia-cublas-cu12 nvidia-cudnn-cu12
+
+export LD_LIBRARY_PATH=`python3 -c 'import os; import nvidia.cublas.lib; import nvidia.cudnn.lib; print(os.path.dirname(nvidia.cublas.lib.__file__) + ":" + os.path.dirname(nvidia.cudnn.lib.__file__))'`
+```
+
+**Note**: Version 9+ of `nvidia-cudnn-cu12` appears to cause issues due its reliance on cuDNN 9 (Faster-Whisper does not currently support cuDNN 9). Ensure your version of the Python package is for cuDNN 8.
+
+#### Download the libraries from Purfview's repository (Windows & Linux)
+
+Purfview's [whisper-standalone-win](https://github.com/Purfview/whisper-standalone-win) provides the required NVIDIA libraries for Windows & Linux in a [single archive](https://github.com/Purfview/whisper-standalone-win/releases/tag/libs). Decompress the archive and place the libraries in a directory included in the `PATH`.
+
+
+
+## Installation
+
+The module can be installed from [PyPI](https://pypi.org/project/faster-whisper/):
+
+```bash
+pip install faster-whisper
+```
+
+
+Other installation methods (click to expand)
+
+### Install the master branch
+
+```bash
+pip install --force-reinstall "faster-whisper @ https://github.com/SYSTRAN/faster-whisper/archive/refs/heads/master.tar.gz"
+```
+
+### Install a specific commit
+
+```bash
+pip install --force-reinstall "faster-whisper @ https://github.com/SYSTRAN/faster-whisper/archive/a4f1cc8f11433e454c3934442b5e1a4ed5e865c3.tar.gz"
+```
+
+
+
+## Usage
+
+### Faster-whisper
+
+```python
+from faster_whisper import WhisperModel
+
+model_size = "large-v3"
+
+# Run on GPU with FP16
+model = WhisperModel(model_size, device="cuda", compute_type="float16")
+
+# or run on GPU with INT8
+# model = WhisperModel(model_size, device="cuda", compute_type="int8_float16")
+# or run on CPU with INT8
+# model = WhisperModel(model_size, device="cpu", compute_type="int8")
+
+segments, info = model.transcribe("audio.mp3", beam_size=5)
+
+print("Detected language '%s' with probability %f" % (info.language, info.language_probability))
+
+for segment in segments:
+ print("[%.2fs -> %.2fs] %s" % (segment.start, segment.end, segment.text))
+```
+
+**Warning:** `segments` is a *generator* so the transcription only starts when you iterate over it. The transcription can be run to completion by gathering the segments in a list or a `for` loop:
+
+```python
+segments, _ = model.transcribe("audio.mp3")
+segments = list(segments) # The transcription will actually run here.
+```
+
+### multi-segment language detection
+
+To directly use the model for improved language detection, the following code snippet can be used:
+
+```python
+from faster_whisper import WhisperModel
+model = WhisperModel("medium", device="cuda", compute_type="float16")
+language_info = model.detect_language_multi_segment("audio.mp3")
+```
+
+### Batched faster-whisper
+
+
+The batched version of faster-whisper is inspired by [whisper-x](https://github.com/m-bain/whisperX) licensed under the BSD-2 Clause license and integrates its VAD model to this library. We modify this implementation and also replaced the feature extraction with a faster torch-based implementation. Batched version improves the speed upto 10-12x compared to openAI implementation and 3-4x compared to the sequential faster_whisper version. It works by transcribing semantically meaningful audio chunks as batches leading to faster inference.
+
+The following code snippet illustrates how to run inference with batched version on an example audio file. Please also refer to the test scripts of batched faster whisper.
+
+```python
+from faster_whisper import WhisperModel, BatchedInferencePipeline
+
+model = WhisperModel("medium", device="cuda", compute_type="float16")
+batched_model = BatchedInferencePipeline(model=model)
+segments, info = batched_model.transcribe("audio.mp3", batch_size=16)
+
+for segment in segments:
+ print("[%.2fs -> %.2fs] %s" % (segment.start, segment.end, segment.text))
+```
+
+### Faster Distil-Whisper
+
+The Distil-Whisper checkpoints are compatible with the Faster-Whisper package. In particular, the latest [distil-large-v3](https://huggingface.co/distil-whisper/distil-large-v3)
+checkpoint is intrinsically designed to work with the Faster-Whisper transcription algorithm. The following code snippet
+demonstrates how to run inference with distil-large-v3 on a specified audio file:
+
+```python
+from faster_whisper import WhisperModel
+
+model_size = "distil-large-v3"
+
+model = WhisperModel(model_size, device="cuda", compute_type="float16")
+segments, info = model.transcribe("audio.mp3", beam_size=5, language="en", condition_on_previous_text=False)
+
+for segment in segments:
+ print("[%.2fs -> %.2fs] %s" % (segment.start, segment.end, segment.text))
+```
+
+For more information about the distil-large-v3 model, refer to the original [model card](https://huggingface.co/distil-whisper/distil-large-v3).
+
+### Word-level timestamps
+
+```python
+segments, _ = model.transcribe("audio.mp3", word_timestamps=True)
+
+for segment in segments:
+ for word in segment.words:
+ print("[%.2fs -> %.2fs] %s" % (word.start, word.end, word.word))
+```
+
+### VAD filter
+
+The library integrates the [Silero VAD](https://github.com/snakers4/silero-vad) model to filter out parts of the audio without speech:
+
+```python
+segments, _ = model.transcribe("audio.mp3", vad_filter=True)
+```
+
+The default behavior is conservative and only removes silence longer than 2 seconds. See the available VAD parameters and default values in the [source code](https://github.com/SYSTRAN/faster-whisper/blob/master/faster_whisper/vad.py). They can be customized with the dictionary argument `vad_parameters`:
+
+```python
+segments, _ = model.transcribe(
+ "audio.mp3",
+ vad_filter=True,
+ vad_parameters=dict(min_silence_duration_ms=500),
+)
+```
+
+### Logging
+
+The library logging level can be configured like this:
+
+```python
+import logging
+
+logging.basicConfig()
+logging.getLogger("faster_whisper").setLevel(logging.DEBUG)
+```
+
+### Going further
+
+See more model and transcription options in the [`WhisperModel`](https://github.com/SYSTRAN/faster-whisper/blob/master/faster_whisper/transcribe.py) class implementation.
+
+## Community integrations
+
+Here is a non exhaustive list of open-source projects using faster-whisper. Feel free to add your project to the list!
+
+
+* [faster-whisper-server](https://github.com/fedirz/faster-whisper-server) is an OpenAI compatible server using `faster-whisper`. It's easily deployable with Docker, works with OpenAI SDKs/CLI, supports streaming, and live transcription.
+* [WhisperX](https://github.com/m-bain/whisperX) is an award-winning Python library that offers speaker diarization and accurate word-level timestamps using wav2vec2 alignment
+* [whisper-ctranslate2](https://github.com/Softcatala/whisper-ctranslate2) is a command line client based on faster-whisper and compatible with the original client from openai/whisper.
+* [whisper-diarize](https://github.com/MahmoudAshraf97/whisper-diarization) is a speaker diarization tool that is based on faster-whisper and NVIDIA NeMo.
+* [whisper-standalone-win](https://github.com/Purfview/whisper-standalone-win) Standalone CLI executables of faster-whisper for Windows, Linux & macOS.
+* [asr-sd-pipeline](https://github.com/hedrergudene/asr-sd-pipeline) provides a scalable, modular, end to end multi-speaker speech to text solution implemented using AzureML pipelines.
+* [Open-Lyrics](https://github.com/zh-plus/Open-Lyrics) is a Python library that transcribes voice files using faster-whisper, and translates/polishes the resulting text into `.lrc` files in the desired language using OpenAI-GPT.
+* [wscribe](https://github.com/geekodour/wscribe) is a flexible transcript generation tool supporting faster-whisper, it can export word level transcript and the exported transcript then can be edited with [wscribe-editor](https://github.com/geekodour/wscribe-editor)
+* [aTrain](https://github.com/BANDAS-Center/aTrain) is a graphical user interface implementation of faster-whisper developed at the BANDAS-Center at the University of Graz for transcription and diarization in Windows ([Windows Store App](https://apps.microsoft.com/detail/atrain/9N15Q44SZNS2)) and Linux.
+* [Whisper-Streaming](https://github.com/ufal/whisper_streaming) implements real-time mode for offline Whisper-like speech-to-text models with faster-whisper as the most recommended back-end. It implements a streaming policy with self-adaptive latency based on the actual source complexity, and demonstrates the state of the art.
+* [WhisperLive](https://github.com/collabora/WhisperLive) is a nearly-live implementation of OpenAI's Whisper which uses faster-whisper as the backend to transcribe audio in real-time.
+* [Faster-Whisper-Transcriber](https://github.com/BBC-Esq/ctranslate2-faster-whisper-transcriber) is a simple but reliable voice transcriber that provides a user-friendly interface.
+
+## Model conversion
+
+When loading a model from its size such as `WhisperModel("large-v3")`, the corresponding CTranslate2 model is automatically downloaded from the [Hugging Face Hub](https://huggingface.co/Systran).
+
+We also provide a script to convert any Whisper models compatible with the Transformers library. They could be the original OpenAI models or user fine-tuned models.
+
+For example the command below converts the [original "large-v3" Whisper model](https://huggingface.co/openai/whisper-large-v3) and saves the weights in FP16:
+
+```bash
+pip install transformers[torch]>=4.23
+
+ct2-transformers-converter --model openai/whisper-large-v3 --output_dir whisper-large-v3-ct2
+--copy_files tokenizer.json preprocessor_config.json --quantization float16
+```
+
+* The option `--model` accepts a model name on the Hub or a path to a model directory.
+* If the option `--copy_files tokenizer.json` is not used, the tokenizer configuration is automatically downloaded when the model is loaded later.
+
+Models can also be converted from the code. See the [conversion API](https://opennmt.net/CTranslate2/python/ctranslate2.converters.TransformersConverter.html).
+
+### Load a converted model
+
+1. Directly load the model from a local directory:
+```python
+model = faster_whisper.WhisperModel("whisper-large-v3-ct2")
+```
+
+2. [Upload your model to the Hugging Face Hub](https://huggingface.co/docs/transformers/model_sharing#upload-with-the-web-interface) and load it from its name:
+```python
+model = faster_whisper.WhisperModel("username/whisper-large-v3-ct2")
+```
+
+## Comparing performance against other implementations
+
+If you are comparing the performance against other Whisper implementations, you should make sure to run the comparison with similar settings. In particular:
+
+* Verify that the same transcription options are used, especially the same beam size. For example in openai/whisper, `model.transcribe` uses a default beam size of 1 but here we use a default beam size of 5.
+* When running on CPU, make sure to set the same number of threads. Many frameworks will read the environment variable `OMP_NUM_THREADS`, which can be set when running your script:
+
+```bash
+OMP_NUM_THREADS=4 python3 my_script.py
+```
diff --git a/whisper_pipeline/faster-whisper-main/benchmark/benchmark.m4a b/whisper_pipeline/faster-whisper-main/benchmark/benchmark.m4a
new file mode 100644
index 0000000000000000000000000000000000000000..9fc8da8c60a0dc0594b3e368b2bffdcbb02edf9c
--- /dev/null
+++ b/whisper_pipeline/faster-whisper-main/benchmark/benchmark.m4a
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5dedec4f587a7940cfab93ff36e5014f155f80e10b7935f67d9eee8761663c34
+size 12935433
diff --git a/whisper_pipeline/faster-whisper-main/benchmark/memory_benchmark.py b/whisper_pipeline/faster-whisper-main/benchmark/memory_benchmark.py
new file mode 100644
index 0000000000000000000000000000000000000000..1fbdfbdf379b4a2b7c71fb192e471db01b37d579
--- /dev/null
+++ b/whisper_pipeline/faster-whisper-main/benchmark/memory_benchmark.py
@@ -0,0 +1,94 @@
+import argparse
+import time
+
+from typing import Callable
+
+import py3nvml.py3nvml as nvml
+
+from memory_profiler import memory_usage
+from utils import MyThread, get_logger, inference
+
+logger = get_logger("faster-whisper")
+parser = argparse.ArgumentParser(description="Memory benchmark")
+parser.add_argument(
+ "--gpu_memory", action="store_true", help="Measure GPU memory usage"
+)
+parser.add_argument("--device-index", type=int, default=0, help="GPU device index")
+parser.add_argument(
+ "--interval",
+ type=float,
+ default=0.5,
+ help="Interval at which measurements are collected",
+)
+args = parser.parse_args()
+device_idx = args.device_index
+interval = args.interval
+
+
+def measure_memory(func: Callable[[], None]):
+ if args.gpu_memory:
+ logger.info(
+ "Measuring maximum GPU memory usage on GPU device."
+ " Make sure to not have additional processes running on the same GPU."
+ )
+ # init nvml
+ nvml.nvmlInit()
+ handle = nvml.nvmlDeviceGetHandleByIndex(device_idx)
+ gpu_name = nvml.nvmlDeviceGetName(handle)
+ gpu_memory_limit = nvml.nvmlDeviceGetMemoryInfo(handle).total >> 20
+ gpu_power_limit = nvml.nvmlDeviceGetPowerManagementLimit(handle) / 1000.0
+ info = {"gpu_memory_usage": [], "gpu_power_usage": []}
+
+ def _get_gpu_info():
+ while True:
+ info["gpu_memory_usage"].append(
+ nvml.nvmlDeviceGetMemoryInfo(handle).used >> 20
+ )
+ info["gpu_power_usage"].append(
+ nvml.nvmlDeviceGetPowerUsage(handle) / 1000
+ )
+ time.sleep(interval)
+
+ if stop:
+ break
+
+ return info
+
+ stop = False
+ thread = MyThread(_get_gpu_info, params=())
+ thread.start()
+ func()
+ stop = True
+ thread.join()
+ result = thread.get_result()
+
+ # shutdown nvml
+ nvml.nvmlShutdown()
+ max_memory_usage = max(result["gpu_memory_usage"])
+ max_power_usage = max(result["gpu_power_usage"])
+ print("GPU name: %s" % gpu_name)
+ print("GPU device index: %s" % device_idx)
+ print(
+ "Maximum GPU memory usage: %dMiB / %dMiB (%.2f%%)"
+ % (
+ max_memory_usage,
+ gpu_memory_limit,
+ (max_memory_usage / gpu_memory_limit) * 100,
+ )
+ )
+ print(
+ "Maximum GPU power usage: %dW / %dW (%.2f%%)"
+ % (
+ max_power_usage,
+ gpu_power_limit,
+ (max_power_usage / gpu_power_limit) * 100,
+ )
+ )
+ else:
+ logger.info("Measuring maximum increase of memory usage.")
+ max_usage = memory_usage(func, max_usage=True, interval=interval)
+ print("Maximum increase of RAM memory usage: %d MiB" % max_usage)
+
+
+if __name__ == "__main__":
+ measure_memory(inference)
diff --git a/whisper_pipeline/faster-whisper-main/benchmark/normalizer.json b/whisper_pipeline/faster-whisper-main/benchmark/normalizer.json
new file mode 100644
index 0000000000000000000000000000000000000000..dd6ae819ad738ac1a546e9f9282ef325c33b9ea0
--- /dev/null
+++ b/whisper_pipeline/faster-whisper-main/benchmark/normalizer.json
@@ -0,0 +1,1742 @@
+{
+ "accessorise": "accessorize",
+ "accessorised": "accessorized",
+ "accessorises": "accessorizes",
+ "accessorising": "accessorizing",
+ "acclimatisation": "acclimatization",
+ "acclimatise": "acclimatize",
+ "acclimatised": "acclimatized",
+ "acclimatises": "acclimatizes",
+ "acclimatising": "acclimatizing",
+ "accoutrements": "accouterments",
+ "aeon": "eon",
+ "aeons": "eons",
+ "aerogramme": "aerogram",
+ "aerogrammes": "aerograms",
+ "aeroplane": "airplane",
+ "aeroplanes": "airplanes",
+ "aesthete": "esthete",
+ "aesthetes": "esthetes",
+ "aesthetic": "esthetic",
+ "aesthetically": "esthetically",
+ "aesthetics": "esthetics",
+ "aetiology": "etiology",
+ "ageing": "aging",
+ "aggrandisement": "aggrandizement",
+ "agonise": "agonize",
+ "agonised": "agonized",
+ "agonises": "agonizes",
+ "agonising": "agonizing",
+ "agonisingly": "agonizingly",
+ "almanack": "almanac",
+ "almanacks": "almanacs",
+ "aluminium": "aluminum",
+ "amortisable": "amortizable",
+ "amortisation": "amortization",
+ "amortisations": "amortizations",
+ "amortise": "amortize",
+ "amortised": "amortized",
+ "amortises": "amortizes",
+ "amortising": "amortizing",
+ "amphitheatre": "amphitheater",
+ "amphitheatres": "amphitheaters",
+ "anaemia": "anemia",
+ "anaemic": "anemic",
+ "anaesthesia": "anesthesia",
+ "anaesthetic": "anesthetic",
+ "anaesthetics": "anesthetics",
+ "anaesthetise": "anesthetize",
+ "anaesthetised": "anesthetized",
+ "anaesthetises": "anesthetizes",
+ "anaesthetising": "anesthetizing",
+ "anaesthetist": "anesthetist",
+ "anaesthetists": "anesthetists",
+ "anaesthetize": "anesthetize",
+ "anaesthetized": "anesthetized",
+ "anaesthetizes": "anesthetizes",
+ "anaesthetizing": "anesthetizing",
+ "analogue": "analog",
+ "analogues": "analogs",
+ "analyse": "analyze",
+ "analysed": "analyzed",
+ "analyses": "analyzes",
+ "analysing": "analyzing",
+ "anglicise": "anglicize",
+ "anglicised": "anglicized",
+ "anglicises": "anglicizes",
+ "anglicising": "anglicizing",
+ "annualised": "annualized",
+ "antagonise": "antagonize",
+ "antagonised": "antagonized",
+ "antagonises": "antagonizes",
+ "antagonising": "antagonizing",
+ "apologise": "apologize",
+ "apologised": "apologized",
+ "apologises": "apologizes",
+ "apologising": "apologizing",
+ "appal": "appall",
+ "appals": "appalls",
+ "appetiser": "appetizer",
+ "appetisers": "appetizers",
+ "appetising": "appetizing",
+ "appetisingly": "appetizingly",
+ "arbour": "arbor",
+ "arbours": "arbors",
+ "archaeologically": "archeologically",
+ "archaeologist": "archeologist",
+ "archaeologists": "archeologists",
+ "archaeology": "archeology",
+ "archeological": "archaeological",
+ "ardour": "ardor",
+ "armour": "armor",
+ "armoured": "armored",
+ "armourer": "armorer",
+ "armourers": "armorers",
+ "armouries": "armories",
+ "armoury": "armory",
+ "artefact": "artifact",
+ "artefacts": "artifacts",
+ "authorise": "authorize",
+ "authorised": "authorized",
+ "authorises": "authorizes",
+ "authorising": "authorizing",
+ "axe": "ax",
+ "backpedalled": "backpedaled",
+ "backpedalling": "backpedaling",
+ "bannister": "banister",
+ "bannisters": "banisters",
+ "baptise": "baptize",
+ "baptised": "baptized",
+ "baptises": "baptizes",
+ "baptising": "baptizing",
+ "bastardise": "bastardize",
+ "bastardised": "bastardized",
+ "bastardises": "bastardizes",
+ "bastardising": "bastardizing",
+ "battleax": "battleaxe",
+ "baulk": "balk",
+ "baulked": "balked",
+ "baulking": "balking",
+ "baulks": "balks",
+ "bedevilled": "bedeviled",
+ "bedevilling": "bedeviling",
+ "behaviour": "behavior",
+ "behavioural": "behavioral",
+ "behaviourism": "behaviorism",
+ "behaviourist": "behaviorist",
+ "behaviourists": "behaviorists",
+ "behaviours": "behaviors",
+ "behove": "behoove",
+ "behoved": "behooved",
+ "behoves": "behooves",
+ "bejewelled": "bejeweled",
+ "belabour": "belabor",
+ "belaboured": "belabored",
+ "belabouring": "belaboring",
+ "belabours": "belabors",
+ "bevelled": "beveled",
+ "bevvies": "bevies",
+ "bevvy": "bevy",
+ "biassed": "biased",
+ "biassing": "biasing",
+ "bingeing": "binging",
+ "bougainvillaea": "bougainvillea",
+ "bougainvillaeas": "bougainvilleas",
+ "bowdlerise": "bowdlerize",
+ "bowdlerised": "bowdlerized",
+ "bowdlerises": "bowdlerizes",
+ "bowdlerising": "bowdlerizing",
+ "breathalyse": "breathalyze",
+ "breathalysed": "breathalyzed",
+ "breathalyser": "breathalyzer",
+ "breathalysers": "breathalyzers",
+ "breathalyses": "breathalyzes",
+ "breathalysing": "breathalyzing",
+ "brutalise": "brutalize",
+ "brutalised": "brutalized",
+ "brutalises": "brutalizes",
+ "brutalising": "brutalizing",
+ "busses": "buses",
+ "bussing": "busing",
+ "caesarean": "cesarean",
+ "caesareans": "cesareans",
+ "calibre": "caliber",
+ "calibres": "calibers",
+ "calliper": "caliper",
+ "callipers": "calipers",
+ "callisthenics": "calisthenics",
+ "canalise": "canalize",
+ "canalised": "canalized",
+ "canalises": "canalizes",
+ "canalising": "canalizing",
+ "cancelation": "cancellation",
+ "cancelations": "cancellations",
+ "cancelled": "canceled",
+ "cancelling": "canceling",
+ "candour": "candor",
+ "cannibalise": "cannibalize",
+ "cannibalised": "cannibalized",
+ "cannibalises": "cannibalizes",
+ "cannibalising": "cannibalizing",
+ "canonise": "canonize",
+ "canonised": "canonized",
+ "canonises": "canonizes",
+ "canonising": "canonizing",
+ "capitalise": "capitalize",
+ "capitalised": "capitalized",
+ "capitalises": "capitalizes",
+ "capitalising": "capitalizing",
+ "caramelise": "caramelize",
+ "caramelised": "caramelized",
+ "caramelises": "caramelizes",
+ "caramelising": "caramelizing",
+ "carbonise": "carbonize",
+ "carbonised": "carbonized",
+ "carbonises": "carbonizes",
+ "carbonising": "carbonizing",
+ "carolled": "caroled",
+ "carolling": "caroling",
+ "catalogue": "catalog",
+ "catalogued": "cataloged",
+ "catalogues": "catalogs",
+ "cataloguing": "cataloging",
+ "catalyse": "catalyze",
+ "catalysed": "catalyzed",
+ "catalyses": "catalyzes",
+ "catalysing": "catalyzing",
+ "categorise": "categorize",
+ "categorised": "categorized",
+ "categorises": "categorizes",
+ "categorising": "categorizing",
+ "cauterise": "cauterize",
+ "cauterised": "cauterized",
+ "cauterises": "cauterizes",
+ "cauterising": "cauterizing",
+ "cavilled": "caviled",
+ "cavilling": "caviling",
+ "centigramme": "centigram",
+ "centigrammes": "centigrams",
+ "centilitre": "centiliter",
+ "centilitres": "centiliters",
+ "centimetre": "centimeter",
+ "centimetres": "centimeters",
+ "centralise": "centralize",
+ "centralised": "centralized",
+ "centralises": "centralizes",
+ "centralising": "centralizing",
+ "centre": "center",
+ "centred": "centered",
+ "centrefold": "centerfold",
+ "centrefolds": "centerfolds",
+ "centrepiece": "centerpiece",
+ "centrepieces": "centerpieces",
+ "centres": "centers",
+ "channelled": "channeled",
+ "channelling": "channeling",
+ "characterise": "characterize",
+ "characterised": "characterized",
+ "characterises": "characterizes",
+ "characterising": "characterizing",
+ "cheque": "check",
+ "chequebook": "checkbook",
+ "chequebooks": "checkbooks",
+ "chequered": "checkered",
+ "cheques": "checks",
+ "chilli": "chili",
+ "chimaera": "chimera",
+ "chimaeras": "chimeras",
+ "chiselled": "chiseled",
+ "chiselling": "chiseling",
+ "circularise": "circularize",
+ "circularised": "circularized",
+ "circularises": "circularizes",
+ "circularising": "circularizing",
+ "civilise": "civilize",
+ "civilised": "civilized",
+ "civilises": "civilizes",
+ "civilising": "civilizing",
+ "clamour": "clamor",
+ "clamoured": "clamored",
+ "clamouring": "clamoring",
+ "clamours": "clamors",
+ "clangour": "clangor",
+ "clarinettist": "clarinetist",
+ "clarinettists": "clarinetists",
+ "collectivise": "collectivize",
+ "collectivised": "collectivized",
+ "collectivises": "collectivizes",
+ "collectivising": "collectivizing",
+ "colonisation": "colonization",
+ "colonise": "colonize",
+ "colonised": "colonized",
+ "coloniser": "colonizer",
+ "colonisers": "colonizers",
+ "colonises": "colonizes",
+ "colonising": "colonizing",
+ "colour": "color",
+ "colourant": "colorant",
+ "colourants": "colorants",
+ "coloured": "colored",
+ "coloureds": "coloreds",
+ "colourful": "colorful",
+ "colourfully": "colorfully",
+ "colouring": "coloring",
+ "colourize": "colorize",
+ "colourized": "colorized",
+ "colourizes": "colorizes",
+ "colourizing": "colorizing",
+ "colourless": "colorless",
+ "colours": "colors",
+ "commercialise": "commercialize",
+ "commercialised": "commercialized",
+ "commercialises": "commercializes",
+ "commercialising": "commercializing",
+ "compartmentalise": "compartmentalize",
+ "compartmentalised": "compartmentalized",
+ "compartmentalises": "compartmentalizes",
+ "compartmentalising": "compartmentalizing",
+ "computerise": "computerize",
+ "computerised": "computerized",
+ "computerises": "computerizes",
+ "computerising": "computerizing",
+ "conceptualise": "conceptualize",
+ "conceptualised": "conceptualized",
+ "conceptualises": "conceptualizes",
+ "conceptualising": "conceptualizing",
+ "connexion": "connection",
+ "connexions": "connections",
+ "contextualise": "contextualize",
+ "contextualised": "contextualized",
+ "contextualises": "contextualizes",
+ "contextualising": "contextualizing",
+ "cosier": "cozier",
+ "cosies": "cozies",
+ "cosiest": "coziest",
+ "cosily": "cozily",
+ "cosiness": "coziness",
+ "cosy": "cozy",
+ "councillor": "councilor",
+ "councillors": "councilors",
+ "counselled": "counseled",
+ "counselling": "counseling",
+ "counsellor": "counselor",
+ "counsellors": "counselors",
+ "crenelated": "crenellated",
+ "criminalise": "criminalize",
+ "criminalised": "criminalized",
+ "criminalises": "criminalizes",
+ "criminalising": "criminalizing",
+ "criticise": "criticize",
+ "criticised": "criticized",
+ "criticises": "criticizes",
+ "criticising": "criticizing",
+ "crueller": "crueler",
+ "cruellest": "cruelest",
+ "crystallisation": "crystallization",
+ "crystallise": "crystallize",
+ "crystallised": "crystallized",
+ "crystallises": "crystallizes",
+ "crystallising": "crystallizing",
+ "cudgelled": "cudgeled",
+ "cudgelling": "cudgeling",
+ "customise": "customize",
+ "customised": "customized",
+ "customises": "customizes",
+ "customising": "customizing",
+ "cypher": "cipher",
+ "cyphers": "ciphers",
+ "decentralisation": "decentralization",
+ "decentralise": "decentralize",
+ "decentralised": "decentralized",
+ "decentralises": "decentralizes",
+ "decentralising": "decentralizing",
+ "decriminalisation": "decriminalization",
+ "decriminalise": "decriminalize",
+ "decriminalised": "decriminalized",
+ "decriminalises": "decriminalizes",
+ "decriminalising": "decriminalizing",
+ "defence": "defense",
+ "defenceless": "defenseless",
+ "defences": "defenses",
+ "dehumanisation": "dehumanization",
+ "dehumanise": "dehumanize",
+ "dehumanised": "dehumanized",
+ "dehumanises": "dehumanizes",
+ "dehumanising": "dehumanizing",
+ "demeanour": "demeanor",
+ "demilitarisation": "demilitarization",
+ "demilitarise": "demilitarize",
+ "demilitarised": "demilitarized",
+ "demilitarises": "demilitarizes",
+ "demilitarising": "demilitarizing",
+ "demobilisation": "demobilization",
+ "demobilise": "demobilize",
+ "demobilised": "demobilized",
+ "demobilises": "demobilizes",
+ "demobilising": "demobilizing",
+ "democratisation": "democratization",
+ "democratise": "democratize",
+ "democratised": "democratized",
+ "democratises": "democratizes",
+ "democratising": "democratizing",
+ "demonise": "demonize",
+ "demonised": "demonized",
+ "demonises": "demonizes",
+ "demonising": "demonizing",
+ "demoralisation": "demoralization",
+ "demoralise": "demoralize",
+ "demoralised": "demoralized",
+ "demoralises": "demoralizes",
+ "demoralising": "demoralizing",
+ "denationalisation": "denationalization",
+ "denationalise": "denationalize",
+ "denationalised": "denationalized",
+ "denationalises": "denationalizes",
+ "denationalising": "denationalizing",
+ "deodorise": "deodorize",
+ "deodorised": "deodorized",
+ "deodorises": "deodorizes",
+ "deodorising": "deodorizing",
+ "depersonalise": "depersonalize",
+ "depersonalised": "depersonalized",
+ "depersonalises": "depersonalizes",
+ "depersonalising": "depersonalizing",
+ "deputise": "deputize",
+ "deputised": "deputized",
+ "deputises": "deputizes",
+ "deputising": "deputizing",
+ "desensitisation": "desensitization",
+ "desensitise": "desensitize",
+ "desensitised": "desensitized",
+ "desensitises": "desensitizes",
+ "desensitising": "desensitizing",
+ "destabilisation": "destabilization",
+ "destabilise": "destabilize",
+ "destabilised": "destabilized",
+ "destabilises": "destabilizes",
+ "destabilising": "destabilizing",
+ "dialled": "dialed",
+ "dialling": "dialing",
+ "dialogue": "dialog",
+ "dialogues": "dialogs",
+ "diarrhoea": "diarrhea",
+ "digitise": "digitize",
+ "digitised": "digitized",
+ "digitises": "digitizes",
+ "digitising": "digitizing",
+ "disc": "disk",
+ "discolour": "discolor",
+ "discoloured": "discolored",
+ "discolouring": "discoloring",
+ "discolours": "discolors",
+ "discs": "disks",
+ "disembowelled": "disemboweled",
+ "disembowelling": "disemboweling",
+ "disfavour": "disfavor",
+ "dishevelled": "disheveled",
+ "dishonour": "dishonor",
+ "dishonourable": "dishonorable",
+ "dishonourably": "dishonorably",
+ "dishonoured": "dishonored",
+ "dishonouring": "dishonoring",
+ "dishonours": "dishonors",
+ "disorganisation": "disorganization",
+ "disorganised": "disorganized",
+ "distil": "distill",
+ "distils": "distills",
+ "dramatisation": "dramatization",
+ "dramatisations": "dramatizations",
+ "dramatise": "dramatize",
+ "dramatised": "dramatized",
+ "dramatises": "dramatizes",
+ "dramatising": "dramatizing",
+ "draught": "draft",
+ "draughtboard": "draftboard",
+ "draughtboards": "draftboards",
+ "draughtier": "draftier",
+ "draughtiest": "draftiest",
+ "draughts": "drafts",
+ "draughtsman": "draftsman",
+ "draughtsmanship": "draftsmanship",
+ "draughtsmen": "draftsmen",
+ "draughtswoman": "draftswoman",
+ "draughtswomen": "draftswomen",
+ "draughty": "drafty",
+ "drivelled": "driveled",
+ "drivelling": "driveling",
+ "duelled": "dueled",
+ "duelling": "dueling",
+ "economise": "economize",
+ "economised": "economized",
+ "economises": "economizes",
+ "economising": "economizing",
+ "editorialise": "editorialize",
+ "editorialised": "editorialized",
+ "editorialises": "editorializes",
+ "editorialising": "editorializing",
+ "edoema": "edema",
+ "empathise": "empathize",
+ "empathised": "empathized",
+ "empathises": "empathizes",
+ "empathising": "empathizing",
+ "emphasise": "emphasize",
+ "emphasised": "emphasized",
+ "emphasises": "emphasizes",
+ "emphasising": "emphasizing",
+ "enamelled": "enameled",
+ "enamelling": "enameling",
+ "enamoured": "enamored",
+ "encyclopaedia": "encyclopedia",
+ "encyclopaedias": "encyclopedias",
+ "encyclopaedic": "encyclopedic",
+ "endeavour": "endeavor",
+ "endeavoured": "endeavored",
+ "endeavouring": "endeavoring",
+ "endeavours": "endeavors",
+ "energise": "energize",
+ "energised": "energized",
+ "energises": "energizes",
+ "energising": "energizing",
+ "enrol": "enroll",
+ "enrols": "enrolls",
+ "enthral": "enthrall",
+ "enthrals": "enthralls",
+ "epaulette": "epaulet",
+ "epaulettes": "epaulets",
+ "epicentre": "epicenter",
+ "epicentres": "epicenters",
+ "epilogue": "epilog",
+ "epilogues": "epilogs",
+ "epitomise": "epitomize",
+ "epitomised": "epitomized",
+ "epitomises": "epitomizes",
+ "epitomising": "epitomizing",
+ "equalisation": "equalization",
+ "equalise": "equalize",
+ "equalised": "equalized",
+ "equaliser": "equalizer",
+ "equalisers": "equalizers",
+ "equalises": "equalizes",
+ "equalising": "equalizing",
+ "eulogise": "eulogize",
+ "eulogised": "eulogized",
+ "eulogises": "eulogizes",
+ "eulogising": "eulogizing",
+ "evangelise": "evangelize",
+ "evangelised": "evangelized",
+ "evangelises": "evangelizes",
+ "evangelising": "evangelizing",
+ "exorcise": "exorcize",
+ "exorcised": "exorcized",
+ "exorcises": "exorcizes",
+ "exorcising": "exorcizing",
+ "extemporisation": "extemporization",
+ "extemporise": "extemporize",
+ "extemporised": "extemporized",
+ "extemporises": "extemporizes",
+ "extemporising": "extemporizing",
+ "externalisation": "externalization",
+ "externalisations": "externalizations",
+ "externalise": "externalize",
+ "externalised": "externalized",
+ "externalises": "externalizes",
+ "externalising": "externalizing",
+ "factorise": "factorize",
+ "factorised": "factorized",
+ "factorises": "factorizes",
+ "factorising": "factorizing",
+ "faecal": "fecal",
+ "faeces": "feces",
+ "familiarisation": "familiarization",
+ "familiarise": "familiarize",
+ "familiarised": "familiarized",
+ "familiarises": "familiarizes",
+ "familiarising": "familiarizing",
+ "fantasise": "fantasize",
+ "fantasised": "fantasized",
+ "fantasises": "fantasizes",
+ "fantasising": "fantasizing",
+ "favour": "favor",
+ "favourable": "favorable",
+ "favourably": "favorably",
+ "favoured": "favored",
+ "favouring": "favoring",
+ "favourite": "favorite",
+ "favourites": "favorites",
+ "favouritism": "favoritism",
+ "favours": "favors",
+ "feminise": "feminize",
+ "feminised": "feminized",
+ "feminises": "feminizes",
+ "feminising": "feminizing",
+ "fertilisation": "fertilization",
+ "fertilise": "fertilize",
+ "fertilised": "fertilized",
+ "fertiliser": "fertilizer",
+ "fertilisers": "fertilizers",
+ "fertilises": "fertilizes",
+ "fertilising": "fertilizing",
+ "fervour": "fervor",
+ "fibre": "fiber",
+ "fibreglass": "fiberglass",
+ "fibres": "fibers",
+ "fictionalisation": "fictionalization",
+ "fictionalisations": "fictionalizations",
+ "fictionalise": "fictionalize",
+ "fictionalised": "fictionalized",
+ "fictionalises": "fictionalizes",
+ "fictionalising": "fictionalizing",
+ "fillet": "filet",
+ "filleted": "fileted",
+ "filleting": "fileting",
+ "fillets": "filets",
+ "finalisation": "finalization",
+ "finalise": "finalize",
+ "finalised": "finalized",
+ "finalises": "finalizes",
+ "finalising": "finalizing",
+ "flautist": "flutist",
+ "flautists": "flutists",
+ "flavour": "flavor",
+ "flavoured": "flavored",
+ "flavouring": "flavoring",
+ "flavourings": "flavorings",
+ "flavourless": "flavorless",
+ "flavours": "flavors",
+ "flavoursome": "flavorsome",
+ "flyer / flier": "flier / flyer",
+ "foetal": "fetal",
+ "foetid": "fetid",
+ "foetus": "fetus",
+ "foetuses": "fetuses",
+ "formalisation": "formalization",
+ "formalise": "formalize",
+ "formalised": "formalized",
+ "formalises": "formalizes",
+ "formalising": "formalizing",
+ "fossilisation": "fossilization",
+ "fossilise": "fossilize",
+ "fossilised": "fossilized",
+ "fossilises": "fossilizes",
+ "fossilising": "fossilizing",
+ "fraternisation": "fraternization",
+ "fraternise": "fraternize",
+ "fraternised": "fraternized",
+ "fraternises": "fraternizes",
+ "fraternising": "fraternizing",
+ "fulfil": "fulfill",
+ "fulfilment": "fulfillment",
+ "fulfils": "fulfills",
+ "funnelled": "funneled",
+ "funnelling": "funneling",
+ "gage": "gauge",
+ "gaged": "gauged",
+ "gages": "gauges",
+ "gaging": "gauging",
+ "galvanise": "galvanize",
+ "galvanised": "galvanized",
+ "galvanises": "galvanizes",
+ "galvanising": "galvanizing",
+ "gambolled": "gamboled",
+ "gambolling": "gamboling",
+ "gaol": "jail",
+ "gaolbird": "jailbird",
+ "gaolbirds": "jailbirds",
+ "gaolbreak": "jailbreak",
+ "gaolbreaks": "jailbreaks",
+ "gaoled": "jailed",
+ "gaoler": "jailer",
+ "gaolers": "jailers",
+ "gaoling": "jailing",
+ "gaols": "jails",
+ "gasses": "gases",
+ "generalisation": "generalization",
+ "generalisations": "generalizations",
+ "generalise": "generalize",
+ "generalised": "generalized",
+ "generalises": "generalizes",
+ "generalising": "generalizing",
+ "ghettoise": "ghettoize",
+ "ghettoised": "ghettoized",
+ "ghettoises": "ghettoizes",
+ "ghettoising": "ghettoizing",
+ "gipsies": "gypsies",
+ "glamor": "glamour",
+ "glamorise": "glamorize",
+ "glamorised": "glamorized",
+ "glamorises": "glamorizes",
+ "glamorising": "glamorizing",
+ "globalisation": "globalization",
+ "globalise": "globalize",
+ "globalised": "globalized",
+ "globalises": "globalizes",
+ "globalising": "globalizing",
+ "glueing": "gluing",
+ "goitre": "goiter",
+ "goitres": "goiters",
+ "gonorrhoea": "gonorrhea",
+ "gramme": "gram",
+ "grammes": "grams",
+ "gravelled": "graveled",
+ "grey": "gray",
+ "greyed": "grayed",
+ "greying": "graying",
+ "greyish": "grayish",
+ "greyness": "grayness",
+ "greys": "grays",
+ "grovelled": "groveled",
+ "grovelling": "groveling",
+ "groyne": "groin",
+ "groynes": "groins",
+ "gruelling": "grueling",
+ "gruellingly": "gruelingly",
+ "gryphon": "griffin",
+ "gryphons": "griffins",
+ "gynaecological": "gynecological",
+ "gynaecologist": "gynecologist",
+ "gynaecologists": "gynecologists",
+ "gynaecology": "gynecology",
+ "haematological": "hematological",
+ "haematologist": "hematologist",
+ "haematologists": "hematologists",
+ "haematology": "hematology",
+ "haemoglobin": "hemoglobin",
+ "haemophilia": "hemophilia",
+ "haemophiliac": "hemophiliac",
+ "haemophiliacs": "hemophiliacs",
+ "haemorrhage": "hemorrhage",
+ "haemorrhaged": "hemorrhaged",
+ "haemorrhages": "hemorrhages",
+ "haemorrhaging": "hemorrhaging",
+ "haemorrhoids": "hemorrhoids",
+ "harbour": "harbor",
+ "harboured": "harbored",
+ "harbouring": "harboring",
+ "harbours": "harbors",
+ "harmonisation": "harmonization",
+ "harmonise": "harmonize",
+ "harmonised": "harmonized",
+ "harmonises": "harmonizes",
+ "harmonising": "harmonizing",
+ "homoeopath": "homeopath",
+ "homoeopathic": "homeopathic",
+ "homoeopaths": "homeopaths",
+ "homoeopathy": "homeopathy",
+ "homogenise": "homogenize",
+ "homogenised": "homogenized",
+ "homogenises": "homogenizes",
+ "homogenising": "homogenizing",
+ "honour": "honor",
+ "honourable": "honorable",
+ "honourably": "honorably",
+ "honoured": "honored",
+ "honouring": "honoring",
+ "honours": "honors",
+ "hospitalisation": "hospitalization",
+ "hospitalise": "hospitalize",
+ "hospitalised": "hospitalized",
+ "hospitalises": "hospitalizes",
+ "hospitalising": "hospitalizing",
+ "humanise": "humanize",
+ "humanised": "humanized",
+ "humanises": "humanizes",
+ "humanising": "humanizing",
+ "humour": "humor",
+ "humoured": "humored",
+ "humouring": "humoring",
+ "humourless": "humorless",
+ "humours": "humors",
+ "hybridise": "hybridize",
+ "hybridised": "hybridized",
+ "hybridises": "hybridizes",
+ "hybridising": "hybridizing",
+ "hypnotise": "hypnotize",
+ "hypnotised": "hypnotized",
+ "hypnotises": "hypnotizes",
+ "hypnotising": "hypnotizing",
+ "hypothesise": "hypothesize",
+ "hypothesised": "hypothesized",
+ "hypothesises": "hypothesizes",
+ "hypothesising": "hypothesizing",
+ "idealisation": "idealization",
+ "idealise": "idealize",
+ "idealised": "idealized",
+ "idealises": "idealizes",
+ "idealising": "idealizing",
+ "idolise": "idolize",
+ "idolised": "idolized",
+ "idolises": "idolizes",
+ "idolising": "idolizing",
+ "immobilisation": "immobilization",
+ "immobilise": "immobilize",
+ "immobilised": "immobilized",
+ "immobiliser": "immobilizer",
+ "immobilisers": "immobilizers",
+ "immobilises": "immobilizes",
+ "immobilising": "immobilizing",
+ "immortalise": "immortalize",
+ "immortalised": "immortalized",
+ "immortalises": "immortalizes",
+ "immortalising": "immortalizing",
+ "immunisation": "immunization",
+ "immunise": "immunize",
+ "immunised": "immunized",
+ "immunises": "immunizes",
+ "immunising": "immunizing",
+ "impanelled": "impaneled",
+ "impanelling": "impaneling",
+ "imperilled": "imperiled",
+ "imperilling": "imperiling",
+ "individualise": "individualize",
+ "individualised": "individualized",
+ "individualises": "individualizes",
+ "individualising": "individualizing",
+ "industrialise": "industrialize",
+ "industrialised": "industrialized",
+ "industrialises": "industrializes",
+ "industrialising": "industrializing",
+ "inflexion": "inflection",
+ "inflexions": "inflections",
+ "initialise": "initialize",
+ "initialised": "initialized",
+ "initialises": "initializes",
+ "initialising": "initializing",
+ "initialled": "initialed",
+ "initialling": "initialing",
+ "instal": "install",
+ "instalment": "installment",
+ "instalments": "installments",
+ "instals": "installs",
+ "instil": "instill",
+ "instils": "instills",
+ "institutionalisation": "institutionalization",
+ "institutionalise": "institutionalize",
+ "institutionalised": "institutionalized",
+ "institutionalises": "institutionalizes",
+ "institutionalising": "institutionalizing",
+ "intellectualise": "intellectualize",
+ "intellectualised": "intellectualized",
+ "intellectualises": "intellectualizes",
+ "intellectualising": "intellectualizing",
+ "internalisation": "internalization",
+ "internalise": "internalize",
+ "internalised": "internalized",
+ "internalises": "internalizes",
+ "internalising": "internalizing",
+ "internationalisation": "internationalization",
+ "internationalise": "internationalize",
+ "internationalised": "internationalized",
+ "internationalises": "internationalizes",
+ "internationalising": "internationalizing",
+ "ionisation": "ionization",
+ "ionise": "ionize",
+ "ionised": "ionized",
+ "ioniser": "ionizer",
+ "ionisers": "ionizers",
+ "ionises": "ionizes",
+ "ionising": "ionizing",
+ "italicise": "italicize",
+ "italicised": "italicized",
+ "italicises": "italicizes",
+ "italicising": "italicizing",
+ "itemise": "itemize",
+ "itemised": "itemized",
+ "itemises": "itemizes",
+ "itemising": "itemizing",
+ "jeopardise": "jeopardize",
+ "jeopardised": "jeopardized",
+ "jeopardises": "jeopardizes",
+ "jeopardising": "jeopardizing",
+ "jewelled": "jeweled",
+ "jeweller": "jeweler",
+ "jewellers": "jewelers",
+ "jewellery": "jewelry",
+ "judgement": "judgment",
+ "kilogramme": "kilogram",
+ "kilogrammes": "kilograms",
+ "kilometre": "kilometer",
+ "kilometres": "kilometers",
+ "labelled": "labeled",
+ "labelling": "labeling",
+ "labour": "labor",
+ "laboured": "labored",
+ "labourer": "laborer",
+ "labourers": "laborers",
+ "labouring": "laboring",
+ "labours": "labors",
+ "lacklustre": "lackluster",
+ "legalisation": "legalization",
+ "legalise": "legalize",
+ "legalised": "legalized",
+ "legalises": "legalizes",
+ "legalising": "legalizing",
+ "legitimise": "legitimize",
+ "legitimised": "legitimized",
+ "legitimises": "legitimizes",
+ "legitimising": "legitimizing",
+ "leukaemia": "leukemia",
+ "levelled": "leveled",
+ "leveller": "leveler",
+ "levellers": "levelers",
+ "levelling": "leveling",
+ "libelled": "libeled",
+ "libelling": "libeling",
+ "libellous": "libelous",
+ "liberalisation": "liberalization",
+ "liberalise": "liberalize",
+ "liberalised": "liberalized",
+ "liberalises": "liberalizes",
+ "liberalising": "liberalizing",
+ "licence": "license",
+ "licenced": "licensed",
+ "licences": "licenses",
+ "licencing": "licensing",
+ "likeable": "likable",
+ "lionisation": "lionization",
+ "lionise": "lionize",
+ "lionised": "lionized",
+ "lionises": "lionizes",
+ "lionising": "lionizing",
+ "liquidise": "liquidize",
+ "liquidised": "liquidized",
+ "liquidiser": "liquidizer",
+ "liquidisers": "liquidizers",
+ "liquidises": "liquidizes",
+ "liquidising": "liquidizing",
+ "litre": "liter",
+ "litres": "liters",
+ "localise": "localize",
+ "localised": "localized",
+ "localises": "localizes",
+ "localising": "localizing",
+ "louvre": "louver",
+ "louvred": "louvered",
+ "louvres": "louvers",
+ "lustre": "luster",
+ "magnetise": "magnetize",
+ "magnetised": "magnetized",
+ "magnetises": "magnetizes",
+ "magnetising": "magnetizing",
+ "manoeuvrability": "maneuverability",
+ "manoeuvrable": "maneuverable",
+ "manoeuvre": "maneuver",
+ "manoeuvred": "maneuvered",
+ "manoeuvres": "maneuvers",
+ "manoeuvring": "maneuvering",
+ "manoeuvrings": "maneuverings",
+ "marginalisation": "marginalization",
+ "marginalise": "marginalize",
+ "marginalised": "marginalized",
+ "marginalises": "marginalizes",
+ "marginalising": "marginalizing",
+ "marshalled": "marshaled",
+ "marshalling": "marshaling",
+ "marvelled": "marveled",
+ "marvelling": "marveling",
+ "marvellous": "marvelous",
+ "marvellously": "marvelously",
+ "materialisation": "materialization",
+ "materialise": "materialize",
+ "materialised": "materialized",
+ "materialises": "materializes",
+ "materialising": "materializing",
+ "maximisation": "maximization",
+ "maximise": "maximize",
+ "maximised": "maximized",
+ "maximises": "maximizes",
+ "maximising": "maximizing",
+ "meagre": "meager",
+ "mechanisation": "mechanization",
+ "mechanise": "mechanize",
+ "mechanised": "mechanized",
+ "mechanises": "mechanizes",
+ "mechanising": "mechanizing",
+ "mediaeval": "medieval",
+ "memorialise": "memorialize",
+ "memorialised": "memorialized",
+ "memorialises": "memorializes",
+ "memorialising": "memorializing",
+ "memorise": "memorize",
+ "memorised": "memorized",
+ "memorises": "memorizes",
+ "memorising": "memorizing",
+ "mesmerise": "mesmerize",
+ "mesmerised": "mesmerized",
+ "mesmerises": "mesmerizes",
+ "mesmerising": "mesmerizing",
+ "metabolise": "metabolize",
+ "metabolised": "metabolized",
+ "metabolises": "metabolizes",
+ "metabolising": "metabolizing",
+ "metre": "meter",
+ "metres": "meters",
+ "mhm": "hmm",
+ "micrometre": "micrometer",
+ "micrometres": "micrometers",
+ "militarise": "militarize",
+ "militarised": "militarized",
+ "militarises": "militarizes",
+ "militarising": "militarizing",
+ "milligramme": "milligram",
+ "milligrammes": "milligrams",
+ "millilitre": "milliliter",
+ "millilitres": "milliliters",
+ "millimetre": "millimeter",
+ "millimetres": "millimeters",
+ "miniaturisation": "miniaturization",
+ "miniaturise": "miniaturize",
+ "miniaturised": "miniaturized",
+ "miniaturises": "miniaturizes",
+ "miniaturising": "miniaturizing",
+ "minibusses": "minibuses",
+ "minimise": "minimize",
+ "minimised": "minimized",
+ "minimises": "minimizes",
+ "minimising": "minimizing",
+ "misbehaviour": "misbehavior",
+ "misdemeanour": "misdemeanor",
+ "misdemeanours": "misdemeanors",
+ "misspelt": "misspelled",
+ "mitre": "miter",
+ "mitres": "miters",
+ "mm": "hmm",
+ "mmm": "hmm",
+ "mobilisation": "mobilization",
+ "mobilise": "mobilize",
+ "mobilised": "mobilized",
+ "mobilises": "mobilizes",
+ "mobilising": "mobilizing",
+ "modelled": "modeled",
+ "modeller": "modeler",
+ "modellers": "modelers",
+ "modelling": "modeling",
+ "modernise": "modernize",
+ "modernised": "modernized",
+ "modernises": "modernizes",
+ "modernising": "modernizing",
+ "moisturise": "moisturize",
+ "moisturised": "moisturized",
+ "moisturiser": "moisturizer",
+ "moisturisers": "moisturizers",
+ "moisturises": "moisturizes",
+ "moisturising": "moisturizing",
+ "monologue": "monolog",
+ "monologues": "monologs",
+ "monopolisation": "monopolization",
+ "monopolise": "monopolize",
+ "monopolised": "monopolized",
+ "monopolises": "monopolizes",
+ "monopolising": "monopolizing",
+ "moralise": "moralize",
+ "moralised": "moralized",
+ "moralises": "moralizes",
+ "moralising": "moralizing",
+ "motorised": "motorized",
+ "mould": "mold",
+ "moulded": "molded",
+ "moulder": "molder",
+ "mouldered": "moldered",
+ "mouldering": "moldering",
+ "moulders": "molders",
+ "mouldier": "moldier",
+ "mouldiest": "moldiest",
+ "moulding": "molding",
+ "mouldings": "moldings",
+ "moulds": "molds",
+ "mouldy": "moldy",
+ "moult": "molt",
+ "moulted": "molted",
+ "moulting": "molting",
+ "moults": "molts",
+ "moustache": "mustache",
+ "moustached": "mustached",
+ "moustaches": "mustaches",
+ "moustachioed": "mustachioed",
+ "multicoloured": "multicolored",
+ "nationalisation": "nationalization",
+ "nationalisations": "nationalizations",
+ "nationalise": "nationalize",
+ "nationalised": "nationalized",
+ "nationalises": "nationalizes",
+ "nationalising": "nationalizing",
+ "naturalisation": "naturalization",
+ "naturalise": "naturalize",
+ "naturalised": "naturalized",
+ "naturalises": "naturalizes",
+ "naturalising": "naturalizing",
+ "neighbour": "neighbor",
+ "neighbourhood": "neighborhood",
+ "neighbourhoods": "neighborhoods",
+ "neighbouring": "neighboring",
+ "neighbourliness": "neighborliness",
+ "neighbourly": "neighborly",
+ "neighbours": "neighbors",
+ "neutralisation": "neutralization",
+ "neutralise": "neutralize",
+ "neutralised": "neutralized",
+ "neutralises": "neutralizes",
+ "neutralising": "neutralizing",
+ "normalisation": "normalization",
+ "normalise": "normalize",
+ "normalised": "normalized",
+ "normalises": "normalizes",
+ "normalising": "normalizing",
+ "odour": "odor",
+ "odourless": "odorless",
+ "odours": "odors",
+ "oesophagus": "esophagus",
+ "oesophaguses": "esophaguses",
+ "oestrogen": "estrogen",
+ "offence": "offense",
+ "offences": "offenses",
+ "omelette": "omelet",
+ "omelettes": "omelets",
+ "optimise": "optimize",
+ "optimised": "optimized",
+ "optimises": "optimizes",
+ "optimising": "optimizing",
+ "organisation": "organization",
+ "organisational": "organizational",
+ "organisations": "organizations",
+ "organise": "organize",
+ "organised": "organized",
+ "organiser": "organizer",
+ "organisers": "organizers",
+ "organises": "organizes",
+ "organising": "organizing",
+ "orthopaedic": "orthopedic",
+ "orthopaedics": "orthopedics",
+ "ostracise": "ostracize",
+ "ostracised": "ostracized",
+ "ostracises": "ostracizes",
+ "ostracising": "ostracizing",
+ "outmanoeuvre": "outmaneuver",
+ "outmanoeuvred": "outmaneuvered",
+ "outmanoeuvres": "outmaneuvers",
+ "outmanoeuvring": "outmaneuvering",
+ "overemphasise": "overemphasize",
+ "overemphasised": "overemphasized",
+ "overemphasises": "overemphasizes",
+ "overemphasising": "overemphasizing",
+ "oxidisation": "oxidization",
+ "oxidise": "oxidize",
+ "oxidised": "oxidized",
+ "oxidises": "oxidizes",
+ "oxidising": "oxidizing",
+ "paederast": "pederast",
+ "paederasts": "pederasts",
+ "paediatric": "pediatric",
+ "paediatrician": "pediatrician",
+ "paediatricians": "pediatricians",
+ "paediatrics": "pediatrics",
+ "paedophile": "pedophile",
+ "paedophiles": "pedophiles",
+ "paedophilia": "pedophilia",
+ "palaeolithic": "paleolithic",
+ "palaeontologist": "paleontologist",
+ "palaeontologists": "paleontologists",
+ "palaeontology": "paleontology",
+ "panelled": "paneled",
+ "panelling": "paneling",
+ "panellist": "panelist",
+ "panellists": "panelists",
+ "paralyse": "paralyze",
+ "paralysed": "paralyzed",
+ "paralyses": "paralyzes",
+ "paralysing": "paralyzing",
+ "parcelled": "parceled",
+ "parcelling": "parceling",
+ "parlour": "parlor",
+ "parlours": "parlors",
+ "particularise": "particularize",
+ "particularised": "particularized",
+ "particularises": "particularizes",
+ "particularising": "particularizing",
+ "passivisation": "passivization",
+ "passivise": "passivize",
+ "passivised": "passivized",
+ "passivises": "passivizes",
+ "passivising": "passivizing",
+ "pasteurisation": "pasteurization",
+ "pasteurise": "pasteurize",
+ "pasteurised": "pasteurized",
+ "pasteurises": "pasteurizes",
+ "pasteurising": "pasteurizing",
+ "patronise": "patronize",
+ "patronised": "patronized",
+ "patronises": "patronizes",
+ "patronising": "patronizing",
+ "patronisingly": "patronizingly",
+ "pedalled": "pedaled",
+ "pedalling": "pedaling",
+ "pedestrianisation": "pedestrianization",
+ "pedestrianise": "pedestrianize",
+ "pedestrianised": "pedestrianized",
+ "pedestrianises": "pedestrianizes",
+ "pedestrianising": "pedestrianizing",
+ "penalise": "penalize",
+ "penalised": "penalized",
+ "penalises": "penalizes",
+ "penalising": "penalizing",
+ "pencilled": "penciled",
+ "pencilling": "penciling",
+ "personalise": "personalize",
+ "personalised": "personalized",
+ "personalises": "personalizes",
+ "personalising": "personalizing",
+ "pharmacopoeia": "pharmacopeia",
+ "pharmacopoeias": "pharmacopeias",
+ "philosophise": "philosophize",
+ "philosophised": "philosophized",
+ "philosophises": "philosophizes",
+ "philosophising": "philosophizing",
+ "philtre": "filter",
+ "philtres": "filters",
+ "phoney": "phony",
+ "plagiarise": "plagiarize",
+ "plagiarised": "plagiarized",
+ "plagiarises": "plagiarizes",
+ "plagiarising": "plagiarizing",
+ "plough": "plow",
+ "ploughed": "plowed",
+ "ploughing": "plowing",
+ "ploughman": "plowman",
+ "ploughmen": "plowmen",
+ "ploughs": "plows",
+ "ploughshare": "plowshare",
+ "ploughshares": "plowshares",
+ "polarisation": "polarization",
+ "polarise": "polarize",
+ "polarised": "polarized",
+ "polarises": "polarizes",
+ "polarising": "polarizing",
+ "politicisation": "politicization",
+ "politicise": "politicize",
+ "politicised": "politicized",
+ "politicises": "politicizes",
+ "politicising": "politicizing",
+ "popularisation": "popularization",
+ "popularise": "popularize",
+ "popularised": "popularized",
+ "popularises": "popularizes",
+ "popularising": "popularizing",
+ "pouffe": "pouf",
+ "pouffes": "poufs",
+ "practise": "practice",
+ "practised": "practiced",
+ "practises": "practices",
+ "practising": "practicing",
+ "praesidium": "presidium",
+ "praesidiums": "presidiums",
+ "pressurisation": "pressurization",
+ "pressurise": "pressurize",
+ "pressurised": "pressurized",
+ "pressurises": "pressurizes",
+ "pressurising": "pressurizing",
+ "pretence": "pretense",
+ "pretences": "pretenses",
+ "primaeval": "primeval",
+ "prioritisation": "prioritization",
+ "prioritise": "prioritize",
+ "prioritised": "prioritized",
+ "prioritises": "prioritizes",
+ "prioritising": "prioritizing",
+ "privatisation": "privatization",
+ "privatisations": "privatizations",
+ "privatise": "privatize",
+ "privatised": "privatized",
+ "privatises": "privatizes",
+ "privatising": "privatizing",
+ "professionalisation": "professionalization",
+ "professionalise": "professionalize",
+ "professionalised": "professionalized",
+ "professionalises": "professionalizes",
+ "professionalising": "professionalizing",
+ "programme": "program",
+ "programmes": "programs",
+ "prologue": "prolog",
+ "prologues": "prologs",
+ "propagandise": "propagandize",
+ "propagandised": "propagandized",
+ "propagandises": "propagandizes",
+ "propagandising": "propagandizing",
+ "proselytise": "proselytize",
+ "proselytised": "proselytized",
+ "proselytiser": "proselytizer",
+ "proselytisers": "proselytizers",
+ "proselytises": "proselytizes",
+ "proselytising": "proselytizing",
+ "psychoanalyse": "psychoanalyze",
+ "psychoanalysed": "psychoanalyzed",
+ "psychoanalyses": "psychoanalyzes",
+ "psychoanalysing": "psychoanalyzing",
+ "publicise": "publicize",
+ "publicised": "publicized",
+ "publicises": "publicizes",
+ "publicising": "publicizing",
+ "pulverisation": "pulverization",
+ "pulverise": "pulverize",
+ "pulverised": "pulverized",
+ "pulverises": "pulverizes",
+ "pulverising": "pulverizing",
+ "pummelled": "pummel",
+ "pummelling": "pummeled",
+ "pyjama": "pajama",
+ "pyjamas": "pajamas",
+ "pzazz": "pizzazz",
+ "quarrelled": "quarreled",
+ "quarrelling": "quarreling",
+ "radicalise": "radicalize",
+ "radicalised": "radicalized",
+ "radicalises": "radicalizes",
+ "radicalising": "radicalizing",
+ "rancour": "rancor",
+ "randomise": "randomize",
+ "randomised": "randomized",
+ "randomises": "randomizes",
+ "randomising": "randomizing",
+ "rationalisation": "rationalization",
+ "rationalisations": "rationalizations",
+ "rationalise": "rationalize",
+ "rationalised": "rationalized",
+ "rationalises": "rationalizes",
+ "rationalising": "rationalizing",
+ "ravelled": "raveled",
+ "ravelling": "raveling",
+ "realisable": "realizable",
+ "realisation": "realization",
+ "realisations": "realizations",
+ "realise": "realize",
+ "realised": "realized",
+ "realises": "realizes",
+ "realising": "realizing",
+ "recognisable": "recognizable",
+ "recognisably": "recognizably",
+ "recognisance": "recognizance",
+ "recognise": "recognize",
+ "recognised": "recognized",
+ "recognises": "recognizes",
+ "recognising": "recognizing",
+ "reconnoitre": "reconnoiter",
+ "reconnoitred": "reconnoitered",
+ "reconnoitres": "reconnoiters",
+ "reconnoitring": "reconnoitering",
+ "refuelled": "refueled",
+ "refuelling": "refueling",
+ "regularisation": "regularization",
+ "regularise": "regularize",
+ "regularised": "regularized",
+ "regularises": "regularizes",
+ "regularising": "regularizing",
+ "remodelled": "remodeled",
+ "remodelling": "remodeling",
+ "remould": "remold",
+ "remoulded": "remolded",
+ "remoulding": "remolding",
+ "remoulds": "remolds",
+ "reorganisation": "reorganization",
+ "reorganisations": "reorganizations",
+ "reorganise": "reorganize",
+ "reorganised": "reorganized",
+ "reorganises": "reorganizes",
+ "reorganising": "reorganizing",
+ "revelled": "reveled",
+ "reveller": "reveler",
+ "revellers": "revelers",
+ "revelling": "reveling",
+ "revitalise": "revitalize",
+ "revitalised": "revitalized",
+ "revitalises": "revitalizes",
+ "revitalising": "revitalizing",
+ "revolutionise": "revolutionize",
+ "revolutionised": "revolutionized",
+ "revolutionises": "revolutionizes",
+ "revolutionising": "revolutionizing",
+ "rhapsodise": "rhapsodize",
+ "rhapsodised": "rhapsodized",
+ "rhapsodises": "rhapsodizes",
+ "rhapsodising": "rhapsodizing",
+ "rigour": "rigor",
+ "rigours": "rigors",
+ "ritualised": "ritualized",
+ "rivalled": "rivaled",
+ "rivalling": "rivaling",
+ "romanticise": "romanticize",
+ "romanticised": "romanticized",
+ "romanticises": "romanticizes",
+ "romanticising": "romanticizing",
+ "rumour": "rumor",
+ "rumoured": "rumored",
+ "rumours": "rumors",
+ "sabre": "saber",
+ "sabres": "sabers",
+ "saltpetre": "saltpeter",
+ "sanitise": "sanitize",
+ "sanitised": "sanitized",
+ "sanitises": "sanitizes",
+ "sanitising": "sanitizing",
+ "satirise": "satirize",
+ "satirised": "satirized",
+ "satirises": "satirizes",
+ "satirising": "satirizing",
+ "saviour": "savior",
+ "saviours": "saviors",
+ "savour": "savor",
+ "savoured": "savored",
+ "savouries": "savories",
+ "savouring": "savoring",
+ "savours": "savors",
+ "savoury": "savory",
+ "scandalise": "scandalize",
+ "scandalised": "scandalized",
+ "scandalises": "scandalizes",
+ "scandalising": "scandalizing",
+ "sceptic": "skeptic",
+ "sceptical": "skeptical",
+ "sceptically": "skeptically",
+ "scepticism": "skepticism",
+ "sceptics": "skeptics",
+ "sceptre": "scepter",
+ "sceptres": "scepters",
+ "scrutinise": "scrutinize",
+ "scrutinised": "scrutinized",
+ "scrutinises": "scrutinizes",
+ "scrutinising": "scrutinizing",
+ "secularisation": "secularization",
+ "secularise": "secularize",
+ "secularised": "secularized",
+ "secularises": "secularizes",
+ "secularising": "secularizing",
+ "sensationalise": "sensationalize",
+ "sensationalised": "sensationalized",
+ "sensationalises": "sensationalizes",
+ "sensationalising": "sensationalizing",
+ "sensitise": "sensitize",
+ "sensitised": "sensitized",
+ "sensitises": "sensitizes",
+ "sensitising": "sensitizing",
+ "sentimentalise": "sentimentalize",
+ "sentimentalised": "sentimentalized",
+ "sentimentalises": "sentimentalizes",
+ "sentimentalising": "sentimentalizing",
+ "sepulchre": "sepulcher",
+ "sepulchres": "sepulchers",
+ "serialisation": "serialization",
+ "serialisations": "serializations",
+ "serialise": "serialize",
+ "serialised": "serialized",
+ "serialises": "serializes",
+ "serialising": "serializing",
+ "sermonise": "sermonize",
+ "sermonised": "sermonized",
+ "sermonises": "sermonizes",
+ "sermonising": "sermonizing",
+ "sheikh": "sheik",
+ "shovelled": "shoveled",
+ "shovelling": "shoveling",
+ "shrivelled": "shriveled",
+ "shrivelling": "shriveling",
+ "signalise": "signalize",
+ "signalised": "signalized",
+ "signalises": "signalizes",
+ "signalising": "signalizing",
+ "signalled": "signaled",
+ "signalling": "signaling",
+ "smoulder": "smolder",
+ "smouldered": "smoldered",
+ "smouldering": "smoldering",
+ "smoulders": "smolders",
+ "snivelled": "sniveled",
+ "snivelling": "sniveling",
+ "snorkelled": "snorkeled",
+ "snorkelling": "snorkeling",
+ "snowplough": "snowplow",
+ "snowploughs": "snowplow",
+ "socialisation": "socialization",
+ "socialise": "socialize",
+ "socialised": "socialized",
+ "socialises": "socializes",
+ "socialising": "socializing",
+ "sodomise": "sodomize",
+ "sodomised": "sodomized",
+ "sodomises": "sodomizes",
+ "sodomising": "sodomizing",
+ "solemnise": "solemnize",
+ "solemnised": "solemnized",
+ "solemnises": "solemnizes",
+ "solemnising": "solemnizing",
+ "sombre": "somber",
+ "specialisation": "specialization",
+ "specialisations": "specializations",
+ "specialise": "specialize",
+ "specialised": "specialized",
+ "specialises": "specializes",
+ "specialising": "specializing",
+ "spectre": "specter",
+ "spectres": "specters",
+ "spiralled": "spiraled",
+ "spiralling": "spiraling",
+ "splendour": "splendor",
+ "splendours": "splendors",
+ "squirrelled": "squirreled",
+ "squirrelling": "squirreling",
+ "stabilisation": "stabilization",
+ "stabilise": "stabilize",
+ "stabilised": "stabilized",
+ "stabiliser": "stabilizer",
+ "stabilisers": "stabilizers",
+ "stabilises": "stabilizes",
+ "stabilising": "stabilizing",
+ "standardisation": "standardization",
+ "standardise": "standardize",
+ "standardised": "standardized",
+ "standardises": "standardizes",
+ "standardising": "standardizing",
+ "stencilled": "stenciled",
+ "stencilling": "stenciling",
+ "sterilisation": "sterilization",
+ "sterilisations": "sterilizations",
+ "sterilise": "sterilize",
+ "sterilised": "sterilized",
+ "steriliser": "sterilizer",
+ "sterilisers": "sterilizers",
+ "sterilises": "sterilizes",
+ "sterilising": "sterilizing",
+ "stigmatisation": "stigmatization",
+ "stigmatise": "stigmatize",
+ "stigmatised": "stigmatized",
+ "stigmatises": "stigmatizes",
+ "stigmatising": "stigmatizing",
+ "storey": "story",
+ "storeys": "stories",
+ "subsidisation": "subsidization",
+ "subsidise": "subsidize",
+ "subsidised": "subsidized",
+ "subsidiser": "subsidizer",
+ "subsidisers": "subsidizers",
+ "subsidises": "subsidizes",
+ "subsidising": "subsidizing",
+ "succour": "succor",
+ "succoured": "succored",
+ "succouring": "succoring",
+ "succours": "succors",
+ "sulphate": "sulfate",
+ "sulphates": "sulfates",
+ "sulphide": "sulfide",
+ "sulphides": "sulfides",
+ "sulphur": "sulfur",
+ "sulphurous": "sulfurous",
+ "summarise": "summarize",
+ "summarised": "summarized",
+ "summarises": "summarizes",
+ "summarising": "summarizing",
+ "swivelled": "swiveled",
+ "swivelling": "swiveling",
+ "symbolise": "symbolize",
+ "symbolised": "symbolized",
+ "symbolises": "symbolizes",
+ "symbolising": "symbolizing",
+ "sympathise": "sympathize",
+ "sympathised": "sympathized",
+ "sympathiser": "sympathizer",
+ "sympathisers": "sympathizers",
+ "sympathises": "sympathizes",
+ "sympathising": "sympathizing",
+ "synchronisation": "synchronization",
+ "synchronise": "synchronize",
+ "synchronised": "synchronized",
+ "synchronises": "synchronizes",
+ "synchronising": "synchronizing",
+ "synthesise": "synthesize",
+ "synthesised": "synthesized",
+ "synthesiser": "synthesizer",
+ "synthesisers": "synthesizers",
+ "synthesises": "synthesizes",
+ "synthesising": "synthesizing",
+ "syphon": "siphon",
+ "syphoned": "siphoned",
+ "syphoning": "siphoning",
+ "syphons": "siphons",
+ "systematisation": "systematization",
+ "systematise": "systematize",
+ "systematised": "systematized",
+ "systematises": "systematizes",
+ "systematising": "systematizing",
+ "tantalise": "tantalize",
+ "tantalised": "tantalized",
+ "tantalises": "tantalizes",
+ "tantalising": "tantalizing",
+ "tantalisingly": "tantalizingly",
+ "tasselled": "tasseled",
+ "technicolour": "technicolor",
+ "temporise": "temporize",
+ "temporised": "temporized",
+ "temporises": "temporizes",
+ "temporising": "temporizing",
+ "tenderise": "tenderize",
+ "tenderised": "tenderized",
+ "tenderises": "tenderizes",
+ "tenderising": "tenderizing",
+ "terrorise": "terrorize",
+ "terrorised": "terrorized",
+ "terrorises": "terrorizes",
+ "terrorising": "terrorizing",
+ "theatre": "theater",
+ "theatregoer": "theatergoer",
+ "theatregoers": "theatergoers",
+ "theatres": "theaters",
+ "theorise": "theorize",
+ "theorised": "theorized",
+ "theorises": "theorizes",
+ "theorising": "theorizing",
+ "tonne": "ton",
+ "tonnes": "tons",
+ "towelled": "toweled",
+ "towelling": "toweling",
+ "toxaemia": "toxemia",
+ "tranquillise": "tranquilize",
+ "tranquillised": "tranquilized",
+ "tranquilliser": "tranquilizer",
+ "tranquillisers": "tranquilizers",
+ "tranquillises": "tranquilizes",
+ "tranquillising": "tranquilizing",
+ "tranquillity": "tranquility",
+ "tranquillize": "tranquilize",
+ "tranquillized": "tranquilized",
+ "tranquillizer": "tranquilizer",
+ "tranquillizers": "tranquilizers",
+ "tranquillizes": "tranquilizes",
+ "tranquillizing": "tranquilizing",
+ "tranquilly": "tranquility",
+ "transistorised": "transistorized",
+ "traumatise": "traumatize",
+ "traumatised": "traumatized",
+ "traumatises": "traumatizes",
+ "traumatising": "traumatizing",
+ "travelled": "traveled",
+ "traveller": "traveler",
+ "travellers": "travelers",
+ "travelling": "traveling",
+ "travelog": "travelogue",
+ "travelogs": "travelogues",
+ "trialled": "trialed",
+ "trialling": "trialing",
+ "tricolour": "tricolor",
+ "tricolours": "tricolors",
+ "trivialise": "trivialize",
+ "trivialised": "trivialized",
+ "trivialises": "trivializes",
+ "trivialising": "trivializing",
+ "tumour": "tumor",
+ "tumours": "tumors",
+ "tunnelled": "tunneled",
+ "tunnelling": "tunneling",
+ "tyrannise": "tyrannize",
+ "tyrannised": "tyrannized",
+ "tyrannises": "tyrannizes",
+ "tyrannising": "tyrannizing",
+ "tyre": "tire",
+ "tyres": "tires",
+ "unauthorised": "unauthorized",
+ "uncivilised": "uncivilized",
+ "underutilised": "underutilized",
+ "unequalled": "unequaled",
+ "unfavourable": "unfavorable",
+ "unfavourably": "unfavorably",
+ "unionisation": "unionization",
+ "unionise": "unionize",
+ "unionised": "unionized",
+ "unionises": "unionizes",
+ "unionising": "unionizing",
+ "unorganised": "unorganized",
+ "unravelled": "unraveled",
+ "unravelling": "unraveling",
+ "unrecognisable": "unrecognizable",
+ "unrecognised": "unrecognized",
+ "unrivalled": "unrivaled",
+ "unsavoury": "unsavory",
+ "untrammelled": "untrammeled",
+ "urbanisation": "urbanization",
+ "urbanise": "urbanize",
+ "urbanised": "urbanized",
+ "urbanises": "urbanizes",
+ "urbanising": "urbanizing",
+ "utilisable": "utilizable",
+ "utilisation": "utilization",
+ "utilise": "utilize",
+ "utilised": "utilized",
+ "utilises": "utilizes",
+ "utilising": "utilizing",
+ "valour": "valor",
+ "vandalise": "vandalize",
+ "vandalised": "vandalized",
+ "vandalises": "vandalizes",
+ "vandalising": "vandalizing",
+ "vaporisation": "vaporization",
+ "vaporise": "vaporize",
+ "vaporised": "vaporized",
+ "vaporises": "vaporizes",
+ "vaporising": "vaporizing",
+ "vapour": "vapor",
+ "vapours": "vapors",
+ "verbalise": "verbalize",
+ "verbalised": "verbalized",
+ "verbalises": "verbalizes",
+ "verbalising": "verbalizing",
+ "victimisation": "victimization",
+ "victimise": "victimize",
+ "victimised": "victimized",
+ "victimises": "victimizes",
+ "victimising": "victimizing",
+ "videodisc": "videodisk",
+ "videodiscs": "videodisks",
+ "vigour": "vigor",
+ "visualisation": "visualization",
+ "visualisations": "visualizations",
+ "visualise": "visualize",
+ "visualised": "visualized",
+ "visualises": "visualizes",
+ "visualising": "visualizing",
+ "vocalisation": "vocalization",
+ "vocalisations": "vocalizations",
+ "vocalise": "vocalize",
+ "vocalised": "vocalized",
+ "vocalises": "vocalizes",
+ "vocalising": "vocalizing",
+ "vulcanised": "vulcanized",
+ "vulgarisation": "vulgarization",
+ "vulgarise": "vulgarize",
+ "vulgarised": "vulgarized",
+ "vulgarises": "vulgarizes",
+ "vulgarising": "vulgarizing",
+ "waggon": "wagon",
+ "waggons": "wagons",
+ "watercolour": "watercolor",
+ "watercolours": "watercolors",
+ "weaselled": "weaseled",
+ "weaselling": "weaseling",
+ "westernisation": "westernization",
+ "westernise": "westernize",
+ "westernised": "westernized",
+ "westernises": "westernizes",
+ "westernising": "westernizing",
+ "womanise": "womanize",
+ "womanised": "womanized",
+ "womaniser": "womanizer",
+ "womanisers": "womanizers",
+ "womanises": "womanizes",
+ "womanising": "womanizing",
+ "woollen": "woolen",
+ "woollens": "woolens",
+ "woollies": "woolies",
+ "woolly": "wooly",
+ "worshipped": "worshiped",
+ "worshipper": "worshiper",
+ "worshipping": "worshiping",
+ "yodelled": "yodeled",
+ "yodelling": "yodeling",
+ "yoghourt": "yogurt",
+ "yoghourts": "yogurts",
+ "yoghurt": "yogurt",
+ "yoghurts": "yogurts"
+}
diff --git a/whisper_pipeline/faster-whisper-main/benchmark/requirements.benchmark.txt b/whisper_pipeline/faster-whisper-main/benchmark/requirements.benchmark.txt
new file mode 100644
index 0000000000000000000000000000000000000000..26450040b7c2ddf00b61f8092ce8d03cae258058
--- /dev/null
+++ b/whisper_pipeline/faster-whisper-main/benchmark/requirements.benchmark.txt
@@ -0,0 +1,6 @@
+transformers
+jiwer
+evaluate
+datasets
+memory_profiler
+py3nvml
diff --git a/whisper_pipeline/faster-whisper-main/benchmark/speed_benchmark.py b/whisper_pipeline/faster-whisper-main/benchmark/speed_benchmark.py
new file mode 100644
index 0000000000000000000000000000000000000000..a3d6ffbc537f5a1cd950459cc0c12a1cdbbc8971
--- /dev/null
+++ b/whisper_pipeline/faster-whisper-main/benchmark/speed_benchmark.py
@@ -0,0 +1,31 @@
+import argparse
+import timeit
+
+from typing import Callable
+
+from utils import inference
+
+parser = argparse.ArgumentParser(description="Speed benchmark")
+parser.add_argument(
+ "--repeat",
+ type=int,
+ default=3,
+ help="Times an experiment will be run.",
+)
+args = parser.parse_args()
+
+
+def measure_speed(func: Callable[[], None]):
+ # as written in https://docs.python.org/3/library/timeit.html#timeit.Timer.repeat,
+ # min should be taken rather than the average
+ runtimes = timeit.repeat(
+ func,
+ repeat=args.repeat,
+ number=10,
+ )
+ print(runtimes)
+ print("Min execution time: %.3fs" % (min(runtimes) / 10.0))
+
+
+if __name__ == "__main__":
+ measure_speed(inference)
diff --git a/whisper_pipeline/faster-whisper-main/benchmark/utils.py b/whisper_pipeline/faster-whisper-main/benchmark/utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..8e5ac466a355e62d4d1534ac4e1f1d7ae37c2d74
--- /dev/null
+++ b/whisper_pipeline/faster-whisper-main/benchmark/utils.py
@@ -0,0 +1,39 @@
+import logging
+
+from threading import Thread
+from typing import Optional
+
+from faster_whisper import WhisperModel
+
+model_path = "large-v3"
+model = WhisperModel(model_path, device="cuda")
+
+
+def inference():
+ segments, info = model.transcribe("benchmark.m4a", language="fr")
+ for segment in segments:
+ print("[%.2fs -> %.2fs] %s" % (segment.start, segment.end, segment.text))
+
+
+def get_logger(name: Optional[str] = None) -> logging.Logger:
+ formatter = logging.Formatter("%(levelname)s: %(message)s")
+ logger = logging.getLogger(name)
+ logger.setLevel(logging.DEBUG)
+ handler = logging.StreamHandler()
+ handler.setFormatter(formatter)
+ logger.addHandler(handler)
+ return logger
+
+
+class MyThread(Thread):
+ def __init__(self, func, params):
+ super(MyThread, self).__init__()
+ self.func = func
+ self.params = params
+ self.result = None
+
+ def run(self):
+ self.result = self.func(*self.params)
+
+ def get_result(self):
+ return self.result
diff --git a/whisper_pipeline/faster-whisper-main/benchmark/wer_benchmark.py b/whisper_pipeline/faster-whisper-main/benchmark/wer_benchmark.py
new file mode 100644
index 0000000000000000000000000000000000000000..f7a0b792df9b137d90cf7277de9a53b9f0c11ded
--- /dev/null
+++ b/whisper_pipeline/faster-whisper-main/benchmark/wer_benchmark.py
@@ -0,0 +1,64 @@
+import argparse
+import json
+import os
+
+from datasets import load_dataset
+from evaluate import load
+from tqdm import tqdm
+from transformers.models.whisper.english_normalizer import EnglishTextNormalizer
+
+from faster_whisper import WhisperModel
+
+parser = argparse.ArgumentParser(description="WER benchmark")
+parser.add_argument(
+ "--audio_numb",
+ type=int,
+ default=None,
+ help="Specify the number of validation audio files in the dataset."
+ " Set to None to retrieve all audio files.",
+)
+args = parser.parse_args()
+
+model_path = "large-v3"
+model = WhisperModel(model_path, device="cuda")
+
+# load the dataset with streaming mode
+dataset = load_dataset("librispeech_asr", "clean", split="validation", streaming=True)
+
+# define the evaluation metric
+wer_metric = load("wer")
+
+with open(os.path.join(os.path.dirname(__file__), "normalizer.json"), "r") as f:
+ normalizer = EnglishTextNormalizer(json.load(f))
+
+
+def inference(batch):
+ batch["transcription"] = []
+ for sample in batch["audio"]:
+ segments, info = model.transcribe(sample["array"], language="en")
+ batch["transcription"].append("".join([segment.text for segment in segments]))
+ batch["reference"] = batch["text"]
+ return batch
+
+
+dataset = dataset.map(function=inference, batched=True, batch_size=16)
+
+all_transcriptions = []
+all_references = []
+
+# iterate over the dataset and run inference
+for i, result in tqdm(enumerate(dataset), desc="Evaluating..."):
+ all_transcriptions.append(result["transcription"])
+ all_references.append(result["reference"])
+ if args.audio_numb and i == (args.audio_numb - 1):
+ break
+
+# normalize predictions and references
+all_transcriptions = [normalizer(transcription) for transcription in all_transcriptions]
+all_references = [normalizer(reference) for reference in all_references]
+
+# compute the WER metric
+wer = 100 * wer_metric.compute(
+ predictions=all_transcriptions, references=all_references
+)
+print("WER: %.3f" % wer)
diff --git a/whisper_pipeline/faster-whisper-main/build/lib/faster_whisper/__init__.py b/whisper_pipeline/faster-whisper-main/build/lib/faster_whisper/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..ad69277853742e3f9f0e0f020c0862cf4ad404fb
--- /dev/null
+++ b/whisper_pipeline/faster-whisper-main/build/lib/faster_whisper/__init__.py
@@ -0,0 +1,14 @@
+from faster_whisper.audio import decode_audio
+from faster_whisper.transcribe import BatchedInferencePipeline, WhisperModel
+from faster_whisper.utils import available_models, download_model, format_timestamp
+from faster_whisper.version import __version__
+
+__all__ = [
+ "available_models",
+ "decode_audio",
+ "WhisperModel",
+ "BatchedInferencePipeline",
+ "download_model",
+ "format_timestamp",
+ "__version__",
+]
diff --git a/whisper_pipeline/faster-whisper-main/build/lib/faster_whisper/assets/__init__.py b/whisper_pipeline/faster-whisper-main/build/lib/faster_whisper/assets/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/whisper_pipeline/faster-whisper-main/build/lib/faster_whisper/assets/pyannote_vad_model.bin b/whisper_pipeline/faster-whisper-main/build/lib/faster_whisper/assets/pyannote_vad_model.bin
new file mode 100644
index 0000000000000000000000000000000000000000..7a0c29f0dbd55f172445e95ae1f0163a7d849c27
--- /dev/null
+++ b/whisper_pipeline/faster-whisper-main/build/lib/faster_whisper/assets/pyannote_vad_model.bin
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0b5b3216d60a2d32fc086b47ea8c67589aaeb26b7e07fcbe620d6d0b83e209ea
+size 17719103
diff --git a/whisper_pipeline/faster-whisper-main/build/lib/faster_whisper/assets/silero_vad.onnx b/whisper_pipeline/faster-whisper-main/build/lib/faster_whisper/assets/silero_vad.onnx
new file mode 100644
index 0000000000000000000000000000000000000000..6ea96ef73cac24d33ad342094d95867c756d3f5c
--- /dev/null
+++ b/whisper_pipeline/faster-whisper-main/build/lib/faster_whisper/assets/silero_vad.onnx
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6b99cbfd39246b6706f98ec13c7c50c6b299181f2474fa05cbc8046acc274396
+size 2313101
diff --git a/whisper_pipeline/faster-whisper-main/build/lib/faster_whisper/audio.py b/whisper_pipeline/faster-whisper-main/build/lib/faster_whisper/audio.py
new file mode 100644
index 0000000000000000000000000000000000000000..7ae68d40055b0df3427c1201d9cd92f663110b12
--- /dev/null
+++ b/whisper_pipeline/faster-whisper-main/build/lib/faster_whisper/audio.py
@@ -0,0 +1,58 @@
+from typing import BinaryIO, Union
+
+import torch
+import torchaudio
+
+
+def decode_audio(
+ input_file: Union[str, BinaryIO],
+ sampling_rate: int = 16000,
+ split_stereo: bool = False,
+):
+ """Decodes the audio.
+
+ Args:
+ input_file: Path to the input file or a file-like object.
+ sampling_rate: Resample the audio to this sample rate.
+ split_stereo: Return separate left and right channels.
+
+ Returns:
+ A float32 Torch Tensor.
+
+ If `split_stereo` is enabled, the function returns a 2-tuple with the
+ separated left and right channels.
+ """
+
+ waveform, audio_sf = torchaudio.load(input_file) # waveform: channels X T
+
+ if audio_sf != sampling_rate:
+ waveform = torchaudio.functional.resample(
+ waveform, orig_freq=audio_sf, new_freq=sampling_rate
+ )
+ if split_stereo:
+ return waveform[0], waveform[1]
+
+ return waveform.mean(0)
+
+
+def pad_or_trim(array, length: int, *, axis: int = -1):
+ """
+ Pad or trim the audio array to N_SAMPLES, as expected by the encoder.
+ """
+ axis = axis % array.ndim
+ if array.shape[axis] > length:
+ idx = [Ellipsis] * axis + [slice(length)] + [Ellipsis] * (array.ndim - axis - 1)
+ return array[idx]
+
+ if array.shape[axis] < length:
+ pad_widths = (
+ [
+ 0,
+ ]
+ * array.ndim
+ * 2
+ )
+ pad_widths[2 * axis] = length - array.shape[axis]
+ array = torch.nn.functional.pad(array, tuple(pad_widths[::-1]))
+
+ return array
diff --git a/whisper_pipeline/faster-whisper-main/build/lib/faster_whisper/feature_extractor.py b/whisper_pipeline/faster-whisper-main/build/lib/faster_whisper/feature_extractor.py
new file mode 100644
index 0000000000000000000000000000000000000000..6371d5ef6864b07ce4b7f3c1cd1075fee9c8e484
--- /dev/null
+++ b/whisper_pipeline/faster-whisper-main/build/lib/faster_whisper/feature_extractor.py
@@ -0,0 +1,114 @@
+import torch
+
+
+# Adapted from https://github.com/huggingface/transformers/blob/main/src/transformers/models/whisper/feature_extraction_whisper.py # noqa: E501
+class FeatureExtractor:
+ def __init__(
+ self,
+ device: str = "auto",
+ feature_size=80,
+ sampling_rate=16000,
+ hop_length=160,
+ chunk_length=30,
+ n_fft=400,
+ ):
+ if device == "auto":
+ self.device = "cuda" if torch.cuda.is_available() else "cpu"
+ else:
+ self.device = device
+ self.n_fft = n_fft
+ self.hop_length = hop_length
+ self.chunk_length = chunk_length
+ self.n_samples = chunk_length * sampling_rate
+ self.nb_max_frames = self.n_samples // hop_length
+ self.time_per_frame = hop_length / sampling_rate
+ self.sampling_rate = sampling_rate
+ self.mel_filters = self.get_mel_filters(
+ sampling_rate, n_fft, n_mels=feature_size
+ )
+
+ @staticmethod
+ def get_mel_filters(sr, n_fft, n_mels=128):
+ """
+ Implementation of librosa.filters.mel in Pytorch
+ """
+ # Initialize the weights
+ n_mels = int(n_mels)
+
+ # Center freqs of each FFT bin
+ fftfreqs = torch.fft.rfftfreq(n=n_fft, d=1.0 / sr)
+
+ # 'Center freqs' of mel bands - uniformly spaced between limits
+ min_mel = 0.0
+ max_mel = 45.245640471924965
+
+ mels = torch.linspace(min_mel, max_mel, n_mels + 2)
+
+ # Fill in the linear scale
+ f_min = 0.0
+ f_sp = 200.0 / 3
+ freqs = f_min + f_sp * mels
+
+ # And now the nonlinear scale
+ min_log_hz = 1000.0 # beginning of log region (Hz)
+ min_log_mel = (min_log_hz - f_min) / f_sp # same (Mels)
+ logstep = torch.log(torch.tensor(6.4)) / 27.0 # step size for log region
+
+ # If we have vector data, vectorize
+ log_t = mels >= min_log_mel
+ freqs[log_t] = min_log_hz * torch.exp(logstep * (mels[log_t] - min_log_mel))
+
+ mel_f = freqs
+
+ fdiff = torch.diff(mel_f)
+ ramps = mel_f.view(-1, 1) - fftfreqs.view(1, -1)
+
+ lower = -ramps[:-2] / fdiff[:-1].unsqueeze(1)
+ upper = ramps[2:] / fdiff[1:].unsqueeze(1)
+
+ # Intersect them with each other and zero, vectorized across all i
+ weights = torch.maximum(torch.zeros_like(lower), torch.minimum(lower, upper))
+
+ # Slaney-style mel is scaled to be approx constant energy per channel
+ enorm = 2.0 / (mel_f[2 : n_mels + 2] - mel_f[:n_mels])
+ weights *= enorm.unsqueeze(1)
+
+ return weights
+
+ def __call__(self, waveform, padding=True, chunk_length=None, to_cpu=False):
+ """
+ Compute the log-Mel spectrogram of the provided audio.
+ """
+
+ if chunk_length is not None:
+ self.n_samples = chunk_length * self.sampling_rate
+ self.nb_max_frames = self.n_samples // self.hop_length
+
+ if waveform.dtype is not torch.float32:
+ waveform = waveform.to(torch.float32)
+
+ waveform = (
+ waveform.to(self.device)
+ if self.device == "cuda" and not waveform.is_cuda
+ else waveform
+ )
+
+ if padding:
+ waveform = torch.nn.functional.pad(waveform, (0, self.n_samples))
+
+ window = torch.hann_window(self.n_fft).to(waveform.device)
+
+ stft = torch.stft(
+ waveform, self.n_fft, self.hop_length, window=window, return_complex=True
+ )
+ magnitudes = stft[..., :-1].abs() ** 2
+
+ mel_spec = self.mel_filters.to(waveform.device) @ magnitudes
+
+ log_spec = torch.clamp(mel_spec, min=1e-10).log10()
+ log_spec = torch.maximum(log_spec, log_spec.max() - 8.0)
+ log_spec = (log_spec + 4.0) / 4.0
+
+ # When the model is running on multiple GPUs, the output should be moved
+ # to the CPU since we don't know which GPU will handle the next job.
+ return log_spec.cpu() if to_cpu else log_spec
diff --git a/whisper_pipeline/faster-whisper-main/build/lib/faster_whisper/tokenizer.py b/whisper_pipeline/faster-whisper-main/build/lib/faster_whisper/tokenizer.py
new file mode 100644
index 0000000000000000000000000000000000000000..3bf76a5f6321d5f17cb778604b3e5e3d73275835
--- /dev/null
+++ b/whisper_pipeline/faster-whisper-main/build/lib/faster_whisper/tokenizer.py
@@ -0,0 +1,314 @@
+import string
+
+from functools import cached_property
+from typing import List, Optional, Tuple
+
+import tokenizers
+
+
+class Tokenizer:
+ """Simple wrapper around a tokenizers.Tokenizer."""
+
+ def __init__(
+ self,
+ tokenizer: tokenizers.Tokenizer,
+ multilingual: bool,
+ task: Optional[str] = None,
+ language: Optional[str] = None,
+ ):
+ self.tokenizer = tokenizer
+
+ if multilingual:
+ if task not in _TASKS:
+ raise ValueError(
+ "'%s' is not a valid task (accepted tasks: %s)"
+ % (task, ", ".join(_TASKS))
+ )
+
+ if language not in _LANGUAGE_CODES:
+ raise ValueError(
+ "'%s' is not a valid language code (accepted language codes: %s)"
+ % (language, ", ".join(_LANGUAGE_CODES))
+ )
+
+ self.task = self.tokenizer.token_to_id("<|%s|>" % task)
+ self.language = self.tokenizer.token_to_id("<|%s|>" % language)
+ self.language_code = language
+ else:
+ self.task = None
+ self.language = None
+ self.language_code = "en"
+
+ @cached_property
+ def transcribe(self) -> int:
+ return self.tokenizer.token_to_id("<|transcribe|>")
+
+ @cached_property
+ def translate(self) -> int:
+ return self.tokenizer.token_to_id("<|translate|>")
+
+ @cached_property
+ def sot(self) -> int:
+ return self.tokenizer.token_to_id("<|startoftranscript|>")
+
+ @cached_property
+ def sot_lm(self) -> int:
+ return self.tokenizer.token_to_id("<|startoflm|>")
+
+ @cached_property
+ def sot_prev(self) -> int:
+ return self.tokenizer.token_to_id("<|startofprev|>")
+
+ @cached_property
+ def eot(self) -> int:
+ return self.tokenizer.token_to_id("<|endoftext|>")
+
+ @cached_property
+ def no_timestamps(self) -> int:
+ return self.tokenizer.token_to_id("<|notimestamps|>")
+
+ @property
+ def timestamp_begin(self) -> int:
+ return self.no_timestamps + 1
+
+ @property
+ def sot_sequence(self) -> List[int]:
+ sequence = [self.sot]
+
+ if self.language is not None:
+ sequence.append(self.language)
+
+ if self.task is not None:
+ sequence.append(self.task)
+
+ return sequence
+
+ def encode(self, text: str) -> List[int]:
+ return self.tokenizer.encode(text, add_special_tokens=False).ids
+
+ def decode(self, tokens: List[int]) -> str:
+ text_tokens = [token for token in tokens if token < self.eot]
+ return self.tokenizer.decode(text_tokens)
+
+ def decode_with_timestamps(self, tokens: List[int]) -> str:
+ outputs = [[]]
+
+ for token in tokens:
+ if token >= self.timestamp_begin:
+ timestamp = f"<|{(token - self.timestamp_begin) * 0.02:.2f}|>"
+ outputs.append(timestamp)
+ outputs.append([])
+ else:
+ outputs[-1].append(token)
+
+ return "".join(
+ [s if isinstance(s, str) else self.tokenizer.decode(s) for s in outputs]
+ )
+
+ @cached_property
+ def non_speech_tokens(self) -> Tuple[int]:
+ """
+ Returns the list of tokens to suppress in order to avoid any speaker tags or non-speech
+ annotations, to prevent sampling texts that are not actually spoken in the audio, e.g.
+
+ - ♪♪♪
+ - ( SPEAKING FOREIGN LANGUAGE )
+ - [DAVID] Hey there,
+
+ keeping basic punctuations like commas, periods, question marks, exclamation points, etc.
+ """
+ symbols = list('"#()*+/:;<=>@[\\]^_`{|}~「」『』')
+ symbols += (
+ "<< >> <<< >>> -- --- -( -[ (' (\" (( )) ((( ))) [[ ]] {{ }} ♪♪ ♪♪♪".split()
+ )
+
+ # symbols that may be a single token or multiple tokens depending on the tokenizer.
+ # In case they're multiple tokens, suppress the first token, which is safe because:
+ # These are between U+2640 and U+267F miscellaneous symbols that are okay to suppress
+ # in generations, and in the 3-byte UTF-8 representation they share the first two bytes.
+ miscellaneous = set("♩♪♫♬♭♮♯")
+ assert all(0x2640 <= ord(c) <= 0x267F for c in miscellaneous)
+
+ # allow hyphens "-" and single quotes "'" between words, but not at the beginning of a word
+ result = {self.encode(" -")[0], self.encode(" '")[0]}
+ for symbol in symbols + list(miscellaneous):
+ for tokens in [
+ self.encode(symbol),
+ self.encode(" " + symbol),
+ ]:
+ if len(tokens) == 1 or symbol in miscellaneous:
+ result.add(tokens[0])
+
+ return tuple(sorted(result))
+
+ def split_to_word_tokens(
+ self, tokens: List[int]
+ ) -> Tuple[List[str], List[List[int]]]:
+ if self.language_code in {"zh", "ja", "th", "lo", "my", "yue"}:
+ # These languages don't typically use spaces, so it is difficult to split words
+ # without morpheme analysis. Here, we instead split words at any
+ # position where the tokens are decoded as valid unicode points
+ return self.split_tokens_on_unicode(tokens)
+
+ return self.split_tokens_on_spaces(tokens)
+
+ def split_tokens_on_unicode(
+ self, tokens: List[int]
+ ) -> Tuple[List[str], List[List[int]]]:
+ decoded_full = self.decode_with_timestamps(tokens)
+ replacement_char = "\ufffd"
+
+ words = []
+ word_tokens = []
+ current_tokens = []
+ unicode_offset = 0
+
+ for token in tokens:
+ current_tokens.append(token)
+ decoded = self.decode_with_timestamps(current_tokens)
+
+ try:
+ replacement_char_index = decoded.index(replacement_char)
+ replacement_char_index += unicode_offset
+ except ValueError:
+ replacement_char_index = None
+
+ if replacement_char_index is None or (
+ replacement_char_index < len(decoded_full)
+ and decoded_full[replacement_char_index] == replacement_char
+ ):
+ words.append(decoded)
+ word_tokens.append(current_tokens)
+ current_tokens = []
+ unicode_offset += len(decoded)
+
+ return words, word_tokens
+
+ def split_tokens_on_spaces(
+ self, tokens: List[int]
+ ) -> Tuple[List[str], List[List[int]]]:
+ subwords, subword_tokens_list = self.split_tokens_on_unicode(tokens)
+ words = []
+ word_tokens = []
+
+ for subword, subword_tokens in zip(subwords, subword_tokens_list):
+ special = subword_tokens[0] >= self.eot
+ with_space = subword.startswith(" ")
+ punctuation = subword.strip() in string.punctuation
+ if special or with_space or punctuation or len(words) == 0:
+ words.append(subword)
+ word_tokens.append(subword_tokens)
+ else:
+ words[-1] = words[-1] + subword
+ word_tokens[-1].extend(subword_tokens)
+
+ return words, word_tokens
+
+
+_TASKS = (
+ "transcribe",
+ "translate",
+)
+
+_LANGUAGE_CODES = (
+ "af",
+ "am",
+ "ar",
+ "as",
+ "az",
+ "ba",
+ "be",
+ "bg",
+ "bn",
+ "bo",
+ "br",
+ "bs",
+ "ca",
+ "cs",
+ "cy",
+ "da",
+ "de",
+ "el",
+ "en",
+ "es",
+ "et",
+ "eu",
+ "fa",
+ "fi",
+ "fo",
+ "fr",
+ "gl",
+ "gu",
+ "ha",
+ "haw",
+ "he",
+ "hi",
+ "hr",
+ "ht",
+ "hu",
+ "hy",
+ "id",
+ "is",
+ "it",
+ "ja",
+ "jw",
+ "ka",
+ "kk",
+ "km",
+ "kn",
+ "ko",
+ "la",
+ "lb",
+ "ln",
+ "lo",
+ "lt",
+ "lv",
+ "mg",
+ "mi",
+ "mk",
+ "ml",
+ "mn",
+ "mr",
+ "ms",
+ "mt",
+ "my",
+ "ne",
+ "nl",
+ "nn",
+ "no",
+ "oc",
+ "pa",
+ "pl",
+ "ps",
+ "pt",
+ "ro",
+ "ru",
+ "sa",
+ "sd",
+ "si",
+ "sk",
+ "sl",
+ "sn",
+ "so",
+ "sq",
+ "sr",
+ "su",
+ "sv",
+ "sw",
+ "ta",
+ "te",
+ "tg",
+ "th",
+ "tk",
+ "tl",
+ "tr",
+ "tt",
+ "uk",
+ "ur",
+ "uz",
+ "vi",
+ "yi",
+ "yo",
+ "zh",
+ "yue",
+)
diff --git a/whisper_pipeline/faster-whisper-main/build/lib/faster_whisper/transcribe.py b/whisper_pipeline/faster-whisper-main/build/lib/faster_whisper/transcribe.py
new file mode 100644
index 0000000000000000000000000000000000000000..8652e82b0463f1d786c50ba32209b62dd167142d
--- /dev/null
+++ b/whisper_pipeline/faster-whisper-main/build/lib/faster_whisper/transcribe.py
@@ -0,0 +1,2170 @@
+import itertools
+import json
+import logging
+import os
+import random
+import zlib
+
+from collections import Counter, defaultdict
+from inspect import signature
+from typing import BinaryIO, Iterable, List, NamedTuple, Optional, Tuple, Union
+
+import ctranslate2
+import numpy as np
+import tokenizers
+import torch
+
+from pyannote.audio import Model
+from tqdm import tqdm
+
+from faster_whisper.audio import decode_audio, pad_or_trim
+from faster_whisper.feature_extractor import FeatureExtractor
+from faster_whisper.tokenizer import _LANGUAGE_CODES, Tokenizer
+from faster_whisper.utils import (
+ download_model,
+ format_timestamp,
+ get_assets_path,
+ get_end,
+ get_logger,
+)
+from faster_whisper.vad import (
+ SpeechTimestampsMap,
+ VadOptions,
+ VoiceActivitySegmentation,
+ collect_chunks,
+ get_speech_timestamps,
+ merge_chunks,
+)
+
+
+class Word(NamedTuple):
+ start: float
+ end: float
+ word: str
+ probability: float
+
+
+class Segment(NamedTuple):
+ id: int
+ seek: int
+ start: float
+ end: float
+ text: str
+ tokens: List[int]
+ avg_logprob: float
+ compression_ratio: float
+ no_speech_prob: float
+ words: Optional[List[Word]]
+ temperature: Optional[float] = 1.0
+
+
+# Added additional parameters for multilingual videos and fixes below
+class TranscriptionOptions(NamedTuple):
+ beam_size: int
+ best_of: int
+ patience: float
+ length_penalty: float
+ repetition_penalty: float
+ no_repeat_ngram_size: int
+ log_prob_threshold: Optional[float]
+ log_prob_low_threshold: Optional[float]
+ no_speech_threshold: Optional[float]
+ compression_ratio_threshold: Optional[float]
+ condition_on_previous_text: bool
+ prompt_reset_on_temperature: float
+ temperatures: List[float]
+ initial_prompt: Optional[Union[str, Iterable[int]]]
+ prefix: Optional[str]
+ suppress_blank: bool
+ suppress_tokens: Optional[List[int]]
+ without_timestamps: bool
+ max_initial_timestamp: float
+ word_timestamps: bool
+ prepend_punctuations: str
+ append_punctuations: str
+ multilingual: bool
+ output_language: Optional[str]
+ max_new_tokens: Optional[int]
+ clip_timestamps: Union[str, List[float]]
+ hallucination_silence_threshold: Optional[float]
+ hotwords: Optional[str]
+
+
+class TranscriptionInfo(NamedTuple):
+ language: str
+ language_probability: float
+ duration: float
+ duration_after_vad: float
+ all_language_probs: Optional[List[Tuple[str, float]]]
+ transcription_options: TranscriptionOptions
+ vad_options: VadOptions
+
+
+# The code below is originally from HF pipeline and is used in whisper-x
+# (https://github.com/m-bain/whisperX) and adapted for faster_whisper
+
+
+class BatchedInferencePipeline:
+ """
+ Huggingface Pipeline wrapper for WhisperModel.
+ Copyright (c) 2022, Max Bain
+ All rights reserved.
+ Modified by Mobius Labs GmbH
+ """
+
+ def __init__(
+ self,
+ model,
+ use_vad_model: bool = True,
+ options: Optional[NamedTuple] = None,
+ tokenizer=None,
+ chunk_length: int = 30,
+ vad_device: Union[int, str, "torch.device"] = "auto",
+ vad_onset: float = 0.500,
+ vad_offset: float = 0.363,
+ language: Optional[str] = None,
+ ):
+ self.model: WhisperModel = model
+ self.tokenizer = tokenizer
+ self.options = options
+ self.preset_language = language
+ self.use_vad_model = use_vad_model
+ self.vad_onset = vad_onset
+ self.vad_offset = vad_offset
+ self.vad_model_path = os.path.join(get_assets_path(), "pyannote_vad_model.bin")
+ if self.use_vad_model:
+ self.vad_device = self.get_device(vad_device)
+ self.vad_model = self.load_vad_model(
+ vad_onset=self.vad_onset, vad_offset=self.vad_offset
+ )
+ else:
+ self.vad_model = None
+ self.chunk_length = chunk_length # VAD merging size
+ self.last_speech_timestamp = 0.0
+
+ def get_device(self, device: Union[int, str, "torch.device"]):
+ """
+ Converts the input device into a torch.device object.
+
+ The input can be an integer, a string, or a `torch.device` object.
+
+ The function handles a special case where the input device is "auto".
+ When "auto" is specified, the device will default to the
+ device of the model (self.model.device). If the model's device is also "auto",
+ it selects "cuda" if a CUDA-capable device is available; otherwise, it selects "cpu".
+ """
+ if isinstance(device, torch.device):
+ return device
+ elif isinstance(device, str):
+ if device == "auto" and self.model.device == "auto":
+ device = "cuda" if torch.cuda.is_available() else "cpu"
+ elif device == "auto":
+ device = self.model.device
+ return torch.device(device)
+ elif device < 0:
+ return torch.device("cpu")
+ else:
+ return torch.device(f"cuda:{device}")
+
+ def forward(self, features, segments_metadata, **forward_params):
+ encoder_output, outputs = self.model.generate_segment_batched(
+ features, self.tokenizer, forward_params
+ )
+
+ segmented_outputs = []
+ segment_sizes = []
+ for segment_metadata, output in zip(segments_metadata, outputs):
+ duration = segment_metadata["end_time"] - segment_metadata["start_time"]
+ segment_size = int(duration * self.model.frames_per_second)
+ segment_sizes.append(segment_size)
+ (
+ subsegments,
+ seek,
+ single_timestamp_ending,
+ ) = self.model._split_segments_by_timestamps(
+ tokenizer=self.tokenizer,
+ tokens=output["tokens"],
+ time_offset=segment_metadata["start_time"],
+ segment_size=segment_size,
+ segment_duration=duration,
+ seek=0,
+ )
+ segmented_outputs.append(
+ [
+ dict(
+ text=self.tokenizer.decode(subsegment["tokens"]),
+ avg_logprob=output["avg_logprob"],
+ no_speech_prob=output["no_speech_prob"],
+ tokens=subsegment["tokens"],
+ start=subsegment["start"],
+ end=subsegment["end"],
+ compression_ratio=get_compression_ratio(
+ self.tokenizer.decode(subsegment["tokens"])
+ ),
+ )
+ for subsegment in subsegments
+ ]
+ )
+ if forward_params["word_timestamps"]:
+ self.last_speech_timestamp = self.model.add_word_timestamps(
+ segmented_outputs,
+ self.tokenizer,
+ encoder_output,
+ segment_sizes,
+ forward_params["prepend_punctuations"],
+ forward_params["append_punctuations"],
+ self.last_speech_timestamp,
+ )
+
+ return segmented_outputs
+
+ def get_language_and_tokenizer(
+ self, audio, task: Optional[str] = None, language: Optional[str] = None
+ ):
+ all_language_probs = None
+ language_probability = 1.0
+
+ if self.tokenizer is None:
+ if not language:
+ (
+ language,
+ language_probability,
+ all_language_probs,
+ ) = self.model.detect_language(audio)
+ task = task or "transcribe"
+ self.tokenizer = Tokenizer(
+ self.model.hf_tokenizer,
+ self.model.model.is_multilingual,
+ task=task,
+ language=language,
+ )
+ else:
+ if task is not None:
+ self.tokenizer.task = self.tokenizer.tokenizer.token_to_id(
+ f"<|{task}|>"
+ )
+
+ if language is not None:
+ self.tokenizer.language = self.tokenizer.tokenizer.token_to_id(
+ f"<|{language}|>"
+ )
+ self.tokenizer.language_code = language
+
+ return language, language_probability, task, all_language_probs
+
+ @staticmethod
+ def audio_split(audio, segments, sampling_rate):
+ """Returns splitted audio chunks as iterator"""
+ audio_segments = []
+ segments_metadata = []
+ for seg in segments:
+ f1 = int(seg["start"] * sampling_rate)
+ f2 = int(seg["end"] * sampling_rate)
+ seg_metadata = {
+ "start_time": seg["start"],
+ "end_time": seg["end"],
+ "stitched_seg": seg["segments"],
+ }
+ audio_segments.append(audio[f1:f2])
+ segments_metadata.append(seg_metadata)
+ return audio_segments, segments_metadata
+
+ def load_vad_model(self, vad_onset=0.500, vad_offset=0.363):
+ vad_model = Model.from_pretrained(self.vad_model_path)
+ hyperparameters = {
+ "onset": vad_onset,
+ "offset": vad_offset,
+ "min_duration_on": 0.1,
+ "min_duration_off": 0.1,
+ }
+
+ vad_pipeline = VoiceActivitySegmentation(
+ segmentation=vad_model, device=torch.device(self.vad_device)
+ )
+ vad_pipeline.instantiate(hyperparameters)
+ return vad_pipeline
+
+ def transcribe(
+ self,
+ audio: Union[str, torch.Tensor, np.ndarray],
+ vad_segments: Optional[List[dict]] = None,
+ batch_size: int = 16,
+ language: Optional[str] = None,
+ task: str = None,
+ log_progress: bool = False,
+ beam_size: int = 5,
+ best_of: int = 5,
+ patience: float = 1,
+ length_penalty: float = 1,
+ repetition_penalty: float = 1,
+ no_repeat_ngram_size: int = 0,
+ temperature: Union[float, List[float], Tuple[float, ...]] = [
+ 0.0,
+ 0.2,
+ 0.4,
+ 0.6,
+ 0.8,
+ 1.0,
+ ],
+ compression_ratio_threshold: Optional[float] = 2.4,
+ log_prob_threshold: Optional[float] = -1.0,
+ log_prob_low_threshold: Optional[float] = None,
+ no_speech_threshold: Optional[float] = 0.6,
+ initial_prompt: Optional[Union[str, Iterable[int]]] = None,
+ prefix: Optional[str] = None,
+ suppress_blank: bool = True,
+ suppress_tokens: Optional[List[int]] = [-1],
+ prepend_punctuations: str = "\"'“¿([{-",
+ append_punctuations: str = "\"'.。,，!！?？:：”)]}、",
+ max_new_tokens: Optional[int] = None,
+ hotwords: Optional[str] = None,
+ word_timestamps: bool = False,
+ without_timestamps: bool = True,
+ ) -> Tuple[Iterable[Segment], TranscriptionInfo]:
+ """transcribe audio in chunks in batched fashion and return with language info.
+
+ Arguments:
+ audio: audio file as numpy array/path for batched transcription.
+ vad_segments: Optionally provide list of dictionaries each containing "start", "end",
+ and "segments" keys.
+ "start" and "end" keys specify the start and end of the voiced region within
+ 30 sec boundary. An additional key "segments" contains all the start
+ and end of voiced regions within that 30sec boundary as a list of tuples.
+ If no vad_segments specified, it uses internal vad model automatically segment them.
+ batch_size: the maximum number of parallel requests to model for decoding.
+ language: The language spoken in the audio.
+ task: either "transcribe" or "translate".
+ log_progress: whether to show progress bar or not.
+ beam_size: Beam size to use for decoding.
+ best_of: Number of candidates when sampling with non-zero temperature.
+ patience: Beam search patience factor.
+ length_penalty: Exponential length penalty constant.
+ repetition_penalty: Penalty applied to the score of previously generated tokens
+ (set > 1 to penalize).
+ no_repeat_ngram_size: Prevent repetitions of ngrams with this size (set 0 to disable).
+ temperature: Temperature for sampling. It can be a tuple of temperatures,
+ which will be successively used upon failures according to either
+ `compression_ratio_threshold` or `log_prob_threshold`.
+ compression_ratio_threshold: If the gzip compression ratio is above this value,
+ treat as failed.
+ log_prob_threshold: If the average log probability over sampled tokens is
+ below this value, treat as failed.
+ log_prob_low_threshold: This parameter alone is sufficient to skip an output text,
+ whereas log_prob_threshold also looks for appropriate no_speech_threshold value.
+ This value should be less than log_prob_threshold.
+ no_speech_threshold: If the no_speech probability is higher than this value AND
+ the average log probability over sampled tokens is below `log_prob_threshold`,
+ consider the segment as silent.
+ initial_prompt: Optional text string or iterable of token ids to provide as a
+ prompt for the first window.
+ prefix: Optional text to provide as a prefix for the first window.
+ suppress_blank: Suppress blank outputs at the beginning of the sampling.
+ suppress_tokens: List of token IDs to suppress. -1 will suppress a default set
+ of symbols as defined in `tokenizer.non_speech_tokens()`.
+ prepend_punctuations: If word_timestamps is True, merge these punctuation symbols
+ with the next word
+ append_punctuations: If word_timestamps is True, merge these punctuation symbols
+ with the previous word
+ max_new_tokens: Maximum number of new tokens to generate per-chunk. If not set,
+ the maximum will be set by the default max_length.
+ hotwords:
+ Hotwords/hint phrases to the model. Has no effect if prefix is not None.
+ word_timestamps: Extract word-level timestamps using the cross-attention pattern
+ and dynamic time warping, and include the timestamps for each word in each segment.
+ Set as False.
+ without_timestamps: Only sample text tokens.
+
+ Static params: (Fixed for batched version)
+ max_initial_timestamp: The initial timestamp cannot be later than this, set at 0.0.
+ multilingual: If True, perform transcription on multilingual videos. Set as False.
+ output_language: Valid only if multilingual is set to True.
+ Specifies the string representing the output language. One of
+ 'en' (English) or 'hybrid' (code-switched transcription). set as None.
+ condition_on_previous_text: If True, the previous output of the model is provided
+ as a prompt for the next window; disabling may make the text inconsistent across
+ windows, but the model becomes less prone to getting stuck in a failure loop,
+ such as repetition looping or timestamps going out of sync. Set as False
+ prompt_reset_on_temperature: Resets prompt if temperature is above this value.
+ Arg has effect only if condition_on_previous_text is True. Set at 0.5
+ #TODO: support "hallucination_silence_threshold" when "word_timestamps=True"
+ hallucination_silence_threshold: Optional[float]
+ When word_timestamps is True, skip silent periods longer than this threshold
+ (in seconds) when a possible hallucination is detected. set as None.
+ clip_timestamps:
+ Comma-separated list start,end,start,end,... timestamps (in seconds) of clips to
+ process. The last end timestamp defaults to the end of the file. Set as "0".
+
+ unused:
+ language_detection_threshold: If the maximum probability of the language tokens is
+ higher than this value, the language is detected.
+ language_detection_segments: Number of segments to consider for the language detection.
+ vad_filter: Enable the voice activity detection (VAD) to filter out parts of the audio
+ without speech. This step is using the Silero VAD model
+ https://github.com/snakers4/silero-vad.
+ vad_parameters: Dictionary of Silero VAD parameters or VadOptions class (see available
+ parameters and default values in the class `VadOptions`).
+ chunk_length: The length of audio segments. If it is not None, it will overwrite the
+ default chunk_length of the FeatureExtractor.
+
+
+ Returns:
+ A tuple with:
+
+ - a generator over transcribed batched segments.
+ - an instance of TranscriptionInfo.
+ """
+
+ sampling_rate = self.model.feature_extractor.sampling_rate
+
+ if isinstance(audio, np.ndarray):
+ audio = torch.from_numpy(audio)
+ elif not isinstance(audio, torch.Tensor):
+ audio = decode_audio(audio, sampling_rate=sampling_rate)
+ duration = audio.shape[0] / sampling_rate
+
+ # if no segment split is provided, use vad_model and generate segments
+ if not vad_segments:
+ # run the audio if it is less than 30 sec even without vad_segments
+ if self.use_vad_model:
+ vad_segments = self.vad_model(
+ {
+ "waveform": audio.unsqueeze(0),
+ "sample_rate": 16000,
+ }
+ )
+ vad_segments = merge_chunks(
+ vad_segments,
+ self.chunk_length,
+ onset=self.vad_onset,
+ offset=self.vad_offset,
+ )
+ elif duration < self.chunk_length:
+ vad_segments = [
+ {"start": 0.0, "end": duration, "segments": [(0.0, duration)]}
+ ]
+ else:
+ raise RuntimeError(
+ "No vad segments found. Set 'use_vad_model' to True while loading the model"
+ )
+ if self.model.model.is_multilingual:
+ language = language or self.preset_language
+ elif language != "en":
+ if language is not None:
+ self.model.logger.warning(
+ f"English-only model is used, but {language} language is"
+ "chosen, setting language to 'en'."
+ )
+ language = "en"
+
+ (
+ language,
+ language_probability,
+ task,
+ all_language_probs,
+ ) = self.get_language_and_tokenizer(audio, task, language)
+
+ duration_after_vad = sum(
+ segment["end"] - segment["start"] for segment in vad_segments
+ )
+
+ # batched options: see the difference with default options in WhisperModel
+ batched_options = TranscriptionOptions(
+ beam_size=beam_size,
+ best_of=best_of,
+ patience=patience,
+ length_penalty=length_penalty,
+ repetition_penalty=repetition_penalty,
+ no_repeat_ngram_size=no_repeat_ngram_size,
+ log_prob_threshold=log_prob_threshold,
+ log_prob_low_threshold=log_prob_low_threshold,
+ no_speech_threshold=no_speech_threshold,
+ compression_ratio_threshold=compression_ratio_threshold,
+ temperatures=(
+ temperature if isinstance(temperature, (list, tuple)) else [temperature]
+ ),
+ initial_prompt=initial_prompt,
+ prefix=prefix,
+ suppress_blank=suppress_blank,
+ suppress_tokens=get_suppressed_tokens(self.tokenizer, suppress_tokens),
+ prepend_punctuations=prepend_punctuations,
+ append_punctuations=append_punctuations,
+ max_new_tokens=max_new_tokens,
+ hotwords=hotwords,
+ word_timestamps=word_timestamps,
+ hallucination_silence_threshold=None,
+ condition_on_previous_text=False,
+ clip_timestamps="0",
+ prompt_reset_on_temperature=0.5,
+ multilingual=False,
+ output_language=None,
+ without_timestamps=without_timestamps,
+ max_initial_timestamp=0.0,
+ )
+
+ info = TranscriptionInfo(
+ language=language,
+ language_probability=language_probability,
+ duration=duration,
+ duration_after_vad=duration_after_vad,
+ transcription_options=batched_options,
+ vad_options=None,
+ all_language_probs=all_language_probs,
+ )
+
+ audio_segments, segments_metadata = self.audio_split(
+ audio, vad_segments, sampling_rate
+ )
+ to_cpu = (
+ self.model.model.device == "cuda" and len(self.model.model.device_index) > 1
+ )
+ audio_segments = torch.nested.nested_tensor(audio_segments).to_padded_tensor(
+ padding=0
+ )
+ features = torch.stack(
+ [
+ self.model.feature_extractor(audio_segment, to_cpu=to_cpu)[
+ ..., : self.model.feature_extractor.nb_max_frames
+ ]
+ for audio_segment in audio_segments
+ ]
+ )
+
+ segments = self._batched_segments_generator(
+ features,
+ segments_metadata,
+ batch_size,
+ batched_options,
+ log_progress,
+ )
+
+ return segments, info
+
+ def _batched_segments_generator(
+ self, features, segments_metadata, batch_size, options, log_progress
+ ):
+ pbar = tqdm(total=len(features), disable=not log_progress, position=0)
+ seg_idx = 0
+ for i in range(0, len(features), batch_size):
+ results = self.forward(
+ features[i : i + batch_size],
+ segments_metadata[i : i + batch_size],
+ **options._asdict(),
+ )
+
+ for result in results:
+ for segment in result:
+ seg_idx += 1
+ yield Segment(
+ seek=int(result[-1]["end"] * self.model.frames_per_second),
+ id=seg_idx,
+ text=segment["text"],
+ start=round(segment["start"], 3),
+ end=round(segment["end"], 3),
+ words=(
+ None
+ if not options.word_timestamps
+ else [Word(**word) for word in segment["words"]]
+ ),
+ tokens=segment["tokens"],
+ avg_logprob=segment["avg_logprob"],
+ no_speech_prob=segment["no_speech_prob"],
+ compression_ratio=segment["compression_ratio"],
+ )
+
+ pbar.update(1)
+
+ pbar.close()
+ # revert the tokenizer if multilingual inference is enabled
+ if self.preset_language is None:
+ self.tokenizer = None
+ self.last_speech_timestamp = 0.0
+
+
+class WhisperModel:
+ def __init__(
+ self,
+ model_size_or_path: str,
+ device: str = "auto",
+ device_index: Union[int, List[int]] = 0,
+ compute_type: str = "default",
+ cpu_threads: int = 16,
+ num_workers: int = 1,
+ download_root: Optional[str] = None,
+ local_files_only: bool = False,
+ files: dict = None,
+ **model_kwargs,
+ ):
+ """Initializes the Whisper model.
+
+ Args:
+ model_size_or_path: Size of the model to use (tiny, tiny.en, base, base.en,
+ small, small.en, distil-small.en, medium, medium.en, distil-medium.en, large-v1,
+ large-v2, large-v3, large, distil-large-v2 or distil-large-v3), a path to a
+ converted model directory, or a CTranslate2-converted Whisper model ID from the HF Hub.
+ When a size or a model ID is configured, the converted model is downloaded
+ from the Hugging Face Hub.
+ device: Device to use for computation ("cpu", "cuda", "auto").
+ device_index: Device ID to use.
+ The model can also be loaded on multiple GPUs by passing a list of IDs
+ (e.g. [0, 1, 2, 3]). In that case, multiple transcriptions can run in parallel
+ when transcribe() is called from multiple Python threads (see also num_workers).
+ compute_type: Type to use for computation.
+ See https://opennmt.net/CTranslate2/quantization.html.
+ cpu_threads: Number of threads to use when running on CPU (4 by default).
+ A non zero value overrides the OMP_NUM_THREADS environment variable.
+ num_workers: When transcribe() is called from multiple Python threads,
+ having multiple workers enables true parallelism when running the model
+ (concurrent calls to self.model.generate() will run in parallel).
+ This can improve the global throughput at the cost of increased memory usage.
+ download_root: Directory where the models should be saved. If not set, the models
+ are saved in the standard Hugging Face cache directory.
+ local_files_only: If True, avoid downloading the file and return the path to the
+ local cached file if it exists.
+ files: Load model files from the memory. This argument is a dictionary mapping file names
+ to file contents as file-like or bytes objects. If this is set, model_path acts as an
+ identifier for this model.
+ """
+ self.logger = get_logger()
+
+ tokenizer_bytes, preprocessor_bytes = None, None
+ if files:
+ model_path = model_size_or_path
+ tokenizer_bytes = files.pop("tokenizer.json", None)
+ preprocessor_bytes = files.pop("preprocessor_config.json", None)
+ elif os.path.isdir(model_size_or_path):
+ model_path = model_size_or_path
+ else:
+ model_path = download_model(
+ model_size_or_path,
+ local_files_only=local_files_only,
+ cache_dir=download_root,
+ )
+ self.device = device
+ # set the random seed to make sure consistency across runs
+ ctranslate2.set_random_seed(42)
+ self.model = ctranslate2.models.Whisper(
+ model_path,
+ device=self.device,
+ device_index=device_index,
+ compute_type=compute_type,
+ intra_threads=cpu_threads,
+ inter_threads=num_workers,
+ files=files,
+ **model_kwargs,
+ )
+
+ tokenizer_file = os.path.join(model_path, "tokenizer.json")
+ if tokenizer_bytes:
+ self.hf_tokenizer = tokenizers.Tokenizer.from_buffer(tokenizer_bytes)
+ elif os.path.isfile(tokenizer_file):
+ self.hf_tokenizer = tokenizers.Tokenizer.from_file(tokenizer_file)
+ else:
+ self.hf_tokenizer = tokenizers.Tokenizer.from_pretrained(
+ "openai/whisper-tiny" + ("" if self.model.is_multilingual else ".en")
+ )
+ self.feat_kwargs = self._get_feature_kwargs(model_path, preprocessor_bytes)
+ self.feature_extractor = FeatureExtractor(
+ **self.feat_kwargs, device=self.device
+ )
+ self.input_stride = 2
+ self.num_samples_per_token = (
+ self.feature_extractor.hop_length * self.input_stride
+ )
+ self.frames_per_second = (
+ self.feature_extractor.sampling_rate // self.feature_extractor.hop_length
+ )
+ self.tokens_per_second = (
+ self.feature_extractor.sampling_rate // self.num_samples_per_token
+ )
+ self.time_precision = 0.02
+ self.max_length = 448
+
+ @property
+ def supported_languages(self) -> List[str]:
+ """The languages supported by the model."""
+ return list(_LANGUAGE_CODES) if self.model.is_multilingual else ["en"]
+
+ def _get_feature_kwargs(self, model_path, preprocessor_bytes=None) -> dict:
+ config = {}
+ try:
+ config_path = os.path.join(model_path, "preprocessor_config.json")
+ if preprocessor_bytes:
+ config = json.loads(preprocessor_bytes)
+ elif os.path.isfile(config_path):
+ with open(config_path, "r", encoding="utf-8") as file:
+ config = json.load(file)
+ else:
+ return config
+ valid_keys = signature(FeatureExtractor.__init__).parameters.keys()
+ return {k: v for k, v in config.items() if k in valid_keys}
+ except json.JSONDecodeError as e:
+ self.logger.warning("Could not load preprocessor config: %s", e)
+
+ return config
+
+ def transcribe(
+ self,
+ audio: Union[str, BinaryIO, torch.Tensor, np.ndarray],
+ language: Optional[str] = None,
+ task: str = "transcribe",
+ beam_size: int = 5,
+ best_of: int = 5,
+ patience: float = 1,
+ length_penalty: float = 1,
+ repetition_penalty: float = 1,
+ no_repeat_ngram_size: int = 0,
+ temperature: Union[float, List[float], Tuple[float, ...]] = [
+ 0.0,
+ 0.2,
+ 0.4,
+ 0.6,
+ 0.8,
+ 1.0,
+ ],
+ compression_ratio_threshold: Optional[float] = 2.4,
+ log_prob_threshold: Optional[float] = -1.0,
+ log_prob_low_threshold: Optional[float] = None,
+ no_speech_threshold: Optional[float] = 0.6,
+ condition_on_previous_text: bool = True,
+ prompt_reset_on_temperature: float = 0.5,
+ initial_prompt: Optional[Union[str, Iterable[int]]] = None,
+ prefix: Optional[str] = None,
+ suppress_blank: bool = True,
+ suppress_tokens: Optional[List[int]] = [-1],
+ without_timestamps: bool = False,
+ max_initial_timestamp: float = 1.0,
+ word_timestamps: bool = False,
+ prepend_punctuations: str = "\"'“¿([{-",
+ append_punctuations: str = "\"'.。,，!！?？:：”)]}、",
+ multilingual: bool = False,
+ output_language: Optional[str] = None,
+ vad_filter: bool = False,
+ vad_parameters: Optional[Union[dict, VadOptions]] = None,
+ max_new_tokens: Optional[int] = None,
+ chunk_length: Optional[int] = None,
+ clip_timestamps: Union[str, List[float]] = "0",
+ hallucination_silence_threshold: Optional[float] = None,
+ hotwords: Optional[str] = None,
+ language_detection_threshold: Optional[float] = None,
+ language_detection_segments: int = 1,
+ ) -> Tuple[Iterable[Segment], TranscriptionInfo]:
+ """Transcribes an input file.
+
+ Arguments:
+ audio: Path to the input file (or a file-like object), or the audio waveform.
+ language: The language spoken in the audio. It should be a language code such
+ as "en" or "fr". If not set, the language will be detected in the first 30 seconds
+ of audio.
+ task: Task to execute (transcribe or translate).
+ beam_size: Beam size to use for decoding.
+ best_of: Number of candidates when sampling with non-zero temperature.
+ patience: Beam search patience factor.
+ length_penalty: Exponential length penalty constant.
+ repetition_penalty: Penalty applied to the score of previously generated tokens
+ (set > 1 to penalize).
+ no_repeat_ngram_size: Prevent repetitions of ngrams with this size (set 0 to disable).
+ temperature: Temperature for sampling. It can be a tuple of temperatures,
+ which will be successively used upon failures according to either
+ `compression_ratio_threshold` or `log_prob_threshold`.
+ compression_ratio_threshold: If the gzip compression ratio is above this value,
+ treat as failed.
+ log_prob_threshold: If the average log probability over sampled tokens is
+ below this value, treat as failed.
+ log_prob_low_threshold: This parameter alone is sufficient to skip an output text,
+ wheras log_prob_threshold also looks for appropriate no_speech_threshold value.
+ This value should be less than log_prob_threshold.
+ no_speech_threshold: If the no_speech probability is higher than this value AND
+ the average log probability over sampled tokens is below `log_prob_threshold`,
+ consider the segment as silent.
+ condition_on_previous_text: If True, the previous output of the model is provided
+ as a prompt for the next window; disabling may make the text inconsistent across
+ windows, but the model becomes less prone to getting stuck in a failure loop,
+ such as repetition looping or timestamps going out of sync.
+ prompt_reset_on_temperature: Resets prompt if temperature is above this value.
+ Arg has effect only if condition_on_previous_text is True.
+ initial_prompt: Optional text string or iterable of token ids to provide as a
+ prompt for the first window.
+ prefix: Optional text to provide as a prefix for the first window.
+ suppress_blank: Suppress blank outputs at the beginning of the sampling.
+ suppress_tokens: List of token IDs to suppress. -1 will suppress a default set
+ of symbols as defined in `tokenizer.non_speech_tokens()`.
+ without_timestamps: Only sample text tokens.
+ max_initial_timestamp: The initial timestamp cannot be later than this.
+ word_timestamps: Extract word-level timestamps using the cross-attention pattern
+ and dynamic time warping, and include the timestamps for each word in each segment.
+ prepend_punctuations: If word_timestamps is True, merge these punctuation symbols
+ with the next word
+ append_punctuations: If word_timestamps is True, merge these punctuation symbols
+ with the previous word
+ multilingual: If True, perform transcription on multilingual videos
+ and return the transcript based
+ on the 'output_language' flag.
+ output_language: Valid only if multilingual is set to True.
+ Specifies the string representing the output language. One of
+ 'en' (English) or 'hybrid' (code-switched transcription).
+ vad_filter: Enable the voice activity detection (VAD) to filter out parts of the audio
+ without speech. This step is using the Silero VAD model
+ https://github.com/snakers4/silero-vad.
+ vad_parameters: Dictionary of Silero VAD parameters or VadOptions class (see available
+ parameters and default values in the class `VadOptions`).
+ max_new_tokens: Maximum number of new tokens to generate per-chunk. If not set,
+ the maximum will be set by the default max_length.
+ chunk_length: The length of audio segments. If it is not None, it will overwrite the
+ default chunk_length of the FeatureExtractor.
+ clip_timestamps:
+ Comma-separated list start,end,start,end,... timestamps (in seconds) of clips to
+ process. The last end timestamp defaults to the end of the file.
+ vad_filter will be ignored if clip_timestamps is used.
+ hallucination_silence_threshold:
+ When word_timestamps is True, skip silent periods longer than this threshold
+ (in seconds) when a possible hallucination is detected
+ hotwords:
+ Hotwords/hint phrases to provide the model with. Has no effect if prefix is not None.
+ language_detection_threshold: If the maximum probability of the language tokens is higher
+ than this value, the language is detected.
+ language_detection_segments: Number of segments to consider for the language detection.
+ Returns:
+ A tuple with:
+
+ - a generator over transcribed segments
+ - an instance of TranscriptionInfo
+ """
+
+ sampling_rate = self.feature_extractor.sampling_rate
+
+ if isinstance(audio, np.ndarray):
+ audio = torch.from_numpy(audio)
+ elif not isinstance(audio, torch.Tensor):
+ audio = decode_audio(audio, sampling_rate=sampling_rate)
+
+ duration = audio.shape[0] / sampling_rate
+ duration_after_vad = duration
+
+ self.logger.info(
+ "Processing audio with duration %s", format_timestamp(duration)
+ )
+
+ if vad_filter and clip_timestamps == "0":
+ if vad_parameters is None:
+ vad_parameters = VadOptions()
+ elif isinstance(vad_parameters, dict):
+ vad_parameters = VadOptions(**vad_parameters)
+ speech_chunks = get_speech_timestamps(audio, vad_parameters)
+ audio = collect_chunks(audio, speech_chunks)
+ duration_after_vad = audio.shape[0] / sampling_rate
+
+ self.logger.info(
+ "VAD filter removed %s of audio",
+ format_timestamp(duration - duration_after_vad),
+ )
+
+ if self.logger.isEnabledFor(logging.DEBUG):
+ self.logger.debug(
+ "VAD filter kept the following audio segments: %s",
+ ", ".join(
+ "[%s -> %s]"
+ % (
+ format_timestamp(chunk["start"] / sampling_rate),
+ format_timestamp(chunk["end"] / sampling_rate),
+ )
+ for chunk in speech_chunks
+ ),
+ )
+
+ else:
+ speech_chunks = None
+
+ to_cpu = self.model.device == "cuda" and len(self.model.device_index) > 1
+ features = self.feature_extractor(
+ audio, chunk_length=chunk_length, to_cpu=to_cpu
+ )
+
+ encoder_output = None
+ all_language_probs = None
+
+ # setting output_language for multilingual videos
+ if multilingual:
+ if output_language is None:
+ output_language = "en"
+ elif output_language not in ["en", "hybrid"]:
+ raise ValueError("Output language needs to be one of 'en'/'hybrid'.")
+
+ # detecting the language if not provided
+ if language is None:
+ if not self.model.is_multilingual:
+ language = "en"
+ language_probability = 1
+ else:
+ if (
+ language_detection_segments is None
+ or language_detection_segments < 1
+ ):
+ language_detection_segments = 1
+ start_timestamp = (
+ float(clip_timestamps.split(",")[0])
+ if isinstance(clip_timestamps, str)
+ else clip_timestamps[0]
+ )
+ content_frames = (
+ features.shape[-1] - self.feature_extractor.nb_max_frames
+ )
+ seek = (
+ int(start_timestamp * self.frames_per_second)
+ if start_timestamp * self.frames_per_second < content_frames
+ else 0
+ )
+ end_frames = min(
+ seek
+ + self.feature_extractor.nb_max_frames
+ * language_detection_segments,
+ content_frames,
+ )
+ detected_language_info = {}
+ while seek <= end_frames:
+ segment = features[
+ :, seek : seek + self.feature_extractor.nb_max_frames
+ ]
+ encoder_output = self.encode(segment)
+ # results is a list of tuple[str, float] with language names and
+ # probabilities.
+ results = self.model.detect_language(encoder_output)[0]
+ # Parse language names to strip out markers
+ all_language_probs = [
+ (token[2:-2], prob) for (token, prob) in results
+ ]
+ # Get top language token and probability
+ language, language_probability = all_language_probs[0]
+ if (
+ language_detection_threshold is None
+ or language_probability > language_detection_threshold
+ ):
+ break
+ detected_language_info.setdefault(language, []).append(
+ language_probability
+ )
+ seek += segment.shape[-1]
+ else:
+ # If no language detected for all segments, the majority vote of the highest
+ # projected languages for all segments is used to determine the language.
+ language = max(
+ detected_language_info,
+ key=lambda lang: len(detected_language_info[lang]),
+ )
+ language_probability = max(detected_language_info[language])
+
+ self.logger.info(
+ "Detected language '%s' with probability %.2f",
+ language,
+ language_probability,
+ )
+ else:
+ if not self.model.is_multilingual and language != "en":
+ self.logger.warning(
+ "The current model is English-only but the language parameter is set to '%s'; "
+ "using 'en' instead." % language
+ )
+ language = "en"
+
+ language_probability = 1
+
+ tokenizer = Tokenizer(
+ self.hf_tokenizer,
+ self.model.is_multilingual,
+ task=task,
+ language=language,
+ )
+
+ options = TranscriptionOptions(
+ beam_size=beam_size,
+ best_of=best_of,
+ patience=patience,
+ length_penalty=length_penalty,
+ repetition_penalty=repetition_penalty,
+ no_repeat_ngram_size=no_repeat_ngram_size,
+ log_prob_threshold=log_prob_threshold,
+ log_prob_low_threshold=log_prob_low_threshold,
+ no_speech_threshold=no_speech_threshold,
+ compression_ratio_threshold=compression_ratio_threshold,
+ condition_on_previous_text=condition_on_previous_text,
+ prompt_reset_on_temperature=prompt_reset_on_temperature,
+ temperatures=(
+ temperature if isinstance(temperature, (list, tuple)) else [temperature]
+ ),
+ initial_prompt=initial_prompt,
+ prefix=prefix,
+ suppress_blank=suppress_blank,
+ suppress_tokens=(
+ get_suppressed_tokens(tokenizer, suppress_tokens)
+ if suppress_tokens
+ else suppress_tokens
+ ),
+ without_timestamps=without_timestamps,
+ max_initial_timestamp=max_initial_timestamp,
+ word_timestamps=word_timestamps,
+ prepend_punctuations=prepend_punctuations,
+ append_punctuations=append_punctuations,
+ multilingual=multilingual,
+ output_language=output_language,
+ max_new_tokens=max_new_tokens,
+ clip_timestamps=clip_timestamps,
+ hallucination_silence_threshold=hallucination_silence_threshold,
+ hotwords=hotwords,
+ )
+
+ segments = self.generate_segments(features, tokenizer, options, encoder_output)
+
+ if speech_chunks:
+ segments = restore_speech_timestamps(segments, speech_chunks, sampling_rate)
+
+ info = TranscriptionInfo(
+ language=language,
+ language_probability=language_probability,
+ duration=duration,
+ duration_after_vad=duration_after_vad,
+ transcription_options=options,
+ vad_options=vad_parameters,
+ all_language_probs=all_language_probs,
+ )
+ return segments, info
+
+ def _split_segments_by_timestamps(
+ self,
+ tokenizer: Tokenizer,
+ tokens: List[int],
+ time_offset: float,
+ segment_size: int,
+ segment_duration: float,
+ seek: int,
+ ) -> List[List[int]]:
+ current_segments = []
+ single_timestamp_ending = (
+ len(tokens) >= 2 and tokens[-2] < tokenizer.timestamp_begin <= tokens[-1]
+ )
+
+ consecutive_timestamps = [
+ i
+ for i in range(len(tokens))
+ if i > 0
+ and tokens[i] >= tokenizer.timestamp_begin
+ and tokens[i - 1] >= tokenizer.timestamp_begin
+ ]
+
+ if len(consecutive_timestamps) > 0:
+ slices = list(consecutive_timestamps)
+ if single_timestamp_ending:
+ slices.append(len(tokens))
+
+ last_slice = 0
+ for current_slice in slices:
+ sliced_tokens = tokens[last_slice:current_slice]
+ start_timestamp_position = sliced_tokens[0] - tokenizer.timestamp_begin
+ end_timestamp_position = sliced_tokens[-1] - tokenizer.timestamp_begin
+ start_time = (
+ time_offset + start_timestamp_position * self.time_precision
+ )
+ end_time = time_offset + end_timestamp_position * self.time_precision
+
+ current_segments.append(
+ dict(
+ seek=seek,
+ start=start_time,
+ end=end_time,
+ tokens=sliced_tokens,
+ )
+ )
+ last_slice = current_slice
+
+ if single_timestamp_ending:
+ # single timestamp at the end means no speech after the last timestamp.
+ seek += segment_size
+ else:
+ # otherwise, ignore the unfinished segment and seek to the last timestamp
+ last_timestamp_position = (
+ tokens[last_slice - 1] - tokenizer.timestamp_begin
+ )
+ seek += last_timestamp_position * self.input_stride
+
+ else:
+ duration = segment_duration
+ timestamps = [
+ token for token in tokens if token >= tokenizer.timestamp_begin
+ ]
+ if len(timestamps) > 0 and timestamps[-1] != tokenizer.timestamp_begin:
+ last_timestamp_position = timestamps[-1] - tokenizer.timestamp_begin
+ duration = last_timestamp_position * self.time_precision
+
+ current_segments.append(
+ dict(
+ seek=seek,
+ start=time_offset,
+ end=time_offset + duration,
+ tokens=tokens,
+ )
+ )
+
+ seek += segment_size
+
+ return current_segments, seek, single_timestamp_ending
+
+ def generate_segments(
+ self,
+ features: torch.Tensor,
+ tokenizer: Tokenizer,
+ options: TranscriptionOptions,
+ encoder_output: Optional[ctranslate2.StorageView] = None,
+ ) -> Iterable[Segment]:
+ content_frames = features.shape[-1] - self.feature_extractor.nb_max_frames
+ content_duration = float(content_frames * self.feature_extractor.time_per_frame)
+
+ if isinstance(options.clip_timestamps, str):
+ options = options._replace(
+ clip_timestamps=[
+ float(ts)
+ for ts in (
+ options.clip_timestamps.split(",")
+ if options.clip_timestamps
+ else []
+ )
+ ]
+ )
+ seek_points: List[int] = [
+ round(ts * self.frames_per_second) for ts in options.clip_timestamps
+ ]
+ if len(seek_points) == 0:
+ seek_points.append(0)
+ if len(seek_points) % 2 == 1:
+ seek_points.append(content_frames)
+ seek_clips: List[Tuple[int, int]] = list(
+ zip(seek_points[::2], seek_points[1::2])
+ )
+
+ punctuation = "\"'“¿([{-\"'.。,，!！?？:：”)]}、"
+
+ idx = 0
+ clip_idx = 0
+ seek = seek_clips[clip_idx][0]
+ all_tokens = []
+ prompt_reset_since = 0
+
+ if options.initial_prompt is not None:
+ if isinstance(options.initial_prompt, str):
+ initial_prompt = " " + options.initial_prompt.strip()
+ initial_prompt_tokens = tokenizer.encode(initial_prompt)
+ all_tokens.extend(initial_prompt_tokens)
+ else:
+ all_tokens.extend(options.initial_prompt)
+
+ last_speech_timestamp = 0.0
+ # NOTE: This loop is obscurely flattened to make the diff readable.
+ # A later commit should turn this into a simpler nested loop.
+ # for seek_clip_start, seek_clip_end in seek_clips:
+ # while seek < seek_clip_end
+ while clip_idx < len(seek_clips):
+ seek_clip_start, seek_clip_end = seek_clips[clip_idx]
+ if seek_clip_end > content_frames:
+ seek_clip_end = content_frames
+ if seek < seek_clip_start:
+ seek = seek_clip_start
+ if seek >= seek_clip_end:
+ clip_idx += 1
+ if clip_idx < len(seek_clips):
+ seek = seek_clips[clip_idx][0]
+ continue
+ time_offset = seek * self.feature_extractor.time_per_frame
+ window_end_time = float(
+ (seek + self.feature_extractor.nb_max_frames)
+ * self.feature_extractor.time_per_frame
+ )
+ segment_size = min(
+ self.feature_extractor.nb_max_frames,
+ content_frames - seek,
+ seek_clip_end - seek,
+ )
+ segment = features[:, seek : seek + segment_size]
+ segment_duration = segment_size * self.feature_extractor.time_per_frame
+ segment = pad_or_trim(segment, self.feature_extractor.nb_max_frames)
+
+ if self.logger.isEnabledFor(logging.DEBUG):
+ self.logger.debug(
+ "Processing segment at %s", format_timestamp(time_offset)
+ )
+
+ previous_tokens = all_tokens[prompt_reset_since:]
+
+ if encoder_output is None:
+ encoder_output = self.encode(segment)
+
+ # Perform language detection at every segment to update task based on output language,
+ # if the language is english, task is transcribe,
+ # else the task is translate to english (default)
+ # or transcribe if 'output_language' is 'hybrid'.
+ if options.multilingual:
+ results = self.model.detect_language(encoder_output)
+ language_token, language_probability = results[0][0]
+ language = language_token[2:-2]
+ if options.output_language == "en" and language != "en":
+ task = "translate"
+ else:
+ task = "transcribe"
+
+ # Update tokenizer based on task and language
+ tokenizer.task = tokenizer.tokenizer.token_to_id(f"<|{task}|>")
+ tokenizer.language = tokenizer.tokenizer.token_to_id(language_token)
+ tokenizer.language_code = language
+ # Update prompt based on task and language
+ prompt = self.get_prompt(
+ tokenizer,
+ previous_tokens,
+ without_timestamps=options.without_timestamps,
+ prefix=options.prefix if seek == 0 else None,
+ hotwords=options.hotwords,
+ )
+
+ if seek > 0 or encoder_output is None:
+ encoder_output = self.encode(segment)
+
+ (
+ result,
+ avg_logprob,
+ temperature,
+ compression_ratio,
+ ) = self.generate_with_fallback(encoder_output, prompt, tokenizer, options)
+
+ if options.no_speech_threshold is not None:
+ # no voice activity check
+ should_skip = result.no_speech_prob > options.no_speech_threshold
+
+ if (
+ options.log_prob_threshold is not None
+ and avg_logprob > options.log_prob_threshold
+ ):
+ # don't skip if the logprob is high enough, despite the no_speech_prob
+ should_skip = False
+
+ if should_skip:
+ self.logger.debug(
+ "No speech threshold is met (%f > %f)",
+ result.no_speech_prob,
+ options.no_speech_threshold,
+ )
+
+ # Skip if the logprob is very low (below the threshold value),
+ # despite no_speech_prob being low (ex: Too ambiguous outputs)
+ if options.log_prob_low_threshold:
+ if avg_logprob < options.log_prob_low_threshold:
+ should_skip = True
+ self.logger.debug(
+ "log prob low threshold is met (%f > %f)",
+ avg_logprob,
+ options.log_prob_low_threshold,
+ )
+
+ if should_skip:
+ # fast-forward to the next segment boundary
+ seek += segment_size
+ continue
+
+ tokens = result.sequences_ids[0]
+
+ previous_seek = seek
+
+ # anomalous words are very long/short/improbable
+ def word_anomaly_score(word: dict) -> float:
+ probability = word.get("probability", 0.0)
+ duration = word["end"] - word["start"]
+ score = 0.0
+ if probability < 0.15:
+ score += 1.0
+ if duration < 0.133:
+ score += (0.133 - duration) * 15
+ if duration > 2.0:
+ score += duration - 2.0
+ return score
+
+ def is_segment_anomaly(segment: Optional[dict]) -> bool:
+ if segment is None or not segment["words"]:
+ return False
+ words = [w for w in segment["words"] if w["word"] not in punctuation]
+ words = words[:8]
+ score = sum(word_anomaly_score(w) for w in words)
+ return score >= 3 or score + 0.01 >= len(words)
+
+ def next_words_segment(segments: List[dict]) -> Optional[dict]:
+ return next((s for s in segments if s["words"]), None)
+
+ (
+ current_segments,
+ seek,
+ single_timestamp_ending,
+ ) = self._split_segments_by_timestamps(
+ tokenizer=tokenizer,
+ tokens=tokens,
+ time_offset=time_offset,
+ segment_size=segment_size,
+ segment_duration=segment_duration,
+ seek=seek,
+ )
+
+ if options.word_timestamps:
+ self.add_word_timestamps(
+ [current_segments],
+ tokenizer,
+ encoder_output,
+ segment_size,
+ options.prepend_punctuations,
+ options.append_punctuations,
+ last_speech_timestamp=last_speech_timestamp,
+ )
+ if not single_timestamp_ending:
+ last_word_end = get_end(current_segments)
+ if last_word_end is not None and last_word_end > time_offset:
+ seek = round(last_word_end * self.frames_per_second)
+
+ # skip silence before possible hallucinations
+ if options.hallucination_silence_threshold is not None:
+ threshold = options.hallucination_silence_threshold
+
+ # if first segment might be a hallucination, skip leading silence
+ first_segment = next_words_segment(current_segments)
+ if first_segment is not None and is_segment_anomaly(first_segment):
+ gap = first_segment["start"] - time_offset
+ if gap > threshold:
+ seek = previous_seek + round(gap * self.frames_per_second)
+ continue
+
+ # skip silence before any possible hallucination that is surrounded
+ # by silence or more hallucinations
+ hal_last_end = last_speech_timestamp
+ for si in range(len(current_segments)):
+ segment = current_segments[si]
+ if not segment["words"]:
+ continue
+ if is_segment_anomaly(segment):
+ next_segment = next_words_segment(
+ current_segments[si + 1 :]
+ )
+ if next_segment is not None:
+ hal_next_start = next_segment["words"][0]["start"]
+ else:
+ hal_next_start = time_offset + segment_duration
+ silence_before = (
+ segment["start"] - hal_last_end > threshold
+ or segment["start"] < threshold
+ or segment["start"] - time_offset < 2.0
+ )
+ silence_after = (
+ hal_next_start - segment["end"] > threshold
+ or is_segment_anomaly(next_segment)
+ or window_end_time - segment["end"] < 2.0
+ )
+ if silence_before and silence_after:
+ seek = round(
+ max(time_offset + 1, segment["start"])
+ * self.frames_per_second
+ )
+ if content_duration - segment["end"] < threshold:
+ seek = content_frames
+ current_segments[si:] = []
+ break
+ hal_last_end = segment["end"]
+
+ last_word_end = get_end(current_segments)
+ if last_word_end is not None:
+ last_speech_timestamp = last_word_end
+ for segment in current_segments:
+ tokens = segment["tokens"]
+ text = tokenizer.decode(tokens)
+
+ if segment["start"] == segment["end"] or not text.strip():
+ continue
+
+ all_tokens.extend(tokens)
+ idx += 1
+
+ yield Segment(
+ id=idx,
+ seek=seek,
+ start=segment["start"],
+ end=segment["end"],
+ text=text,
+ tokens=tokens,
+ temperature=temperature,
+ avg_logprob=avg_logprob,
+ compression_ratio=compression_ratio,
+ no_speech_prob=result.no_speech_prob,
+ words=(
+ [Word(**word) for word in segment["words"]]
+ if options.word_timestamps
+ else None
+ ),
+ )
+
+ if (
+ not options.condition_on_previous_text
+ or temperature > options.prompt_reset_on_temperature
+ ):
+ if options.condition_on_previous_text:
+ self.logger.debug(
+ "Reset prompt. prompt_reset_on_temperature threshold is met %f > %f",
+ temperature,
+ options.prompt_reset_on_temperature,
+ )
+
+ prompt_reset_since = len(all_tokens)
+
+ def encode(self, features: torch.Tensor) -> ctranslate2.StorageView:
+ # When the model is running on multiple GPUs, the encoder output should be moved
+ # to the CPU since we don't know which GPU will handle the next job.
+ to_cpu = self.model.device == "cuda" and len(self.model.device_index) > 1
+
+ if features.ndim == 2:
+ features = features.unsqueeze(0)
+ features = get_ctranslate2_storage(features)
+
+ return self.model.encode(features, to_cpu=to_cpu)
+
+ def generate_with_fallback(
+ self,
+ encoder_output: ctranslate2.StorageView,
+ prompt: List[int],
+ tokenizer: Tokenizer,
+ options: TranscriptionOptions,
+ ) -> Tuple[ctranslate2.models.WhisperGenerationResult, float, float, float]:
+ decode_result = None
+ all_results = []
+ below_cr_threshold_results = []
+
+ max_initial_timestamp_index = int(
+ round(options.max_initial_timestamp / self.time_precision)
+ )
+ if options.max_new_tokens is not None:
+ max_length = len(prompt) + options.max_new_tokens
+ else:
+ max_length = self.max_length
+
+ if max_length > self.max_length:
+ raise ValueError(
+ f"The length of the prompt is {len(prompt)}, and the `max_new_tokens` "
+ f"{max_length - len(prompt)}. Thus, the combined length of the prompt "
+ f"and `max_new_tokens` is: {max_length}. This exceeds the "
+ f"`max_length` of the Whisper model: {self.max_length}. "
+ "You should either reduce the length of your prompt, or "
+ "reduce the value of `max_new_tokens`, "
+ f"so that their combined length is less that {self.max_length}."
+ )
+
+ for temperature in options.temperatures:
+ if temperature > 0:
+ kwargs = {
+ "beam_size": 1,
+ "num_hypotheses": options.best_of,
+ "sampling_topk": 0,
+ "sampling_temperature": temperature,
+ }
+ else:
+ kwargs = {
+ "beam_size": options.beam_size,
+ "patience": options.patience,
+ }
+
+ result = self.model.generate(
+ encoder_output,
+ [prompt],
+ length_penalty=options.length_penalty,
+ repetition_penalty=options.repetition_penalty,
+ no_repeat_ngram_size=options.no_repeat_ngram_size,
+ max_length=max_length,
+ return_scores=True,
+ return_no_speech_prob=True,
+ suppress_blank=options.suppress_blank,
+ suppress_tokens=options.suppress_tokens,
+ max_initial_timestamp_index=max_initial_timestamp_index,
+ **kwargs,
+ )[0]
+
+ tokens = result.sequences_ids[0]
+
+ # Recover the average log prob from the returned score.
+ seq_len = len(tokens)
+ cum_logprob = result.scores[0] * (seq_len**options.length_penalty)
+ avg_logprob = cum_logprob / (seq_len + 1)
+
+ text = tokenizer.decode(tokens).strip()
+ compression_ratio = get_compression_ratio(text)
+
+ decode_result = (
+ result,
+ avg_logprob,
+ temperature,
+ compression_ratio,
+ )
+ all_results.append(decode_result)
+
+ needs_fallback = False
+
+ if options.compression_ratio_threshold is not None:
+ if compression_ratio > options.compression_ratio_threshold:
+ needs_fallback = True # too repetitive
+
+ self.logger.debug(
+ "Compression ratio threshold is not met with temperature %.1f (%f > %f)",
+ temperature,
+ compression_ratio,
+ options.compression_ratio_threshold,
+ )
+ else:
+ below_cr_threshold_results.append(decode_result)
+
+ if (
+ options.log_prob_threshold is not None
+ and avg_logprob < options.log_prob_threshold
+ ):
+ needs_fallback = True # average log probability is too low
+
+ self.logger.debug(
+ "Log probability threshold is not met with temperature %.1f (%f < %f)",
+ temperature,
+ avg_logprob,
+ options.log_prob_threshold,
+ )
+
+ if (
+ options.no_speech_threshold is not None
+ and result.no_speech_prob > options.no_speech_threshold
+ and options.log_prob_threshold is not None
+ and avg_logprob < options.log_prob_threshold
+ ):
+ needs_fallback = False # silence
+
+ if not needs_fallback:
+ break
+ else:
+ # all failed, select the result with the highest average log probability
+ decode_result = max(
+ below_cr_threshold_results or all_results, key=lambda x: x[1]
+ )
+ # to pass final temperature for prompt_reset_on_temperature
+ decode_result = (
+ decode_result[0],
+ decode_result[1],
+ temperature,
+ decode_result[3],
+ )
+
+ return decode_result
+
+ def get_prompt(
+ self,
+ tokenizer: Tokenizer,
+ previous_tokens: List[int],
+ without_timestamps: bool = False,
+ prefix: Optional[str] = None,
+ hotwords: Optional[str] = None,
+ ) -> List[int]:
+ prompt = []
+
+ if previous_tokens or (hotwords and not prefix):
+ prompt.append(tokenizer.sot_prev)
+ if hotwords and not prefix:
+ hotwords_tokens = tokenizer.encode(" " + hotwords.strip())
+ if len(hotwords_tokens) >= self.max_length // 2:
+ hotwords_tokens = hotwords_tokens[: self.max_length // 2 - 1]
+ prompt.extend(hotwords_tokens)
+ if previous_tokens:
+ prompt.extend(previous_tokens[-(self.max_length // 2 - 1) :])
+
+ prompt.extend(tokenizer.sot_sequence)
+
+ if without_timestamps:
+ prompt.append(tokenizer.no_timestamps)
+
+ if prefix:
+ prefix_tokens = tokenizer.encode(" " + prefix.strip())
+ if len(prefix_tokens) >= self.max_length // 2:
+ prefix_tokens = prefix_tokens[: self.max_length // 2 - 1]
+ if not without_timestamps:
+ prompt.append(tokenizer.timestamp_begin)
+ prompt.extend(prefix_tokens)
+
+ return prompt
+
+ def add_word_timestamps(
+ self,
+ segments: List[dict],
+ tokenizer: Tokenizer,
+ encoder_output: ctranslate2.StorageView,
+ num_frames: int,
+ prepend_punctuations: str,
+ append_punctuations: str,
+ last_speech_timestamp: float,
+ ) -> float:
+ if len(segments) == 0:
+ return
+
+ text_tokens = []
+ text_tokens_per_segment = []
+ for segment in segments:
+ segment_tokens = [
+ [token for token in subsegment["tokens"] if token < tokenizer.eot]
+ for subsegment in segment
+ ]
+ text_tokens.append(list(itertools.chain.from_iterable(segment_tokens)))
+ text_tokens_per_segment.append(segment_tokens)
+
+ alignments = self.find_alignment(
+ tokenizer, text_tokens, encoder_output, num_frames
+ )
+ median_max_durations = []
+ for alignment in alignments:
+ word_durations = np.array(
+ [word["end"] - word["start"] for word in alignment]
+ )
+ word_durations = word_durations[word_durations.nonzero()]
+ median_duration = (
+ np.median(word_durations) if len(word_durations) > 0 else 0.0
+ )
+ median_duration = min(0.7, float(median_duration))
+ max_duration = median_duration * 2
+
+ # hack: truncate long words at sentence boundaries.
+ # a better segmentation algorithm based on VAD should be able to replace this.
+ if len(word_durations) > 0:
+ sentence_end_marks = ".。!！?？"
+ # ensure words at sentence boundaries
+ # are not longer than twice the median word duration.
+ for i in range(1, len(alignment)):
+ if alignment[i]["end"] - alignment[i]["start"] > max_duration:
+ if alignment[i]["word"] in sentence_end_marks:
+ alignment[i]["end"] = alignment[i]["start"] + max_duration
+ elif alignment[i - 1]["word"] in sentence_end_marks:
+ alignment[i]["start"] = alignment[i]["end"] - max_duration
+
+ merge_punctuations(alignment, prepend_punctuations, append_punctuations)
+ median_max_durations.append((median_duration, max_duration))
+
+ for segment_idx, segment in enumerate(segments):
+ word_index = 0
+ time_offset = segment[0]["start"]
+ median_duration, max_duration = median_max_durations[segment_idx]
+ for subsegment_idx, subsegment in enumerate(segment):
+ saved_tokens = 0
+ words = []
+
+ while word_index < len(alignments[segment_idx]) and saved_tokens < len(
+ text_tokens_per_segment[segment_idx][subsegment_idx]
+ ):
+ timing = alignments[segment_idx][word_index]
+
+ if timing["word"]:
+ words.append(
+ dict(
+ word=timing["word"],
+ start=round(time_offset + timing["start"], 2),
+ end=round(time_offset + timing["end"], 2),
+ probability=timing["probability"],
+ )
+ )
+
+ saved_tokens += len(timing["tokens"])
+ word_index += 1
+
+ # hack: truncate long words at segment boundaries.
+ # a better segmentation algorithm based on VAD should be able to replace this.
+ if len(words) > 0:
+ # ensure the first and second word after a pause is not longer than
+ # twice the median word duration.
+ if words[0][
+ "end"
+ ] - last_speech_timestamp > median_duration * 4 and (
+ words[0]["end"] - words[0]["start"] > max_duration
+ or (
+ len(words) > 1
+ and words[1]["end"] - words[0]["start"] > max_duration * 2
+ )
+ ):
+ if (
+ len(words) > 1
+ and words[1]["end"] - words[1]["start"] > max_duration
+ ):
+ boundary = max(
+ words[1]["end"] / 2, words[1]["end"] - max_duration
+ )
+ words[0]["end"] = words[1]["start"] = boundary
+ words[0]["start"] = max(0, words[0]["end"] - max_duration)
+
+ # prefer the segment-level start timestamp if the first word is too long.
+ if (
+ subsegment["start"] < words[0]["end"]
+ and subsegment["start"] - 0.5 > words[0]["start"]
+ ):
+ words[0]["start"] = max(
+ 0,
+ min(words[0]["end"] - median_duration, subsegment["start"]),
+ )
+ else:
+ subsegment["start"] = words[0]["start"]
+
+ # prefer the segment-level end timestamp if the last word is too long.
+ if (
+ subsegment["end"] > words[-1]["start"]
+ and subsegment["end"] + 0.5 < words[-1]["end"]
+ ):
+ words[-1]["end"] = max(
+ words[-1]["start"] + median_duration, subsegment["end"]
+ )
+ else:
+ subsegment["end"] = words[-1]["end"]
+
+ last_speech_timestamp = subsegment["end"]
+ segments[segment_idx][subsegment_idx]["words"] = words
+ return last_speech_timestamp
+
+ def find_alignment(
+ self,
+ tokenizer: Tokenizer,
+ text_tokens: List[int],
+ encoder_output: ctranslate2.StorageView,
+ num_frames: int,
+ median_filter_width: int = 7,
+ ) -> List[dict]:
+ if len(text_tokens) == 0:
+ return []
+
+ results = self.model.align(
+ encoder_output,
+ tokenizer.sot_sequence,
+ text_tokens,
+ num_frames,
+ median_filter_width=median_filter_width,
+ )
+ return_list = []
+ for result, text_token in zip(results, text_tokens):
+ text_token_probs = result.text_token_probs
+ alignments = result.alignments
+ text_indices = np.array([pair[0] for pair in alignments])
+ time_indices = np.array([pair[1] for pair in alignments])
+
+ words, word_tokens = tokenizer.split_to_word_tokens(
+ text_token + [tokenizer.eot]
+ )
+ if len(word_tokens) <= 1:
+ # return on eot only
+ # >>> np.pad([], (1, 0))
+ # array([0.])
+ # This results in crashes when we lookup jump_times with float, like
+ # IndexError: arrays used as indices must be of integer (or boolean) type
+ return []
+ word_boundaries = np.pad(
+ np.cumsum([len(t) for t in word_tokens[:-1]]), (1, 0)
+ )
+ if len(word_boundaries) <= 1:
+ return []
+
+ jumps = np.pad(np.diff(text_indices), (1, 0), constant_values=1).astype(
+ bool
+ )
+ jump_times = time_indices[jumps] / self.tokens_per_second
+ start_times = jump_times[word_boundaries[:-1]]
+ end_times = jump_times[word_boundaries[1:]]
+ word_probabilities = [
+ np.mean(text_token_probs[i:j])
+ for i, j in zip(word_boundaries[:-1], word_boundaries[1:])
+ ]
+
+ return_list.append(
+ [
+ dict(
+ word=word,
+ tokens=tokens,
+ start=start,
+ end=end,
+ probability=probability,
+ )
+ for word, tokens, start, end, probability in zip(
+ words, word_tokens, start_times, end_times, word_probabilities
+ )
+ ]
+ )
+ return return_list
+
+ def generate_segment_batched(
+ self,
+ features: torch.Tensor,
+ tokenizer: Tokenizer,
+ options: dict,
+ ):
+ batch_size = features.shape[0]
+ all_tokens = []
+ prompt_reset_since = 0
+
+ if options["initial_prompt"] is not None:
+ initial_prompt = " " + options["initial_prompt"].strip()
+ initial_prompt_tokens = tokenizer.encode(initial_prompt)
+ all_tokens.extend(initial_prompt_tokens)
+ previous_tokens = all_tokens[prompt_reset_since:]
+ prompt = self.get_prompt(
+ tokenizer,
+ previous_tokens,
+ without_timestamps=options["without_timestamps"],
+ prefix=options["prefix"],
+ )
+
+ encoder_output = self.encode(features)
+
+ result = self.model.generate(
+ encoder_output,
+ [prompt] * batch_size,
+ beam_size=options["beam_size"],
+ patience=options["patience"],
+ length_penalty=options["length_penalty"],
+ max_length=self.max_length,
+ suppress_blank=options["suppress_blank"],
+ suppress_tokens=options["suppress_tokens"],
+ return_scores=True,
+ return_no_speech_prob=True,
+ )
+
+ output = []
+ for res in result:
+ output.append({})
+ # return scores
+ seq_len = len(res.sequences_ids[0])
+ cum_logprob = res.scores[0] * (seq_len ** options["length_penalty"])
+ output[-1]["avg_logprob"] = cum_logprob / (seq_len + 1)
+
+ # return no speech prob
+ output[-1]["no_speech_prob"] = res.no_speech_prob
+ output[-1]["tokens"] = res.sequences_ids[0]
+
+ return encoder_output, output
+
+ def detect_language(self, audio: torch.Tensor):
+ to_cpu = self.model.device == "cuda" and len(self.model.device_index) > 1
+ segment = self.feature_extractor(audio, padding=True, to_cpu=to_cpu)[
+ :, : self.feature_extractor.nb_max_frames
+ ]
+ encoder_output = self.encode(segment)
+ results = self.model.detect_language(encoder_output)
+ language_token, language_probability = results[0][0]
+ language = language_token[2:-2]
+ self.logger.info(
+ f"Detected language: {language} ({language_probability:.2f}) in first 30s of audio..."
+ )
+ all_language_probs = [(token[2:-2], prob) for (token, prob) in results[0]]
+ return language, language_probability, all_language_probs
+
+ def detect_language_multi_segment(
+ self, audio: Union[str, BinaryIO, torch.Tensor], params: Optional[dict] = None
+ ):
+ """
+ Detect language based on N highly-confident segments of a language.
+ """
+ # The threshold is used to decide if the audio is silence or not.
+ # The default is 0.02 (2.0%) i.e, if more than 2.0% of the audio is silent,
+ # the audio is considered as silence.
+ if not params:
+ params = {
+ "multilingual": False,
+ "speech_percentage_threshold": 0.02,
+ "language_detection_segments": 4,
+ "vad_filter": True,
+ "vad_min_silence_duration": 2500,
+ "language_threshold": 0.7,
+ }
+
+ if params.get("multilingual", False):
+ logging.warning(
+ "lang_id is not supported for multilingual audios, detecting the major language."
+ )
+
+ speech_percentage_threshold = params.get("speech_percentage_threshold", 0.02)
+ language_threshold = params.get("language_threshold", 0.7)
+ num_detection_segments = params.get("language_detection_segments", 4)
+ vad_filter_enabled = params.get("vad_filter", True)
+ vad_params = dict(
+ min_silence_duration_ms=params.get("vad_min_silence_duration", 2500)
+ )
+
+ if vad_filter_enabled:
+ vad_params = VadOptions(**vad_params)
+
+ # decode audio if it is not decoded already
+ sampling_rate = self.feature_extractor.sampling_rate
+ if not isinstance(audio, torch.Tensor):
+ audio: torch.Tensor = decode_audio(audio, sampling_rate=sampling_rate)
+
+ # calculate duration of audio as number of seconds
+ # audio.shape[0] is the number of samples in the audio
+ # sampling_rate is the number of samples per second
+ # if we divide the number of samples by the number of samples per second,
+ # we get the duration in seconds
+ duration = audio.shape[0] / sampling_rate
+
+ # Check if vad is enabled, and collect voiced segments
+ if vad_filter_enabled:
+ # get chunks of audio that contain speech
+ speech_chunks = get_speech_timestamps(audio, vad_params)
+ # merge chunks of audio that contain speech into a single array
+ audio = collect_chunks(audio, speech_chunks)
+
+ # calculate new duration of audio without silence
+ duration_vad = audio.shape[0] / sampling_rate
+
+ logging.debug(
+ f"Lang ID: VAD filter removed {duration - duration_vad} sec of audio"
+ )
+
+ # if the audio after VAD is less than 2% of the original audio, consider it as silence
+ if duration_vad / duration < speech_percentage_threshold:
+ return {"language_code": None, "language_confidence": 1.0}
+
+ # update duration to be the duration after VAD
+ duration = duration_vad
+
+ # if the duration of the audio is less than 1 second, consider it as silence
+ if duration < 1.0:
+ return {"language_code": None, "language_confidence": 1.0}
+
+ # number of feature frames in 30 seconds of audio is 3000
+ nb_max_frames = self.feature_extractor.nb_max_frames
+
+ # extract features from audio with padding (default)
+ to_cpu = self.model.device == "cuda" and len(self.model.device_index) > 1
+ features = self.feature_extractor(audio, to_cpu=to_cpu)
+
+ # number of segments in the audio
+ num_segments = features.shape[-1] // nb_max_frames
+ # more number of segments than possible with the duration of file
+ if num_detection_segments > num_segments:
+ logging.warning(
+ f"Lang ID: Can not have more segments, setting {num_segments} segments."
+ )
+ num_detection_segments = num_segments
+
+ # create a list of indices to randomly select segments from
+ indices = list(range(num_detection_segments))
+
+ # fix seed to get deterministic results
+ random.seed(0)
+ random.shuffle(indices)
+
+ detected_languages = []
+ all_language_probabilities = defaultdict(list)
+ confident_language_probabilities = defaultdict(list)
+ num_confident_segments_per_language = defaultdict(int)
+
+ # Iterate over the randomly selected indices of the segments.
+ #
+ # For each segment, extract features and detect language.
+ #
+ # If the language is confident, add it to the list of confident segments for that language.
+ #
+ # If the number of confident segments for a language
+ # is greater than or equal to the number of detection segments,
+ # return the language and the average probability of the language.
+ #
+ # If we are unable to get sufficient number of confident predcitions,
+ # return the most frequently detected language with maximum probability.
+ #
+ # We need to get sufficient number of confident predictions per language, not in total.
+
+ for i in indices:
+ segment_features = features[:, i * nb_max_frames : (i + 1) * nb_max_frames]
+ try:
+ encoder_output = self.encode(segment_features)
+ results = self.model.detect_language(encoder_output)[0]
+
+ except ValueError as e: # or RuntimeError
+ logging.error(f"Inference error:{e}")
+
+ # results is the list of classes (languages) and their probabilities (descending),
+ # for eg: [('<|de|>', 0.482177734375),('<|en|>', 0.283447265625),...]
+
+ # take top language token and probability
+ # and parse language token to strip out markers
+ # for eg: '<|de|>' -> 'de'
+
+ language_token = results[0][0]
+ language = language_token[2:-2]
+
+ language_probability = results[0][1]
+
+ detected_languages.append(language)
+ all_language_probabilities[language].append(language_probability)
+
+ # only consider if the language prediction is confident
+ if language_probability > language_threshold:
+ num_confident_segments_per_language[language] += 1
+
+ # Add language and probability to the list of languages when it is confident
+ confident_language_probabilities[language].append(language_probability)
+
+ # return the language when sufficient number of confident segments is achieved
+ if (
+ num_confident_segments_per_language[language]
+ >= num_detection_segments
+ ):
+ # Considering the average probability of only confident segments
+ mean = sum(confident_language_probabilities[language]) / len(
+ confident_language_probabilities[language]
+ )
+ return {
+ "language_code": language,
+ "language_confidence": mean,
+ }
+
+ # if we are unable to get sufficient number of confident predictions,
+ # return the most frequently detected language.
+ # if there is a tie, return the one with maximum average probability.
+ counter = Counter(detected_languages)
+
+ # Define the key function to select frequent language with attached probabilities
+ def key_func(language):
+ # Calculate the frequency of the language
+ frequency = counter[language]
+
+ # Calculate the average probability of the language
+ prob_avg = sum(all_language_probabilities[language]) / len(
+ all_language_probabilities[language]
+ )
+
+ return frequency, prob_avg
+
+ if detected_languages:
+ # Use the key function to find the language with maximum frequency and probability
+ max_language = max(detected_languages, key=key_func)
+ max_probability = sum(all_language_probabilities[max_language]) / len(
+ all_language_probabilities[max_language]
+ )
+
+ # Do additional checks for silence for non-confident case
+ # calculate RMS amplitude and DC offset
+ dc_offset = audio.mean()
+ audio_minus_dc_offset = audio - dc_offset
+ is_silent = (
+ torch.all(audio.abs() < 0.01)
+ or torch.sqrt(torch.mean(audio_minus_dc_offset**2)) < 0.01
+ )
+
+ if is_silent:
+ return {"language_code": None, "language_confidence": 1.0}
+
+ return {
+ "language_code": max_language,
+ "language_confidence": max_probability,
+ }
+
+ # Language is not detected for any segment and none of prev conditions met
+ return {"language_code": None, "language_confidence": 1.0}
+
+
+def restore_speech_timestamps(
+ segments: Iterable[Segment],
+ speech_chunks: List[dict],
+ sampling_rate: int,
+) -> Iterable[Segment]:
+ ts_map = SpeechTimestampsMap(speech_chunks, sampling_rate)
+
+ for segment in segments:
+ if segment.words:
+ words = []
+ for word in segment.words:
+ # Ensure the word start and end times are resolved to the same chunk.
+ middle = (word.start + word.end) / 2
+ chunk_index = ts_map.get_chunk_index(middle)
+ word = word._replace(
+ start=ts_map.get_original_time(word.start, chunk_index),
+ end=ts_map.get_original_time(word.end, chunk_index),
+ )
+ words.append(word)
+
+ segment = segment._replace(
+ start=words[0].start,
+ end=words[-1].end,
+ words=words,
+ )
+
+ else:
+ segment = segment._replace(
+ start=ts_map.get_original_time(segment.start),
+ end=ts_map.get_original_time(segment.end),
+ )
+
+ yield segment
+
+
+def get_ctranslate2_storage(segment: torch.Tensor) -> ctranslate2.StorageView:
+ segment = segment.contiguous()
+ segment = ctranslate2.StorageView.from_array(
+ segment if segment.is_cuda else segment.numpy()
+ ) # torch cpu tensors don't implement __array_interface__
+ # https://github.com/pytorch/pytorch/issues/51156
+ return segment
+
+
+def get_compression_ratio(text: str) -> float:
+ text_bytes = text.encode("utf-8")
+ return len(text_bytes) / len(zlib.compress(text_bytes))
+
+
+def get_suppressed_tokens(
+ tokenizer: Tokenizer,
+ suppress_tokens: Tuple[int],
+) -> Optional[List[int]]:
+ if -1 in suppress_tokens:
+ suppress_tokens = [t for t in suppress_tokens if t >= 0]
+ suppress_tokens.extend(tokenizer.non_speech_tokens)
+ elif suppress_tokens is None or len(suppress_tokens) == 0:
+ suppress_tokens = [] # interpret empty string as an empty list
+ else:
+ assert isinstance(suppress_tokens, list), "suppress_tokens must be a list"
+
+ suppress_tokens.extend(
+ [
+ tokenizer.transcribe,
+ tokenizer.translate,
+ tokenizer.sot,
+ tokenizer.sot_prev,
+ tokenizer.sot_lm,
+ ]
+ )
+
+ return tuple(sorted(set(suppress_tokens)))
+
+
+def merge_punctuations(alignment: List[dict], prepended: str, appended: str) -> None:
+ # merge prepended punctuations
+ i = len(alignment) - 2
+ j = len(alignment) - 1
+ while i >= 0:
+ previous = alignment[i]
+ following = alignment[j]
+ if previous["word"].startswith(" ") and previous["word"].strip() in prepended:
+ # prepend it to the following word
+ following["word"] = previous["word"] + following["word"]
+ if "tokens" in alignment[0].keys():
+ following["tokens"] = previous["tokens"] + following["tokens"]
+ previous["tokens"] = []
+ previous["word"] = ""
+
+ else:
+ j = i
+ i -= 1
+
+ # merge appended punctuations
+ i = 0
+ j = 1
+ while j < len(alignment):
+ previous = alignment[i]
+ following = alignment[j]
+ if not previous["word"].endswith(" ") and following["word"] in appended:
+ # append it to the previous word
+ previous["word"] = previous["word"] + following["word"]
+ if "tokens" in alignment[0].keys():
+ previous["tokens"] = previous["tokens"] + following["tokens"]
+ following["tokens"] = []
+ following["word"] = ""
+
+ else:
+ i = j
+ j += 1
diff --git a/whisper_pipeline/faster-whisper-main/build/lib/faster_whisper/utils.py b/whisper_pipeline/faster-whisper-main/build/lib/faster_whisper/utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..481bd748ec0daec58681289c38559d5968e6630d
--- /dev/null
+++ b/whisper_pipeline/faster-whisper-main/build/lib/faster_whisper/utils.py
@@ -0,0 +1,157 @@
+import logging
+import os
+import re
+
+from typing import List, Optional
+
+import huggingface_hub
+import requests
+
+from tqdm.auto import tqdm
+
+_MODELS = {
+ "tiny.en": "Systran/faster-whisper-tiny.en",
+ "tiny": "Systran/faster-whisper-tiny",
+ "base.en": "Systran/faster-whisper-base.en",
+ "base": "Systran/faster-whisper-base",
+ "small.en": "Systran/faster-whisper-small.en",
+ "small": "Systran/faster-whisper-small",
+ "medium.en": "Systran/faster-whisper-medium.en",
+ "medium": "Systran/faster-whisper-medium",
+ "large-v1": "Systran/faster-whisper-large-v1",
+ "large-v2": "Systran/faster-whisper-large-v2",
+ "large-v3": "Systran/faster-whisper-large-v3",
+ "large": "Systran/faster-whisper-large-v3",
+ "distil-large-v2": "Systran/faster-distil-whisper-large-v2",
+ "distil-medium.en": "Systran/faster-distil-whisper-medium.en",
+ "distil-small.en": "Systran/faster-distil-whisper-small.en",
+ "distil-large-v3": "Systran/faster-distil-whisper-large-v3",
+}
+
+
+def available_models() -> List[str]:
+ """Returns the names of available models."""
+ return list(_MODELS.keys())
+
+
+def get_assets_path():
+ """Returns the path to the assets directory."""
+ return os.path.join(os.path.dirname(os.path.abspath(__file__)), "assets")
+
+
+def get_logger():
+ """Returns the module logger."""
+ return logging.getLogger("faster_whisper")
+
+
+def download_model(
+ size_or_id: str,
+ output_dir: Optional[str] = None,
+ local_files_only: bool = False,
+ cache_dir: Optional[str] = None,
+):
+ """Downloads a CTranslate2 Whisper model from the Hugging Face Hub.
+
+ Args:
+ size_or_id: Size of the model to download from https://huggingface.co/Systran
+ (tiny, tiny.en, base, base.en, small, small.en, distil-small.en, medium, medium.en,
+ distil-medium.en, large-v1, large-v2, large-v3, large, distil-large-v2,
+ distil-large-v3), or a CTranslate2-converted model ID from the Hugging Face Hub
+ (e.g. Systran/faster-whisper-large-v3).
+ output_dir: Directory where the model should be saved. If not set, the model is saved in
+ the cache directory.
+ local_files_only: If True, avoid downloading the file and return the path to the local
+ cached file if it exists.
+ cache_dir: Path to the folder where cached files are stored.
+
+ Returns:
+ The path to the downloaded model.
+
+ Raises:
+ ValueError: if the model size is invalid.
+ """
+ if re.match(r".*/.*", size_or_id):
+ repo_id = size_or_id
+ else:
+ repo_id = _MODELS.get(size_or_id)
+ if repo_id is None:
+ raise ValueError(
+ "Invalid model size '%s', expected one of: %s"
+ % (size_or_id, ", ".join(_MODELS.keys()))
+ )
+
+ allow_patterns = [
+ "config.json",
+ "preprocessor_config.json",
+ "model.bin",
+ "tokenizer.json",
+ "vocabulary.*",
+ ]
+
+ kwargs = {
+ "local_files_only": local_files_only,
+ "allow_patterns": allow_patterns,
+ "tqdm_class": disabled_tqdm,
+ }
+
+ if output_dir is not None:
+ kwargs["local_dir"] = output_dir
+ kwargs["local_dir_use_symlinks"] = False
+
+ if cache_dir is not None:
+ kwargs["cache_dir"] = cache_dir
+
+ try:
+ return huggingface_hub.snapshot_download(repo_id, **kwargs)
+ except (
+ huggingface_hub.utils.HfHubHTTPError,
+ requests.exceptions.ConnectionError,
+ ) as exception:
+ logger = get_logger()
+ logger.warning(
+ "An error occured while synchronizing the model %s from the Hugging Face Hub:\n%s",
+ repo_id,
+ exception,
+ )
+ logger.warning(
+ "Trying to load the model directly from the local cache, if it exists."
+ )
+
+ kwargs["local_files_only"] = True
+ return huggingface_hub.snapshot_download(repo_id, **kwargs)
+
+
+def format_timestamp(
+ seconds: float,
+ always_include_hours: bool = False,
+ decimal_marker: str = ".",
+) -> str:
+ assert seconds >= 0, "non-negative timestamp expected"
+ milliseconds = round(seconds * 1000.0)
+
+ hours = milliseconds // 3_600_000
+ milliseconds -= hours * 3_600_000
+
+ minutes = milliseconds // 60_000
+ milliseconds -= minutes * 60_000
+
+ seconds = milliseconds // 1_000
+ milliseconds -= seconds * 1_000
+
+ hours_marker = f"{hours:02d}:" if always_include_hours or hours > 0 else ""
+ return (
+ f"{hours_marker}{minutes:02d}:{seconds:02d}{decimal_marker}{milliseconds:03d}"
+ )
+
+
+class disabled_tqdm(tqdm):
+ def __init__(self, *args, **kwargs):
+ kwargs["disable"] = True
+ super().__init__(*args, **kwargs)
+
+
+def get_end(segments: List[dict]) -> Optional[float]:
+ return next(
+ (w["end"] for s in reversed(segments) for w in reversed(s["words"])),
+ segments[-1]["end"] if segments else None,
+ )
diff --git a/whisper_pipeline/faster-whisper-main/build/lib/faster_whisper/vad.py b/whisper_pipeline/faster-whisper-main/build/lib/faster_whisper/vad.py
new file mode 100644
index 0000000000000000000000000000000000000000..3881fd8185b439ef714af1f28b4e7a36f4fe24d6
--- /dev/null
+++ b/whisper_pipeline/faster-whisper-main/build/lib/faster_whisper/vad.py
@@ -0,0 +1,596 @@
+import bisect
+import functools
+import os
+
+from abc import ABC
+from collections.abc import Callable
+from typing import List, NamedTuple, Optional, Union
+
+import numpy as np
+import torch
+
+from pyannote.audio.core.io import AudioFile
+from pyannote.audio.pipelines import VoiceActivityDetection
+from pyannote.audio.pipelines.utils import PipelineModel
+from pyannote.core import Annotation, Segment, SlidingWindowFeature
+
+from faster_whisper.utils import get_assets_path
+
+
+# The code below is adapted from https://github.com/snakers4/silero-vad.
+class VadOptions(NamedTuple):
+ """VAD options.
+
+ Attributes:
+ threshold: Speech threshold. Silero VAD outputs speech probabilities for each audio chunk,
+ probabilities ABOVE this value are considered as SPEECH. It is better to tune this
+ parameter for each dataset separately, but "lazy" 0.5 is pretty good for most datasets.
+ min_speech_duration_ms: Final speech chunks shorter min_speech_duration_ms are thrown out.
+ max_speech_duration_s: Maximum duration of speech chunks in seconds. Chunks longer
+ than max_speech_duration_s will be split at the timestamp of the last silence that
+ lasts more than 100ms (if any), to prevent aggressive cutting. Otherwise, they will be
+ split aggressively just before max_speech_duration_s.
+ min_silence_duration_ms: In the end of each speech chunk wait for min_silence_duration_ms
+ before separating it
+ speech_pad_ms: Final speech chunks are padded by speech_pad_ms each side
+ """
+
+ threshold: float = 0.5
+ min_speech_duration_ms: int = 250
+ max_speech_duration_s: float = float("inf")
+ min_silence_duration_ms: int = 2000
+ speech_pad_ms: int = 400
+
+
+def get_speech_timestamps(
+ audio: torch.Tensor,
+ vad_options: Optional[VadOptions] = None,
+ **kwargs,
+) -> List[dict]:
+ """This method is used for splitting long audios into speech chunks using silero VAD.
+
+ Args:
+ audio: One dimensional float array.
+ vad_options: Options for VAD processing.
+ kwargs: VAD options passed as keyword arguments for backward compatibility.
+
+ Returns:
+ List of dicts containing begin and end samples of each speech chunk.
+ """
+ if vad_options is None:
+ vad_options = VadOptions(**kwargs)
+
+ threshold = vad_options.threshold
+ min_speech_duration_ms = vad_options.min_speech_duration_ms
+ max_speech_duration_s = vad_options.max_speech_duration_s
+ min_silence_duration_ms = vad_options.min_silence_duration_ms
+ window_size_samples = 512
+ speech_pad_ms = vad_options.speech_pad_ms
+ sampling_rate = 16000
+ min_speech_samples = sampling_rate * min_speech_duration_ms / 1000
+ speech_pad_samples = sampling_rate * speech_pad_ms / 1000
+ max_speech_samples = (
+ sampling_rate * max_speech_duration_s
+ - window_size_samples
+ - 2 * speech_pad_samples
+ )
+ min_silence_samples = sampling_rate * min_silence_duration_ms / 1000
+ min_silence_samples_at_max_speech = sampling_rate * 98 / 1000
+
+ audio_length_samples = len(audio)
+
+ model = get_vad_model()
+ state, context = model.get_initial_states(batch_size=1)
+
+ speech_probs = []
+ for current_start_sample in range(0, audio_length_samples, window_size_samples):
+ chunk = audio[current_start_sample : current_start_sample + window_size_samples]
+ if len(chunk) < window_size_samples:
+ chunk = np.pad(chunk, (0, int(window_size_samples - len(chunk))))
+ speech_prob, state, context = model(chunk, state, context, sampling_rate)
+ speech_probs.append(speech_prob)
+
+ triggered = False
+ speeches = []
+ current_speech = {}
+ neg_threshold = threshold - 0.15
+
+ # to save potential segment end (and tolerate some silence)
+ temp_end = 0
+ # to save potential segment limits in case of maximum segment size reached
+ prev_end = next_start = 0
+
+ for i, speech_prob in enumerate(speech_probs):
+ if (speech_prob >= threshold) and temp_end:
+ temp_end = 0
+ if next_start < prev_end:
+ next_start = window_size_samples * i
+
+ if (speech_prob >= threshold) and not triggered:
+ triggered = True
+ current_speech["start"] = window_size_samples * i
+ continue
+
+ if (
+ triggered
+ and (window_size_samples * i) - current_speech["start"] > max_speech_samples
+ ):
+ if prev_end:
+ current_speech["end"] = prev_end
+ speeches.append(current_speech)
+ current_speech = {}
+ # previously reached silence (< neg_thres) and is still not speech (< thres)
+ if next_start < prev_end:
+ triggered = False
+ else:
+ current_speech["start"] = next_start
+ prev_end = next_start = temp_end = 0
+ else:
+ current_speech["end"] = window_size_samples * i
+ speeches.append(current_speech)
+ current_speech = {}
+ prev_end = next_start = temp_end = 0
+ triggered = False
+ continue
+
+ if (speech_prob < neg_threshold) and triggered:
+ if not temp_end:
+ temp_end = window_size_samples * i
+ # condition to avoid cutting in very short silence
+ if (window_size_samples * i) - temp_end > min_silence_samples_at_max_speech:
+ prev_end = temp_end
+ if (window_size_samples * i) - temp_end < min_silence_samples:
+ continue
+ else:
+ current_speech["end"] = temp_end
+ if (
+ current_speech["end"] - current_speech["start"]
+ ) > min_speech_samples:
+ speeches.append(current_speech)
+ current_speech = {}
+ prev_end = next_start = temp_end = 0
+ triggered = False
+ continue
+
+ if (
+ current_speech
+ and (audio_length_samples - current_speech["start"]) > min_speech_samples
+ ):
+ current_speech["end"] = audio_length_samples
+ speeches.append(current_speech)
+
+ for i, speech in enumerate(speeches):
+ if i == 0:
+ speech["start"] = int(max(0, speech["start"] - speech_pad_samples))
+ if i != len(speeches) - 1:
+ silence_duration = speeches[i + 1]["start"] - speech["end"]
+ if silence_duration < 2 * speech_pad_samples:
+ speech["end"] += int(silence_duration // 2)
+ speeches[i + 1]["start"] = int(
+ max(0, speeches[i + 1]["start"] - silence_duration // 2)
+ )
+ else:
+ speech["end"] = int(
+ min(audio_length_samples, speech["end"] + speech_pad_samples)
+ )
+ speeches[i + 1]["start"] = int(
+ max(0, speeches[i + 1]["start"] - speech_pad_samples)
+ )
+ else:
+ speech["end"] = int(
+ min(audio_length_samples, speech["end"] + speech_pad_samples)
+ )
+
+ return speeches
+
+
+def collect_chunks(audio: torch.Tensor, chunks: List[dict]) -> torch.Tensor:
+ """Collects and concatenates audio chunks."""
+ if not chunks:
+ return torch.tensor([], dtype=torch.float32)
+
+ return torch.cat([audio[chunk["start"] : chunk["end"]] for chunk in chunks])
+
+
+class SpeechTimestampsMap:
+ """Helper class to restore original speech timestamps."""
+
+ def __init__(self, chunks: List[dict], sampling_rate: int, time_precision: int = 2):
+ self.sampling_rate = sampling_rate
+ self.time_precision = time_precision
+ self.chunk_end_sample = []
+ self.total_silence_before = []
+
+ previous_end = 0
+ silent_samples = 0
+
+ for chunk in chunks:
+ silent_samples += chunk["start"] - previous_end
+ previous_end = chunk["end"]
+
+ self.chunk_end_sample.append(chunk["end"] - silent_samples)
+ self.total_silence_before.append(silent_samples / sampling_rate)
+
+ def get_original_time(
+ self,
+ time: float,
+ chunk_index: Optional[int] = None,
+ ) -> float:
+ if chunk_index is None:
+ chunk_index = self.get_chunk_index(time)
+
+ total_silence_before = self.total_silence_before[chunk_index]
+ return round(total_silence_before + time, self.time_precision)
+
+ def get_chunk_index(self, time: float) -> int:
+ sample = int(time * self.sampling_rate)
+ return min(
+ bisect.bisect(self.chunk_end_sample, sample),
+ len(self.chunk_end_sample) - 1,
+ )
+
+
+@functools.lru_cache
+def get_vad_model():
+ """Returns the VAD model instance."""
+ path = os.path.join(get_assets_path(), "silero_vad.onnx")
+ return SileroVADModel(path)
+
+
+class SileroVADModel:
+ def __init__(self, path):
+ try:
+ import onnxruntime
+ except ImportError as e:
+ raise RuntimeError(
+ "Applying the VAD filter requires the onnxruntime package"
+ ) from e
+
+ opts = onnxruntime.SessionOptions()
+ opts.inter_op_num_threads = 1
+ opts.intra_op_num_threads = 1
+ opts.log_severity_level = 4
+
+ self.session = onnxruntime.InferenceSession(
+ path,
+ providers=["CPUExecutionProvider"],
+ sess_options=opts,
+ )
+
+ def get_initial_states(self, batch_size: int):
+ state = np.zeros((2, batch_size, 128), dtype=np.float32)
+ context = np.zeros((batch_size, 64), dtype=np.float32)
+ return state, context
+
+ def __call__(self, x, state, context, sr: int):
+ if len(x.shape) == 1:
+ x = np.expand_dims(x, 0)
+ if len(x.shape) > 2:
+ raise ValueError(
+ f"Too many dimensions for input audio chunk {len(x.shape)}"
+ )
+ if sr / x.shape[1] > 31.25:
+ raise ValueError("Input audio chunk is too short")
+
+ x = np.concatenate([context, x], axis=1)
+
+ ort_inputs = {
+ "input": x,
+ "state": state,
+ "sr": np.array(sr, dtype="int64"),
+ }
+
+ out, state = self.session.run(None, ort_inputs)
+ context = x[..., -64:]
+
+ return out, state, context
+
+
+# BSD 2-Clause License
+
+# Copyright (c) 2024, Max Bain
+
+# Redistribution and use in source and binary forms, with or without
+# modification, are permitted provided that the following conditions are met:
+
+# 1. Redistributions of source code must retain the above copyright notice, this
+# list of conditions and the following disclaimer.
+
+# 2. Redistributions in binary form must reproduce the above copyright notice,
+# this list of conditions and the following disclaimer in the documentation
+# and/or other materials provided with the distribution.
+
+# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+# DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
+# FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
+# DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
+# SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
+# OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+
+# The code below is copied from whisper-x (https://github.com/m-bain/whisperX)
+# and adapted for faster_whisper.
+class SegmentX:
+ def __init__(self, start, end, speaker=None):
+ self.start = start
+ self.end = end
+ self.speaker = speaker
+
+
+class VoiceActivitySegmentation(VoiceActivityDetection, ABC):
+ """Pipeline wrapper class for Voice Activity Segmentation based on VAD scores."""
+
+ def __init__(
+ self,
+ segmentation: PipelineModel = "pyannote/segmentation",
+ device: Optional[Union[str, torch.device]] = None,
+ fscore: bool = False,
+ use_auth_token: Optional[str] = None,
+ **inference_kwargs,
+ ):
+ """Initialize the pipeline with the model name and the optional device.
+
+ Args:
+ dict parameters of VoiceActivityDetection class from pyannote:
+ segmentation (PipelineModel): Loaded model name.
+ device (torch.device or None): Device to perform the segmentation.
+ fscore (bool): Flag indicating whether to compute F-score during inference.
+ use_auth_token (str or None): Optional authentication token for model access.
+ inference_kwargs (dict): Additional arguments from VoiceActivityDetection pipeline.
+ """
+ super().__init__(
+ segmentation=segmentation,
+ device=device,
+ fscore=fscore,
+ use_auth_token=use_auth_token,
+ **inference_kwargs,
+ )
+
+ def apply(
+ self, file: AudioFile, hook: Optional[Callable] = None
+ ) -> SlidingWindowFeature:
+ """Apply voice activity detection on the audio file.
+
+ Args:
+ file (AudioFile): Processed file.
+ hook (callable): Hook called with signature: hook("step_name", step_artefact, file=file)
+
+ Returns:
+ segmentations (SlidingWindowFeature): Voice activity segmentation.
+ """
+ # setup hook (e.g. for debugging purposes)
+ hook = self.setup_hook(file, hook=hook)
+
+ # apply segmentation model if needed
+ # output shape is (num_chunks, num_frames, 1)
+ if self.training:
+ if self.CACHED_SEGMENTATION in file:
+ segmentations = file[self.CACHED_SEGMENTATION]
+ else:
+ segmentations = self._segmentation(file)
+ file[self.CACHED_SEGMENTATION] = segmentations
+ else:
+ segmentations: SlidingWindowFeature = self._segmentation(file)
+
+ return segmentations
+
+
+class BinarizeVadScores:
+ """Binarize detection scores using hysteresis thresholding.
+
+ Reference:
+ Gregory Gelly and Jean-Luc Gauvain. "Minimum Word Error Training of
+ RNN-based Voice Activity Detection", InterSpeech 2015.
+
+ Modified by Max Bain to include WhisperX's min-cut operation
+ https://arxiv.org/abs/2303.00747
+
+ """
+
+ def __init__(
+ self,
+ onset: float = 0.5,
+ offset: Optional[float] = None,
+ min_duration_on: float = 0.0,
+ min_duration_off: float = 0.0,
+ pad_onset: float = 0.0,
+ pad_offset: float = 0.0,
+ max_duration: float = float("inf"),
+ ):
+ """Initializes the parameters for Binarizing the VAD scores.
+
+ Args:
+ onset (float, optional):
+ Onset threshold. Defaults to 0.5.
+ offset (float, optional):
+ Offset threshold. Defaults to `onset`.
+ min_duration_on (float, optional):
+ Remove active regions shorter than that many seconds. Defaults to 0s.
+ min_duration_off (float, optional):
+ Fill inactive regions shorter than that many seconds. Defaults to 0s.
+ pad_onset (float, optional):
+ Extend active regions by moving their start time by that many seconds.
+ Defaults to 0s.
+ pad_offset (float, optional):
+ Extend active regions by moving their end time by that many seconds.
+ Defaults to 0s.
+ max_duration (float):
+ The maximum length of an active segment.
+ """
+ super().__init__()
+
+ self.onset = onset
+ self.offset = offset or onset
+
+ self.pad_onset = pad_onset
+ self.pad_offset = pad_offset
+
+ self.min_duration_on = min_duration_on
+ self.min_duration_off = min_duration_off
+
+ self.max_duration = max_duration
+
+ def __get_active_regions(self, scores: SlidingWindowFeature) -> Annotation:
+ """Extract active regions from VAD scores.
+
+ Args:
+ scores (SlidingWindowFeature): Detection scores.
+
+ Returns:
+ active (Annotation): Active regions.
+ """
+ num_frames, num_classes = scores.data.shape
+ frames = scores.sliding_window
+ timestamps = [frames[i].middle for i in range(num_frames)]
+ # annotation meant to store 'active' regions
+ active = Annotation()
+ for k, k_scores in enumerate(scores.data.T):
+ label = k if scores.labels is None else scores.labels[k]
+
+ # initial state
+ start = timestamps[0]
+ is_active = k_scores[0] > self.onset
+ curr_scores = [k_scores[0]]
+ curr_timestamps = [start]
+ t = start
+ # optionally add `strict=False` for python 3.10 or later
+ for t, y in zip(timestamps[1:], k_scores[1:]):
+ # currently active
+ if is_active:
+ curr_duration = t - start
+ if curr_duration > self.max_duration:
+ search_after = len(curr_scores) // 2
+ # divide segment
+ min_score_div_idx = search_after + np.argmin(
+ curr_scores[search_after:]
+ )
+ min_score_t = curr_timestamps[min_score_div_idx]
+ region = Segment(
+ start - self.pad_onset, min_score_t + self.pad_offset
+ )
+ active[region, k] = label
+ start = curr_timestamps[min_score_div_idx]
+ curr_scores = curr_scores[min_score_div_idx + 1 :]
+ curr_timestamps = curr_timestamps[min_score_div_idx + 1 :]
+ # switching from active to inactive
+ elif y < self.offset:
+ region = Segment(start - self.pad_onset, t + self.pad_offset)
+ active[region, k] = label
+ start = t
+ is_active = False
+ curr_scores = []
+ curr_timestamps = []
+ curr_scores.append(y)
+ curr_timestamps.append(t)
+ # currently inactive
+ else:
+ # switching from inactive to active
+ if y > self.onset:
+ start = t
+ is_active = True
+
+ # if active at the end, add final region
+ if is_active:
+ region = Segment(start - self.pad_onset, t + self.pad_offset)
+ active[region, k] = label
+
+ return active
+
+ def __call__(self, scores: SlidingWindowFeature) -> Annotation:
+ """Binarize detection scores.
+
+ Args:
+ scores (SlidingWindowFeature): Detection scores.
+
+ Returns:
+ active (Annotation): Binarized scores.
+ """
+ active = self.__get_active_regions(scores)
+ # because of padding, some active regions might be overlapping: merge them.
+ # also: fill same speaker gaps shorter than min_duration_off
+ if self.pad_offset > 0.0 or self.pad_onset > 0.0 or self.min_duration_off > 0.0:
+ if self.max_duration < float("inf"):
+ raise NotImplementedError("This would break current max_duration param")
+ active = active.support(collar=self.min_duration_off)
+
+ # remove tracks shorter than min_duration_on
+ if self.min_duration_on > 0:
+ for segment, track in list(active.itertracks()):
+ if segment.duration < self.min_duration_on:
+ del active[segment, track]
+
+ return active
+
+
+def merge_chunks(
+ segments,
+ chunk_length,
+ onset: float = 0.5,
+ offset: Optional[float] = None,
+ edge_padding: float = 0.1,
+):
+ """
+ Merge operation described in whisper-x paper
+ """
+ curr_end = 0
+ merged_segments = []
+ seg_idxs = []
+ speaker_idxs = []
+
+ assert chunk_length > 0
+ binarize = BinarizeVadScores(max_duration=chunk_length, onset=onset, offset=offset)
+ segments = binarize(segments)
+ segments_list = []
+ for speech_turn in segments.get_timeline():
+ segments_list.append(
+ SegmentX(
+ max(0.0, speech_turn.start - edge_padding),
+ speech_turn.end + edge_padding,
+ "UNKNOWN",
+ )
+ ) # 100ms edge padding to account for edge errors
+
+ if len(segments_list) == 0:
+ print("No active speech found in audio")
+ return []
+
+ # Make sur the starting point is the start of the segment.
+ curr_start = segments_list[0].start
+
+ for idx, seg in enumerate(segments_list):
+ # if any segment start timing is less than previous segment end timing,
+ # reset the edge padding. Similarly for end timing.
+ if idx > 0:
+ if seg.start < segments_list[idx - 1].end:
+ seg.start += edge_padding
+ if idx < len(segments_list) - 1:
+ if seg.end > segments_list[idx + 1].start:
+ seg.end -= edge_padding
+
+ if seg.end - curr_start > chunk_length and curr_end - curr_start > 0:
+ merged_segments.append(
+ {
+ "start": curr_start,
+ "end": curr_end,
+ "segments": seg_idxs,
+ }
+ )
+ curr_start = seg.start
+ seg_idxs = []
+ speaker_idxs = []
+ curr_end = seg.end
+ seg_idxs.append((seg.start, seg.end))
+ speaker_idxs.append(seg.speaker)
+ # add final
+ merged_segments.append(
+ {
+ "start": curr_start,
+ "end": curr_end,
+ "segments": seg_idxs,
+ }
+ )
+ return merged_segments
diff --git a/whisper_pipeline/faster-whisper-main/build/lib/faster_whisper/version.py b/whisper_pipeline/faster-whisper-main/build/lib/faster_whisper/version.py
new file mode 100644
index 0000000000000000000000000000000000000000..65eaef429fb3048ee8d105fe67da4da43f5a2324
--- /dev/null
+++ b/whisper_pipeline/faster-whisper-main/build/lib/faster_whisper/version.py
@@ -0,0 +1,3 @@
+"""Version information."""
+
+__version__ = "1.0.3"
diff --git a/whisper_pipeline/faster-whisper-main/docker/Dockerfile b/whisper_pipeline/faster-whisper-main/docker/Dockerfile
new file mode 100644
index 0000000000000000000000000000000000000000..604c8e17b788e11c228eceec75a57d19a147a074
--- /dev/null
+++ b/whisper_pipeline/faster-whisper-main/docker/Dockerfile
@@ -0,0 +1,6 @@
+FROM nvidia/cuda:12.2.2-cudnn8-runtime-ubuntu22.04
+WORKDIR /root
+RUN apt-get update -y && apt-get install -y python3-pip
+COPY infer.py jfk.flac ./
+RUN pip3 install faster-whisper
+CMD ["python3", "infer.py"]
diff --git a/whisper_pipeline/faster-whisper-main/docker/infer.py b/whisper_pipeline/faster-whisper-main/docker/infer.py
new file mode 100644
index 0000000000000000000000000000000000000000..5d6b12cb516f3f7942798eeb41411de835cb611b
--- /dev/null
+++ b/whisper_pipeline/faster-whisper-main/docker/infer.py
@@ -0,0 +1,7 @@
+from faster_whisper import WhisperModel
+
+jfk_path = "jfk.flac"
+model = WhisperModel("tiny", device="cuda")
+segments, info = model.transcribe(jfk_path, word_timestamps=True)
+for segment in segments:
+ print("[%.2fs -> %.2fs] %s" % (segment.start, segment.end, segment.text))
diff --git a/whisper_pipeline/faster-whisper-main/docker/jfk.flac b/whisper_pipeline/faster-whisper-main/docker/jfk.flac
new file mode 100644
index 0000000000000000000000000000000000000000..8cf66fea45dd2f1ac2b182a37a2208657c11e8af
--- /dev/null
+++ b/whisper_pipeline/faster-whisper-main/docker/jfk.flac
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:63a4b1e4c1dc655ac70961ffbf518acd249df237e5a0152faae9a4a836949715
+size 1152693
diff --git a/whisper_pipeline/faster-whisper-main/faster_whisper.egg-info/PKG-INFO b/whisper_pipeline/faster-whisper-main/faster_whisper.egg-info/PKG-INFO
new file mode 100644
index 0000000000000000000000000000000000000000..6605d3d781db119560c992155867c00cde82c11d
--- /dev/null
+++ b/whisper_pipeline/faster-whisper-main/faster_whisper.egg-info/PKG-INFO
@@ -0,0 +1,347 @@
+Metadata-Version: 2.1
+Name: faster-whisper
+Version: 1.0.3
+Summary: Faster Whisper transcription with CTranslate2
+Home-page: https://github.com/SYSTRAN/faster-whisper
+Author: Guillaume Klein
+License: MIT
+Keywords: openai whisper speech ctranslate2 inference quantization transformer
+Platform: UNKNOWN
+Classifier: Development Status :: 4 - Beta
+Classifier: Intended Audience :: Developers
+Classifier: Intended Audience :: Science/Research
+Classifier: License :: OSI Approved :: MIT License
+Classifier: Programming Language :: Python :: 3
+Classifier: Programming Language :: Python :: 3 :: Only
+Classifier: Programming Language :: Python :: 3.8
+Classifier: Programming Language :: Python :: 3.9
+Classifier: Programming Language :: Python :: 3.10
+Classifier: Programming Language :: Python :: 3.11
+Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
+Requires-Python: >=3.8
+Description-Content-Type: text/markdown
+Provides-Extra: conversion
+Provides-Extra: dev
+License-File: LICENSE
+
+[](https://github.com/SYSTRAN/faster-whisper/actions?query=workflow%3ACI) [](https://badge.fury.io/py/faster-whisper)
+
+# Faster Whisper transcription with CTranslate2
+
+**faster-whisper** is a reimplementation of OpenAI's Whisper model using [CTranslate2](https://github.com/OpenNMT/CTranslate2/), which is a fast inference engine for Transformer models.
+
+This implementation is up to 4 times faster than [openai/whisper](https://github.com/openai/whisper) for the same accuracy while using less memory. The efficiency can be further improved with 8-bit quantization on both CPU and GPU.
+
+## Benchmark
+
+### Whisper
+
+For reference, here's the time and memory usage that are required to transcribe [**13 minutes**](https://www.youtube.com/watch?v=0u7tTptBo9I) of audio using different implementations:
+
+* [openai/whisper](https://github.com/openai/whisper)@[6dea21fd](https://github.com/openai/whisper/commit/6dea21fd7f7253bfe450f1e2512a0fe47ee2d258)
+* [whisper.cpp](https://github.com/ggerganov/whisper.cpp)@[3b010f9](https://github.com/ggerganov/whisper.cpp/commit/3b010f9bed9a6068609e9faf52383aea792b0362)
+* [faster-whisper](https://github.com/SYSTRAN/faster-whisper)@[cce6b53e](https://github.com/SYSTRAN/faster-whisper/commit/cce6b53e4554f71172dad188c45f10fb100f6e3e)
+
+### Large-v2 model on GPU
+
+| Implementation | Precision | Beam size | Time | Max. GPU memory | Max. CPU memory |
+| --- | --- | --- | --- | --- | --- |
+| openai/whisper | fp16 | 5 | 4m30s | 11325MB | 9439MB |
+| faster-whisper | fp16 | 5 | 54s | 4755MB | 3244MB |
+| faster-whisper | int8 | 5 | 59s | 3091MB | 3117MB |
+
+*Executed with CUDA 11.7.1 on a NVIDIA Tesla V100S.*
+
+### Small model on CPU
+
+| Implementation | Precision | Beam size | Time | Max. memory |
+| --- | --- | --- | --- | --- |
+| openai/whisper | fp32 | 5 | 10m31s | 3101MB |
+| whisper.cpp | fp32 | 5 | 17m42s | 1581MB |
+| whisper.cpp | fp16 | 5 | 12m39s | 873MB |
+| faster-whisper | fp32 | 5 | 2m44s | 1675MB |
+| faster-whisper | int8 | 5 | 2m04s | 995MB |
+
+*Executed with 8 threads on a Intel(R) Xeon(R) Gold 6226R.*
+
+
+### Distil-whisper
+
+| Implementation | Precision | Beam size | Time | Gigaspeech WER |
+| --- | --- | --- | --- | --- |
+| distil-whisper/distil-large-v2 | fp16 | 4 |- | 10.36 |
+| [faster-distil-large-v2](https://huggingface.co/Systran/faster-distil-whisper-large-v2) | fp16 | 5 | - | 10.28 |
+| distil-whisper/distil-medium.en | fp16 | 4 | - | 11.21 |
+| [faster-distil-medium.en](https://huggingface.co/Systran/faster-distil-whisper-medium.en) | fp16 | 5 | - | 11.21 |
+
+*Executed with CUDA 11.4 on a NVIDIA 3090.*
+
+
+testing details (click to expand)
+
+For `distil-whisper/distil-large-v2`, the WER is tested with code sample from [link](https://huggingface.co/distil-whisper/distil-large-v2#evaluation). for `faster-distil-whisper`, the WER is tested with setting:
+```python
+from faster_whisper import WhisperModel
+
+model_size = "distil-large-v2"
+# model_size = "distil-medium.en"
+# Run on GPU with FP16
+model = WhisperModel(model_size, device="cuda", compute_type="float16")
+segments, info = model.transcribe("audio.mp3", beam_size=5, language="en")
+```
+
+
+## Requirements
+
+* Python 3.8 or greater
+
+
+### GPU
+
+GPU execution requires the following NVIDIA libraries to be installed:
+
+* [cuBLAS for CUDA 12](https://developer.nvidia.com/cublas)
+* [cuDNN 8 for CUDA 12](https://developer.nvidia.com/cudnn)
+
+**Note**: Latest versions of `ctranslate2` support CUDA 12 only. For CUDA 11, the current workaround is downgrading to the `3.24.0` version of `ctranslate2` (This can be done with `pip install --force-reinstall ctranslate2==3.24.0` or specifying the version in a `requirements.txt`).
+
+There are multiple ways to install the NVIDIA libraries mentioned above. The recommended way is described in the official NVIDIA documentation, but we also suggest other installation methods below.
+
+
+Other installation methods (click to expand)
+
+
+**Note:** For all these methods below, keep in mind the above note regarding CUDA versions. Depending on your setup, you may need to install the _CUDA 11_ versions of libraries that correspond to the CUDA 12 libraries listed in the instructions below.
+
+#### Use Docker
+
+The libraries (cuBLAS, cuDNN) are installed in these official NVIDIA CUDA Docker images: `nvidia/cuda:12.0.0-runtime-ubuntu20.04` or `nvidia/cuda:12.0.0-runtime-ubuntu22.04`.
+
+#### Install with `pip` (Linux only)
+
+On Linux these libraries can be installed with `pip`. Note that `LD_LIBRARY_PATH` must be set before launching Python.
+
+```bash
+pip install nvidia-cublas-cu12 nvidia-cudnn-cu12
+
+export LD_LIBRARY_PATH=`python3 -c 'import os; import nvidia.cublas.lib; import nvidia.cudnn.lib; print(os.path.dirname(nvidia.cublas.lib.__file__) + ":" + os.path.dirname(nvidia.cudnn.lib.__file__))'`
+```
+
+**Note**: Version 9+ of `nvidia-cudnn-cu12` appears to cause issues due its reliance on cuDNN 9 (Faster-Whisper does not currently support cuDNN 9). Ensure your version of the Python package is for cuDNN 8.
+
+#### Download the libraries from Purfview's repository (Windows & Linux)
+
+Purfview's [whisper-standalone-win](https://github.com/Purfview/whisper-standalone-win) provides the required NVIDIA libraries for Windows & Linux in a [single archive](https://github.com/Purfview/whisper-standalone-win/releases/tag/libs). Decompress the archive and place the libraries in a directory included in the `PATH`.
+
+
+
+## Installation
+
+The module can be installed from [PyPI](https://pypi.org/project/faster-whisper/):
+
+```bash
+pip install faster-whisper
+```
+
+
+Other installation methods (click to expand)
+
+### Install the master branch
+
+```bash
+pip install --force-reinstall "faster-whisper @ https://github.com/SYSTRAN/faster-whisper/archive/refs/heads/master.tar.gz"
+```
+
+### Install a specific commit
+
+```bash
+pip install --force-reinstall "faster-whisper @ https://github.com/SYSTRAN/faster-whisper/archive/a4f1cc8f11433e454c3934442b5e1a4ed5e865c3.tar.gz"
+```
+
+
+
+## Usage
+
+### Faster-whisper
+
+```python
+from faster_whisper import WhisperModel
+
+model_size = "large-v3"
+
+# Run on GPU with FP16
+model = WhisperModel(model_size, device="cuda", compute_type="float16")
+
+# or run on GPU with INT8
+# model = WhisperModel(model_size, device="cuda", compute_type="int8_float16")
+# or run on CPU with INT8
+# model = WhisperModel(model_size, device="cpu", compute_type="int8")
+
+segments, info = model.transcribe("audio.mp3", beam_size=5)
+
+print("Detected language '%s' with probability %f" % (info.language, info.language_probability))
+
+for segment in segments:
+ print("[%.2fs -> %.2fs] %s" % (segment.start, segment.end, segment.text))
+```
+
+**Warning:** `segments` is a *generator* so the transcription only starts when you iterate over it. The transcription can be run to completion by gathering the segments in a list or a `for` loop:
+
+```python
+segments, _ = model.transcribe("audio.mp3")
+segments = list(segments) # The transcription will actually run here.
+```
+
+### multi-segment language detection
+
+To directly use the model for improved language detection, the following code snippet can be used:
+
+```python
+from faster_whisper import WhisperModel
+model = WhisperModel("medium", device="cuda", compute_type="float16")
+language_info = model.detect_language_multi_segment("audio.mp3")
+```
+
+### Batched faster-whisper
+
+
+The batched version of faster-whisper is inspired by [whisper-x](https://github.com/m-bain/whisperX) licensed under the BSD-2 Clause license and integrates its VAD model to this library. We modify this implementation and also replaced the feature extraction with a faster torch-based implementation. Batched version improves the speed upto 10-12x compared to openAI implementation and 3-4x compared to the sequential faster_whisper version. It works by transcribing semantically meaningful audio chunks as batches leading to faster inference.
+
+The following code snippet illustrates how to run inference with batched version on an example audio file. Please also refer to the test scripts of batched faster whisper.
+
+```python
+from faster_whisper import WhisperModel, BatchedInferencePipeline
+
+model = WhisperModel("medium", device="cuda", compute_type="float16")
+batched_model = BatchedInferencePipeline(model=model)
+segments, info = batched_model.transcribe("audio.mp3", batch_size=16)
+
+for segment in segments:
+ print("[%.2fs -> %.2fs] %s" % (segment.start, segment.end, segment.text))
+```
+
+### Faster Distil-Whisper
+
+The Distil-Whisper checkpoints are compatible with the Faster-Whisper package. In particular, the latest [distil-large-v3](https://huggingface.co/distil-whisper/distil-large-v3)
+checkpoint is intrinsically designed to work with the Faster-Whisper transcription algorithm. The following code snippet
+demonstrates how to run inference with distil-large-v3 on a specified audio file:
+
+```python
+from faster_whisper import WhisperModel
+
+model_size = "distil-large-v3"
+
+model = WhisperModel(model_size, device="cuda", compute_type="float16")
+segments, info = model.transcribe("audio.mp3", beam_size=5, language="en", condition_on_previous_text=False)
+
+for segment in segments:
+ print("[%.2fs -> %.2fs] %s" % (segment.start, segment.end, segment.text))
+```
+
+For more information about the distil-large-v3 model, refer to the original [model card](https://huggingface.co/distil-whisper/distil-large-v3).
+
+### Word-level timestamps
+
+```python
+segments, _ = model.transcribe("audio.mp3", word_timestamps=True)
+
+for segment in segments:
+ for word in segment.words:
+ print("[%.2fs -> %.2fs] %s" % (word.start, word.end, word.word))
+```
+
+### VAD filter
+
+The library integrates the [Silero VAD](https://github.com/snakers4/silero-vad) model to filter out parts of the audio without speech:
+
+```python
+segments, _ = model.transcribe("audio.mp3", vad_filter=True)
+```
+
+The default behavior is conservative and only removes silence longer than 2 seconds. See the available VAD parameters and default values in the [source code](https://github.com/SYSTRAN/faster-whisper/blob/master/faster_whisper/vad.py). They can be customized with the dictionary argument `vad_parameters`:
+
+```python
+segments, _ = model.transcribe(
+ "audio.mp3",
+ vad_filter=True,
+ vad_parameters=dict(min_silence_duration_ms=500),
+)
+```
+
+### Logging
+
+The library logging level can be configured like this:
+
+```python
+import logging
+
+logging.basicConfig()
+logging.getLogger("faster_whisper").setLevel(logging.DEBUG)
+```
+
+### Going further
+
+See more model and transcription options in the [`WhisperModel`](https://github.com/SYSTRAN/faster-whisper/blob/master/faster_whisper/transcribe.py) class implementation.
+
+## Community integrations
+
+Here is a non exhaustive list of open-source projects using faster-whisper. Feel free to add your project to the list!
+
+
+* [faster-whisper-server](https://github.com/fedirz/faster-whisper-server) is an OpenAI compatible server using `faster-whisper`. It's easily deployable with Docker, works with OpenAI SDKs/CLI, supports streaming, and live transcription.
+* [WhisperX](https://github.com/m-bain/whisperX) is an award-winning Python library that offers speaker diarization and accurate word-level timestamps using wav2vec2 alignment
+* [whisper-ctranslate2](https://github.com/Softcatala/whisper-ctranslate2) is a command line client based on faster-whisper and compatible with the original client from openai/whisper.
+* [whisper-diarize](https://github.com/MahmoudAshraf97/whisper-diarization) is a speaker diarization tool that is based on faster-whisper and NVIDIA NeMo.
+* [whisper-standalone-win](https://github.com/Purfview/whisper-standalone-win) Standalone CLI executables of faster-whisper for Windows, Linux & macOS.
+* [asr-sd-pipeline](https://github.com/hedrergudene/asr-sd-pipeline) provides a scalable, modular, end to end multi-speaker speech to text solution implemented using AzureML pipelines.
+* [Open-Lyrics](https://github.com/zh-plus/Open-Lyrics) is a Python library that transcribes voice files using faster-whisper, and translates/polishes the resulting text into `.lrc` files in the desired language using OpenAI-GPT.
+* [wscribe](https://github.com/geekodour/wscribe) is a flexible transcript generation tool supporting faster-whisper, it can export word level transcript and the exported transcript then can be edited with [wscribe-editor](https://github.com/geekodour/wscribe-editor)
+* [aTrain](https://github.com/BANDAS-Center/aTrain) is a graphical user interface implementation of faster-whisper developed at the BANDAS-Center at the University of Graz for transcription and diarization in Windows ([Windows Store App](https://apps.microsoft.com/detail/atrain/9N15Q44SZNS2)) and Linux.
+* [Whisper-Streaming](https://github.com/ufal/whisper_streaming) implements real-time mode for offline Whisper-like speech-to-text models with faster-whisper as the most recommended back-end. It implements a streaming policy with self-adaptive latency based on the actual source complexity, and demonstrates the state of the art.
+* [WhisperLive](https://github.com/collabora/WhisperLive) is a nearly-live implementation of OpenAI's Whisper which uses faster-whisper as the backend to transcribe audio in real-time.
+* [Faster-Whisper-Transcriber](https://github.com/BBC-Esq/ctranslate2-faster-whisper-transcriber) is a simple but reliable voice transcriber that provides a user-friendly interface.
+
+## Model conversion
+
+When loading a model from its size such as `WhisperModel("large-v3")`, the corresponding CTranslate2 model is automatically downloaded from the [Hugging Face Hub](https://huggingface.co/Systran).
+
+We also provide a script to convert any Whisper models compatible with the Transformers library. They could be the original OpenAI models or user fine-tuned models.
+
+For example the command below converts the [original "large-v3" Whisper model](https://huggingface.co/openai/whisper-large-v3) and saves the weights in FP16:
+
+```bash
+pip install transformers[torch]>=4.23
+
+ct2-transformers-converter --model openai/whisper-large-v3 --output_dir whisper-large-v3-ct2
+--copy_files tokenizer.json preprocessor_config.json --quantization float16
+```
+
+* The option `--model` accepts a model name on the Hub or a path to a model directory.
+* If the option `--copy_files tokenizer.json` is not used, the tokenizer configuration is automatically downloaded when the model is loaded later.
+
+Models can also be converted from the code. See the [conversion API](https://opennmt.net/CTranslate2/python/ctranslate2.converters.TransformersConverter.html).
+
+### Load a converted model
+
+1. Directly load the model from a local directory:
+```python
+model = faster_whisper.WhisperModel("whisper-large-v3-ct2")
+```
+
+2. [Upload your model to the Hugging Face Hub](https://huggingface.co/docs/transformers/model_sharing#upload-with-the-web-interface) and load it from its name:
+```python
+model = faster_whisper.WhisperModel("username/whisper-large-v3-ct2")
+```
+
+## Comparing performance against other implementations
+
+If you are comparing the performance against other Whisper implementations, you should make sure to run the comparison with similar settings. In particular:
+
+* Verify that the same transcription options are used, especially the same beam size. For example in openai/whisper, `model.transcribe` uses a default beam size of 1 but here we use a default beam size of 5.
+* When running on CPU, make sure to set the same number of threads. Many frameworks will read the environment variable `OMP_NUM_THREADS`, which can be set when running your script:
+
+```bash
+OMP_NUM_THREADS=4 python3 my_script.py
+```
+
+
diff --git a/whisper_pipeline/faster-whisper-main/faster_whisper.egg-info/SOURCES.txt b/whisper_pipeline/faster-whisper-main/faster_whisper.egg-info/SOURCES.txt
new file mode 100644
index 0000000000000000000000000000000000000000..99cda55c53be74ad03fc02e764c6e689d4c30bae
--- /dev/null
+++ b/whisper_pipeline/faster-whisper-main/faster_whisper.egg-info/SOURCES.txt
@@ -0,0 +1,25 @@
+LICENSE
+MANIFEST.in
+README.md
+requirements.conversion.txt
+requirements.txt
+setup.cfg
+setup.py
+faster_whisper/__init__.py
+faster_whisper/audio.py
+faster_whisper/feature_extractor.py
+faster_whisper/tokenizer.py
+faster_whisper/transcribe.py
+faster_whisper/utils.py
+faster_whisper/vad.py
+faster_whisper/version.py
+faster_whisper.egg-info/PKG-INFO
+faster_whisper.egg-info/SOURCES.txt
+faster_whisper.egg-info/dependency_links.txt
+faster_whisper.egg-info/requires.txt
+faster_whisper.egg-info/top_level.txt
+faster_whisper/assets/__init__.py
+faster_whisper/assets/pyannote_vad_model.bin
+faster_whisper/assets/silero_vad.onnx
+tests/test_transcribe.py
+tests/test_utils.py
\ No newline at end of file
diff --git a/whisper_pipeline/faster-whisper-main/faster_whisper.egg-info/dependency_links.txt b/whisper_pipeline/faster-whisper-main/faster_whisper.egg-info/dependency_links.txt
new file mode 100644
index 0000000000000000000000000000000000000000..8b137891791fe96927ad78e64b0aad7bded08bdc
--- /dev/null
+++ b/whisper_pipeline/faster-whisper-main/faster_whisper.egg-info/dependency_links.txt
@@ -0,0 +1 @@
+
diff --git a/whisper_pipeline/faster-whisper-main/faster_whisper.egg-info/requires.txt b/whisper_pipeline/faster-whisper-main/faster_whisper.egg-info/requires.txt
new file mode 100644
index 0000000000000000000000000000000000000000..41e7caccbf2fdcaaf21b26f84624acb386d214c2
--- /dev/null
+++ b/whisper_pipeline/faster-whisper-main/faster_whisper.egg-info/requires.txt
@@ -0,0 +1,17 @@
+ctranslate2<5,>=4.0
+huggingface_hub>=0.13
+onnxruntime<2,>=1.14
+pyannote-audio
+tokenizers<1,>=0.13
+torch
+torchaudio
+tqdm
+
+[conversion]
+transformers[torch]>=4.23
+
+[dev]
+black==23.*
+flake8==6.*
+isort==5.*
+pytest==7.*
diff --git a/whisper_pipeline/faster-whisper-main/faster_whisper.egg-info/top_level.txt b/whisper_pipeline/faster-whisper-main/faster_whisper.egg-info/top_level.txt
new file mode 100644
index 0000000000000000000000000000000000000000..a0e0f023cbf7607475e5adaee2ab32cab009ba62
--- /dev/null
+++ b/whisper_pipeline/faster-whisper-main/faster_whisper.egg-info/top_level.txt
@@ -0,0 +1 @@
+faster_whisper
diff --git a/whisper_pipeline/faster-whisper-main/faster_whisper/__init__.py b/whisper_pipeline/faster-whisper-main/faster_whisper/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..ad69277853742e3f9f0e0f020c0862cf4ad404fb
--- /dev/null
+++ b/whisper_pipeline/faster-whisper-main/faster_whisper/__init__.py
@@ -0,0 +1,14 @@
+from faster_whisper.audio import decode_audio
+from faster_whisper.transcribe import BatchedInferencePipeline, WhisperModel
+from faster_whisper.utils import available_models, download_model, format_timestamp
+from faster_whisper.version import __version__
+
+__all__ = [
+ "available_models",
+ "decode_audio",
+ "WhisperModel",
+ "BatchedInferencePipeline",
+ "download_model",
+ "format_timestamp",
+ "__version__",
+]
diff --git a/whisper_pipeline/faster-whisper-main/faster_whisper/__pycache__/__init__.cpython-310.pyc b/whisper_pipeline/faster-whisper-main/faster_whisper/__pycache__/__init__.cpython-310.pyc
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diff --git a/whisper_pipeline/faster-whisper-main/faster_whisper/assets/__init__.py b/whisper_pipeline/faster-whisper-main/faster_whisper/assets/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/whisper_pipeline/faster-whisper-main/faster_whisper/assets/pyannote_vad_model.bin b/whisper_pipeline/faster-whisper-main/faster_whisper/assets/pyannote_vad_model.bin
new file mode 100644
index 0000000000000000000000000000000000000000..7a0c29f0dbd55f172445e95ae1f0163a7d849c27
--- /dev/null
+++ b/whisper_pipeline/faster-whisper-main/faster_whisper/assets/pyannote_vad_model.bin
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0b5b3216d60a2d32fc086b47ea8c67589aaeb26b7e07fcbe620d6d0b83e209ea
+size 17719103
diff --git a/whisper_pipeline/faster-whisper-main/faster_whisper/assets/silero_vad.onnx b/whisper_pipeline/faster-whisper-main/faster_whisper/assets/silero_vad.onnx
new file mode 100644
index 0000000000000000000000000000000000000000..6ea96ef73cac24d33ad342094d95867c756d3f5c
--- /dev/null
+++ b/whisper_pipeline/faster-whisper-main/faster_whisper/assets/silero_vad.onnx
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6b99cbfd39246b6706f98ec13c7c50c6b299181f2474fa05cbc8046acc274396
+size 2313101
diff --git a/whisper_pipeline/faster-whisper-main/faster_whisper/audio.py b/whisper_pipeline/faster-whisper-main/faster_whisper/audio.py
new file mode 100644
index 0000000000000000000000000000000000000000..7ae68d40055b0df3427c1201d9cd92f663110b12
--- /dev/null
+++ b/whisper_pipeline/faster-whisper-main/faster_whisper/audio.py
@@ -0,0 +1,58 @@
+from typing import BinaryIO, Union
+
+import torch
+import torchaudio
+
+
+def decode_audio(
+ input_file: Union[str, BinaryIO],
+ sampling_rate: int = 16000,
+ split_stereo: bool = False,
+):
+ """Decodes the audio.
+
+ Args:
+ input_file: Path to the input file or a file-like object.
+ sampling_rate: Resample the audio to this sample rate.
+ split_stereo: Return separate left and right channels.
+
+ Returns:
+ A float32 Torch Tensor.
+
+ If `split_stereo` is enabled, the function returns a 2-tuple with the
+ separated left and right channels.
+ """
+
+ waveform, audio_sf = torchaudio.load(input_file) # waveform: channels X T
+
+ if audio_sf != sampling_rate:
+ waveform = torchaudio.functional.resample(
+ waveform, orig_freq=audio_sf, new_freq=sampling_rate
+ )
+ if split_stereo:
+ return waveform[0], waveform[1]
+
+ return waveform.mean(0)
+
+
+def pad_or_trim(array, length: int, *, axis: int = -1):
+ """
+ Pad or trim the audio array to N_SAMPLES, as expected by the encoder.
+ """
+ axis = axis % array.ndim
+ if array.shape[axis] > length:
+ idx = [Ellipsis] * axis + [slice(length)] + [Ellipsis] * (array.ndim - axis - 1)
+ return array[idx]
+
+ if array.shape[axis] < length:
+ pad_widths = (
+ [
+ 0,
+ ]
+ * array.ndim
+ * 2
+ )
+ pad_widths[2 * axis] = length - array.shape[axis]
+ array = torch.nn.functional.pad(array, tuple(pad_widths[::-1]))
+
+ return array
diff --git a/whisper_pipeline/faster-whisper-main/faster_whisper/feature_extractor.py b/whisper_pipeline/faster-whisper-main/faster_whisper/feature_extractor.py
new file mode 100644
index 0000000000000000000000000000000000000000..6371d5ef6864b07ce4b7f3c1cd1075fee9c8e484
--- /dev/null
+++ b/whisper_pipeline/faster-whisper-main/faster_whisper/feature_extractor.py
@@ -0,0 +1,114 @@
+import torch
+
+
+# Adapted from https://github.com/huggingface/transformers/blob/main/src/transformers/models/whisper/feature_extraction_whisper.py # noqa: E501
+class FeatureExtractor:
+ def __init__(
+ self,
+ device: str = "auto",
+ feature_size=80,
+ sampling_rate=16000,
+ hop_length=160,
+ chunk_length=30,
+ n_fft=400,
+ ):
+ if device == "auto":
+ self.device = "cuda" if torch.cuda.is_available() else "cpu"
+ else:
+ self.device = device
+ self.n_fft = n_fft
+ self.hop_length = hop_length
+ self.chunk_length = chunk_length
+ self.n_samples = chunk_length * sampling_rate
+ self.nb_max_frames = self.n_samples // hop_length
+ self.time_per_frame = hop_length / sampling_rate
+ self.sampling_rate = sampling_rate
+ self.mel_filters = self.get_mel_filters(
+ sampling_rate, n_fft, n_mels=feature_size
+ )
+
+ @staticmethod
+ def get_mel_filters(sr, n_fft, n_mels=128):
+ """
+ Implementation of librosa.filters.mel in Pytorch
+ """
+ # Initialize the weights
+ n_mels = int(n_mels)
+
+ # Center freqs of each FFT bin
+ fftfreqs = torch.fft.rfftfreq(n=n_fft, d=1.0 / sr)
+
+ # 'Center freqs' of mel bands - uniformly spaced between limits
+ min_mel = 0.0
+ max_mel = 45.245640471924965
+
+ mels = torch.linspace(min_mel, max_mel, n_mels + 2)
+
+ # Fill in the linear scale
+ f_min = 0.0
+ f_sp = 200.0 / 3
+ freqs = f_min + f_sp * mels
+
+ # And now the nonlinear scale
+ min_log_hz = 1000.0 # beginning of log region (Hz)
+ min_log_mel = (min_log_hz - f_min) / f_sp # same (Mels)
+ logstep = torch.log(torch.tensor(6.4)) / 27.0 # step size for log region
+
+ # If we have vector data, vectorize
+ log_t = mels >= min_log_mel
+ freqs[log_t] = min_log_hz * torch.exp(logstep * (mels[log_t] - min_log_mel))
+
+ mel_f = freqs
+
+ fdiff = torch.diff(mel_f)
+ ramps = mel_f.view(-1, 1) - fftfreqs.view(1, -1)
+
+ lower = -ramps[:-2] / fdiff[:-1].unsqueeze(1)
+ upper = ramps[2:] / fdiff[1:].unsqueeze(1)
+
+ # Intersect them with each other and zero, vectorized across all i
+ weights = torch.maximum(torch.zeros_like(lower), torch.minimum(lower, upper))
+
+ # Slaney-style mel is scaled to be approx constant energy per channel
+ enorm = 2.0 / (mel_f[2 : n_mels + 2] - mel_f[:n_mels])
+ weights *= enorm.unsqueeze(1)
+
+ return weights
+
+ def __call__(self, waveform, padding=True, chunk_length=None, to_cpu=False):
+ """
+ Compute the log-Mel spectrogram of the provided audio.
+ """
+
+ if chunk_length is not None:
+ self.n_samples = chunk_length * self.sampling_rate
+ self.nb_max_frames = self.n_samples // self.hop_length
+
+ if waveform.dtype is not torch.float32:
+ waveform = waveform.to(torch.float32)
+
+ waveform = (
+ waveform.to(self.device)
+ if self.device == "cuda" and not waveform.is_cuda
+ else waveform
+ )
+
+ if padding:
+ waveform = torch.nn.functional.pad(waveform, (0, self.n_samples))
+
+ window = torch.hann_window(self.n_fft).to(waveform.device)
+
+ stft = torch.stft(
+ waveform, self.n_fft, self.hop_length, window=window, return_complex=True
+ )
+ magnitudes = stft[..., :-1].abs() ** 2
+
+ mel_spec = self.mel_filters.to(waveform.device) @ magnitudes
+
+ log_spec = torch.clamp(mel_spec, min=1e-10).log10()
+ log_spec = torch.maximum(log_spec, log_spec.max() - 8.0)
+ log_spec = (log_spec + 4.0) / 4.0
+
+ # When the model is running on multiple GPUs, the output should be moved
+ # to the CPU since we don't know which GPU will handle the next job.
+ return log_spec.cpu() if to_cpu else log_spec
diff --git a/whisper_pipeline/faster-whisper-main/faster_whisper/tokenizer.py b/whisper_pipeline/faster-whisper-main/faster_whisper/tokenizer.py
new file mode 100644
index 0000000000000000000000000000000000000000..3bf76a5f6321d5f17cb778604b3e5e3d73275835
--- /dev/null
+++ b/whisper_pipeline/faster-whisper-main/faster_whisper/tokenizer.py
@@ -0,0 +1,314 @@
+import string
+
+from functools import cached_property
+from typing import List, Optional, Tuple
+
+import tokenizers
+
+
+class Tokenizer:
+ """Simple wrapper around a tokenizers.Tokenizer."""
+
+ def __init__(
+ self,
+ tokenizer: tokenizers.Tokenizer,
+ multilingual: bool,
+ task: Optional[str] = None,
+ language: Optional[str] = None,
+ ):
+ self.tokenizer = tokenizer
+
+ if multilingual:
+ if task not in _TASKS:
+ raise ValueError(
+ "'%s' is not a valid task (accepted tasks: %s)"
+ % (task, ", ".join(_TASKS))
+ )
+
+ if language not in _LANGUAGE_CODES:
+ raise ValueError(
+ "'%s' is not a valid language code (accepted language codes: %s)"
+ % (language, ", ".join(_LANGUAGE_CODES))
+ )
+
+ self.task = self.tokenizer.token_to_id("<|%s|>" % task)
+ self.language = self.tokenizer.token_to_id("<|%s|>" % language)
+ self.language_code = language
+ else:
+ self.task = None
+ self.language = None
+ self.language_code = "en"
+
+ @cached_property
+ def transcribe(self) -> int:
+ return self.tokenizer.token_to_id("<|transcribe|>")
+
+ @cached_property
+ def translate(self) -> int:
+ return self.tokenizer.token_to_id("<|translate|>")
+
+ @cached_property
+ def sot(self) -> int:
+ return self.tokenizer.token_to_id("<|startoftranscript|>")
+
+ @cached_property
+ def sot_lm(self) -> int:
+ return self.tokenizer.token_to_id("<|startoflm|>")
+
+ @cached_property
+ def sot_prev(self) -> int:
+ return self.tokenizer.token_to_id("<|startofprev|>")
+
+ @cached_property
+ def eot(self) -> int:
+ return self.tokenizer.token_to_id("<|endoftext|>")
+
+ @cached_property
+ def no_timestamps(self) -> int:
+ return self.tokenizer.token_to_id("<|notimestamps|>")
+
+ @property
+ def timestamp_begin(self) -> int:
+ return self.no_timestamps + 1
+
+ @property
+ def sot_sequence(self) -> List[int]:
+ sequence = [self.sot]
+
+ if self.language is not None:
+ sequence.append(self.language)
+
+ if self.task is not None:
+ sequence.append(self.task)
+
+ return sequence
+
+ def encode(self, text: str) -> List[int]:
+ return self.tokenizer.encode(text, add_special_tokens=False).ids
+
+ def decode(self, tokens: List[int]) -> str:
+ text_tokens = [token for token in tokens if token < self.eot]
+ return self.tokenizer.decode(text_tokens)
+
+ def decode_with_timestamps(self, tokens: List[int]) -> str:
+ outputs = [[]]
+
+ for token in tokens:
+ if token >= self.timestamp_begin:
+ timestamp = f"<|{(token - self.timestamp_begin) * 0.02:.2f}|>"
+ outputs.append(timestamp)
+ outputs.append([])
+ else:
+ outputs[-1].append(token)
+
+ return "".join(
+ [s if isinstance(s, str) else self.tokenizer.decode(s) for s in outputs]
+ )
+
+ @cached_property
+ def non_speech_tokens(self) -> Tuple[int]:
+ """
+ Returns the list of tokens to suppress in order to avoid any speaker tags or non-speech
+ annotations, to prevent sampling texts that are not actually spoken in the audio, e.g.
+
+ - ♪♪♪
+ - ( SPEAKING FOREIGN LANGUAGE )
+ - [DAVID] Hey there,
+
+ keeping basic punctuations like commas, periods, question marks, exclamation points, etc.
+ """
+ symbols = list('"#()*+/:;<=>@[\\]^_`{|}~「」『』')
+ symbols += (
+ "<< >> <<< >>> -- --- -( -[ (' (\" (( )) ((( ))) [[ ]] {{ }} ♪♪ ♪♪♪".split()
+ )
+
+ # symbols that may be a single token or multiple tokens depending on the tokenizer.
+ # In case they're multiple tokens, suppress the first token, which is safe because:
+ # These are between U+2640 and U+267F miscellaneous symbols that are okay to suppress
+ # in generations, and in the 3-byte UTF-8 representation they share the first two bytes.
+ miscellaneous = set("♩♪♫♬♭♮♯")
+ assert all(0x2640 <= ord(c) <= 0x267F for c in miscellaneous)
+
+ # allow hyphens "-" and single quotes "'" between words, but not at the beginning of a word
+ result = {self.encode(" -")[0], self.encode(" '")[0]}
+ for symbol in symbols + list(miscellaneous):
+ for tokens in [
+ self.encode(symbol),
+ self.encode(" " + symbol),
+ ]:
+ if len(tokens) == 1 or symbol in miscellaneous:
+ result.add(tokens[0])
+
+ return tuple(sorted(result))
+
+ def split_to_word_tokens(
+ self, tokens: List[int]
+ ) -> Tuple[List[str], List[List[int]]]:
+ if self.language_code in {"zh", "ja", "th", "lo", "my", "yue"}:
+ # These languages don't typically use spaces, so it is difficult to split words
+ # without morpheme analysis. Here, we instead split words at any
+ # position where the tokens are decoded as valid unicode points
+ return self.split_tokens_on_unicode(tokens)
+
+ return self.split_tokens_on_spaces(tokens)
+
+ def split_tokens_on_unicode(
+ self, tokens: List[int]
+ ) -> Tuple[List[str], List[List[int]]]:
+ decoded_full = self.decode_with_timestamps(tokens)
+ replacement_char = "\ufffd"
+
+ words = []
+ word_tokens = []
+ current_tokens = []
+ unicode_offset = 0
+
+ for token in tokens:
+ current_tokens.append(token)
+ decoded = self.decode_with_timestamps(current_tokens)
+
+ try:
+ replacement_char_index = decoded.index(replacement_char)
+ replacement_char_index += unicode_offset
+ except ValueError:
+ replacement_char_index = None
+
+ if replacement_char_index is None or (
+ replacement_char_index < len(decoded_full)
+ and decoded_full[replacement_char_index] == replacement_char
+ ):
+ words.append(decoded)
+ word_tokens.append(current_tokens)
+ current_tokens = []
+ unicode_offset += len(decoded)
+
+ return words, word_tokens
+
+ def split_tokens_on_spaces(
+ self, tokens: List[int]
+ ) -> Tuple[List[str], List[List[int]]]:
+ subwords, subword_tokens_list = self.split_tokens_on_unicode(tokens)
+ words = []
+ word_tokens = []
+
+ for subword, subword_tokens in zip(subwords, subword_tokens_list):
+ special = subword_tokens[0] >= self.eot
+ with_space = subword.startswith(" ")
+ punctuation = subword.strip() in string.punctuation
+ if special or with_space or punctuation or len(words) == 0:
+ words.append(subword)
+ word_tokens.append(subword_tokens)
+ else:
+ words[-1] = words[-1] + subword
+ word_tokens[-1].extend(subword_tokens)
+
+ return words, word_tokens
+
+
+_TASKS = (
+ "transcribe",
+ "translate",
+)
+
+_LANGUAGE_CODES = (
+ "af",
+ "am",
+ "ar",
+ "as",
+ "az",
+ "ba",
+ "be",
+ "bg",
+ "bn",
+ "bo",
+ "br",
+ "bs",
+ "ca",
+ "cs",
+ "cy",
+ "da",
+ "de",
+ "el",
+ "en",
+ "es",
+ "et",
+ "eu",
+ "fa",
+ "fi",
+ "fo",
+ "fr",
+ "gl",
+ "gu",
+ "ha",
+ "haw",
+ "he",
+ "hi",
+ "hr",
+ "ht",
+ "hu",
+ "hy",
+ "id",
+ "is",
+ "it",
+ "ja",
+ "jw",
+ "ka",
+ "kk",
+ "km",
+ "kn",
+ "ko",
+ "la",
+ "lb",
+ "ln",
+ "lo",
+ "lt",
+ "lv",
+ "mg",
+ "mi",
+ "mk",
+ "ml",
+ "mn",
+ "mr",
+ "ms",
+ "mt",
+ "my",
+ "ne",
+ "nl",
+ "nn",
+ "no",
+ "oc",
+ "pa",
+ "pl",
+ "ps",
+ "pt",
+ "ro",
+ "ru",
+ "sa",
+ "sd",
+ "si",
+ "sk",
+ "sl",
+ "sn",
+ "so",
+ "sq",
+ "sr",
+ "su",
+ "sv",
+ "sw",
+ "ta",
+ "te",
+ "tg",
+ "th",
+ "tk",
+ "tl",
+ "tr",
+ "tt",
+ "uk",
+ "ur",
+ "uz",
+ "vi",
+ "yi",
+ "yo",
+ "zh",
+ "yue",
+)
diff --git a/whisper_pipeline/faster-whisper-main/faster_whisper/transcribe.py b/whisper_pipeline/faster-whisper-main/faster_whisper/transcribe.py
new file mode 100644
index 0000000000000000000000000000000000000000..8652e82b0463f1d786c50ba32209b62dd167142d
--- /dev/null
+++ b/whisper_pipeline/faster-whisper-main/faster_whisper/transcribe.py
@@ -0,0 +1,2170 @@
+import itertools
+import json
+import logging
+import os
+import random
+import zlib
+
+from collections import Counter, defaultdict
+from inspect import signature
+from typing import BinaryIO, Iterable, List, NamedTuple, Optional, Tuple, Union
+
+import ctranslate2
+import numpy as np
+import tokenizers
+import torch
+
+from pyannote.audio import Model
+from tqdm import tqdm
+
+from faster_whisper.audio import decode_audio, pad_or_trim
+from faster_whisper.feature_extractor import FeatureExtractor
+from faster_whisper.tokenizer import _LANGUAGE_CODES, Tokenizer
+from faster_whisper.utils import (
+ download_model,
+ format_timestamp,
+ get_assets_path,
+ get_end,
+ get_logger,
+)
+from faster_whisper.vad import (
+ SpeechTimestampsMap,
+ VadOptions,
+ VoiceActivitySegmentation,
+ collect_chunks,
+ get_speech_timestamps,
+ merge_chunks,
+)
+
+
+class Word(NamedTuple):
+ start: float
+ end: float
+ word: str
+ probability: float
+
+
+class Segment(NamedTuple):
+ id: int
+ seek: int
+ start: float
+ end: float
+ text: str
+ tokens: List[int]
+ avg_logprob: float
+ compression_ratio: float
+ no_speech_prob: float
+ words: Optional[List[Word]]
+ temperature: Optional[float] = 1.0
+
+
+# Added additional parameters for multilingual videos and fixes below
+class TranscriptionOptions(NamedTuple):
+ beam_size: int
+ best_of: int
+ patience: float
+ length_penalty: float
+ repetition_penalty: float
+ no_repeat_ngram_size: int
+ log_prob_threshold: Optional[float]
+ log_prob_low_threshold: Optional[float]
+ no_speech_threshold: Optional[float]
+ compression_ratio_threshold: Optional[float]
+ condition_on_previous_text: bool
+ prompt_reset_on_temperature: float
+ temperatures: List[float]
+ initial_prompt: Optional[Union[str, Iterable[int]]]
+ prefix: Optional[str]
+ suppress_blank: bool
+ suppress_tokens: Optional[List[int]]
+ without_timestamps: bool
+ max_initial_timestamp: float
+ word_timestamps: bool
+ prepend_punctuations: str
+ append_punctuations: str
+ multilingual: bool
+ output_language: Optional[str]
+ max_new_tokens: Optional[int]
+ clip_timestamps: Union[str, List[float]]
+ hallucination_silence_threshold: Optional[float]
+ hotwords: Optional[str]
+
+
+class TranscriptionInfo(NamedTuple):
+ language: str
+ language_probability: float
+ duration: float
+ duration_after_vad: float
+ all_language_probs: Optional[List[Tuple[str, float]]]
+ transcription_options: TranscriptionOptions
+ vad_options: VadOptions
+
+
+# The code below is originally from HF pipeline and is used in whisper-x
+# (https://github.com/m-bain/whisperX) and adapted for faster_whisper
+
+
+class BatchedInferencePipeline:
+ """
+ Huggingface Pipeline wrapper for WhisperModel.
+ Copyright (c) 2022, Max Bain
+ All rights reserved.
+ Modified by Mobius Labs GmbH
+ """
+
+ def __init__(
+ self,
+ model,
+ use_vad_model: bool = True,
+ options: Optional[NamedTuple] = None,
+ tokenizer=None,
+ chunk_length: int = 30,
+ vad_device: Union[int, str, "torch.device"] = "auto",
+ vad_onset: float = 0.500,
+ vad_offset: float = 0.363,
+ language: Optional[str] = None,
+ ):
+ self.model: WhisperModel = model
+ self.tokenizer = tokenizer
+ self.options = options
+ self.preset_language = language
+ self.use_vad_model = use_vad_model
+ self.vad_onset = vad_onset
+ self.vad_offset = vad_offset
+ self.vad_model_path = os.path.join(get_assets_path(), "pyannote_vad_model.bin")
+ if self.use_vad_model:
+ self.vad_device = self.get_device(vad_device)
+ self.vad_model = self.load_vad_model(
+ vad_onset=self.vad_onset, vad_offset=self.vad_offset
+ )
+ else:
+ self.vad_model = None
+ self.chunk_length = chunk_length # VAD merging size
+ self.last_speech_timestamp = 0.0
+
+ def get_device(self, device: Union[int, str, "torch.device"]):
+ """
+ Converts the input device into a torch.device object.
+
+ The input can be an integer, a string, or a `torch.device` object.
+
+ The function handles a special case where the input device is "auto".
+ When "auto" is specified, the device will default to the
+ device of the model (self.model.device). If the model's device is also "auto",
+ it selects "cuda" if a CUDA-capable device is available; otherwise, it selects "cpu".
+ """
+ if isinstance(device, torch.device):
+ return device
+ elif isinstance(device, str):
+ if device == "auto" and self.model.device == "auto":
+ device = "cuda" if torch.cuda.is_available() else "cpu"
+ elif device == "auto":
+ device = self.model.device
+ return torch.device(device)
+ elif device < 0:
+ return torch.device("cpu")
+ else:
+ return torch.device(f"cuda:{device}")
+
+ def forward(self, features, segments_metadata, **forward_params):
+ encoder_output, outputs = self.model.generate_segment_batched(
+ features, self.tokenizer, forward_params
+ )
+
+ segmented_outputs = []
+ segment_sizes = []
+ for segment_metadata, output in zip(segments_metadata, outputs):
+ duration = segment_metadata["end_time"] - segment_metadata["start_time"]
+ segment_size = int(duration * self.model.frames_per_second)
+ segment_sizes.append(segment_size)
+ (
+ subsegments,
+ seek,
+ single_timestamp_ending,
+ ) = self.model._split_segments_by_timestamps(
+ tokenizer=self.tokenizer,
+ tokens=output["tokens"],
+ time_offset=segment_metadata["start_time"],
+ segment_size=segment_size,
+ segment_duration=duration,
+ seek=0,
+ )
+ segmented_outputs.append(
+ [
+ dict(
+ text=self.tokenizer.decode(subsegment["tokens"]),
+ avg_logprob=output["avg_logprob"],
+ no_speech_prob=output["no_speech_prob"],
+ tokens=subsegment["tokens"],
+ start=subsegment["start"],
+ end=subsegment["end"],
+ compression_ratio=get_compression_ratio(
+ self.tokenizer.decode(subsegment["tokens"])
+ ),
+ )
+ for subsegment in subsegments
+ ]
+ )
+ if forward_params["word_timestamps"]:
+ self.last_speech_timestamp = self.model.add_word_timestamps(
+ segmented_outputs,
+ self.tokenizer,
+ encoder_output,
+ segment_sizes,
+ forward_params["prepend_punctuations"],
+ forward_params["append_punctuations"],
+ self.last_speech_timestamp,
+ )
+
+ return segmented_outputs
+
+ def get_language_and_tokenizer(
+ self, audio, task: Optional[str] = None, language: Optional[str] = None
+ ):
+ all_language_probs = None
+ language_probability = 1.0
+
+ if self.tokenizer is None:
+ if not language:
+ (
+ language,
+ language_probability,
+ all_language_probs,
+ ) = self.model.detect_language(audio)
+ task = task or "transcribe"
+ self.tokenizer = Tokenizer(
+ self.model.hf_tokenizer,
+ self.model.model.is_multilingual,
+ task=task,
+ language=language,
+ )
+ else:
+ if task is not None:
+ self.tokenizer.task = self.tokenizer.tokenizer.token_to_id(
+ f"<|{task}|>"
+ )
+
+ if language is not None:
+ self.tokenizer.language = self.tokenizer.tokenizer.token_to_id(
+ f"<|{language}|>"
+ )
+ self.tokenizer.language_code = language
+
+ return language, language_probability, task, all_language_probs
+
+ @staticmethod
+ def audio_split(audio, segments, sampling_rate):
+ """Returns splitted audio chunks as iterator"""
+ audio_segments = []
+ segments_metadata = []
+ for seg in segments:
+ f1 = int(seg["start"] * sampling_rate)
+ f2 = int(seg["end"] * sampling_rate)
+ seg_metadata = {
+ "start_time": seg["start"],
+ "end_time": seg["end"],
+ "stitched_seg": seg["segments"],
+ }
+ audio_segments.append(audio[f1:f2])
+ segments_metadata.append(seg_metadata)
+ return audio_segments, segments_metadata
+
+ def load_vad_model(self, vad_onset=0.500, vad_offset=0.363):
+ vad_model = Model.from_pretrained(self.vad_model_path)
+ hyperparameters = {
+ "onset": vad_onset,
+ "offset": vad_offset,
+ "min_duration_on": 0.1,
+ "min_duration_off": 0.1,
+ }
+
+ vad_pipeline = VoiceActivitySegmentation(
+ segmentation=vad_model, device=torch.device(self.vad_device)
+ )
+ vad_pipeline.instantiate(hyperparameters)
+ return vad_pipeline
+
+ def transcribe(
+ self,
+ audio: Union[str, torch.Tensor, np.ndarray],
+ vad_segments: Optional[List[dict]] = None,
+ batch_size: int = 16,
+ language: Optional[str] = None,
+ task: str = None,
+ log_progress: bool = False,
+ beam_size: int = 5,
+ best_of: int = 5,
+ patience: float = 1,
+ length_penalty: float = 1,
+ repetition_penalty: float = 1,
+ no_repeat_ngram_size: int = 0,
+ temperature: Union[float, List[float], Tuple[float, ...]] = [
+ 0.0,
+ 0.2,
+ 0.4,
+ 0.6,
+ 0.8,
+ 1.0,
+ ],
+ compression_ratio_threshold: Optional[float] = 2.4,
+ log_prob_threshold: Optional[float] = -1.0,
+ log_prob_low_threshold: Optional[float] = None,
+ no_speech_threshold: Optional[float] = 0.6,
+ initial_prompt: Optional[Union[str, Iterable[int]]] = None,
+ prefix: Optional[str] = None,
+ suppress_blank: bool = True,
+ suppress_tokens: Optional[List[int]] = [-1],
+ prepend_punctuations: str = "\"'“¿([{-",
+ append_punctuations: str = "\"'.。,，!！?？:：”)]}、",
+ max_new_tokens: Optional[int] = None,
+ hotwords: Optional[str] = None,
+ word_timestamps: bool = False,
+ without_timestamps: bool = True,
+ ) -> Tuple[Iterable[Segment], TranscriptionInfo]:
+ """transcribe audio in chunks in batched fashion and return with language info.
+
+ Arguments:
+ audio: audio file as numpy array/path for batched transcription.
+ vad_segments: Optionally provide list of dictionaries each containing "start", "end",
+ and "segments" keys.
+ "start" and "end" keys specify the start and end of the voiced region within
+ 30 sec boundary. An additional key "segments" contains all the start
+ and end of voiced regions within that 30sec boundary as a list of tuples.
+ If no vad_segments specified, it uses internal vad model automatically segment them.
+ batch_size: the maximum number of parallel requests to model for decoding.
+ language: The language spoken in the audio.
+ task: either "transcribe" or "translate".
+ log_progress: whether to show progress bar or not.
+ beam_size: Beam size to use for decoding.
+ best_of: Number of candidates when sampling with non-zero temperature.
+ patience: Beam search patience factor.
+ length_penalty: Exponential length penalty constant.
+ repetition_penalty: Penalty applied to the score of previously generated tokens
+ (set > 1 to penalize).
+ no_repeat_ngram_size: Prevent repetitions of ngrams with this size (set 0 to disable).
+ temperature: Temperature for sampling. It can be a tuple of temperatures,
+ which will be successively used upon failures according to either
+ `compression_ratio_threshold` or `log_prob_threshold`.
+ compression_ratio_threshold: If the gzip compression ratio is above this value,
+ treat as failed.
+ log_prob_threshold: If the average log probability over sampled tokens is
+ below this value, treat as failed.
+ log_prob_low_threshold: This parameter alone is sufficient to skip an output text,
+ whereas log_prob_threshold also looks for appropriate no_speech_threshold value.
+ This value should be less than log_prob_threshold.
+ no_speech_threshold: If the no_speech probability is higher than this value AND
+ the average log probability over sampled tokens is below `log_prob_threshold`,
+ consider the segment as silent.
+ initial_prompt: Optional text string or iterable of token ids to provide as a
+ prompt for the first window.
+ prefix: Optional text to provide as a prefix for the first window.
+ suppress_blank: Suppress blank outputs at the beginning of the sampling.
+ suppress_tokens: List of token IDs to suppress. -1 will suppress a default set
+ of symbols as defined in `tokenizer.non_speech_tokens()`.
+ prepend_punctuations: If word_timestamps is True, merge these punctuation symbols
+ with the next word
+ append_punctuations: If word_timestamps is True, merge these punctuation symbols
+ with the previous word
+ max_new_tokens: Maximum number of new tokens to generate per-chunk. If not set,
+ the maximum will be set by the default max_length.
+ hotwords:
+ Hotwords/hint phrases to the model. Has no effect if prefix is not None.
+ word_timestamps: Extract word-level timestamps using the cross-attention pattern
+ and dynamic time warping, and include the timestamps for each word in each segment.
+ Set as False.
+ without_timestamps: Only sample text tokens.
+
+ Static params: (Fixed for batched version)
+ max_initial_timestamp: The initial timestamp cannot be later than this, set at 0.0.
+ multilingual: If True, perform transcription on multilingual videos. Set as False.
+ output_language: Valid only if multilingual is set to True.
+ Specifies the string representing the output language. One of
+ 'en' (English) or 'hybrid' (code-switched transcription). set as None.
+ condition_on_previous_text: If True, the previous output of the model is provided
+ as a prompt for the next window; disabling may make the text inconsistent across
+ windows, but the model becomes less prone to getting stuck in a failure loop,
+ such as repetition looping or timestamps going out of sync. Set as False
+ prompt_reset_on_temperature: Resets prompt if temperature is above this value.
+ Arg has effect only if condition_on_previous_text is True. Set at 0.5
+ #TODO: support "hallucination_silence_threshold" when "word_timestamps=True"
+ hallucination_silence_threshold: Optional[float]
+ When word_timestamps is True, skip silent periods longer than this threshold
+ (in seconds) when a possible hallucination is detected. set as None.
+ clip_timestamps:
+ Comma-separated list start,end,start,end,... timestamps (in seconds) of clips to
+ process. The last end timestamp defaults to the end of the file. Set as "0".
+
+ unused:
+ language_detection_threshold: If the maximum probability of the language tokens is
+ higher than this value, the language is detected.
+ language_detection_segments: Number of segments to consider for the language detection.
+ vad_filter: Enable the voice activity detection (VAD) to filter out parts of the audio
+ without speech. This step is using the Silero VAD model
+ https://github.com/snakers4/silero-vad.
+ vad_parameters: Dictionary of Silero VAD parameters or VadOptions class (see available
+ parameters and default values in the class `VadOptions`).
+ chunk_length: The length of audio segments. If it is not None, it will overwrite the
+ default chunk_length of the FeatureExtractor.
+
+
+ Returns:
+ A tuple with:
+
+ - a generator over transcribed batched segments.
+ - an instance of TranscriptionInfo.
+ """
+
+ sampling_rate = self.model.feature_extractor.sampling_rate
+
+ if isinstance(audio, np.ndarray):
+ audio = torch.from_numpy(audio)
+ elif not isinstance(audio, torch.Tensor):
+ audio = decode_audio(audio, sampling_rate=sampling_rate)
+ duration = audio.shape[0] / sampling_rate
+
+ # if no segment split is provided, use vad_model and generate segments
+ if not vad_segments:
+ # run the audio if it is less than 30 sec even without vad_segments
+ if self.use_vad_model:
+ vad_segments = self.vad_model(
+ {
+ "waveform": audio.unsqueeze(0),
+ "sample_rate": 16000,
+ }
+ )
+ vad_segments = merge_chunks(
+ vad_segments,
+ self.chunk_length,
+ onset=self.vad_onset,
+ offset=self.vad_offset,
+ )
+ elif duration < self.chunk_length:
+ vad_segments = [
+ {"start": 0.0, "end": duration, "segments": [(0.0, duration)]}
+ ]
+ else:
+ raise RuntimeError(
+ "No vad segments found. Set 'use_vad_model' to True while loading the model"
+ )
+ if self.model.model.is_multilingual:
+ language = language or self.preset_language
+ elif language != "en":
+ if language is not None:
+ self.model.logger.warning(
+ f"English-only model is used, but {language} language is"
+ "chosen, setting language to 'en'."
+ )
+ language = "en"
+
+ (
+ language,
+ language_probability,
+ task,
+ all_language_probs,
+ ) = self.get_language_and_tokenizer(audio, task, language)
+
+ duration_after_vad = sum(
+ segment["end"] - segment["start"] for segment in vad_segments
+ )
+
+ # batched options: see the difference with default options in WhisperModel
+ batched_options = TranscriptionOptions(
+ beam_size=beam_size,
+ best_of=best_of,
+ patience=patience,
+ length_penalty=length_penalty,
+ repetition_penalty=repetition_penalty,
+ no_repeat_ngram_size=no_repeat_ngram_size,
+ log_prob_threshold=log_prob_threshold,
+ log_prob_low_threshold=log_prob_low_threshold,
+ no_speech_threshold=no_speech_threshold,
+ compression_ratio_threshold=compression_ratio_threshold,
+ temperatures=(
+ temperature if isinstance(temperature, (list, tuple)) else [temperature]
+ ),
+ initial_prompt=initial_prompt,
+ prefix=prefix,
+ suppress_blank=suppress_blank,
+ suppress_tokens=get_suppressed_tokens(self.tokenizer, suppress_tokens),
+ prepend_punctuations=prepend_punctuations,
+ append_punctuations=append_punctuations,
+ max_new_tokens=max_new_tokens,
+ hotwords=hotwords,
+ word_timestamps=word_timestamps,
+ hallucination_silence_threshold=None,
+ condition_on_previous_text=False,
+ clip_timestamps="0",
+ prompt_reset_on_temperature=0.5,
+ multilingual=False,
+ output_language=None,
+ without_timestamps=without_timestamps,
+ max_initial_timestamp=0.0,
+ )
+
+ info = TranscriptionInfo(
+ language=language,
+ language_probability=language_probability,
+ duration=duration,
+ duration_after_vad=duration_after_vad,
+ transcription_options=batched_options,
+ vad_options=None,
+ all_language_probs=all_language_probs,
+ )
+
+ audio_segments, segments_metadata = self.audio_split(
+ audio, vad_segments, sampling_rate
+ )
+ to_cpu = (
+ self.model.model.device == "cuda" and len(self.model.model.device_index) > 1
+ )
+ audio_segments = torch.nested.nested_tensor(audio_segments).to_padded_tensor(
+ padding=0
+ )
+ features = torch.stack(
+ [
+ self.model.feature_extractor(audio_segment, to_cpu=to_cpu)[
+ ..., : self.model.feature_extractor.nb_max_frames
+ ]
+ for audio_segment in audio_segments
+ ]
+ )
+
+ segments = self._batched_segments_generator(
+ features,
+ segments_metadata,
+ batch_size,
+ batched_options,
+ log_progress,
+ )
+
+ return segments, info
+
+ def _batched_segments_generator(
+ self, features, segments_metadata, batch_size, options, log_progress
+ ):
+ pbar = tqdm(total=len(features), disable=not log_progress, position=0)
+ seg_idx = 0
+ for i in range(0, len(features), batch_size):
+ results = self.forward(
+ features[i : i + batch_size],
+ segments_metadata[i : i + batch_size],
+ **options._asdict(),
+ )
+
+ for result in results:
+ for segment in result:
+ seg_idx += 1
+ yield Segment(
+ seek=int(result[-1]["end"] * self.model.frames_per_second),
+ id=seg_idx,
+ text=segment["text"],
+ start=round(segment["start"], 3),
+ end=round(segment["end"], 3),
+ words=(
+ None
+ if not options.word_timestamps
+ else [Word(**word) for word in segment["words"]]
+ ),
+ tokens=segment["tokens"],
+ avg_logprob=segment["avg_logprob"],
+ no_speech_prob=segment["no_speech_prob"],
+ compression_ratio=segment["compression_ratio"],
+ )
+
+ pbar.update(1)
+
+ pbar.close()
+ # revert the tokenizer if multilingual inference is enabled
+ if self.preset_language is None:
+ self.tokenizer = None
+ self.last_speech_timestamp = 0.0
+
+
+class WhisperModel:
+ def __init__(
+ self,
+ model_size_or_path: str,
+ device: str = "auto",
+ device_index: Union[int, List[int]] = 0,
+ compute_type: str = "default",
+ cpu_threads: int = 16,
+ num_workers: int = 1,
+ download_root: Optional[str] = None,
+ local_files_only: bool = False,
+ files: dict = None,
+ **model_kwargs,
+ ):
+ """Initializes the Whisper model.
+
+ Args:
+ model_size_or_path: Size of the model to use (tiny, tiny.en, base, base.en,
+ small, small.en, distil-small.en, medium, medium.en, distil-medium.en, large-v1,
+ large-v2, large-v3, large, distil-large-v2 or distil-large-v3), a path to a
+ converted model directory, or a CTranslate2-converted Whisper model ID from the HF Hub.
+ When a size or a model ID is configured, the converted model is downloaded
+ from the Hugging Face Hub.
+ device: Device to use for computation ("cpu", "cuda", "auto").
+ device_index: Device ID to use.
+ The model can also be loaded on multiple GPUs by passing a list of IDs
+ (e.g. [0, 1, 2, 3]). In that case, multiple transcriptions can run in parallel
+ when transcribe() is called from multiple Python threads (see also num_workers).
+ compute_type: Type to use for computation.
+ See https://opennmt.net/CTranslate2/quantization.html.
+ cpu_threads: Number of threads to use when running on CPU (4 by default).
+ A non zero value overrides the OMP_NUM_THREADS environment variable.
+ num_workers: When transcribe() is called from multiple Python threads,
+ having multiple workers enables true parallelism when running the model
+ (concurrent calls to self.model.generate() will run in parallel).
+ This can improve the global throughput at the cost of increased memory usage.
+ download_root: Directory where the models should be saved. If not set, the models
+ are saved in the standard Hugging Face cache directory.
+ local_files_only: If True, avoid downloading the file and return the path to the
+ local cached file if it exists.
+ files: Load model files from the memory. This argument is a dictionary mapping file names
+ to file contents as file-like or bytes objects. If this is set, model_path acts as an
+ identifier for this model.
+ """
+ self.logger = get_logger()
+
+ tokenizer_bytes, preprocessor_bytes = None, None
+ if files:
+ model_path = model_size_or_path
+ tokenizer_bytes = files.pop("tokenizer.json", None)
+ preprocessor_bytes = files.pop("preprocessor_config.json", None)
+ elif os.path.isdir(model_size_or_path):
+ model_path = model_size_or_path
+ else:
+ model_path = download_model(
+ model_size_or_path,
+ local_files_only=local_files_only,
+ cache_dir=download_root,
+ )
+ self.device = device
+ # set the random seed to make sure consistency across runs
+ ctranslate2.set_random_seed(42)
+ self.model = ctranslate2.models.Whisper(
+ model_path,
+ device=self.device,
+ device_index=device_index,
+ compute_type=compute_type,
+ intra_threads=cpu_threads,
+ inter_threads=num_workers,
+ files=files,
+ **model_kwargs,
+ )
+
+ tokenizer_file = os.path.join(model_path, "tokenizer.json")
+ if tokenizer_bytes:
+ self.hf_tokenizer = tokenizers.Tokenizer.from_buffer(tokenizer_bytes)
+ elif os.path.isfile(tokenizer_file):
+ self.hf_tokenizer = tokenizers.Tokenizer.from_file(tokenizer_file)
+ else:
+ self.hf_tokenizer = tokenizers.Tokenizer.from_pretrained(
+ "openai/whisper-tiny" + ("" if self.model.is_multilingual else ".en")
+ )
+ self.feat_kwargs = self._get_feature_kwargs(model_path, preprocessor_bytes)
+ self.feature_extractor = FeatureExtractor(
+ **self.feat_kwargs, device=self.device
+ )
+ self.input_stride = 2
+ self.num_samples_per_token = (
+ self.feature_extractor.hop_length * self.input_stride
+ )
+ self.frames_per_second = (
+ self.feature_extractor.sampling_rate // self.feature_extractor.hop_length
+ )
+ self.tokens_per_second = (
+ self.feature_extractor.sampling_rate // self.num_samples_per_token
+ )
+ self.time_precision = 0.02
+ self.max_length = 448
+
+ @property
+ def supported_languages(self) -> List[str]:
+ """The languages supported by the model."""
+ return list(_LANGUAGE_CODES) if self.model.is_multilingual else ["en"]
+
+ def _get_feature_kwargs(self, model_path, preprocessor_bytes=None) -> dict:
+ config = {}
+ try:
+ config_path = os.path.join(model_path, "preprocessor_config.json")
+ if preprocessor_bytes:
+ config = json.loads(preprocessor_bytes)
+ elif os.path.isfile(config_path):
+ with open(config_path, "r", encoding="utf-8") as file:
+ config = json.load(file)
+ else:
+ return config
+ valid_keys = signature(FeatureExtractor.__init__).parameters.keys()
+ return {k: v for k, v in config.items() if k in valid_keys}
+ except json.JSONDecodeError as e:
+ self.logger.warning("Could not load preprocessor config: %s", e)
+
+ return config
+
+ def transcribe(
+ self,
+ audio: Union[str, BinaryIO, torch.Tensor, np.ndarray],
+ language: Optional[str] = None,
+ task: str = "transcribe",
+ beam_size: int = 5,
+ best_of: int = 5,
+ patience: float = 1,
+ length_penalty: float = 1,
+ repetition_penalty: float = 1,
+ no_repeat_ngram_size: int = 0,
+ temperature: Union[float, List[float], Tuple[float, ...]] = [
+ 0.0,
+ 0.2,
+ 0.4,
+ 0.6,
+ 0.8,
+ 1.0,
+ ],
+ compression_ratio_threshold: Optional[float] = 2.4,
+ log_prob_threshold: Optional[float] = -1.0,
+ log_prob_low_threshold: Optional[float] = None,
+ no_speech_threshold: Optional[float] = 0.6,
+ condition_on_previous_text: bool = True,
+ prompt_reset_on_temperature: float = 0.5,
+ initial_prompt: Optional[Union[str, Iterable[int]]] = None,
+ prefix: Optional[str] = None,
+ suppress_blank: bool = True,
+ suppress_tokens: Optional[List[int]] = [-1],
+ without_timestamps: bool = False,
+ max_initial_timestamp: float = 1.0,
+ word_timestamps: bool = False,
+ prepend_punctuations: str = "\"'“¿([{-",
+ append_punctuations: str = "\"'.。,，!！?？:：”)]}、",
+ multilingual: bool = False,
+ output_language: Optional[str] = None,
+ vad_filter: bool = False,
+ vad_parameters: Optional[Union[dict, VadOptions]] = None,
+ max_new_tokens: Optional[int] = None,
+ chunk_length: Optional[int] = None,
+ clip_timestamps: Union[str, List[float]] = "0",
+ hallucination_silence_threshold: Optional[float] = None,
+ hotwords: Optional[str] = None,
+ language_detection_threshold: Optional[float] = None,
+ language_detection_segments: int = 1,
+ ) -> Tuple[Iterable[Segment], TranscriptionInfo]:
+ """Transcribes an input file.
+
+ Arguments:
+ audio: Path to the input file (or a file-like object), or the audio waveform.
+ language: The language spoken in the audio. It should be a language code such
+ as "en" or "fr". If not set, the language will be detected in the first 30 seconds
+ of audio.
+ task: Task to execute (transcribe or translate).
+ beam_size: Beam size to use for decoding.
+ best_of: Number of candidates when sampling with non-zero temperature.
+ patience: Beam search patience factor.
+ length_penalty: Exponential length penalty constant.
+ repetition_penalty: Penalty applied to the score of previously generated tokens
+ (set > 1 to penalize).
+ no_repeat_ngram_size: Prevent repetitions of ngrams with this size (set 0 to disable).
+ temperature: Temperature for sampling. It can be a tuple of temperatures,
+ which will be successively used upon failures according to either
+ `compression_ratio_threshold` or `log_prob_threshold`.
+ compression_ratio_threshold: If the gzip compression ratio is above this value,
+ treat as failed.
+ log_prob_threshold: If the average log probability over sampled tokens is
+ below this value, treat as failed.
+ log_prob_low_threshold: This parameter alone is sufficient to skip an output text,
+ wheras log_prob_threshold also looks for appropriate no_speech_threshold value.
+ This value should be less than log_prob_threshold.
+ no_speech_threshold: If the no_speech probability is higher than this value AND
+ the average log probability over sampled tokens is below `log_prob_threshold`,
+ consider the segment as silent.
+ condition_on_previous_text: If True, the previous output of the model is provided
+ as a prompt for the next window; disabling may make the text inconsistent across
+ windows, but the model becomes less prone to getting stuck in a failure loop,
+ such as repetition looping or timestamps going out of sync.
+ prompt_reset_on_temperature: Resets prompt if temperature is above this value.
+ Arg has effect only if condition_on_previous_text is True.
+ initial_prompt: Optional text string or iterable of token ids to provide as a
+ prompt for the first window.
+ prefix: Optional text to provide as a prefix for the first window.
+ suppress_blank: Suppress blank outputs at the beginning of the sampling.
+ suppress_tokens: List of token IDs to suppress. -1 will suppress a default set
+ of symbols as defined in `tokenizer.non_speech_tokens()`.
+ without_timestamps: Only sample text tokens.
+ max_initial_timestamp: The initial timestamp cannot be later than this.
+ word_timestamps: Extract word-level timestamps using the cross-attention pattern
+ and dynamic time warping, and include the timestamps for each word in each segment.
+ prepend_punctuations: If word_timestamps is True, merge these punctuation symbols
+ with the next word
+ append_punctuations: If word_timestamps is True, merge these punctuation symbols
+ with the previous word
+ multilingual: If True, perform transcription on multilingual videos
+ and return the transcript based
+ on the 'output_language' flag.
+ output_language: Valid only if multilingual is set to True.
+ Specifies the string representing the output language. One of
+ 'en' (English) or 'hybrid' (code-switched transcription).
+ vad_filter: Enable the voice activity detection (VAD) to filter out parts of the audio
+ without speech. This step is using the Silero VAD model
+ https://github.com/snakers4/silero-vad.
+ vad_parameters: Dictionary of Silero VAD parameters or VadOptions class (see available
+ parameters and default values in the class `VadOptions`).
+ max_new_tokens: Maximum number of new tokens to generate per-chunk. If not set,
+ the maximum will be set by the default max_length.
+ chunk_length: The length of audio segments. If it is not None, it will overwrite the
+ default chunk_length of the FeatureExtractor.
+ clip_timestamps:
+ Comma-separated list start,end,start,end,... timestamps (in seconds) of clips to
+ process. The last end timestamp defaults to the end of the file.
+ vad_filter will be ignored if clip_timestamps is used.
+ hallucination_silence_threshold:
+ When word_timestamps is True, skip silent periods longer than this threshold
+ (in seconds) when a possible hallucination is detected
+ hotwords:
+ Hotwords/hint phrases to provide the model with. Has no effect if prefix is not None.
+ language_detection_threshold: If the maximum probability of the language tokens is higher
+ than this value, the language is detected.
+ language_detection_segments: Number of segments to consider for the language detection.
+ Returns:
+ A tuple with:
+
+ - a generator over transcribed segments
+ - an instance of TranscriptionInfo
+ """
+
+ sampling_rate = self.feature_extractor.sampling_rate
+
+ if isinstance(audio, np.ndarray):
+ audio = torch.from_numpy(audio)
+ elif not isinstance(audio, torch.Tensor):
+ audio = decode_audio(audio, sampling_rate=sampling_rate)
+
+ duration = audio.shape[0] / sampling_rate
+ duration_after_vad = duration
+
+ self.logger.info(
+ "Processing audio with duration %s", format_timestamp(duration)
+ )
+
+ if vad_filter and clip_timestamps == "0":
+ if vad_parameters is None:
+ vad_parameters = VadOptions()
+ elif isinstance(vad_parameters, dict):
+ vad_parameters = VadOptions(**vad_parameters)
+ speech_chunks = get_speech_timestamps(audio, vad_parameters)
+ audio = collect_chunks(audio, speech_chunks)
+ duration_after_vad = audio.shape[0] / sampling_rate
+
+ self.logger.info(
+ "VAD filter removed %s of audio",
+ format_timestamp(duration - duration_after_vad),
+ )
+
+ if self.logger.isEnabledFor(logging.DEBUG):
+ self.logger.debug(
+ "VAD filter kept the following audio segments: %s",
+ ", ".join(
+ "[%s -> %s]"
+ % (
+ format_timestamp(chunk["start"] / sampling_rate),
+ format_timestamp(chunk["end"] / sampling_rate),
+ )
+ for chunk in speech_chunks
+ ),
+ )
+
+ else:
+ speech_chunks = None
+
+ to_cpu = self.model.device == "cuda" and len(self.model.device_index) > 1
+ features = self.feature_extractor(
+ audio, chunk_length=chunk_length, to_cpu=to_cpu
+ )
+
+ encoder_output = None
+ all_language_probs = None
+
+ # setting output_language for multilingual videos
+ if multilingual:
+ if output_language is None:
+ output_language = "en"
+ elif output_language not in ["en", "hybrid"]:
+ raise ValueError("Output language needs to be one of 'en'/'hybrid'.")
+
+ # detecting the language if not provided
+ if language is None:
+ if not self.model.is_multilingual:
+ language = "en"
+ language_probability = 1
+ else:
+ if (
+ language_detection_segments is None
+ or language_detection_segments < 1
+ ):
+ language_detection_segments = 1
+ start_timestamp = (
+ float(clip_timestamps.split(",")[0])
+ if isinstance(clip_timestamps, str)
+ else clip_timestamps[0]
+ )
+ content_frames = (
+ features.shape[-1] - self.feature_extractor.nb_max_frames
+ )
+ seek = (
+ int(start_timestamp * self.frames_per_second)
+ if start_timestamp * self.frames_per_second < content_frames
+ else 0
+ )
+ end_frames = min(
+ seek
+ + self.feature_extractor.nb_max_frames
+ * language_detection_segments,
+ content_frames,
+ )
+ detected_language_info = {}
+ while seek <= end_frames:
+ segment = features[
+ :, seek : seek + self.feature_extractor.nb_max_frames
+ ]
+ encoder_output = self.encode(segment)
+ # results is a list of tuple[str, float] with language names and
+ # probabilities.
+ results = self.model.detect_language(encoder_output)[0]
+ # Parse language names to strip out markers
+ all_language_probs = [
+ (token[2:-2], prob) for (token, prob) in results
+ ]
+ # Get top language token and probability
+ language, language_probability = all_language_probs[0]
+ if (
+ language_detection_threshold is None
+ or language_probability > language_detection_threshold
+ ):
+ break
+ detected_language_info.setdefault(language, []).append(
+ language_probability
+ )
+ seek += segment.shape[-1]
+ else:
+ # If no language detected for all segments, the majority vote of the highest
+ # projected languages for all segments is used to determine the language.
+ language = max(
+ detected_language_info,
+ key=lambda lang: len(detected_language_info[lang]),
+ )
+ language_probability = max(detected_language_info[language])
+
+ self.logger.info(
+ "Detected language '%s' with probability %.2f",
+ language,
+ language_probability,
+ )
+ else:
+ if not self.model.is_multilingual and language != "en":
+ self.logger.warning(
+ "The current model is English-only but the language parameter is set to '%s'; "
+ "using 'en' instead." % language
+ )
+ language = "en"
+
+ language_probability = 1
+
+ tokenizer = Tokenizer(
+ self.hf_tokenizer,
+ self.model.is_multilingual,
+ task=task,
+ language=language,
+ )
+
+ options = TranscriptionOptions(
+ beam_size=beam_size,
+ best_of=best_of,
+ patience=patience,
+ length_penalty=length_penalty,
+ repetition_penalty=repetition_penalty,
+ no_repeat_ngram_size=no_repeat_ngram_size,
+ log_prob_threshold=log_prob_threshold,
+ log_prob_low_threshold=log_prob_low_threshold,
+ no_speech_threshold=no_speech_threshold,
+ compression_ratio_threshold=compression_ratio_threshold,
+ condition_on_previous_text=condition_on_previous_text,
+ prompt_reset_on_temperature=prompt_reset_on_temperature,
+ temperatures=(
+ temperature if isinstance(temperature, (list, tuple)) else [temperature]
+ ),
+ initial_prompt=initial_prompt,
+ prefix=prefix,
+ suppress_blank=suppress_blank,
+ suppress_tokens=(
+ get_suppressed_tokens(tokenizer, suppress_tokens)
+ if suppress_tokens
+ else suppress_tokens
+ ),
+ without_timestamps=without_timestamps,
+ max_initial_timestamp=max_initial_timestamp,
+ word_timestamps=word_timestamps,
+ prepend_punctuations=prepend_punctuations,
+ append_punctuations=append_punctuations,
+ multilingual=multilingual,
+ output_language=output_language,
+ max_new_tokens=max_new_tokens,
+ clip_timestamps=clip_timestamps,
+ hallucination_silence_threshold=hallucination_silence_threshold,
+ hotwords=hotwords,
+ )
+
+ segments = self.generate_segments(features, tokenizer, options, encoder_output)
+
+ if speech_chunks:
+ segments = restore_speech_timestamps(segments, speech_chunks, sampling_rate)
+
+ info = TranscriptionInfo(
+ language=language,
+ language_probability=language_probability,
+ duration=duration,
+ duration_after_vad=duration_after_vad,
+ transcription_options=options,
+ vad_options=vad_parameters,
+ all_language_probs=all_language_probs,
+ )
+ return segments, info
+
+ def _split_segments_by_timestamps(
+ self,
+ tokenizer: Tokenizer,
+ tokens: List[int],
+ time_offset: float,
+ segment_size: int,
+ segment_duration: float,
+ seek: int,
+ ) -> List[List[int]]:
+ current_segments = []
+ single_timestamp_ending = (
+ len(tokens) >= 2 and tokens[-2] < tokenizer.timestamp_begin <= tokens[-1]
+ )
+
+ consecutive_timestamps = [
+ i
+ for i in range(len(tokens))
+ if i > 0
+ and tokens[i] >= tokenizer.timestamp_begin
+ and tokens[i - 1] >= tokenizer.timestamp_begin
+ ]
+
+ if len(consecutive_timestamps) > 0:
+ slices = list(consecutive_timestamps)
+ if single_timestamp_ending:
+ slices.append(len(tokens))
+
+ last_slice = 0
+ for current_slice in slices:
+ sliced_tokens = tokens[last_slice:current_slice]
+ start_timestamp_position = sliced_tokens[0] - tokenizer.timestamp_begin
+ end_timestamp_position = sliced_tokens[-1] - tokenizer.timestamp_begin
+ start_time = (
+ time_offset + start_timestamp_position * self.time_precision
+ )
+ end_time = time_offset + end_timestamp_position * self.time_precision
+
+ current_segments.append(
+ dict(
+ seek=seek,
+ start=start_time,
+ end=end_time,
+ tokens=sliced_tokens,
+ )
+ )
+ last_slice = current_slice
+
+ if single_timestamp_ending:
+ # single timestamp at the end means no speech after the last timestamp.
+ seek += segment_size
+ else:
+ # otherwise, ignore the unfinished segment and seek to the last timestamp
+ last_timestamp_position = (
+ tokens[last_slice - 1] - tokenizer.timestamp_begin
+ )
+ seek += last_timestamp_position * self.input_stride
+
+ else:
+ duration = segment_duration
+ timestamps = [
+ token for token in tokens if token >= tokenizer.timestamp_begin
+ ]
+ if len(timestamps) > 0 and timestamps[-1] != tokenizer.timestamp_begin:
+ last_timestamp_position = timestamps[-1] - tokenizer.timestamp_begin
+ duration = last_timestamp_position * self.time_precision
+
+ current_segments.append(
+ dict(
+ seek=seek,
+ start=time_offset,
+ end=time_offset + duration,
+ tokens=tokens,
+ )
+ )
+
+ seek += segment_size
+
+ return current_segments, seek, single_timestamp_ending
+
+ def generate_segments(
+ self,
+ features: torch.Tensor,
+ tokenizer: Tokenizer,
+ options: TranscriptionOptions,
+ encoder_output: Optional[ctranslate2.StorageView] = None,
+ ) -> Iterable[Segment]:
+ content_frames = features.shape[-1] - self.feature_extractor.nb_max_frames
+ content_duration = float(content_frames * self.feature_extractor.time_per_frame)
+
+ if isinstance(options.clip_timestamps, str):
+ options = options._replace(
+ clip_timestamps=[
+ float(ts)
+ for ts in (
+ options.clip_timestamps.split(",")
+ if options.clip_timestamps
+ else []
+ )
+ ]
+ )
+ seek_points: List[int] = [
+ round(ts * self.frames_per_second) for ts in options.clip_timestamps
+ ]
+ if len(seek_points) == 0:
+ seek_points.append(0)
+ if len(seek_points) % 2 == 1:
+ seek_points.append(content_frames)
+ seek_clips: List[Tuple[int, int]] = list(
+ zip(seek_points[::2], seek_points[1::2])
+ )
+
+ punctuation = "\"'“¿([{-\"'.。,，!！?？:：”)]}、"
+
+ idx = 0
+ clip_idx = 0
+ seek = seek_clips[clip_idx][0]
+ all_tokens = []
+ prompt_reset_since = 0
+
+ if options.initial_prompt is not None:
+ if isinstance(options.initial_prompt, str):
+ initial_prompt = " " + options.initial_prompt.strip()
+ initial_prompt_tokens = tokenizer.encode(initial_prompt)
+ all_tokens.extend(initial_prompt_tokens)
+ else:
+ all_tokens.extend(options.initial_prompt)
+
+ last_speech_timestamp = 0.0
+ # NOTE: This loop is obscurely flattened to make the diff readable.
+ # A later commit should turn this into a simpler nested loop.
+ # for seek_clip_start, seek_clip_end in seek_clips:
+ # while seek < seek_clip_end
+ while clip_idx < len(seek_clips):
+ seek_clip_start, seek_clip_end = seek_clips[clip_idx]
+ if seek_clip_end > content_frames:
+ seek_clip_end = content_frames
+ if seek < seek_clip_start:
+ seek = seek_clip_start
+ if seek >= seek_clip_end:
+ clip_idx += 1
+ if clip_idx < len(seek_clips):
+ seek = seek_clips[clip_idx][0]
+ continue
+ time_offset = seek * self.feature_extractor.time_per_frame
+ window_end_time = float(
+ (seek + self.feature_extractor.nb_max_frames)
+ * self.feature_extractor.time_per_frame
+ )
+ segment_size = min(
+ self.feature_extractor.nb_max_frames,
+ content_frames - seek,
+ seek_clip_end - seek,
+ )
+ segment = features[:, seek : seek + segment_size]
+ segment_duration = segment_size * self.feature_extractor.time_per_frame
+ segment = pad_or_trim(segment, self.feature_extractor.nb_max_frames)
+
+ if self.logger.isEnabledFor(logging.DEBUG):
+ self.logger.debug(
+ "Processing segment at %s", format_timestamp(time_offset)
+ )
+
+ previous_tokens = all_tokens[prompt_reset_since:]
+
+ if encoder_output is None:
+ encoder_output = self.encode(segment)
+
+ # Perform language detection at every segment to update task based on output language,
+ # if the language is english, task is transcribe,
+ # else the task is translate to english (default)
+ # or transcribe if 'output_language' is 'hybrid'.
+ if options.multilingual:
+ results = self.model.detect_language(encoder_output)
+ language_token, language_probability = results[0][0]
+ language = language_token[2:-2]
+ if options.output_language == "en" and language != "en":
+ task = "translate"
+ else:
+ task = "transcribe"
+
+ # Update tokenizer based on task and language
+ tokenizer.task = tokenizer.tokenizer.token_to_id(f"<|{task}|>")
+ tokenizer.language = tokenizer.tokenizer.token_to_id(language_token)
+ tokenizer.language_code = language
+ # Update prompt based on task and language
+ prompt = self.get_prompt(
+ tokenizer,
+ previous_tokens,
+ without_timestamps=options.without_timestamps,
+ prefix=options.prefix if seek == 0 else None,
+ hotwords=options.hotwords,
+ )
+
+ if seek > 0 or encoder_output is None:
+ encoder_output = self.encode(segment)
+
+ (
+ result,
+ avg_logprob,
+ temperature,
+ compression_ratio,
+ ) = self.generate_with_fallback(encoder_output, prompt, tokenizer, options)
+
+ if options.no_speech_threshold is not None:
+ # no voice activity check
+ should_skip = result.no_speech_prob > options.no_speech_threshold
+
+ if (
+ options.log_prob_threshold is not None
+ and avg_logprob > options.log_prob_threshold
+ ):
+ # don't skip if the logprob is high enough, despite the no_speech_prob
+ should_skip = False
+
+ if should_skip:
+ self.logger.debug(
+ "No speech threshold is met (%f > %f)",
+ result.no_speech_prob,
+ options.no_speech_threshold,
+ )
+
+ # Skip if the logprob is very low (below the threshold value),
+ # despite no_speech_prob being low (ex: Too ambiguous outputs)
+ if options.log_prob_low_threshold:
+ if avg_logprob < options.log_prob_low_threshold:
+ should_skip = True
+ self.logger.debug(
+ "log prob low threshold is met (%f > %f)",
+ avg_logprob,
+ options.log_prob_low_threshold,
+ )
+
+ if should_skip:
+ # fast-forward to the next segment boundary
+ seek += segment_size
+ continue
+
+ tokens = result.sequences_ids[0]
+
+ previous_seek = seek
+
+ # anomalous words are very long/short/improbable
+ def word_anomaly_score(word: dict) -> float:
+ probability = word.get("probability", 0.0)
+ duration = word["end"] - word["start"]
+ score = 0.0
+ if probability < 0.15:
+ score += 1.0
+ if duration < 0.133:
+ score += (0.133 - duration) * 15
+ if duration > 2.0:
+ score += duration - 2.0
+ return score
+
+ def is_segment_anomaly(segment: Optional[dict]) -> bool:
+ if segment is None or not segment["words"]:
+ return False
+ words = [w for w in segment["words"] if w["word"] not in punctuation]
+ words = words[:8]
+ score = sum(word_anomaly_score(w) for w in words)
+ return score >= 3 or score + 0.01 >= len(words)
+
+ def next_words_segment(segments: List[dict]) -> Optional[dict]:
+ return next((s for s in segments if s["words"]), None)
+
+ (
+ current_segments,
+ seek,
+ single_timestamp_ending,
+ ) = self._split_segments_by_timestamps(
+ tokenizer=tokenizer,
+ tokens=tokens,
+ time_offset=time_offset,
+ segment_size=segment_size,
+ segment_duration=segment_duration,
+ seek=seek,
+ )
+
+ if options.word_timestamps:
+ self.add_word_timestamps(
+ [current_segments],
+ tokenizer,
+ encoder_output,
+ segment_size,
+ options.prepend_punctuations,
+ options.append_punctuations,
+ last_speech_timestamp=last_speech_timestamp,
+ )
+ if not single_timestamp_ending:
+ last_word_end = get_end(current_segments)
+ if last_word_end is not None and last_word_end > time_offset:
+ seek = round(last_word_end * self.frames_per_second)
+
+ # skip silence before possible hallucinations
+ if options.hallucination_silence_threshold is not None:
+ threshold = options.hallucination_silence_threshold
+
+ # if first segment might be a hallucination, skip leading silence
+ first_segment = next_words_segment(current_segments)
+ if first_segment is not None and is_segment_anomaly(first_segment):
+ gap = first_segment["start"] - time_offset
+ if gap > threshold:
+ seek = previous_seek + round(gap * self.frames_per_second)
+ continue
+
+ # skip silence before any possible hallucination that is surrounded
+ # by silence or more hallucinations
+ hal_last_end = last_speech_timestamp
+ for si in range(len(current_segments)):
+ segment = current_segments[si]
+ if not segment["words"]:
+ continue
+ if is_segment_anomaly(segment):
+ next_segment = next_words_segment(
+ current_segments[si + 1 :]
+ )
+ if next_segment is not None:
+ hal_next_start = next_segment["words"][0]["start"]
+ else:
+ hal_next_start = time_offset + segment_duration
+ silence_before = (
+ segment["start"] - hal_last_end > threshold
+ or segment["start"] < threshold
+ or segment["start"] - time_offset < 2.0
+ )
+ silence_after = (
+ hal_next_start - segment["end"] > threshold
+ or is_segment_anomaly(next_segment)
+ or window_end_time - segment["end"] < 2.0
+ )
+ if silence_before and silence_after:
+ seek = round(
+ max(time_offset + 1, segment["start"])
+ * self.frames_per_second
+ )
+ if content_duration - segment["end"] < threshold:
+ seek = content_frames
+ current_segments[si:] = []
+ break
+ hal_last_end = segment["end"]
+
+ last_word_end = get_end(current_segments)
+ if last_word_end is not None:
+ last_speech_timestamp = last_word_end
+ for segment in current_segments:
+ tokens = segment["tokens"]
+ text = tokenizer.decode(tokens)
+
+ if segment["start"] == segment["end"] or not text.strip():
+ continue
+
+ all_tokens.extend(tokens)
+ idx += 1
+
+ yield Segment(
+ id=idx,
+ seek=seek,
+ start=segment["start"],
+ end=segment["end"],
+ text=text,
+ tokens=tokens,
+ temperature=temperature,
+ avg_logprob=avg_logprob,
+ compression_ratio=compression_ratio,
+ no_speech_prob=result.no_speech_prob,
+ words=(
+ [Word(**word) for word in segment["words"]]
+ if options.word_timestamps
+ else None
+ ),
+ )
+
+ if (
+ not options.condition_on_previous_text
+ or temperature > options.prompt_reset_on_temperature
+ ):
+ if options.condition_on_previous_text:
+ self.logger.debug(
+ "Reset prompt. prompt_reset_on_temperature threshold is met %f > %f",
+ temperature,
+ options.prompt_reset_on_temperature,
+ )
+
+ prompt_reset_since = len(all_tokens)
+
+ def encode(self, features: torch.Tensor) -> ctranslate2.StorageView:
+ # When the model is running on multiple GPUs, the encoder output should be moved
+ # to the CPU since we don't know which GPU will handle the next job.
+ to_cpu = self.model.device == "cuda" and len(self.model.device_index) > 1
+
+ if features.ndim == 2:
+ features = features.unsqueeze(0)
+ features = get_ctranslate2_storage(features)
+
+ return self.model.encode(features, to_cpu=to_cpu)
+
+ def generate_with_fallback(
+ self,
+ encoder_output: ctranslate2.StorageView,
+ prompt: List[int],
+ tokenizer: Tokenizer,
+ options: TranscriptionOptions,
+ ) -> Tuple[ctranslate2.models.WhisperGenerationResult, float, float, float]:
+ decode_result = None
+ all_results = []
+ below_cr_threshold_results = []
+
+ max_initial_timestamp_index = int(
+ round(options.max_initial_timestamp / self.time_precision)
+ )
+ if options.max_new_tokens is not None:
+ max_length = len(prompt) + options.max_new_tokens
+ else:
+ max_length = self.max_length
+
+ if max_length > self.max_length:
+ raise ValueError(
+ f"The length of the prompt is {len(prompt)}, and the `max_new_tokens` "
+ f"{max_length - len(prompt)}. Thus, the combined length of the prompt "
+ f"and `max_new_tokens` is: {max_length}. This exceeds the "
+ f"`max_length` of the Whisper model: {self.max_length}. "
+ "You should either reduce the length of your prompt, or "
+ "reduce the value of `max_new_tokens`, "
+ f"so that their combined length is less that {self.max_length}."
+ )
+
+ for temperature in options.temperatures:
+ if temperature > 0:
+ kwargs = {
+ "beam_size": 1,
+ "num_hypotheses": options.best_of,
+ "sampling_topk": 0,
+ "sampling_temperature": temperature,
+ }
+ else:
+ kwargs = {
+ "beam_size": options.beam_size,
+ "patience": options.patience,
+ }
+
+ result = self.model.generate(
+ encoder_output,
+ [prompt],
+ length_penalty=options.length_penalty,
+ repetition_penalty=options.repetition_penalty,
+ no_repeat_ngram_size=options.no_repeat_ngram_size,
+ max_length=max_length,
+ return_scores=True,
+ return_no_speech_prob=True,
+ suppress_blank=options.suppress_blank,
+ suppress_tokens=options.suppress_tokens,
+ max_initial_timestamp_index=max_initial_timestamp_index,
+ **kwargs,
+ )[0]
+
+ tokens = result.sequences_ids[0]
+
+ # Recover the average log prob from the returned score.
+ seq_len = len(tokens)
+ cum_logprob = result.scores[0] * (seq_len**options.length_penalty)
+ avg_logprob = cum_logprob / (seq_len + 1)
+
+ text = tokenizer.decode(tokens).strip()
+ compression_ratio = get_compression_ratio(text)
+
+ decode_result = (
+ result,
+ avg_logprob,
+ temperature,
+ compression_ratio,
+ )
+ all_results.append(decode_result)
+
+ needs_fallback = False
+
+ if options.compression_ratio_threshold is not None:
+ if compression_ratio > options.compression_ratio_threshold:
+ needs_fallback = True # too repetitive
+
+ self.logger.debug(
+ "Compression ratio threshold is not met with temperature %.1f (%f > %f)",
+ temperature,
+ compression_ratio,
+ options.compression_ratio_threshold,
+ )
+ else:
+ below_cr_threshold_results.append(decode_result)
+
+ if (
+ options.log_prob_threshold is not None
+ and avg_logprob < options.log_prob_threshold
+ ):
+ needs_fallback = True # average log probability is too low
+
+ self.logger.debug(
+ "Log probability threshold is not met with temperature %.1f (%f < %f)",
+ temperature,
+ avg_logprob,
+ options.log_prob_threshold,
+ )
+
+ if (
+ options.no_speech_threshold is not None
+ and result.no_speech_prob > options.no_speech_threshold
+ and options.log_prob_threshold is not None
+ and avg_logprob < options.log_prob_threshold
+ ):
+ needs_fallback = False # silence
+
+ if not needs_fallback:
+ break
+ else:
+ # all failed, select the result with the highest average log probability
+ decode_result = max(
+ below_cr_threshold_results or all_results, key=lambda x: x[1]
+ )
+ # to pass final temperature for prompt_reset_on_temperature
+ decode_result = (
+ decode_result[0],
+ decode_result[1],
+ temperature,
+ decode_result[3],
+ )
+
+ return decode_result
+
+ def get_prompt(
+ self,
+ tokenizer: Tokenizer,
+ previous_tokens: List[int],
+ without_timestamps: bool = False,
+ prefix: Optional[str] = None,
+ hotwords: Optional[str] = None,
+ ) -> List[int]:
+ prompt = []
+
+ if previous_tokens or (hotwords and not prefix):
+ prompt.append(tokenizer.sot_prev)
+ if hotwords and not prefix:
+ hotwords_tokens = tokenizer.encode(" " + hotwords.strip())
+ if len(hotwords_tokens) >= self.max_length // 2:
+ hotwords_tokens = hotwords_tokens[: self.max_length // 2 - 1]
+ prompt.extend(hotwords_tokens)
+ if previous_tokens:
+ prompt.extend(previous_tokens[-(self.max_length // 2 - 1) :])
+
+ prompt.extend(tokenizer.sot_sequence)
+
+ if without_timestamps:
+ prompt.append(tokenizer.no_timestamps)
+
+ if prefix:
+ prefix_tokens = tokenizer.encode(" " + prefix.strip())
+ if len(prefix_tokens) >= self.max_length // 2:
+ prefix_tokens = prefix_tokens[: self.max_length // 2 - 1]
+ if not without_timestamps:
+ prompt.append(tokenizer.timestamp_begin)
+ prompt.extend(prefix_tokens)
+
+ return prompt
+
+ def add_word_timestamps(
+ self,
+ segments: List[dict],
+ tokenizer: Tokenizer,
+ encoder_output: ctranslate2.StorageView,
+ num_frames: int,
+ prepend_punctuations: str,
+ append_punctuations: str,
+ last_speech_timestamp: float,
+ ) -> float:
+ if len(segments) == 0:
+ return
+
+ text_tokens = []
+ text_tokens_per_segment = []
+ for segment in segments:
+ segment_tokens = [
+ [token for token in subsegment["tokens"] if token < tokenizer.eot]
+ for subsegment in segment
+ ]
+ text_tokens.append(list(itertools.chain.from_iterable(segment_tokens)))
+ text_tokens_per_segment.append(segment_tokens)
+
+ alignments = self.find_alignment(
+ tokenizer, text_tokens, encoder_output, num_frames
+ )
+ median_max_durations = []
+ for alignment in alignments:
+ word_durations = np.array(
+ [word["end"] - word["start"] for word in alignment]
+ )
+ word_durations = word_durations[word_durations.nonzero()]
+ median_duration = (
+ np.median(word_durations) if len(word_durations) > 0 else 0.0
+ )
+ median_duration = min(0.7, float(median_duration))
+ max_duration = median_duration * 2
+
+ # hack: truncate long words at sentence boundaries.
+ # a better segmentation algorithm based on VAD should be able to replace this.
+ if len(word_durations) > 0:
+ sentence_end_marks = ".。!！?？"
+ # ensure words at sentence boundaries
+ # are not longer than twice the median word duration.
+ for i in range(1, len(alignment)):
+ if alignment[i]["end"] - alignment[i]["start"] > max_duration:
+ if alignment[i]["word"] in sentence_end_marks:
+ alignment[i]["end"] = alignment[i]["start"] + max_duration
+ elif alignment[i - 1]["word"] in sentence_end_marks:
+ alignment[i]["start"] = alignment[i]["end"] - max_duration
+
+ merge_punctuations(alignment, prepend_punctuations, append_punctuations)
+ median_max_durations.append((median_duration, max_duration))
+
+ for segment_idx, segment in enumerate(segments):
+ word_index = 0
+ time_offset = segment[0]["start"]
+ median_duration, max_duration = median_max_durations[segment_idx]
+ for subsegment_idx, subsegment in enumerate(segment):
+ saved_tokens = 0
+ words = []
+
+ while word_index < len(alignments[segment_idx]) and saved_tokens < len(
+ text_tokens_per_segment[segment_idx][subsegment_idx]
+ ):
+ timing = alignments[segment_idx][word_index]
+
+ if timing["word"]:
+ words.append(
+ dict(
+ word=timing["word"],
+ start=round(time_offset + timing["start"], 2),
+ end=round(time_offset + timing["end"], 2),
+ probability=timing["probability"],
+ )
+ )
+
+ saved_tokens += len(timing["tokens"])
+ word_index += 1
+
+ # hack: truncate long words at segment boundaries.
+ # a better segmentation algorithm based on VAD should be able to replace this.
+ if len(words) > 0:
+ # ensure the first and second word after a pause is not longer than
+ # twice the median word duration.
+ if words[0][
+ "end"
+ ] - last_speech_timestamp > median_duration * 4 and (
+ words[0]["end"] - words[0]["start"] > max_duration
+ or (
+ len(words) > 1
+ and words[1]["end"] - words[0]["start"] > max_duration * 2
+ )
+ ):
+ if (
+ len(words) > 1
+ and words[1]["end"] - words[1]["start"] > max_duration
+ ):
+ boundary = max(
+ words[1]["end"] / 2, words[1]["end"] - max_duration
+ )
+ words[0]["end"] = words[1]["start"] = boundary
+ words[0]["start"] = max(0, words[0]["end"] - max_duration)
+
+ # prefer the segment-level start timestamp if the first word is too long.
+ if (
+ subsegment["start"] < words[0]["end"]
+ and subsegment["start"] - 0.5 > words[0]["start"]
+ ):
+ words[0]["start"] = max(
+ 0,
+ min(words[0]["end"] - median_duration, subsegment["start"]),
+ )
+ else:
+ subsegment["start"] = words[0]["start"]
+
+ # prefer the segment-level end timestamp if the last word is too long.
+ if (
+ subsegment["end"] > words[-1]["start"]
+ and subsegment["end"] + 0.5 < words[-1]["end"]
+ ):
+ words[-1]["end"] = max(
+ words[-1]["start"] + median_duration, subsegment["end"]
+ )
+ else:
+ subsegment["end"] = words[-1]["end"]
+
+ last_speech_timestamp = subsegment["end"]
+ segments[segment_idx][subsegment_idx]["words"] = words
+ return last_speech_timestamp
+
+ def find_alignment(
+ self,
+ tokenizer: Tokenizer,
+ text_tokens: List[int],
+ encoder_output: ctranslate2.StorageView,
+ num_frames: int,
+ median_filter_width: int = 7,
+ ) -> List[dict]:
+ if len(text_tokens) == 0:
+ return []
+
+ results = self.model.align(
+ encoder_output,
+ tokenizer.sot_sequence,
+ text_tokens,
+ num_frames,
+ median_filter_width=median_filter_width,
+ )
+ return_list = []
+ for result, text_token in zip(results, text_tokens):
+ text_token_probs = result.text_token_probs
+ alignments = result.alignments
+ text_indices = np.array([pair[0] for pair in alignments])
+ time_indices = np.array([pair[1] for pair in alignments])
+
+ words, word_tokens = tokenizer.split_to_word_tokens(
+ text_token + [tokenizer.eot]
+ )
+ if len(word_tokens) <= 1:
+ # return on eot only
+ # >>> np.pad([], (1, 0))
+ # array([0.])
+ # This results in crashes when we lookup jump_times with float, like
+ # IndexError: arrays used as indices must be of integer (or boolean) type
+ return []
+ word_boundaries = np.pad(
+ np.cumsum([len(t) for t in word_tokens[:-1]]), (1, 0)
+ )
+ if len(word_boundaries) <= 1:
+ return []
+
+ jumps = np.pad(np.diff(text_indices), (1, 0), constant_values=1).astype(
+ bool
+ )
+ jump_times = time_indices[jumps] / self.tokens_per_second
+ start_times = jump_times[word_boundaries[:-1]]
+ end_times = jump_times[word_boundaries[1:]]
+ word_probabilities = [
+ np.mean(text_token_probs[i:j])
+ for i, j in zip(word_boundaries[:-1], word_boundaries[1:])
+ ]
+
+ return_list.append(
+ [
+ dict(
+ word=word,
+ tokens=tokens,
+ start=start,
+ end=end,
+ probability=probability,
+ )
+ for word, tokens, start, end, probability in zip(
+ words, word_tokens, start_times, end_times, word_probabilities
+ )
+ ]
+ )
+ return return_list
+
+ def generate_segment_batched(
+ self,
+ features: torch.Tensor,
+ tokenizer: Tokenizer,
+ options: dict,
+ ):
+ batch_size = features.shape[0]
+ all_tokens = []
+ prompt_reset_since = 0
+
+ if options["initial_prompt"] is not None:
+ initial_prompt = " " + options["initial_prompt"].strip()
+ initial_prompt_tokens = tokenizer.encode(initial_prompt)
+ all_tokens.extend(initial_prompt_tokens)
+ previous_tokens = all_tokens[prompt_reset_since:]
+ prompt = self.get_prompt(
+ tokenizer,
+ previous_tokens,
+ without_timestamps=options["without_timestamps"],
+ prefix=options["prefix"],
+ )
+
+ encoder_output = self.encode(features)
+
+ result = self.model.generate(
+ encoder_output,
+ [prompt] * batch_size,
+ beam_size=options["beam_size"],
+ patience=options["patience"],
+ length_penalty=options["length_penalty"],
+ max_length=self.max_length,
+ suppress_blank=options["suppress_blank"],
+ suppress_tokens=options["suppress_tokens"],
+ return_scores=True,
+ return_no_speech_prob=True,
+ )
+
+ output = []
+ for res in result:
+ output.append({})
+ # return scores
+ seq_len = len(res.sequences_ids[0])
+ cum_logprob = res.scores[0] * (seq_len ** options["length_penalty"])
+ output[-1]["avg_logprob"] = cum_logprob / (seq_len + 1)
+
+ # return no speech prob
+ output[-1]["no_speech_prob"] = res.no_speech_prob
+ output[-1]["tokens"] = res.sequences_ids[0]
+
+ return encoder_output, output
+
+ def detect_language(self, audio: torch.Tensor):
+ to_cpu = self.model.device == "cuda" and len(self.model.device_index) > 1
+ segment = self.feature_extractor(audio, padding=True, to_cpu=to_cpu)[
+ :, : self.feature_extractor.nb_max_frames
+ ]
+ encoder_output = self.encode(segment)
+ results = self.model.detect_language(encoder_output)
+ language_token, language_probability = results[0][0]
+ language = language_token[2:-2]
+ self.logger.info(
+ f"Detected language: {language} ({language_probability:.2f}) in first 30s of audio..."
+ )
+ all_language_probs = [(token[2:-2], prob) for (token, prob) in results[0]]
+ return language, language_probability, all_language_probs
+
+ def detect_language_multi_segment(
+ self, audio: Union[str, BinaryIO, torch.Tensor], params: Optional[dict] = None
+ ):
+ """
+ Detect language based on N highly-confident segments of a language.
+ """
+ # The threshold is used to decide if the audio is silence or not.
+ # The default is 0.02 (2.0%) i.e, if more than 2.0% of the audio is silent,
+ # the audio is considered as silence.
+ if not params:
+ params = {
+ "multilingual": False,
+ "speech_percentage_threshold": 0.02,
+ "language_detection_segments": 4,
+ "vad_filter": True,
+ "vad_min_silence_duration": 2500,
+ "language_threshold": 0.7,
+ }
+
+ if params.get("multilingual", False):
+ logging.warning(
+ "lang_id is not supported for multilingual audios, detecting the major language."
+ )
+
+ speech_percentage_threshold = params.get("speech_percentage_threshold", 0.02)
+ language_threshold = params.get("language_threshold", 0.7)
+ num_detection_segments = params.get("language_detection_segments", 4)
+ vad_filter_enabled = params.get("vad_filter", True)
+ vad_params = dict(
+ min_silence_duration_ms=params.get("vad_min_silence_duration", 2500)
+ )
+
+ if vad_filter_enabled:
+ vad_params = VadOptions(**vad_params)
+
+ # decode audio if it is not decoded already
+ sampling_rate = self.feature_extractor.sampling_rate
+ if not isinstance(audio, torch.Tensor):
+ audio: torch.Tensor = decode_audio(audio, sampling_rate=sampling_rate)
+
+ # calculate duration of audio as number of seconds
+ # audio.shape[0] is the number of samples in the audio
+ # sampling_rate is the number of samples per second
+ # if we divide the number of samples by the number of samples per second,
+ # we get the duration in seconds
+ duration = audio.shape[0] / sampling_rate
+
+ # Check if vad is enabled, and collect voiced segments
+ if vad_filter_enabled:
+ # get chunks of audio that contain speech
+ speech_chunks = get_speech_timestamps(audio, vad_params)
+ # merge chunks of audio that contain speech into a single array
+ audio = collect_chunks(audio, speech_chunks)
+
+ # calculate new duration of audio without silence
+ duration_vad = audio.shape[0] / sampling_rate
+
+ logging.debug(
+ f"Lang ID: VAD filter removed {duration - duration_vad} sec of audio"
+ )
+
+ # if the audio after VAD is less than 2% of the original audio, consider it as silence
+ if duration_vad / duration < speech_percentage_threshold:
+ return {"language_code": None, "language_confidence": 1.0}
+
+ # update duration to be the duration after VAD
+ duration = duration_vad
+
+ # if the duration of the audio is less than 1 second, consider it as silence
+ if duration < 1.0:
+ return {"language_code": None, "language_confidence": 1.0}
+
+ # number of feature frames in 30 seconds of audio is 3000
+ nb_max_frames = self.feature_extractor.nb_max_frames
+
+ # extract features from audio with padding (default)
+ to_cpu = self.model.device == "cuda" and len(self.model.device_index) > 1
+ features = self.feature_extractor(audio, to_cpu=to_cpu)
+
+ # number of segments in the audio
+ num_segments = features.shape[-1] // nb_max_frames
+ # more number of segments than possible with the duration of file
+ if num_detection_segments > num_segments:
+ logging.warning(
+ f"Lang ID: Can not have more segments, setting {num_segments} segments."
+ )
+ num_detection_segments = num_segments
+
+ # create a list of indices to randomly select segments from
+ indices = list(range(num_detection_segments))
+
+ # fix seed to get deterministic results
+ random.seed(0)
+ random.shuffle(indices)
+
+ detected_languages = []
+ all_language_probabilities = defaultdict(list)
+ confident_language_probabilities = defaultdict(list)
+ num_confident_segments_per_language = defaultdict(int)
+
+ # Iterate over the randomly selected indices of the segments.
+ #
+ # For each segment, extract features and detect language.
+ #
+ # If the language is confident, add it to the list of confident segments for that language.
+ #
+ # If the number of confident segments for a language
+ # is greater than or equal to the number of detection segments,
+ # return the language and the average probability of the language.
+ #
+ # If we are unable to get sufficient number of confident predcitions,
+ # return the most frequently detected language with maximum probability.
+ #
+ # We need to get sufficient number of confident predictions per language, not in total.
+
+ for i in indices:
+ segment_features = features[:, i * nb_max_frames : (i + 1) * nb_max_frames]
+ try:
+ encoder_output = self.encode(segment_features)
+ results = self.model.detect_language(encoder_output)[0]
+
+ except ValueError as e: # or RuntimeError
+ logging.error(f"Inference error:{e}")
+
+ # results is the list of classes (languages) and their probabilities (descending),
+ # for eg: [('<|de|>', 0.482177734375),('<|en|>', 0.283447265625),...]
+
+ # take top language token and probability
+ # and parse language token to strip out markers
+ # for eg: '<|de|>' -> 'de'
+
+ language_token = results[0][0]
+ language = language_token[2:-2]
+
+ language_probability = results[0][1]
+
+ detected_languages.append(language)
+ all_language_probabilities[language].append(language_probability)
+
+ # only consider if the language prediction is confident
+ if language_probability > language_threshold:
+ num_confident_segments_per_language[language] += 1
+
+ # Add language and probability to the list of languages when it is confident
+ confident_language_probabilities[language].append(language_probability)
+
+ # return the language when sufficient number of confident segments is achieved
+ if (
+ num_confident_segments_per_language[language]
+ >= num_detection_segments
+ ):
+ # Considering the average probability of only confident segments
+ mean = sum(confident_language_probabilities[language]) / len(
+ confident_language_probabilities[language]
+ )
+ return {
+ "language_code": language,
+ "language_confidence": mean,
+ }
+
+ # if we are unable to get sufficient number of confident predictions,
+ # return the most frequently detected language.
+ # if there is a tie, return the one with maximum average probability.
+ counter = Counter(detected_languages)
+
+ # Define the key function to select frequent language with attached probabilities
+ def key_func(language):
+ # Calculate the frequency of the language
+ frequency = counter[language]
+
+ # Calculate the average probability of the language
+ prob_avg = sum(all_language_probabilities[language]) / len(
+ all_language_probabilities[language]
+ )
+
+ return frequency, prob_avg
+
+ if detected_languages:
+ # Use the key function to find the language with maximum frequency and probability
+ max_language = max(detected_languages, key=key_func)
+ max_probability = sum(all_language_probabilities[max_language]) / len(
+ all_language_probabilities[max_language]
+ )
+
+ # Do additional checks for silence for non-confident case
+ # calculate RMS amplitude and DC offset
+ dc_offset = audio.mean()
+ audio_minus_dc_offset = audio - dc_offset
+ is_silent = (
+ torch.all(audio.abs() < 0.01)
+ or torch.sqrt(torch.mean(audio_minus_dc_offset**2)) < 0.01
+ )
+
+ if is_silent:
+ return {"language_code": None, "language_confidence": 1.0}
+
+ return {
+ "language_code": max_language,
+ "language_confidence": max_probability,
+ }
+
+ # Language is not detected for any segment and none of prev conditions met
+ return {"language_code": None, "language_confidence": 1.0}
+
+
+def restore_speech_timestamps(
+ segments: Iterable[Segment],
+ speech_chunks: List[dict],
+ sampling_rate: int,
+) -> Iterable[Segment]:
+ ts_map = SpeechTimestampsMap(speech_chunks, sampling_rate)
+
+ for segment in segments:
+ if segment.words:
+ words = []
+ for word in segment.words:
+ # Ensure the word start and end times are resolved to the same chunk.
+ middle = (word.start + word.end) / 2
+ chunk_index = ts_map.get_chunk_index(middle)
+ word = word._replace(
+ start=ts_map.get_original_time(word.start, chunk_index),
+ end=ts_map.get_original_time(word.end, chunk_index),
+ )
+ words.append(word)
+
+ segment = segment._replace(
+ start=words[0].start,
+ end=words[-1].end,
+ words=words,
+ )
+
+ else:
+ segment = segment._replace(
+ start=ts_map.get_original_time(segment.start),
+ end=ts_map.get_original_time(segment.end),
+ )
+
+ yield segment
+
+
+def get_ctranslate2_storage(segment: torch.Tensor) -> ctranslate2.StorageView:
+ segment = segment.contiguous()
+ segment = ctranslate2.StorageView.from_array(
+ segment if segment.is_cuda else segment.numpy()
+ ) # torch cpu tensors don't implement __array_interface__
+ # https://github.com/pytorch/pytorch/issues/51156
+ return segment
+
+
+def get_compression_ratio(text: str) -> float:
+ text_bytes = text.encode("utf-8")
+ return len(text_bytes) / len(zlib.compress(text_bytes))
+
+
+def get_suppressed_tokens(
+ tokenizer: Tokenizer,
+ suppress_tokens: Tuple[int],
+) -> Optional[List[int]]:
+ if -1 in suppress_tokens:
+ suppress_tokens = [t for t in suppress_tokens if t >= 0]
+ suppress_tokens.extend(tokenizer.non_speech_tokens)
+ elif suppress_tokens is None or len(suppress_tokens) == 0:
+ suppress_tokens = [] # interpret empty string as an empty list
+ else:
+ assert isinstance(suppress_tokens, list), "suppress_tokens must be a list"
+
+ suppress_tokens.extend(
+ [
+ tokenizer.transcribe,
+ tokenizer.translate,
+ tokenizer.sot,
+ tokenizer.sot_prev,
+ tokenizer.sot_lm,
+ ]
+ )
+
+ return tuple(sorted(set(suppress_tokens)))
+
+
+def merge_punctuations(alignment: List[dict], prepended: str, appended: str) -> None:
+ # merge prepended punctuations
+ i = len(alignment) - 2
+ j = len(alignment) - 1
+ while i >= 0:
+ previous = alignment[i]
+ following = alignment[j]
+ if previous["word"].startswith(" ") and previous["word"].strip() in prepended:
+ # prepend it to the following word
+ following["word"] = previous["word"] + following["word"]
+ if "tokens" in alignment[0].keys():
+ following["tokens"] = previous["tokens"] + following["tokens"]
+ previous["tokens"] = []
+ previous["word"] = ""
+
+ else:
+ j = i
+ i -= 1
+
+ # merge appended punctuations
+ i = 0
+ j = 1
+ while j < len(alignment):
+ previous = alignment[i]
+ following = alignment[j]
+ if not previous["word"].endswith(" ") and following["word"] in appended:
+ # append it to the previous word
+ previous["word"] = previous["word"] + following["word"]
+ if "tokens" in alignment[0].keys():
+ previous["tokens"] = previous["tokens"] + following["tokens"]
+ following["tokens"] = []
+ following["word"] = ""
+
+ else:
+ i = j
+ j += 1
diff --git a/whisper_pipeline/faster-whisper-main/faster_whisper/utils.py b/whisper_pipeline/faster-whisper-main/faster_whisper/utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..481bd748ec0daec58681289c38559d5968e6630d
--- /dev/null
+++ b/whisper_pipeline/faster-whisper-main/faster_whisper/utils.py
@@ -0,0 +1,157 @@
+import logging
+import os
+import re
+
+from typing import List, Optional
+
+import huggingface_hub
+import requests
+
+from tqdm.auto import tqdm
+
+_MODELS = {
+ "tiny.en": "Systran/faster-whisper-tiny.en",
+ "tiny": "Systran/faster-whisper-tiny",
+ "base.en": "Systran/faster-whisper-base.en",
+ "base": "Systran/faster-whisper-base",
+ "small.en": "Systran/faster-whisper-small.en",
+ "small": "Systran/faster-whisper-small",
+ "medium.en": "Systran/faster-whisper-medium.en",
+ "medium": "Systran/faster-whisper-medium",
+ "large-v1": "Systran/faster-whisper-large-v1",
+ "large-v2": "Systran/faster-whisper-large-v2",
+ "large-v3": "Systran/faster-whisper-large-v3",
+ "large": "Systran/faster-whisper-large-v3",
+ "distil-large-v2": "Systran/faster-distil-whisper-large-v2",
+ "distil-medium.en": "Systran/faster-distil-whisper-medium.en",
+ "distil-small.en": "Systran/faster-distil-whisper-small.en",
+ "distil-large-v3": "Systran/faster-distil-whisper-large-v3",
+}
+
+
+def available_models() -> List[str]:
+ """Returns the names of available models."""
+ return list(_MODELS.keys())
+
+
+def get_assets_path():
+ """Returns the path to the assets directory."""
+ return os.path.join(os.path.dirname(os.path.abspath(__file__)), "assets")
+
+
+def get_logger():
+ """Returns the module logger."""
+ return logging.getLogger("faster_whisper")
+
+
+def download_model(
+ size_or_id: str,
+ output_dir: Optional[str] = None,
+ local_files_only: bool = False,
+ cache_dir: Optional[str] = None,
+):
+ """Downloads a CTranslate2 Whisper model from the Hugging Face Hub.
+
+ Args:
+ size_or_id: Size of the model to download from https://huggingface.co/Systran
+ (tiny, tiny.en, base, base.en, small, small.en, distil-small.en, medium, medium.en,
+ distil-medium.en, large-v1, large-v2, large-v3, large, distil-large-v2,
+ distil-large-v3), or a CTranslate2-converted model ID from the Hugging Face Hub
+ (e.g. Systran/faster-whisper-large-v3).
+ output_dir: Directory where the model should be saved. If not set, the model is saved in
+ the cache directory.
+ local_files_only: If True, avoid downloading the file and return the path to the local
+ cached file if it exists.
+ cache_dir: Path to the folder where cached files are stored.
+
+ Returns:
+ The path to the downloaded model.
+
+ Raises:
+ ValueError: if the model size is invalid.
+ """
+ if re.match(r".*/.*", size_or_id):
+ repo_id = size_or_id
+ else:
+ repo_id = _MODELS.get(size_or_id)
+ if repo_id is None:
+ raise ValueError(
+ "Invalid model size '%s', expected one of: %s"
+ % (size_or_id, ", ".join(_MODELS.keys()))
+ )
+
+ allow_patterns = [
+ "config.json",
+ "preprocessor_config.json",
+ "model.bin",
+ "tokenizer.json",
+ "vocabulary.*",
+ ]
+
+ kwargs = {
+ "local_files_only": local_files_only,
+ "allow_patterns": allow_patterns,
+ "tqdm_class": disabled_tqdm,
+ }
+
+ if output_dir is not None:
+ kwargs["local_dir"] = output_dir
+ kwargs["local_dir_use_symlinks"] = False
+
+ if cache_dir is not None:
+ kwargs["cache_dir"] = cache_dir
+
+ try:
+ return huggingface_hub.snapshot_download(repo_id, **kwargs)
+ except (
+ huggingface_hub.utils.HfHubHTTPError,
+ requests.exceptions.ConnectionError,
+ ) as exception:
+ logger = get_logger()
+ logger.warning(
+ "An error occured while synchronizing the model %s from the Hugging Face Hub:\n%s",
+ repo_id,
+ exception,
+ )
+ logger.warning(
+ "Trying to load the model directly from the local cache, if it exists."
+ )
+
+ kwargs["local_files_only"] = True
+ return huggingface_hub.snapshot_download(repo_id, **kwargs)
+
+
+def format_timestamp(
+ seconds: float,
+ always_include_hours: bool = False,
+ decimal_marker: str = ".",
+) -> str:
+ assert seconds >= 0, "non-negative timestamp expected"
+ milliseconds = round(seconds * 1000.0)
+
+ hours = milliseconds // 3_600_000
+ milliseconds -= hours * 3_600_000
+
+ minutes = milliseconds // 60_000
+ milliseconds -= minutes * 60_000
+
+ seconds = milliseconds // 1_000
+ milliseconds -= seconds * 1_000
+
+ hours_marker = f"{hours:02d}:" if always_include_hours or hours > 0 else ""
+ return (
+ f"{hours_marker}{minutes:02d}:{seconds:02d}{decimal_marker}{milliseconds:03d}"
+ )
+
+
+class disabled_tqdm(tqdm):
+ def __init__(self, *args, **kwargs):
+ kwargs["disable"] = True
+ super().__init__(*args, **kwargs)
+
+
+def get_end(segments: List[dict]) -> Optional[float]:
+ return next(
+ (w["end"] for s in reversed(segments) for w in reversed(s["words"])),
+ segments[-1]["end"] if segments else None,
+ )
diff --git a/whisper_pipeline/faster-whisper-main/faster_whisper/vad.py b/whisper_pipeline/faster-whisper-main/faster_whisper/vad.py
new file mode 100644
index 0000000000000000000000000000000000000000..3881fd8185b439ef714af1f28b4e7a36f4fe24d6
--- /dev/null
+++ b/whisper_pipeline/faster-whisper-main/faster_whisper/vad.py
@@ -0,0 +1,596 @@
+import bisect
+import functools
+import os
+
+from abc import ABC
+from collections.abc import Callable
+from typing import List, NamedTuple, Optional, Union
+
+import numpy as np
+import torch
+
+from pyannote.audio.core.io import AudioFile
+from pyannote.audio.pipelines import VoiceActivityDetection
+from pyannote.audio.pipelines.utils import PipelineModel
+from pyannote.core import Annotation, Segment, SlidingWindowFeature
+
+from faster_whisper.utils import get_assets_path
+
+
+# The code below is adapted from https://github.com/snakers4/silero-vad.
+class VadOptions(NamedTuple):
+ """VAD options.
+
+ Attributes:
+ threshold: Speech threshold. Silero VAD outputs speech probabilities for each audio chunk,
+ probabilities ABOVE this value are considered as SPEECH. It is better to tune this
+ parameter for each dataset separately, but "lazy" 0.5 is pretty good for most datasets.
+ min_speech_duration_ms: Final speech chunks shorter min_speech_duration_ms are thrown out.
+ max_speech_duration_s: Maximum duration of speech chunks in seconds. Chunks longer
+ than max_speech_duration_s will be split at the timestamp of the last silence that
+ lasts more than 100ms (if any), to prevent aggressive cutting. Otherwise, they will be
+ split aggressively just before max_speech_duration_s.
+ min_silence_duration_ms: In the end of each speech chunk wait for min_silence_duration_ms
+ before separating it
+ speech_pad_ms: Final speech chunks are padded by speech_pad_ms each side
+ """
+
+ threshold: float = 0.5
+ min_speech_duration_ms: int = 250
+ max_speech_duration_s: float = float("inf")
+ min_silence_duration_ms: int = 2000
+ speech_pad_ms: int = 400
+
+
+def get_speech_timestamps(
+ audio: torch.Tensor,
+ vad_options: Optional[VadOptions] = None,
+ **kwargs,
+) -> List[dict]:
+ """This method is used for splitting long audios into speech chunks using silero VAD.
+
+ Args:
+ audio: One dimensional float array.
+ vad_options: Options for VAD processing.
+ kwargs: VAD options passed as keyword arguments for backward compatibility.
+
+ Returns:
+ List of dicts containing begin and end samples of each speech chunk.
+ """
+ if vad_options is None:
+ vad_options = VadOptions(**kwargs)
+
+ threshold = vad_options.threshold
+ min_speech_duration_ms = vad_options.min_speech_duration_ms
+ max_speech_duration_s = vad_options.max_speech_duration_s
+ min_silence_duration_ms = vad_options.min_silence_duration_ms
+ window_size_samples = 512
+ speech_pad_ms = vad_options.speech_pad_ms
+ sampling_rate = 16000
+ min_speech_samples = sampling_rate * min_speech_duration_ms / 1000
+ speech_pad_samples = sampling_rate * speech_pad_ms / 1000
+ max_speech_samples = (
+ sampling_rate * max_speech_duration_s
+ - window_size_samples
+ - 2 * speech_pad_samples
+ )
+ min_silence_samples = sampling_rate * min_silence_duration_ms / 1000
+ min_silence_samples_at_max_speech = sampling_rate * 98 / 1000
+
+ audio_length_samples = len(audio)
+
+ model = get_vad_model()
+ state, context = model.get_initial_states(batch_size=1)
+
+ speech_probs = []
+ for current_start_sample in range(0, audio_length_samples, window_size_samples):
+ chunk = audio[current_start_sample : current_start_sample + window_size_samples]
+ if len(chunk) < window_size_samples:
+ chunk = np.pad(chunk, (0, int(window_size_samples - len(chunk))))
+ speech_prob, state, context = model(chunk, state, context, sampling_rate)
+ speech_probs.append(speech_prob)
+
+ triggered = False
+ speeches = []
+ current_speech = {}
+ neg_threshold = threshold - 0.15
+
+ # to save potential segment end (and tolerate some silence)
+ temp_end = 0
+ # to save potential segment limits in case of maximum segment size reached
+ prev_end = next_start = 0
+
+ for i, speech_prob in enumerate(speech_probs):
+ if (speech_prob >= threshold) and temp_end:
+ temp_end = 0
+ if next_start < prev_end:
+ next_start = window_size_samples * i
+
+ if (speech_prob >= threshold) and not triggered:
+ triggered = True
+ current_speech["start"] = window_size_samples * i
+ continue
+
+ if (
+ triggered
+ and (window_size_samples * i) - current_speech["start"] > max_speech_samples
+ ):
+ if prev_end:
+ current_speech["end"] = prev_end
+ speeches.append(current_speech)
+ current_speech = {}
+ # previously reached silence (< neg_thres) and is still not speech (< thres)
+ if next_start < prev_end:
+ triggered = False
+ else:
+ current_speech["start"] = next_start
+ prev_end = next_start = temp_end = 0
+ else:
+ current_speech["end"] = window_size_samples * i
+ speeches.append(current_speech)
+ current_speech = {}
+ prev_end = next_start = temp_end = 0
+ triggered = False
+ continue
+
+ if (speech_prob < neg_threshold) and triggered:
+ if not temp_end:
+ temp_end = window_size_samples * i
+ # condition to avoid cutting in very short silence
+ if (window_size_samples * i) - temp_end > min_silence_samples_at_max_speech:
+ prev_end = temp_end
+ if (window_size_samples * i) - temp_end < min_silence_samples:
+ continue
+ else:
+ current_speech["end"] = temp_end
+ if (
+ current_speech["end"] - current_speech["start"]
+ ) > min_speech_samples:
+ speeches.append(current_speech)
+ current_speech = {}
+ prev_end = next_start = temp_end = 0
+ triggered = False
+ continue
+
+ if (
+ current_speech
+ and (audio_length_samples - current_speech["start"]) > min_speech_samples
+ ):
+ current_speech["end"] = audio_length_samples
+ speeches.append(current_speech)
+
+ for i, speech in enumerate(speeches):
+ if i == 0:
+ speech["start"] = int(max(0, speech["start"] - speech_pad_samples))
+ if i != len(speeches) - 1:
+ silence_duration = speeches[i + 1]["start"] - speech["end"]
+ if silence_duration < 2 * speech_pad_samples:
+ speech["end"] += int(silence_duration // 2)
+ speeches[i + 1]["start"] = int(
+ max(0, speeches[i + 1]["start"] - silence_duration // 2)
+ )
+ else:
+ speech["end"] = int(
+ min(audio_length_samples, speech["end"] + speech_pad_samples)
+ )
+ speeches[i + 1]["start"] = int(
+ max(0, speeches[i + 1]["start"] - speech_pad_samples)
+ )
+ else:
+ speech["end"] = int(
+ min(audio_length_samples, speech["end"] + speech_pad_samples)
+ )
+
+ return speeches
+
+
+def collect_chunks(audio: torch.Tensor, chunks: List[dict]) -> torch.Tensor:
+ """Collects and concatenates audio chunks."""
+ if not chunks:
+ return torch.tensor([], dtype=torch.float32)
+
+ return torch.cat([audio[chunk["start"] : chunk["end"]] for chunk in chunks])
+
+
+class SpeechTimestampsMap:
+ """Helper class to restore original speech timestamps."""
+
+ def __init__(self, chunks: List[dict], sampling_rate: int, time_precision: int = 2):
+ self.sampling_rate = sampling_rate
+ self.time_precision = time_precision
+ self.chunk_end_sample = []
+ self.total_silence_before = []
+
+ previous_end = 0
+ silent_samples = 0
+
+ for chunk in chunks:
+ silent_samples += chunk["start"] - previous_end
+ previous_end = chunk["end"]
+
+ self.chunk_end_sample.append(chunk["end"] - silent_samples)
+ self.total_silence_before.append(silent_samples / sampling_rate)
+
+ def get_original_time(
+ self,
+ time: float,
+ chunk_index: Optional[int] = None,
+ ) -> float:
+ if chunk_index is None:
+ chunk_index = self.get_chunk_index(time)
+
+ total_silence_before = self.total_silence_before[chunk_index]
+ return round(total_silence_before + time, self.time_precision)
+
+ def get_chunk_index(self, time: float) -> int:
+ sample = int(time * self.sampling_rate)
+ return min(
+ bisect.bisect(self.chunk_end_sample, sample),
+ len(self.chunk_end_sample) - 1,
+ )
+
+
+@functools.lru_cache
+def get_vad_model():
+ """Returns the VAD model instance."""
+ path = os.path.join(get_assets_path(), "silero_vad.onnx")
+ return SileroVADModel(path)
+
+
+class SileroVADModel:
+ def __init__(self, path):
+ try:
+ import onnxruntime
+ except ImportError as e:
+ raise RuntimeError(
+ "Applying the VAD filter requires the onnxruntime package"
+ ) from e
+
+ opts = onnxruntime.SessionOptions()
+ opts.inter_op_num_threads = 1
+ opts.intra_op_num_threads = 1
+ opts.log_severity_level = 4
+
+ self.session = onnxruntime.InferenceSession(
+ path,
+ providers=["CPUExecutionProvider"],
+ sess_options=opts,
+ )
+
+ def get_initial_states(self, batch_size: int):
+ state = np.zeros((2, batch_size, 128), dtype=np.float32)
+ context = np.zeros((batch_size, 64), dtype=np.float32)
+ return state, context
+
+ def __call__(self, x, state, context, sr: int):
+ if len(x.shape) == 1:
+ x = np.expand_dims(x, 0)
+ if len(x.shape) > 2:
+ raise ValueError(
+ f"Too many dimensions for input audio chunk {len(x.shape)}"
+ )
+ if sr / x.shape[1] > 31.25:
+ raise ValueError("Input audio chunk is too short")
+
+ x = np.concatenate([context, x], axis=1)
+
+ ort_inputs = {
+ "input": x,
+ "state": state,
+ "sr": np.array(sr, dtype="int64"),
+ }
+
+ out, state = self.session.run(None, ort_inputs)
+ context = x[..., -64:]
+
+ return out, state, context
+
+
+# BSD 2-Clause License
+
+# Copyright (c) 2024, Max Bain
+
+# Redistribution and use in source and binary forms, with or without
+# modification, are permitted provided that the following conditions are met:
+
+# 1. Redistributions of source code must retain the above copyright notice, this
+# list of conditions and the following disclaimer.
+
+# 2. Redistributions in binary form must reproduce the above copyright notice,
+# this list of conditions and the following disclaimer in the documentation
+# and/or other materials provided with the distribution.
+
+# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+# DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
+# FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
+# DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
+# SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
+# OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+
+# The code below is copied from whisper-x (https://github.com/m-bain/whisperX)
+# and adapted for faster_whisper.
+class SegmentX:
+ def __init__(self, start, end, speaker=None):
+ self.start = start
+ self.end = end
+ self.speaker = speaker
+
+
+class VoiceActivitySegmentation(VoiceActivityDetection, ABC):
+ """Pipeline wrapper class for Voice Activity Segmentation based on VAD scores."""
+
+ def __init__(
+ self,
+ segmentation: PipelineModel = "pyannote/segmentation",
+ device: Optional[Union[str, torch.device]] = None,
+ fscore: bool = False,
+ use_auth_token: Optional[str] = None,
+ **inference_kwargs,
+ ):
+ """Initialize the pipeline with the model name and the optional device.
+
+ Args:
+ dict parameters of VoiceActivityDetection class from pyannote:
+ segmentation (PipelineModel): Loaded model name.
+ device (torch.device or None): Device to perform the segmentation.
+ fscore (bool): Flag indicating whether to compute F-score during inference.
+ use_auth_token (str or None): Optional authentication token for model access.
+ inference_kwargs (dict): Additional arguments from VoiceActivityDetection pipeline.
+ """
+ super().__init__(
+ segmentation=segmentation,
+ device=device,
+ fscore=fscore,
+ use_auth_token=use_auth_token,
+ **inference_kwargs,
+ )
+
+ def apply(
+ self, file: AudioFile, hook: Optional[Callable] = None
+ ) -> SlidingWindowFeature:
+ """Apply voice activity detection on the audio file.
+
+ Args:
+ file (AudioFile): Processed file.
+ hook (callable): Hook called with signature: hook("step_name", step_artefact, file=file)
+
+ Returns:
+ segmentations (SlidingWindowFeature): Voice activity segmentation.
+ """
+ # setup hook (e.g. for debugging purposes)
+ hook = self.setup_hook(file, hook=hook)
+
+ # apply segmentation model if needed
+ # output shape is (num_chunks, num_frames, 1)
+ if self.training:
+ if self.CACHED_SEGMENTATION in file:
+ segmentations = file[self.CACHED_SEGMENTATION]
+ else:
+ segmentations = self._segmentation(file)
+ file[self.CACHED_SEGMENTATION] = segmentations
+ else:
+ segmentations: SlidingWindowFeature = self._segmentation(file)
+
+ return segmentations
+
+
+class BinarizeVadScores:
+ """Binarize detection scores using hysteresis thresholding.
+
+ Reference:
+ Gregory Gelly and Jean-Luc Gauvain. "Minimum Word Error Training of
+ RNN-based Voice Activity Detection", InterSpeech 2015.
+
+ Modified by Max Bain to include WhisperX's min-cut operation
+ https://arxiv.org/abs/2303.00747
+
+ """
+
+ def __init__(
+ self,
+ onset: float = 0.5,
+ offset: Optional[float] = None,
+ min_duration_on: float = 0.0,
+ min_duration_off: float = 0.0,
+ pad_onset: float = 0.0,
+ pad_offset: float = 0.0,
+ max_duration: float = float("inf"),
+ ):
+ """Initializes the parameters for Binarizing the VAD scores.
+
+ Args:
+ onset (float, optional):
+ Onset threshold. Defaults to 0.5.
+ offset (float, optional):
+ Offset threshold. Defaults to `onset`.
+ min_duration_on (float, optional):
+ Remove active regions shorter than that many seconds. Defaults to 0s.
+ min_duration_off (float, optional):
+ Fill inactive regions shorter than that many seconds. Defaults to 0s.
+ pad_onset (float, optional):
+ Extend active regions by moving their start time by that many seconds.
+ Defaults to 0s.
+ pad_offset (float, optional):
+ Extend active regions by moving their end time by that many seconds.
+ Defaults to 0s.
+ max_duration (float):
+ The maximum length of an active segment.
+ """
+ super().__init__()
+
+ self.onset = onset
+ self.offset = offset or onset
+
+ self.pad_onset = pad_onset
+ self.pad_offset = pad_offset
+
+ self.min_duration_on = min_duration_on
+ self.min_duration_off = min_duration_off
+
+ self.max_duration = max_duration
+
+ def __get_active_regions(self, scores: SlidingWindowFeature) -> Annotation:
+ """Extract active regions from VAD scores.
+
+ Args:
+ scores (SlidingWindowFeature): Detection scores.
+
+ Returns:
+ active (Annotation): Active regions.
+ """
+ num_frames, num_classes = scores.data.shape
+ frames = scores.sliding_window
+ timestamps = [frames[i].middle for i in range(num_frames)]
+ # annotation meant to store 'active' regions
+ active = Annotation()
+ for k, k_scores in enumerate(scores.data.T):
+ label = k if scores.labels is None else scores.labels[k]
+
+ # initial state
+ start = timestamps[0]
+ is_active = k_scores[0] > self.onset
+ curr_scores = [k_scores[0]]
+ curr_timestamps = [start]
+ t = start
+ # optionally add `strict=False` for python 3.10 or later
+ for t, y in zip(timestamps[1:], k_scores[1:]):
+ # currently active
+ if is_active:
+ curr_duration = t - start
+ if curr_duration > self.max_duration:
+ search_after = len(curr_scores) // 2
+ # divide segment
+ min_score_div_idx = search_after + np.argmin(
+ curr_scores[search_after:]
+ )
+ min_score_t = curr_timestamps[min_score_div_idx]
+ region = Segment(
+ start - self.pad_onset, min_score_t + self.pad_offset
+ )
+ active[region, k] = label
+ start = curr_timestamps[min_score_div_idx]
+ curr_scores = curr_scores[min_score_div_idx + 1 :]
+ curr_timestamps = curr_timestamps[min_score_div_idx + 1 :]
+ # switching from active to inactive
+ elif y < self.offset:
+ region = Segment(start - self.pad_onset, t + self.pad_offset)
+ active[region, k] = label
+ start = t
+ is_active = False
+ curr_scores = []
+ curr_timestamps = []
+ curr_scores.append(y)
+ curr_timestamps.append(t)
+ # currently inactive
+ else:
+ # switching from inactive to active
+ if y > self.onset:
+ start = t
+ is_active = True
+
+ # if active at the end, add final region
+ if is_active:
+ region = Segment(start - self.pad_onset, t + self.pad_offset)
+ active[region, k] = label
+
+ return active
+
+ def __call__(self, scores: SlidingWindowFeature) -> Annotation:
+ """Binarize detection scores.
+
+ Args:
+ scores (SlidingWindowFeature): Detection scores.
+
+ Returns:
+ active (Annotation): Binarized scores.
+ """
+ active = self.__get_active_regions(scores)
+ # because of padding, some active regions might be overlapping: merge them.
+ # also: fill same speaker gaps shorter than min_duration_off
+ if self.pad_offset > 0.0 or self.pad_onset > 0.0 or self.min_duration_off > 0.0:
+ if self.max_duration < float("inf"):
+ raise NotImplementedError("This would break current max_duration param")
+ active = active.support(collar=self.min_duration_off)
+
+ # remove tracks shorter than min_duration_on
+ if self.min_duration_on > 0:
+ for segment, track in list(active.itertracks()):
+ if segment.duration < self.min_duration_on:
+ del active[segment, track]
+
+ return active
+
+
+def merge_chunks(
+ segments,
+ chunk_length,
+ onset: float = 0.5,
+ offset: Optional[float] = None,
+ edge_padding: float = 0.1,
+):
+ """
+ Merge operation described in whisper-x paper
+ """
+ curr_end = 0
+ merged_segments = []
+ seg_idxs = []
+ speaker_idxs = []
+
+ assert chunk_length > 0
+ binarize = BinarizeVadScores(max_duration=chunk_length, onset=onset, offset=offset)
+ segments = binarize(segments)
+ segments_list = []
+ for speech_turn in segments.get_timeline():
+ segments_list.append(
+ SegmentX(
+ max(0.0, speech_turn.start - edge_padding),
+ speech_turn.end + edge_padding,
+ "UNKNOWN",
+ )
+ ) # 100ms edge padding to account for edge errors
+
+ if len(segments_list) == 0:
+ print("No active speech found in audio")
+ return []
+
+ # Make sur the starting point is the start of the segment.
+ curr_start = segments_list[0].start
+
+ for idx, seg in enumerate(segments_list):
+ # if any segment start timing is less than previous segment end timing,
+ # reset the edge padding. Similarly for end timing.
+ if idx > 0:
+ if seg.start < segments_list[idx - 1].end:
+ seg.start += edge_padding
+ if idx < len(segments_list) - 1:
+ if seg.end > segments_list[idx + 1].start:
+ seg.end -= edge_padding
+
+ if seg.end - curr_start > chunk_length and curr_end - curr_start > 0:
+ merged_segments.append(
+ {
+ "start": curr_start,
+ "end": curr_end,
+ "segments": seg_idxs,
+ }
+ )
+ curr_start = seg.start
+ seg_idxs = []
+ speaker_idxs = []
+ curr_end = seg.end
+ seg_idxs.append((seg.start, seg.end))
+ speaker_idxs.append(seg.speaker)
+ # add final
+ merged_segments.append(
+ {
+ "start": curr_start,
+ "end": curr_end,
+ "segments": seg_idxs,
+ }
+ )
+ return merged_segments
diff --git a/whisper_pipeline/faster-whisper-main/faster_whisper/version.py b/whisper_pipeline/faster-whisper-main/faster_whisper/version.py
new file mode 100644
index 0000000000000000000000000000000000000000..65eaef429fb3048ee8d105fe67da4da43f5a2324
--- /dev/null
+++ b/whisper_pipeline/faster-whisper-main/faster_whisper/version.py
@@ -0,0 +1,3 @@
+"""Version information."""
+
+__version__ = "1.0.3"
diff --git a/whisper_pipeline/faster-whisper-main/requirements.conversion.txt b/whisper_pipeline/faster-whisper-main/requirements.conversion.txt
new file mode 100644
index 0000000000000000000000000000000000000000..56fdf5f004baa48a8427cd1085e73244483d1b09
--- /dev/null
+++ b/whisper_pipeline/faster-whisper-main/requirements.conversion.txt
@@ -0,0 +1 @@
+transformers[torch]>=4.23
diff --git a/whisper_pipeline/faster-whisper-main/requirements.txt b/whisper_pipeline/faster-whisper-main/requirements.txt
new file mode 100644
index 0000000000000000000000000000000000000000..0c106e5e136d9c2931b5907d9aeb608b4673ce1c
--- /dev/null
+++ b/whisper_pipeline/faster-whisper-main/requirements.txt
@@ -0,0 +1,8 @@
+ctranslate2>=4.0,<5
+huggingface_hub>=0.13
+tokenizers>=0.13,<1
+onnxruntime>=1.14,<2
+pyannote-audio
+torch
+torchaudio
+tqdm
\ No newline at end of file
diff --git a/whisper_pipeline/faster-whisper-main/setup.cfg b/whisper_pipeline/faster-whisper-main/setup.cfg
new file mode 100644
index 0000000000000000000000000000000000000000..bf2da8684c8b2df8b5d2c9b732ed23018e0763a9
--- /dev/null
+++ b/whisper_pipeline/faster-whisper-main/setup.cfg
@@ -0,0 +1,9 @@
+[flake8]
+max-line-length = 100
+ignore =
+ E203,
+ W503,
+
+[isort]
+profile=black
+lines_between_types=1
diff --git a/whisper_pipeline/faster-whisper-main/setup.py b/whisper_pipeline/faster-whisper-main/setup.py
new file mode 100644
index 0000000000000000000000000000000000000000..782f1b275264cccb501f36be8e0c3054fdd11c3a
--- /dev/null
+++ b/whisper_pipeline/faster-whisper-main/setup.py
@@ -0,0 +1,68 @@
+import os
+
+from setuptools import find_packages, setup
+
+base_dir = os.path.dirname(os.path.abspath(__file__))
+
+
+def get_long_description():
+ readme_path = os.path.join(base_dir, "README.md")
+ with open(readme_path, encoding="utf-8") as readme_file:
+ return readme_file.read()
+
+
+def get_project_version():
+ version_path = os.path.join(base_dir, "faster_whisper", "version.py")
+ version = {}
+ with open(version_path, encoding="utf-8") as fp:
+ exec(fp.read(), version)
+ return version["__version__"]
+
+
+def get_requirements(path):
+ with open(path, encoding="utf-8") as requirements:
+ return [requirement.strip() for requirement in requirements]
+
+
+install_requires = get_requirements(os.path.join(base_dir, "requirements.txt"))
+conversion_requires = get_requirements(
+ os.path.join(base_dir, "requirements.conversion.txt")
+)
+
+setup(
+ name="faster-whisper",
+ version=get_project_version(),
+ license="MIT",
+ description="Faster Whisper transcription with CTranslate2",
+ long_description=get_long_description(),
+ long_description_content_type="text/markdown",
+ author="Guillaume Klein",
+ url="https://github.com/SYSTRAN/faster-whisper",
+ classifiers=[
+ "Development Status :: 4 - Beta",
+ "Intended Audience :: Developers",
+ "Intended Audience :: Science/Research",
+ "License :: OSI Approved :: MIT License",
+ "Programming Language :: Python :: 3",
+ "Programming Language :: Python :: 3 :: Only",
+ "Programming Language :: Python :: 3.8",
+ "Programming Language :: Python :: 3.9",
+ "Programming Language :: Python :: 3.10",
+ "Programming Language :: Python :: 3.11",
+ "Topic :: Scientific/Engineering :: Artificial Intelligence",
+ ],
+ keywords="openai whisper speech ctranslate2 inference quantization transformer",
+ python_requires=">=3.8",
+ install_requires=install_requires,
+ extras_require={
+ "conversion": conversion_requires,
+ "dev": [
+ "black==23.*",
+ "flake8==6.*",
+ "isort==5.*",
+ "pytest==7.*",
+ ],
+ },
+ packages=find_packages(),
+ include_package_data=True,
+)
diff --git a/whisper_pipeline/faster-whisper-main/tests/conftest.py b/whisper_pipeline/faster-whisper-main/tests/conftest.py
new file mode 100644
index 0000000000000000000000000000000000000000..0c0f42483b021a80c00bcda32e35f1107058f72b
--- /dev/null
+++ b/whisper_pipeline/faster-whisper-main/tests/conftest.py
@@ -0,0 +1,18 @@
+import os
+
+import pytest
+
+
+@pytest.fixture
+def data_dir():
+ return os.path.join(os.path.dirname(os.path.abspath(__file__)), "data")
+
+
+@pytest.fixture
+def jfk_path(data_dir):
+ return os.path.join(data_dir, "jfk.flac")
+
+
+@pytest.fixture
+def physcisworks_path(data_dir):
+ return os.path.join(data_dir, "physicsworks.wav")
diff --git a/whisper_pipeline/faster-whisper-main/tests/data/jfk.flac b/whisper_pipeline/faster-whisper-main/tests/data/jfk.flac
new file mode 100644
index 0000000000000000000000000000000000000000..8cf66fea45dd2f1ac2b182a37a2208657c11e8af
--- /dev/null
+++ b/whisper_pipeline/faster-whisper-main/tests/data/jfk.flac
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:63a4b1e4c1dc655ac70961ffbf518acd249df237e5a0152faae9a4a836949715
+size 1152693
diff --git a/whisper_pipeline/faster-whisper-main/tests/data/physicsworks.wav b/whisper_pipeline/faster-whisper-main/tests/data/physicsworks.wav
new file mode 100644
index 0000000000000000000000000000000000000000..ee71bd791592ccaf0084099e8ba81c967f01035f
--- /dev/null
+++ b/whisper_pipeline/faster-whisper-main/tests/data/physicsworks.wav
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:329d029898a53fcc1d79be9d38f23268704bd896c65928719e41593b1d9c5578
+size 6505148
diff --git a/whisper_pipeline/faster-whisper-main/tests/data/stereo_diarization.wav b/whisper_pipeline/faster-whisper-main/tests/data/stereo_diarization.wav
new file mode 100644
index 0000000000000000000000000000000000000000..3f5ae75dac40be2b33c2c76ac291a4d147b0b47d
Binary files /dev/null and b/whisper_pipeline/faster-whisper-main/tests/data/stereo_diarization.wav differ
diff --git a/whisper_pipeline/faster-whisper-main/tests/test_transcribe.py b/whisper_pipeline/faster-whisper-main/tests/test_transcribe.py
new file mode 100644
index 0000000000000000000000000000000000000000..96eb68c3331a11dcdfbe52192ab3bd1732bda097
--- /dev/null
+++ b/whisper_pipeline/faster-whisper-main/tests/test_transcribe.py
@@ -0,0 +1,258 @@
+import os
+
+from faster_whisper import BatchedInferencePipeline, WhisperModel, decode_audio
+from faster_whisper.tokenizer import Tokenizer
+from faster_whisper.transcribe import get_suppressed_tokens
+
+
+def test_supported_languages():
+ model = WhisperModel("tiny.en")
+ assert model.supported_languages == ["en"]
+
+
+def test_transcribe(jfk_path):
+ model = WhisperModel("tiny")
+ segments, info = model.transcribe(jfk_path, word_timestamps=True)
+ assert info.all_language_probs is not None
+
+ assert info.language == "en"
+ assert info.language_probability > 0.9
+ assert info.duration == 11
+
+ # Get top language info from all results, which should match the
+ # already existing metadata
+ top_lang, top_lang_score = info.all_language_probs[0]
+ assert info.language == top_lang
+ assert abs(info.language_probability - top_lang_score) < 1e-16
+
+ segments = list(segments)
+
+ assert len(segments) == 1
+
+ segment = segments[0]
+
+ assert segment.text == (
+ " And so my fellow Americans ask not what your country can do for you, "
+ "ask what you can do for your country."
+ )
+
+ assert segment.text == "".join(word.word for word in segment.words)
+ assert segment.start == segment.words[0].start
+ assert segment.end == segment.words[-1].end
+ batched_model = BatchedInferencePipeline(model=model, use_vad_model=False)
+ result, info = batched_model.transcribe(jfk_path, word_timestamps=True)
+ assert info.language == "en"
+ assert info.language_probability > 0.7
+ segments = []
+ for segment in result:
+ segments.append(
+ {"start": segment.start, "end": segment.end, "text": segment.text}
+ )
+
+ assert len(segments) == 1
+ assert segment.text == (
+ " And so my fellow Americans ask not what your country can do for you, "
+ "ask what you can do for your country."
+ )
+
+
+def test_batched_transcribe(physcisworks_path):
+ model = WhisperModel("tiny")
+ batched_model = BatchedInferencePipeline(model=model)
+ result, info = batched_model.transcribe(physcisworks_path, batch_size=16)
+ assert info.language == "en"
+ assert info.language_probability > 0.7
+ segments = []
+ for segment in result:
+ segments.append(
+ {"start": segment.start, "end": segment.end, "text": segment.text}
+ )
+ # number of near 30 sec segments
+ assert len(segments) == 8
+
+ result, info = batched_model.transcribe(
+ physcisworks_path,
+ batch_size=16,
+ without_timestamps=False,
+ word_timestamps=True,
+ )
+ segments = []
+ for segment in result:
+ assert segment.words is not None
+ segments.append(
+ {"start": segment.start, "end": segment.end, "text": segment.text}
+ )
+ assert len(segments) > 8
+
+
+def test_prefix_with_timestamps(jfk_path):
+ model = WhisperModel("tiny")
+ segments, _ = model.transcribe(jfk_path, prefix="And so my fellow Americans")
+ segments = list(segments)
+
+ assert len(segments) == 1
+
+ segment = segments[0]
+
+ assert segment.text == (
+ " And so my fellow Americans ask not what your country can do for you, "
+ "ask what you can do for your country."
+ )
+
+ assert segment.start == 0
+ assert 10 < segment.end < 11
+
+
+def test_vad(jfk_path):
+ model = WhisperModel("tiny")
+ segments, info = model.transcribe(
+ jfk_path,
+ vad_filter=True,
+ vad_parameters=dict(min_silence_duration_ms=500, speech_pad_ms=200),
+ )
+ segments = list(segments)
+
+ assert len(segments) == 1
+ segment = segments[0]
+
+ assert segment.text == (
+ " And so my fellow Americans ask not what your country can do for you, "
+ "ask what you can do for your country."
+ )
+
+ assert 0 < segment.start < 1
+ assert 10 < segment.end < 11
+
+ assert info.vad_options.min_silence_duration_ms == 500
+ assert info.vad_options.speech_pad_ms == 200
+
+
+def test_stereo_diarization(data_dir):
+ model = WhisperModel("tiny")
+
+ audio_path = os.path.join(data_dir, "stereo_diarization.wav")
+ left, right = decode_audio(audio_path, split_stereo=True)
+
+ segments, _ = model.transcribe(left)
+ transcription = "".join(segment.text for segment in segments).strip()
+ assert transcription == (
+ "He began a confused complaint against the wizard, "
+ "who had vanished behind the curtain on the left."
+ )
+
+ segments, _ = model.transcribe(right)
+ transcription = "".join(segment.text for segment in segments).strip()
+ assert transcription == "The horizon seems extremely distant."
+
+
+def test_multisegment_lang_id(physcisworks_path):
+ model = WhisperModel("tiny")
+ language_info = model.detect_language_multi_segment(physcisworks_path)
+ assert language_info["language_code"] == "en"
+ assert language_info["language_confidence"] > 0.8
+
+
+def test_suppressed_tokens_minus_1():
+ model = WhisperModel("tiny.en")
+
+ tokenizer = Tokenizer(model.hf_tokenizer, False)
+ tokens = get_suppressed_tokens(tokenizer, [-1])
+ assert tokens == (
+ 1,
+ 2,
+ 7,
+ 8,
+ 9,
+ 10,
+ 14,
+ 25,
+ 26,
+ 27,
+ 28,
+ 29,
+ 31,
+ 58,
+ 59,
+ 60,
+ 61,
+ 62,
+ 63,
+ 90,
+ 91,
+ 92,
+ 93,
+ 357,
+ 366,
+ 438,
+ 532,
+ 685,
+ 705,
+ 796,
+ 930,
+ 1058,
+ 1220,
+ 1267,
+ 1279,
+ 1303,
+ 1343,
+ 1377,
+ 1391,
+ 1635,
+ 1782,
+ 1875,
+ 2162,
+ 2361,
+ 2488,
+ 3467,
+ 4008,
+ 4211,
+ 4600,
+ 4808,
+ 5299,
+ 5855,
+ 6329,
+ 7203,
+ 9609,
+ 9959,
+ 10563,
+ 10786,
+ 11420,
+ 11709,
+ 11907,
+ 13163,
+ 13697,
+ 13700,
+ 14808,
+ 15306,
+ 16410,
+ 16791,
+ 17992,
+ 19203,
+ 19510,
+ 20724,
+ 22305,
+ 22935,
+ 27007,
+ 30109,
+ 30420,
+ 33409,
+ 34949,
+ 40283,
+ 40493,
+ 40549,
+ 47282,
+ 49146,
+ 50257,
+ 50357,
+ 50358,
+ 50359,
+ 50360,
+ )
+
+
+def test_suppressed_tokens_minus_value():
+ model = WhisperModel("tiny.en")
+
+ tokenizer = Tokenizer(model.hf_tokenizer, False)
+ tokens = get_suppressed_tokens(tokenizer, [13])
+ assert tokens == (13, 50257, 50357, 50358, 50359, 50360)
diff --git a/whisper_pipeline/faster-whisper-main/tests/test_utils.py b/whisper_pipeline/faster-whisper-main/tests/test_utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..bb488feca5c95c75b6be03ce93e4c90ddd4d0587
--- /dev/null
+++ b/whisper_pipeline/faster-whisper-main/tests/test_utils.py
@@ -0,0 +1,29 @@
+import os
+
+from faster_whisper import available_models, download_model
+
+
+def test_available_models():
+ models = available_models()
+ assert isinstance(models, list)
+ assert "tiny" in models
+
+
+def test_download_model(tmpdir):
+ output_dir = str(tmpdir.join("model"))
+
+ model_dir = download_model("tiny", output_dir=output_dir)
+
+ assert model_dir == output_dir
+ assert os.path.isdir(model_dir)
+ assert not os.path.islink(model_dir)
+
+ for filename in os.listdir(model_dir):
+ path = os.path.join(model_dir, filename)
+ assert not os.path.islink(path)
+
+
+def test_download_model_in_cache(tmpdir):
+ cache_dir = str(tmpdir.join("model"))
+ download_model("tiny", cache_dir=cache_dir)
+ assert os.path.isdir(cache_dir)
diff --git a/whisper_pipeline/gector/Model_GECTOR/config.json b/whisper_pipeline/gector/Model_GECTOR/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..708c207ae1bed120ad563c3a395a186ded0f120f
--- /dev/null
+++ b/whisper_pipeline/gector/Model_GECTOR/config.json
@@ -0,0 +1,31 @@
+{
+ "_name_or_path": "dragonSwing/vibert-capu",
+ "architectures": [
+ "Seq2LabelsModel"
+ ],
+ "attention_probs_dropout_prob": 0.1,
+ "classifier_dropout": null,
+ "hidden_act": "gelu",
+ "hidden_dropout_prob": 0.1,
+ "hidden_size": 768,
+ "initializer_range": 0.02,
+ "intermediate_size": 3072,
+ "label_smoothing": 0.0,
+ "layer_norm_eps": 1e-12,
+ "load_pretrained": false,
+ "max_position_embeddings": 512,
+ "model_type": "bert",
+ "num_attention_heads": 12,
+ "num_detect_classes": 4,
+ "num_hidden_layers": 12,
+ "pad_token_id": 0,
+ "position_embedding_type": "absolute",
+ "predictor_dropout": 0.0,
+ "pretrained_name_or_path": "FPTAI/vibert-base-cased",
+ "special_tokens_fix": true,
+ "torch_dtype": "float32",
+ "transformers_version": "4.28.1",
+ "type_vocab_size": 2,
+ "use_cache": true,
+ "vocab_size": 15
+}
diff --git a/whisper_pipeline/gector/Model_GECTOR/pytorch_model.bin b/whisper_pipeline/gector/Model_GECTOR/pytorch_model.bin
new file mode 100644
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+}
\ No newline at end of file
diff --git a/whisper_pipeline/gector/Tokenize_GEC/tokenizer_config.json b/whisper_pipeline/gector/Tokenize_GEC/tokenizer_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..03f0f6a007aa8f152549658702b6a870e0e6b493
--- /dev/null
+++ b/whisper_pipeline/gector/Tokenize_GEC/tokenizer_config.json
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+ "tokenize_chinese_chars": true,
+ "tokenizer_class": "BertTokenizer",
+ "unk_token": "[UNK]"
+}
diff --git a/whisper_pipeline/gector/Tokenize_GEC/vocab.txt b/whisper_pipeline/gector/Tokenize_GEC/vocab.txt
new file mode 100644
index 0000000000000000000000000000000000000000..191dbe0b329816a0dca59c9529607abd0fa7804b
--- /dev/null
+++ b/whisper_pipeline/gector/Tokenize_GEC/vocab.txt
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+organisms
+independence
+##brata
+besar
+Landgericht
+ingin
+largely
+##partiet
+##ziek
+friendship
+visited
+heritage
+paintings
+testament
+pilots
+agreed
+embargo
+racial
+impose
+voters
+traveling
+succeeded
+registration
+modifications
+desired
+covering
+appearance
+frequent
+consistently
+##plaints
+counted
+owners
+withdraw
+considering
+##sante
+##preis
+Polizei
+Belgique
+molte
+rossa
+##bija
+Englisch
+##lativo
+temporal
+##blia
+Technologie
+##ytet
+salud
+##ulare
+Etiopia
+espera
+carica
+violent
+##runda
+scientifica
+hidrogen
+prova
+sido
+Biografie
+##ènement
+unang
+assume
+relationships
+reaches
+##cismo
+variations
+concentration
+##fected
+retain
+holds
+relating
+ordo
+mentioned
+adel
+lowest
+ranks
+fuselage
+attitude
+prohibited
+discussion
+poter
+##karz
+presa
+massive
+##atok
+##plitude
+initiated
+compose
+##alainen
+kleine
+crashed
+##nyata
+preventing
+Partito
+partito
+Jurist
+formats
+##zlik
+coupled
+outbreak
+##kels
+Medien
+delt
+finali
+appointment
+Ministro
+##versario
+relatives
+participating
+melhor
+qualidade
+Gesundheit
+alemana
+samma
+##gène
+Conservative
+Beide
+##aag
+##kammer
+reporting
+##tener
+Kálmán
+Voogd
diff --git a/whisper_pipeline/gector/__init__.py b/whisper_pipeline/gector/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..a45f8a9f5b84e9105f594bfff0082d6a1d40e7d6
--- /dev/null
+++ b/whisper_pipeline/gector/__init__.py
@@ -0,0 +1 @@
+from .gec_model import GecBERTModel
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diff --git a/whisper_pipeline/gector/configuration_seq2labels.py b/whisper_pipeline/gector/configuration_seq2labels.py
new file mode 100644
index 0000000000000000000000000000000000000000..451e7367cc36ac85bdc9023e3c1b9377da81a484
--- /dev/null
+++ b/whisper_pipeline/gector/configuration_seq2labels.py
@@ -0,0 +1,61 @@
+from transformers import PretrainedConfig
+
+class Seq2LabelsConfig(PretrainedConfig):
+ r"""
+ This is the configuration class to store the configuration of a [`Seq2LabelsModel`]. It is used to
+ instantiate a Seq2Labels model according to the specified arguments, defining the model architecture. Instantiating a
+ configuration with the defaults will yield a similar configuration to that of the Seq2Labels architecture.
+ Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
+ documentation from [`PretrainedConfig`] for more information.
+ Args:
+ vocab_size (`int`, *optional*, defaults to 30522):
+ Vocabulary size of the BERT model. Defines the number of different tokens that can be represented by the
+ `inputs_ids` passed when calling [`BertModel`] or [`TFBertModel`].
+ pretrained_name_or_path (`str`, *optional*, defaults to `bert-base-cased`):
+ Pretrained BERT-like model path
+ load_pretrained (`bool`, *optional*, defaults to `False`):
+ Whether to load pretrained model from `pretrained_name_or_path`
+ use_cache (`bool`, *optional*, defaults to `True`):
+ Whether or not the model should return the last key/values attentions (not used by all models). Only
+ relevant if `config.is_decoder=True`.
+ predictor_dropout (`float`, *optional*):
+ The dropout ratio for the classification head.
+ special_tokens_fix (`bool`, *optional*, defaults to `False`):
+ Whether to add additional tokens to the BERT's embedding layer.
+ Examples:
+ ```python
+ >>> from transformers import BertModel, BertConfig
+ >>> # Initializing a Seq2Labels style configuration
+ >>> configuration = Seq2LabelsConfig()
+ >>> # Initializing a model from the bert-base-uncased style configuration
+ >>> model = Seq2LabelsModel(configuration)
+ >>> # Accessing the model configuration
+ >>> configuration = model.config
+ ```"""
+ model_type = "bert"
+
+ def __init__(
+ self,
+ pretrained_name_or_path="bert-base-cased",
+ vocab_size=15,
+ num_detect_classes=4,
+ load_pretrained=False,
+ initializer_range=0.02,
+ pad_token_id=0,
+ use_cache=True,
+ predictor_dropout=0.0,
+ special_tokens_fix=False,
+ label_smoothing=0.0,
+ **kwargs
+ ):
+ super().__init__(pad_token_id=pad_token_id, **kwargs)
+
+ self.vocab_size = vocab_size
+ self.num_detect_classes = num_detect_classes
+ self.pretrained_name_or_path = pretrained_name_or_path
+ self.load_pretrained = load_pretrained
+ self.initializer_range = initializer_range
+ self.use_cache = use_cache
+ self.predictor_dropout = predictor_dropout
+ self.special_tokens_fix = special_tokens_fix
+ self.label_smoothing = label_smoothing
diff --git a/whisper_pipeline/gector/gec_model.py b/whisper_pipeline/gector/gec_model.py
new file mode 100644
index 0000000000000000000000000000000000000000..945b809eaf58de054f874665283c81e94cdaba4d
--- /dev/null
+++ b/whisper_pipeline/gector/gec_model.py
@@ -0,0 +1,445 @@
+"""Wrapper of Seq2Labels model. Fixes errors based on model predictions"""
+from collections import defaultdict
+from difflib import SequenceMatcher
+import logging
+import re
+from time import time
+from typing import List, Union
+
+import torch
+from transformers import AutoTokenizer
+from gector.modeling_seq2labels import Seq2LabelsModel
+from gector.vocabulary import Vocabulary
+from gector.utils import PAD, UNK, START_TOKEN, get_target_sent_by_edits
+
+logging.getLogger("werkzeug").setLevel(logging.ERROR)
+logger = logging.getLogger(__file__)
+
+
+class GecBERTModel(torch.nn.Module):
+ def __init__(
+ self,
+ vocab_path=None,
+ model_paths=None,
+ weights=None,
+ device=None,
+ max_len=64,
+ min_len=3,
+ lowercase_tokens=False,
+ log=False,
+ iterations=3,
+ min_error_probability=0.0,
+ confidence=0,
+ resolve_cycles=False,
+ split_chunk=False,
+ chunk_size=48,
+ overlap_size=12,
+ min_words_cut=6,
+ punc_dict={':', ".", ",", "?"},
+ ):
+ r"""
+ Args:
+ vocab_path (`str`):
+ Path to vocabulary directory.
+ model_paths (`List[str]`):
+ List of model paths.
+ weights (`int`, *Optional*, defaults to None):
+ Weights of each model. Only relevant if `is_ensemble is True`.
+ device (`int`, *Optional*, defaults to None):
+ Device to load model. If not set, device will be automatically choose.
+ max_len (`int`, defaults to 64):
+ Max sentence length to be processed (all longer will be truncated).
+ min_len (`int`, defaults to 3):
+ Min sentence length to be processed (all shorted will be returned w/o changes).
+ lowercase_tokens (`bool`, defaults to False):
+ Whether to lowercase tokens.
+ log (`bool`, defaults to False):
+ Whether to enable logging.
+ iterations (`int`, defaults to 3):
+ Max iterations to run during inference.
+ special_tokens_fix (`bool`, defaults to True):
+ Whether to fix problem with [CLS], [SEP] tokens tokenization.
+ min_error_probability (`float`, defaults to `0.0`):
+ Minimum probability for each action to apply.
+ confidence (`float`, defaults to `0.0`):
+ How many probability to add to $KEEP token.
+ split_chunk (`bool`, defaults to False):
+ Whether to split long sentences to multiple segments of `chunk_size`.
+ !Warning: if `chunk_size > max_len`, each segment will be truncate to `max_len`.
+ chunk_size (`int`, defaults to 48):
+ Length of each segment (in words). Only relevant if `split_chunk is True`.
+ overlap_size (`int`, defaults to 12):
+ Overlap size (in words) between two consecutive segments. Only relevant if `split_chunk is True`.
+ min_words_cut (`int`, defaults to 6):
+ Minimun number of words to be cut while merging two consecutive segments.
+ Only relevant if `split_chunk is True`.
+ punc_dict (List[str], defaults to `{':', ".", ",", "?"}`):
+ List of punctuations.
+ """
+ super().__init__()
+ if isinstance(model_paths, str):
+ model_paths = [model_paths]
+ self.model_weights = list(map(float, weights)) if weights else [1] * len(model_paths)
+ self.device = (
+ torch.device("cuda" if torch.cuda.is_available() else "cpu") if device is None else torch.device(device)
+ )
+ self.max_len = max_len
+ self.min_len = min_len
+ self.lowercase_tokens = lowercase_tokens
+ self.min_error_probability = min_error_probability
+ self.vocab = Vocabulary.from_files(vocab_path)
+ self.incorr_index = self.vocab.get_token_index("INCORRECT", "d_tags")
+ self.log = log
+ self.iterations = iterations
+ self.confidence = confidence
+ self.resolve_cycles = resolve_cycles
+ assert (
+ chunk_size > 0 and chunk_size // 2 >= overlap_size
+ ), "Chunk merging required overlap size must be smaller than half of chunk size"
+ self.split_chunk = split_chunk
+ self.chunk_size = chunk_size
+ self.overlap_size = overlap_size
+ self.min_words_cut = min_words_cut
+ self.stride = chunk_size - overlap_size
+ self.punc_dict = punc_dict
+ self.punc_str = '[' + ''.join([f'\{x}' for x in punc_dict]) + ']'
+ # set training parameters and operations
+
+ self.indexers = []
+ self.models = []
+ for model_path in model_paths:
+ model = Seq2LabelsModel.from_pretrained(model_path)
+ config = model.config
+ model_name = config.pretrained_name_or_path
+ special_tokens_fix = config.special_tokens_fix
+ self.indexers.append(self._get_indexer(model_name, special_tokens_fix))
+ model.eval().to(self.device)
+ self.models.append(model)
+
+ def _get_indexer(self, weights_name, special_tokens_fix):
+ tokenizer = AutoTokenizer.from_pretrained(
+ weights_name, do_basic_tokenize=False, do_lower_case=self.lowercase_tokens, model_max_length=1024
+ )
+ # to adjust all tokenizers
+ if hasattr(tokenizer, 'encoder'):
+ tokenizer.vocab = tokenizer.encoder
+ if hasattr(tokenizer, 'sp_model'):
+ tokenizer.vocab = defaultdict(lambda: 1)
+ for i in range(tokenizer.sp_model.get_piece_size()):
+ tokenizer.vocab[tokenizer.sp_model.id_to_piece(i)] = i
+
+ if special_tokens_fix:
+ tokenizer.add_tokens([START_TOKEN])
+ tokenizer.vocab[START_TOKEN] = len(tokenizer) - 1
+ return tokenizer
+
+ def forward(self, text: Union[str, List[str], List[List[str]]], is_split_into_words=False):
+ # Input type checking for clearer error
+ def _is_valid_text_input(t):
+ if isinstance(t, str):
+ # Strings are fine
+ return True
+ elif isinstance(t, (list, tuple)):
+ # List are fine as long as they are...
+ if len(t) == 0:
+ # ... empty
+ return True
+ elif isinstance(t[0], str):
+ # ... list of strings
+ return True
+ elif isinstance(t[0], (list, tuple)):
+ # ... list with an empty list or with a list of strings
+ return len(t[0]) == 0 or isinstance(t[0][0], str)
+ else:
+ return False
+ else:
+ return False
+
+ if not _is_valid_text_input(text):
+ raise ValueError(
+ "text input must of type `str` (single example), `List[str]` (batch or single pretokenized example) "
+ "or `List[List[str]]` (batch of pretokenized examples)."
+ )
+
+ if is_split_into_words:
+ is_batched = isinstance(text, (list, tuple)) and text and isinstance(text[0], (list, tuple))
+ else:
+ is_batched = isinstance(text, (list, tuple))
+ if is_batched:
+ text = [x.split() for x in text]
+ else:
+ text = text.split()
+
+ if not is_batched:
+ text = [text]
+
+ return self.handle_batch(text)
+
+ def split_chunks(self, batch):
+ # return batch pairs of indices
+ result = []
+ indices = []
+ for tokens in batch:
+ start = len(result)
+ num_token = len(tokens)
+ if num_token <= self.chunk_size:
+ result.append(tokens)
+ elif num_token > self.chunk_size and num_token < (self.chunk_size * 2 - self.overlap_size):
+ split_idx = (num_token + self.overlap_size + 1) // 2
+ result.append(tokens[:split_idx])
+ result.append(tokens[split_idx - self.overlap_size :])
+ else:
+ for i in range(0, num_token - self.overlap_size, self.stride):
+ result.append(tokens[i : i + self.chunk_size])
+
+ indices.append((start, len(result)))
+
+ return result, indices
+
+ def check_alnum(self, s):
+ if len(s) < 2:
+ return False
+ return not (s.isalpha() or s.isdigit())
+
+ def apply_chunk_merging(self, tokens, next_tokens):
+ # Return next tokens if current tokens list is empty
+ if not tokens:
+ return next_tokens
+
+ source_token_idx = []
+ target_token_idx = []
+ source_tokens = []
+ target_tokens = []
+ num_keep = self.overlap_size - self.min_words_cut
+ i = 0
+ while len(source_token_idx) < self.overlap_size and -i < len(tokens):
+ i -= 1
+ if tokens[i] not in self.punc_dict:
+ source_token_idx.insert(0, i)
+ source_tokens.insert(0, tokens[i].lower())
+
+ i = 0
+ while len(target_token_idx) < self.overlap_size and i < len(next_tokens):
+ if next_tokens[i] not in self.punc_dict:
+ target_token_idx.append(i)
+ target_tokens.append(next_tokens[i].lower())
+ i += 1
+
+ matcher = SequenceMatcher(None, source_tokens, target_tokens)
+ diffs = list(matcher.get_opcodes())
+
+ for diff in diffs:
+ tag, i1, i2, j1, j2 = diff
+ if tag == "equal":
+ if i1 >= num_keep:
+ tail_idx = source_token_idx[i1]
+ head_idx = target_token_idx[j1]
+ break
+ elif i2 > num_keep:
+ tail_idx = source_token_idx[num_keep]
+ head_idx = target_token_idx[j2 - i2 + num_keep]
+ break
+ elif tag == "delete" and i1 == 0:
+ num_keep += i2 // 2
+
+ tokens = tokens[:tail_idx] + next_tokens[head_idx:]
+ return tokens
+
+ def merge_chunks(self, batch):
+ result = []
+ if len(batch) == 1 or self.overlap_size == 0:
+ for sub_tokens in batch:
+ result.extend(sub_tokens)
+ else:
+ for _, sub_tokens in enumerate(batch):
+ try:
+ result = self.apply_chunk_merging(result, sub_tokens)
+ except Exception as e:
+ print(e)
+
+ result = " ".join(result)
+ return result
+
+ def predict(self, batches):
+ t11 = time()
+ predictions = []
+ for batch, model in zip(batches, self.models):
+ batch = batch.to(self.device)
+ with torch.no_grad():
+ prediction = model.forward(**batch)
+ predictions.append(prediction)
+
+ preds, idx, error_probs = self._convert(predictions)
+ t55 = time()
+ if self.log:
+ print(f"Inference time {t55 - t11}")
+ return preds, idx, error_probs
+
+ def get_token_action(self, token, index, prob, sugg_token):
+ """Get lost of suggested actions for token."""
+ # cases when we don't need to do anything
+ if prob < self.min_error_probability or sugg_token in [UNK, PAD, '$KEEP']:
+ return None
+
+ if sugg_token.startswith('$REPLACE_') or sugg_token.startswith('$TRANSFORM_') or sugg_token == '$DELETE':
+ start_pos = index
+ end_pos = index + 1
+ elif sugg_token.startswith("$APPEND_") or sugg_token.startswith("$MERGE_"):
+ start_pos = index + 1
+ end_pos = index + 1
+
+ if sugg_token == "$DELETE":
+ sugg_token_clear = ""
+ elif sugg_token.startswith('$TRANSFORM_') or sugg_token.startswith("$MERGE_"):
+ sugg_token_clear = sugg_token[:]
+ else:
+ sugg_token_clear = sugg_token[sugg_token.index('_') + 1 :]
+
+ return start_pos - 1, end_pos - 1, sugg_token_clear, prob
+
+ def preprocess(self, token_batch):
+ seq_lens = [len(sequence) for sequence in token_batch if sequence]
+ if not seq_lens:
+ return []
+ max_len = min(max(seq_lens), self.max_len)
+ batches = []
+ for indexer in self.indexers:
+ token_batch = [[START_TOKEN] + sequence[:max_len] for sequence in token_batch]
+ batch = indexer(
+ token_batch,
+ return_tensors="pt",
+ padding=True,
+ is_split_into_words=True,
+ truncation=True,
+ add_special_tokens=False,
+ )
+ offset_batch = []
+ for i in range(len(token_batch)):
+ word_ids = batch.word_ids(batch_index=i)
+ offsets = [0]
+ for i in range(1, len(word_ids)):
+ if word_ids[i] != word_ids[i - 1]:
+ offsets.append(i)
+ offset_batch.append(torch.LongTensor(offsets))
+
+ batch["input_offsets"] = torch.nn.utils.rnn.pad_sequence(
+ offset_batch, batch_first=True, padding_value=0
+ ).to(torch.long)
+
+ batches.append(batch)
+
+ return batches
+
+ def _convert(self, data):
+ all_class_probs = torch.zeros_like(data[0]['logits'])
+ error_probs = torch.zeros_like(data[0]['max_error_probability'])
+ for output, weight in zip(data, self.model_weights):
+ class_probabilities_labels = torch.softmax(output['logits'], dim=-1)
+ all_class_probs += weight * class_probabilities_labels / sum(self.model_weights)
+ class_probabilities_d = torch.softmax(output['detect_logits'], dim=-1)
+ error_probs_d = class_probabilities_d[:, :, self.incorr_index]
+ incorr_prob = torch.max(error_probs_d, dim=-1)[0]
+ error_probs += weight * incorr_prob / sum(self.model_weights)
+
+ max_vals = torch.max(all_class_probs, dim=-1)
+ probs = max_vals[0].tolist()
+ idx = max_vals[1].tolist()
+ return probs, idx, error_probs.tolist()
+
+ def update_final_batch(self, final_batch, pred_ids, pred_batch, prev_preds_dict):
+ new_pred_ids = []
+ total_updated = 0
+ for i, orig_id in enumerate(pred_ids):
+ orig = final_batch[orig_id]
+ pred = pred_batch[i]
+ prev_preds = prev_preds_dict[orig_id]
+ if orig != pred and pred not in prev_preds:
+ final_batch[orig_id] = pred
+ new_pred_ids.append(orig_id)
+ prev_preds_dict[orig_id].append(pred)
+ total_updated += 1
+ elif orig != pred and pred in prev_preds:
+ # update final batch, but stop iterations
+ final_batch[orig_id] = pred
+ total_updated += 1
+ else:
+ continue
+ return final_batch, new_pred_ids, total_updated
+
+ def postprocess_batch(self, batch, all_probabilities, all_idxs, error_probs):
+ all_results = []
+ noop_index = self.vocab.get_token_index("$KEEP", "labels")
+ for tokens, probabilities, idxs, error_prob in zip(batch, all_probabilities, all_idxs, error_probs):
+ length = min(len(tokens), self.max_len)
+ edits = []
+
+ # skip whole sentences if there no errors
+ if max(idxs) == 0:
+ all_results.append(tokens)
+ continue
+
+ # skip whole sentence if probability of correctness is not high
+ if error_prob < self.min_error_probability:
+ all_results.append(tokens)
+ continue
+
+ for i in range(length + 1):
+ # because of START token
+ if i == 0:
+ token = START_TOKEN
+ else:
+ token = tokens[i - 1]
+ # skip if there is no error
+ if idxs[i] == noop_index:
+ continue
+
+ sugg_token = self.vocab.get_token_from_index(idxs[i], namespace='labels')
+ action = self.get_token_action(token, i, probabilities[i], sugg_token)
+ if not action:
+ continue
+
+ edits.append(action)
+ all_results.append(get_target_sent_by_edits(tokens, edits))
+ return all_results
+
+ def handle_batch(self, full_batch, merge_punc=True):
+ """
+ Handle batch of requests.
+ """
+ if self.split_chunk:
+ full_batch, indices = self.split_chunks(full_batch)
+ else:
+ indices = None
+ final_batch = full_batch[:]
+ batch_size = len(full_batch)
+ prev_preds_dict = {i: [final_batch[i]] for i in range(len(final_batch))}
+ short_ids = [i for i in range(len(full_batch)) if len(full_batch[i]) < self.min_len]
+ pred_ids = [i for i in range(len(full_batch)) if i not in short_ids]
+ total_updates = 0
+
+ for n_iter in range(self.iterations):
+ orig_batch = [final_batch[i] for i in pred_ids]
+
+ sequences = self.preprocess(orig_batch)
+
+ if not sequences:
+ break
+ probabilities, idxs, error_probs = self.predict(sequences)
+
+ pred_batch = self.postprocess_batch(orig_batch, probabilities, idxs, error_probs)
+ if self.log:
+ print(f"Iteration {n_iter + 1}. Predicted {round(100*len(pred_ids)/batch_size, 1)}% of sentences.")
+
+ final_batch, pred_ids, cnt = self.update_final_batch(final_batch, pred_ids, pred_batch, prev_preds_dict)
+ total_updates += cnt
+
+ if not pred_ids:
+ break
+ if self.split_chunk:
+ final_batch = [self.merge_chunks(final_batch[start:end]) for (start, end) in indices]
+ else:
+ final_batch = [" ".join(x) for x in final_batch]
+ if merge_punc:
+ final_batch = [re.sub(r'\s+(%s)' % self.punc_str, r'\1', x) for x in final_batch]
+
+ return final_batch
\ No newline at end of file
diff --git a/whisper_pipeline/gector/modeling_seq2labels.py b/whisper_pipeline/gector/modeling_seq2labels.py
new file mode 100644
index 0000000000000000000000000000000000000000..0ed970120d929d3e4eacf014887bb2f54203c737
--- /dev/null
+++ b/whisper_pipeline/gector/modeling_seq2labels.py
@@ -0,0 +1,124 @@
+from dataclasses import dataclass
+from typing import Optional, Tuple, Union
+from torch import nn
+from torch.nn import CrossEntropyLoss
+from transformers import AutoConfig, AutoModel, BertPreTrainedModel
+from transformers.modeling_outputs import ModelOutput
+
+import torch
+
+
+def get_range_vector(size: int, device: int) -> torch.Tensor:
+ """
+ Returns a range vector with the desired size, starting at 0. The CUDA implementation
+ is meant to avoid copy data from CPU to GPU.
+ """
+ return torch.arange(0, size, dtype=torch.long, device=device)
+
+@dataclass
+class Seq2LabelsOutput(ModelOutput):
+ loss: Optional[torch.FloatTensor] = None
+ logits: torch.FloatTensor = None
+ detect_logits: torch.FloatTensor = None
+ hidden_states: Optional[Tuple[torch.FloatTensor]] = None
+ attentions: Optional[Tuple[torch.FloatTensor]] = None
+ max_error_probability: Optional[torch.FloatTensor] = None
+
+
+class Seq2LabelsModel(BertPreTrainedModel):
+
+ _keys_to_ignore_on_load_unexpected = [r"pooler"]
+
+ def __init__(self, config):
+ super().__init__(config)
+ self.num_labels = config.num_labels
+ self.num_detect_classes = config.num_detect_classes
+ self.label_smoothing = config.label_smoothing
+
+ if config.load_pretrained:
+ self.bert = AutoModel.from_pretrained(config.pretrained_name_or_path)
+ bert_config = self.bert.config
+ else:
+ bert_config = AutoConfig.from_pretrained(config.pretrained_name_or_path)
+ self.bert = AutoModel.from_config(bert_config)
+
+ if config.special_tokens_fix:
+ try:
+ vocab_size = self.bert.embeddings.word_embeddings.num_embeddings
+ except AttributeError:
+ # reserve more space
+ vocab_size = self.bert.word_embedding.num_embeddings + 5
+ self.bert.resize_token_embeddings(vocab_size + 1)
+
+ predictor_dropout = config.predictor_dropout if config.predictor_dropout is not None else 0.0
+ self.dropout = nn.Dropout(predictor_dropout)
+ self.classifier = nn.Linear(bert_config.hidden_size, config.vocab_size)
+ self.detector = nn.Linear(bert_config.hidden_size, config.num_detect_classes)
+
+ # Initialize weights and apply final processing
+ self.post_init()
+
+ def forward(
+ self,
+ input_ids: Optional[torch.Tensor] = None,
+ input_offsets: Optional[torch.Tensor] = None,
+ attention_mask: Optional[torch.Tensor] = None,
+ token_type_ids: Optional[torch.Tensor] = None,
+ position_ids: Optional[torch.Tensor] = None,
+ head_mask: Optional[torch.Tensor] = None,
+ inputs_embeds: Optional[torch.Tensor] = None,
+ labels: Optional[torch.Tensor] = None,
+ d_tags: Optional[torch.Tensor] = None,
+ output_attentions: Optional[bool] = None,
+ output_hidden_states: Optional[bool] = None,
+ return_dict: Optional[bool] = None,
+ ) -> Union[Tuple[torch.Tensor], Seq2LabelsOutput]:
+ r"""
+ labels (`torch.LongTensor` of shape `(batch_size, sequence_length)`, *optional*):
+ Labels for computing the token classification loss. Indices should be in `[0, ..., config.num_labels - 1]`.
+ """
+ return_dict = return_dict if return_dict is not None else self.config.use_return_dict
+
+ outputs = self.bert(
+ input_ids,
+ attention_mask=attention_mask,
+ token_type_ids=token_type_ids,
+ position_ids=position_ids,
+ head_mask=head_mask,
+ inputs_embeds=inputs_embeds,
+ output_attentions=output_attentions,
+ output_hidden_states=output_hidden_states,
+ return_dict=return_dict,
+ )
+
+ sequence_output = outputs[0]
+
+ if input_offsets is not None:
+ # offsets is (batch_size, d1, ..., dn, orig_sequence_length)
+ range_vector = get_range_vector(input_offsets.size(0), device=sequence_output.device).unsqueeze(1)
+ # selected embeddings is also (batch_size * d1 * ... * dn, orig_sequence_length)
+ sequence_output = sequence_output[range_vector, input_offsets]
+
+ logits = self.classifier(self.dropout(sequence_output))
+ logits_d = self.detector(sequence_output)
+
+ loss = None
+ if labels is not None and d_tags is not None:
+ loss_labels_fct = CrossEntropyLoss(label_smoothing=self.label_smoothing)
+ loss_d_fct = CrossEntropyLoss()
+ loss_labels = loss_labels_fct(logits.view(-1, self.num_labels), labels.view(-1))
+ loss_d = loss_d_fct(logits_d.view(-1, self.num_detect_classes), d_tags.view(-1))
+ loss = loss_labels + loss_d
+
+ if not return_dict:
+ output = (logits, logits_d) + outputs[2:]
+ return ((loss,) + output) if loss is not None else output
+
+ return Seq2LabelsOutput(
+ loss=loss,
+ logits=logits,
+ detect_logits=logits_d,
+ hidden_states=outputs.hidden_states,
+ attentions=outputs.attentions,
+ max_error_probability=torch.ones(logits.size(0), device=logits.device),
+ )
diff --git a/whisper_pipeline/gector/utils.py b/whisper_pipeline/gector/utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..af4dc55eb8eb364bf7da9dfd08170b422ce2166b
--- /dev/null
+++ b/whisper_pipeline/gector/utils.py
@@ -0,0 +1,233 @@
+import os
+from pathlib import Path
+import re
+
+
+VOCAB_DIR = Path(__file__).resolve().parent
+PAD = "@@PADDING@@"
+UNK = "@@UNKNOWN@@"
+START_TOKEN = "$START"
+SEQ_DELIMETERS = {"tokens": " ", "labels": "SEPL|||SEPR", "operations": "SEPL__SEPR"}
+
+
+def get_verb_form_dicts():
+ path_to_dict = os.path.join(VOCAB_DIR, "verb-form-vocab.txt")
+ encode, decode = {}, {}
+ with open(path_to_dict, encoding="utf-8") as f:
+ for line in f:
+ words, tags = line.split(":")
+ word1, word2 = words.split("_")
+ tag1, tag2 = tags.split("_")
+ decode_key = f"{word1}_{tag1}_{tag2.strip()}"
+ if decode_key not in decode:
+ encode[words] = tags
+ decode[decode_key] = word2
+ return encode, decode
+
+
+ENCODE_VERB_DICT, DECODE_VERB_DICT = get_verb_form_dicts()
+
+
+def get_target_sent_by_edits(source_tokens, edits):
+ target_tokens = source_tokens[:]
+ shift_idx = 0
+ for edit in edits:
+ start, end, label, _ = edit
+ target_pos = start + shift_idx
+ if start < 0:
+ continue
+ elif len(target_tokens) > target_pos:
+ source_token = target_tokens[target_pos]
+ else:
+ source_token = ""
+ if label == "":
+ del target_tokens[target_pos]
+ shift_idx -= 1
+ elif start == end:
+ word = label.replace("$APPEND_", "")
+ # Avoid appending same token twice
+ if (target_pos < len(target_tokens) and target_tokens[target_pos] == word) or (
+ target_pos > 0 and target_tokens[target_pos - 1] == word
+ ):
+ continue
+ target_tokens[target_pos:target_pos] = [word]
+ shift_idx += 1
+ elif label.startswith("$TRANSFORM_"):
+ word = apply_reverse_transformation(source_token, label)
+ if word is None:
+ word = source_token
+ target_tokens[target_pos] = word
+ elif start == end - 1:
+ word = label.replace("$REPLACE_", "")
+ target_tokens[target_pos] = word
+ elif label.startswith("$MERGE_"):
+ target_tokens[target_pos + 1 : target_pos + 1] = [label]
+ shift_idx += 1
+
+ return replace_merge_transforms(target_tokens)
+
+
+def replace_merge_transforms(tokens):
+ if all(not x.startswith("$MERGE_") for x in tokens):
+ return tokens
+ if tokens[0].startswith("$MERGE_"):
+ tokens = tokens[1:]
+ if tokens[-1].startswith("$MERGE_"):
+ tokens = tokens[:-1]
+
+ target_line = " ".join(tokens)
+ target_line = target_line.replace(" $MERGE_HYPHEN ", "-")
+ target_line = target_line.replace(" $MERGE_SPACE ", "")
+ target_line = re.sub(r'([\.\,\?\:]\s+)+', r'\1', target_line)
+ return target_line.split()
+
+
+def convert_using_case(token, smart_action):
+ if not smart_action.startswith("$TRANSFORM_CASE_"):
+ return token
+ if smart_action.endswith("LOWER"):
+ return token.lower()
+ elif smart_action.endswith("UPPER"):
+ return token.upper()
+ elif smart_action.endswith("CAPITAL"):
+ return token.capitalize()
+ elif smart_action.endswith("CAPITAL_1"):
+ return token[0] + token[1:].capitalize()
+ elif smart_action.endswith("UPPER_-1"):
+ return token[:-1].upper() + token[-1]
+ else:
+ return token
+
+
+def convert_using_verb(token, smart_action):
+ key_word = "$TRANSFORM_VERB_"
+ if not smart_action.startswith(key_word):
+ raise Exception(f"Unknown action type {smart_action}")
+ encoding_part = f"{token}_{smart_action[len(key_word):]}"
+ decoded_target_word = decode_verb_form(encoding_part)
+ return decoded_target_word
+
+
+def convert_using_split(token, smart_action):
+ key_word = "$TRANSFORM_SPLIT"
+ if not smart_action.startswith(key_word):
+ raise Exception(f"Unknown action type {smart_action}")
+ target_words = token.split("-")
+ return " ".join(target_words)
+
+
+def convert_using_plural(token, smart_action):
+ if smart_action.endswith("PLURAL"):
+ return token + "s"
+ elif smart_action.endswith("SINGULAR"):
+ return token[:-1]
+ else:
+ raise Exception(f"Unknown action type {smart_action}")
+
+
+def apply_reverse_transformation(source_token, transform):
+ if transform.startswith("$TRANSFORM"):
+ # deal with equal
+ if transform == "$KEEP":
+ return source_token
+ # deal with case
+ if transform.startswith("$TRANSFORM_CASE"):
+ return convert_using_case(source_token, transform)
+ # deal with verb
+ if transform.startswith("$TRANSFORM_VERB"):
+ return convert_using_verb(source_token, transform)
+ # deal with split
+ if transform.startswith("$TRANSFORM_SPLIT"):
+ return convert_using_split(source_token, transform)
+ # deal with single/plural
+ if transform.startswith("$TRANSFORM_AGREEMENT"):
+ return convert_using_plural(source_token, transform)
+ # raise exception if not find correct type
+ raise Exception(f"Unknown action type {transform}")
+ else:
+ return source_token
+
+
+# def read_parallel_lines(fn1, fn2):
+# lines1 = read_lines(fn1, skip_strip=True)
+# lines2 = read_lines(fn2, skip_strip=True)
+# assert len(lines1) == len(lines2)
+# out_lines1, out_lines2 = [], []
+# for line1, line2 in zip(lines1, lines2):
+# if not line1.strip() or not line2.strip():
+# continue
+# else:
+# out_lines1.append(line1)
+# out_lines2.append(line2)
+# return out_lines1, out_lines2
+
+
+def read_parallel_lines(fn1, fn2):
+ with open(fn1, encoding='utf-8') as f1, open(fn2, encoding='utf-8') as f2:
+ for line1, line2 in zip(f1, f2):
+ line1 = line1.strip()
+ line2 = line2.strip()
+
+ yield line1, line2
+
+
+def read_lines(fn, skip_strip=False):
+ if not os.path.exists(fn):
+ return []
+ with open(fn, 'r', encoding='utf-8') as f:
+ lines = f.readlines()
+ return [s.strip() for s in lines if s.strip() or skip_strip]
+
+
+def write_lines(fn, lines, mode='w'):
+ if mode == 'w' and os.path.exists(fn):
+ os.remove(fn)
+ with open(fn, encoding='utf-8', mode=mode) as f:
+ f.writelines(['%s\n' % s for s in lines])
+
+
+def decode_verb_form(original):
+ return DECODE_VERB_DICT.get(original)
+
+
+def encode_verb_form(original_word, corrected_word):
+ decoding_request = original_word + "_" + corrected_word
+ decoding_response = ENCODE_VERB_DICT.get(decoding_request, "").strip()
+ if original_word and decoding_response:
+ answer = decoding_response
+ else:
+ answer = None
+ return answer
+
+
+def get_weights_name(transformer_name, lowercase):
+ if transformer_name == 'bert' and lowercase:
+ return 'bert-base-uncased'
+ if transformer_name == 'bert' and not lowercase:
+ return 'bert-base-cased'
+ if transformer_name == 'bert-large' and not lowercase:
+ return 'bert-large-cased'
+ if transformer_name == 'distilbert':
+ if not lowercase:
+ print('Warning! This model was trained only on uncased sentences.')
+ return 'distilbert-base-uncased'
+ if transformer_name == 'albert':
+ if not lowercase:
+ print('Warning! This model was trained only on uncased sentences.')
+ return 'albert-base-v1'
+ if lowercase:
+ print('Warning! This model was trained only on cased sentences.')
+ if transformer_name == 'roberta':
+ return 'roberta-base'
+ if transformer_name == 'roberta-large':
+ return 'roberta-large'
+ if transformer_name == 'gpt2':
+ return 'gpt2'
+ if transformer_name == 'transformerxl':
+ return 'transfo-xl-wt103'
+ if transformer_name == 'xlnet':
+ return 'xlnet-base-cased'
+ if transformer_name == 'xlnet-large':
+ return 'xlnet-large-cased'
+
+ return transformer_name
\ No newline at end of file
diff --git a/whisper_pipeline/gector/verb-form-vocab.txt b/whisper_pipeline/gector/verb-form-vocab.txt
new file mode 100644
index 0000000000000000000000000000000000000000..2ee7e41c2276d48bfed15aff2b92dff8692e16a6
--- /dev/null
+++ b/whisper_pipeline/gector/verb-form-vocab.txt
@@ -0,0 +1,36216 @@
+không_0:VB_VBN
+một_1:VB_VBN
+hai_2:VB_VBN
+ba_3:VB_VBN
+bốn_4:VB_VBN
+năm_5:VB_VBN
+sáu_6:VB_VBN
+bảy_7:VB_VBN
+bẩy_7:VB_VBN
+tám_8:VB_VBN
+chín_9:VB_VBN
+bờ_b:VB_VBN
+bê_b:VB_VBN
+bi_b:VB_VBN
+ci_c:VB_VBN
+si_c:VB_VBN
+xi_c:VB_VBN
+cờ_c:VB_VBN
+cê_c:VB_VBN
+xê_c:VB_VBN
+xe_c:VB_VBN
+sê_c:VB_VBN
+dê_d:VB_VBN
+đê_d:VB_VBN
+đi_d:VB_VBN
+ép_f:VB_VBN
+gờ_g:VB_VBN
+hát_h:VB_VBN
+hắt_h:VB_VBN
+di_j:VB_VBN
+ri_j:VB_VBN
+gi_j:VB_VBN
+ca_k:VB_VBN
+ka_k:VB_VBN
+lờ_l:VB_VBN
+eo_l:VB_VBN
+mờ_m:VB_VBN
+em_m:VB_VBN
+nờ_n:VB_VBN
+en_n:VB_VBN
+pê_p:VB_VBN
+pờ_p:VB_VBN
+quy_q:VB_VBN
+rờ_r:VB_VBN
+er_r:VB_VBN
+ét_s:VB_VBN
+tê_t:VB_VBN
+ti_t:VB_VBN
+tờ_t:VB_VBN
+vê_v:VB_VBN
+vi_v:VB_VBN
+vờ_v:VB_VBN
+ích_x:VB_VBN
+ít_x:VB_VBN
+íc_x:VB_VBN
+dét_z:VB_VBN
+rét_z:VB_VBN
+zét_z:VB_VBN
+bờ_B:VB_VBC
+bê_B:VB_VBC
+bi_B:VB_VBC
+ci_C:VB_VBC
+si_C:VB_VBC
+xi_C:VB_VBC
+cờ_C:VB_VBC
+cê_C:VB_VBC
+xê_C:VB_VBC
+xe_C:VB_VBC
+sê_C:VB_VBC
+dê_D:VB_VBC
+đê_D:VB_VBC
+đi_D:VB_VBC
+ép_F:VB_VBC
+gờ_G:VB_VBC
+hát_H:VB_VBC
+hắt_H:VB_VBC
+di_J:VB_VBC
+ri_J:VB_VBC
+gi_J:VB_VBC
+ca_K:VB_VBC
+ka_K:VB_VBC
+lờ_L:VB_VBC
+eo_L:VB_VBC
+mờ_M:VB_VBC
+em_M:VB_VBC
+nờ_N:VB_VBC
+en_N:VB_VBC
+pê_P:VB_VBC
+pờ_P:VB_VBC
+quy_Q:VB_VBC
+rờ_R:VB_VBC
+er_R:VB_VBC
+ét_S:VB_VBC
+tê_T:VB_VBC
+ti_T:VB_VBC
+tờ_T:VB_VBC
+vê_V:VB_VBC
+vi_V:VB_VBC
+vờ_V:VB_VBC
+ích_X:VB_VBC
+ít_X:VB_VBC
+íc_X:VB_VBC
+dét_Z:VB_VBC
+rét_Z:VB_VBC
+zét_Z:VB_VBC
+aaaa_AAaa:VB_VBN
+aaabb_AAaBb:VB_VBN
+aaafloorsandingdublin_AAAfloorsandingdublin:VB_VBN
+aabbccddee_AaBbCcDdEe:VB_VBN
+aabbccde_AaBbCcDE:VB_VBN
+aabbdd_AaBbDd:VB_VBN
+aabbddeehh_AabbDdEEHh:VB_VBN
+aabbddhh_AaBbDdHh:VB_VBN
+aabbddxy_AaBbDdXY:VB_VBN
+aabbxde_AaBbXDE:VB_VBN
+aabbxdexde_AaBbXDeXdE:VB_VBN
+aabbxdxd_AaBbXdXd:VB_VBN
+aaclean_AAClean:VB_VBN
+aair_aAIR:VB_VBN
+aaj_AaJ:VB_VBN
+aalink_AALink:VB_VBN
+aalock_AALock:VB_VBN
+aamail_AAMail:VB_VBN
+aapanel_aaPanel:VB_VBN
+aapoly_AAPoly:VB_VBN
+aarduino_AArduino:VB_VBN
+aarongillion_AaronGillion:VB_VBN
+aatrox_AAtrox:VB_VBN
+aaum_AAum:VB_VBN
+aaxdeyde_AaXDEYde:VB_VBN
+aaxmxm_AaXMXm:VB_VBN
+aaxmy_aaXMY:VB_VBN
+aayys_AAyys:VB_VBN
+ababxdxd_ABabXDXd:VB_VBN
+ababxdy_ABabXDY:VB_VBN
+abank_ABank:VB_VBN
+abantecart_AbanteCart:VB_VBN
+abbank_ABBank:VB_VBN
+abbankmobile_ABBANKmobile:VB_VBN
+abbd_ABbD:VB_VBN
+abbvie_AbbVie:VB_VBN
+abcdfgh_ABcdFGH:VB_VBN
+abcer_ABCer:VB_VBN
+abcgroup_ABCGroup:VB_VBN
+abcmouse_ABCmouse:VB_VBN
+abcnews_ABCNews:VB_VBN
+abctech_ABCTech:VB_VBN
+abcuts_AbCuts:VB_VBN
+abcya_ABCya:VB_VBN
+abdeg_abDEg:VB_VBN
+abeha_AbeHa:VB_VBN
+abell_ABell:VB_VBN
+abemaprime_AbemaPrime:VB_VBN
+abfuco_AbFUCO:VB_VBN
+abgroup_ABgroup:VB_VBN
+abhouse_ABhouse:VB_VBN
+abicc_ABiCC:VB_VBN
+abicollab_AbiCollab:VB_VBN
+abiword_AbiWord:VB_VBN
+aboutphaedra_AboutPhaedra:VB_VBN
+aboutsee_AboutSee:VB_VBN
+abramsxe_AbramsXe:VB_VBN
+abroad_ABroad:VB_VBN
+abs_AbS:VB_VBN
+abshop_ABshop:VB_VBN
+absoft_ABSoft:VB_VBN
+absolutelayout_AbsoluteLayout:VB_VBN
+abstractfactory_AbstractFactory:VB_VBN
+abstracthandlerexceptionresolver_AbstractHandlerExceptionResolver:VB_VBN
+abstractjpapersistable_AbstractJpaPersistable:VB_VBN
+abstractset_AbstractSet:VB_VBN
+abstractshare_AbstractShare:VB_VBN
+abstractsocial_AbstractSocial:VB_VBN
+abudhabi_AbuDhabi:VB_VBN
+abvietfrance_ABVietFrance:VB_VBN
+abxde_abXde:VB_VBN
+abxdefaultdeeplinkactivity_AbxDefaultDeeplinkActivity:VB_VBN
+abyssrium_AbyssRium:VB_VBN
+abzesolar_AbzeSolar:VB_VBN
+acapulcoadmin_AcapulcoAdmin:VB_VBN
+acbbank_ACBbank:VB_VBN
+acbel_AcBel:VB_VBN
+acbtower_ACBTower:VB_VBN
+acceledent_AcceleDent:VB_VBN
+accentcolor_accentColor:VB_VBN
+accesskey_AccessKey:VB_VBN
+accesspoint_AccessPoint:VB_VBN
+accesspress_AccessPress:VB_VBN
+accessscience_AccessScience:VB_VBN
+accesstrade_AccessTrade:VB_VBN
+accessurl_AccessURL:VB_VBN
+acchelper_AccHelper:VB_VBN
+acchome_AccHome:VB_VBN
+accnet_AccNet:VB_VBN
+accnetba_AccNetBA:VB_VBN
+accorhotels_AccorHotels:VB_VBN
+accountaddress_AccountAddress:VB_VBN
+accountdepidor_AccountDepidor:VB_VBN
+accountgroup_accountGroup:VB_VBN
+accountholder_AccountHolder:VB_VBN
+accountingsuite_AccountingSuite:VB_VBN
+accountlist_accountList:VB_VBN
+accpro_AccPro:VB_VBN
+accradio_AccRadio:VB_VBN
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+zerotype_ZeroType:VB_VBN
+zetamail_ZetaMail:VB_VBN
+zetcode_ZetCode:VB_VBN
+zeze_ZeZe:VB_VBN
+zfill_ZFill:VB_VBN
+zfix_ZFix:VB_VBN
+zfood_ZFood:VB_VBN
+zgold_ZGold:VB_VBN
+zgscan_ZGScan:VB_VBN
+zhaori_ZhaoRi:VB_VBN
+zhengda_ZhengDa:VB_VBN
+zhipat_ZhiPat:VB_VBN
+zhongan_ZhongAn:VB_VBN
+zhongdun_ZhongDun:VB_VBN
+zhongjianti_ZhongJianTi:VB_VBN
+zhongkai_ZHongkai:VB_VBN
+zhoushan_ZhouShan:VB_VBN
+zhouyang_ZhouYang:VB_VBN
+zichao_ZiChao:VB_VBN
+ziczac_ZicZac:VB_VBN
+zigbee_ZigBee:VB_VBN
+zigtech_ZigTech:VB_VBN
+zigzac_ZigZac:VB_VBN
+zigzag_ZigZag:VB_VBN
+zigzagame_ZigZaGame:VB_VBN
+zika_ZiKa:VB_VBN
+ziksolution_ZikSolution:VB_VBN
+zil_ZiL:VB_VBN
+zila_ZiLa:VB_VBN
+zilis_ZIlis:VB_VBN
+zimdaily_ZimDaily:VB_VBN
+zimken_ZimKen:VB_VBN
+zimonline_ZimOnline:VB_VBN
+zinc_ZinC:VB_VBN
+zindenon_zinDENON:VB_VBN
+zing_ZIng:VB_VBN
+zingbet_ZingBet:VB_VBN
+zingerexcess_ZingerExcess:VB_VBN
+zingid_ZingID:VB_VBN
+zingmusic_ZingMuSic:VB_VBN
+zingnews_ZingNews:VB_VBN
+zingplay_ZingPlay:VB_VBN
+zingplayer_ZingPlayer:VB_VBN
+zingplays_ZingPlays:VB_VBN
+zingplaytrong_zingplayTrong:VB_VBN
+zingserver_ZingServer:VB_VBN
+zingspeed_ZingSpeed:VB_VBN
+zingspy_ZingSpy:VB_VBN
+zingtv_ZingTV:VB_VBN
+zingvip_ZingVip:VB_VBN
+zingxu_ZingXu:VB_VBN
+zini_ZiNi:VB_VBN
+zinp_ZinP:VB_VBN
+zinreal_zinREAL:VB_VBN
+zinspa_ZinSpa:VB_VBN
+zintech_ZinTech:VB_VBN
+zinzin_ZinZin:VB_VBN
+zip_ZiP:VB_VBN
+zipboosters_ZipBoosters:VB_VBN
+ziplist_ZipList:VB_VBN
+zipper_ZIpper:VB_VBN
+zippo_ZiPPO:VB_VBN
+ziprealty_ZipRealty:VB_VBN
+ziprecbeaner_ZipRecbeaner:VB_VBN
+ziprecruiter_ZipRecruiter:VB_VBN
+zipshare_ZipShare:VB_VBN
+zipx_ZipX:VB_VBN
+ziq_ZiQ:VB_VBN
+zis_ZiS:VB_VBN
+zkaccess_ZKaccess:VB_VBN
+zkbiolock_ZKBiolock:VB_VBN
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+zkinh_ZKinh:VB_VBN
+zkong_ZKong:VB_VBN
+zksensor_ZKSensor:VB_VBN
+zkswap_ZKSwap:VB_VBN
+zktco_ZKtco:VB_VBN
+zkteco_ZKTeco:VB_VBN
+zkucoin_ZKucoin:VB_VBN
+zland_ZLand:VB_VBN
+zlatanibrahimovic_ZlatanIbrahimovic:VB_VBN
+zled_ZLed:VB_VBN
+zlink_ZLink:VB_VBN
+zlis_zLIS:VB_VBN
+zlpower_ZLPower:VB_VBN
+zmapp_ZMapp:VB_VBN
+znc_ZnC:VB_VBN
+zncl_ZnCl:VB_VBN
+znextnext_ZNextNext:VB_VBN
+znhwethanh_znhWethanh:VB_VBN
+zno_ZnO:VB_VBN
+zns_ZnS:VB_VBN
+zocdoc_ZocDoc:VB_VBN
+zoeetree_ZoeeTree:VB_VBN
+zoekeendate_ZoekEenDate:VB_VBN
+zombieload_ZombieLoad:VB_VBN
+zone_ZOne:VB_VBN
+zonealarm_ZoneAlarm:VB_VBN
+zonedirector_ZoneDirector:VB_VBN
+zoneflex_ZoneFlex:VB_VBN
+zonefollow_ZoneFollow:VB_VBN
+zoneid_ZoneID:VB_VBN
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+zonepro_ZonePRO:VB_VBN
+zongkai_ZongKai:VB_VBN
+zonvip_ZonVip:VB_VBN
+zoodoo_ZooDoo:VB_VBN
+zookeeper_ZooKeeper:VB_VBN
+zookeys_ZooKeys:VB_VBN
+zoomplus_ZoomPlus:VB_VBN
+zoomsounds_ZoomSounds:VB_VBN
+zoomsource_ZoomSource:VB_VBN
+zoomstudio_ZoomStudio:VB_VBN
+zoomtobookmark_ZoomToBookmark:VB_VBN
+zoomtravel_ZoomTravel:VB_VBN
+zoomworld_ZoomWorld:VB_VBN
+zoomx_ZoomX:VB_VBN
+zoomzoom_zoomZoom:VB_VBN
+zoostudio_ZooStudio:VB_VBN
+zooyoo_ZooYoo:VB_VBN
+zoozoo_ZooZoo:VB_VBN
+zopffc_ZoPFFC:VB_VBN
+zowin_ZoWin:VB_VBN
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+zoza_ZoZa:VB_VBN
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+zpos_zPOS:VB_VBN
+zqgame_ZQgame:VB_VBN
+zral_ZrAl:VB_VBN
+zscaler_ZScaler:VB_VBN
+zscamera_ZSCamera:VB_VBN
+zseed_zSEED:VB_VBN
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+zsofa_zSOFA:VB_VBN
+zstack_ZStack:VB_VBN
+zsvsolar_ZSVSolar:VB_VBN
+ztech_ZTech:VB_VBN
+ztelink_ZTELink:VB_VBN
+zugangarbeitfluechtlinge_ZugangArbeitFluechtlinge:VB_VBN
+zugzwang_ZugZwang:VB_VBN
+zulihome_ZuliHome:VB_VBN
+zulnour_ZulNour:VB_VBN
+zulutrade_ZuluTrade:VB_VBN
+zumin_ZuMin:VB_VBN
+zumocast_ZumoCast:VB_VBN
+zumodrive_ZumoDrive:VB_VBN
+zumwhere_ZumWhere:VB_VBN
+zuparestaurant_ZupaRestaurant:VB_VBN
+zuttoride_ZuttoRide:VB_VBN
+zuumviet_ZuumViet:VB_VBN
+zuzu_ZuZu:VB_VBN
+zuzumobile_ZuzuMobile:VB_VBN
+zweb_ZWeb:VB_VBN
+zxing_ZXing:VB_VBN
+zymad_ZymaD:VB_VBN
+zywoo_ZywOo:VB_VBN
+zyxel_ZyXEL:VB_VBN
+zyxvip_zyxVIP:VB_VBN
+zzcapuchino_ZzCapuchino:VB_VBN
+zzuuiii_ZZuuiii:VB_VBN
+zzvenus_zzVENUS:VB_VBN
+zzzsovipzzz_zZzSoVipzZz:VB_VBN
+zzztraveling_zZzTraveling:VB_VBN
diff --git a/whisper_pipeline/gector/vocabulary.py b/whisper_pipeline/gector/vocabulary.py
new file mode 100644
index 0000000000000000000000000000000000000000..c508c7d5e33f7254dd25c7ffe08ec9c76c8011d6
--- /dev/null
+++ b/whisper_pipeline/gector/vocabulary.py
@@ -0,0 +1,277 @@
+import codecs
+from collections import defaultdict
+import logging
+import os
+import re
+from typing import Any, Callable, Dict, Iterable, List, Optional, Set, Union
+from filelock import FileLock
+
+
+logger = logging.getLogger(__name__)
+
+DEFAULT_NON_PADDED_NAMESPACES = ("*tags", "*labels")
+DEFAULT_PADDING_TOKEN = "@@PADDING@@"
+DEFAULT_OOV_TOKEN = "@@UNKNOWN@@"
+NAMESPACE_PADDING_FILE = "non_padded_namespaces.txt"
+_NEW_LINE_REGEX = re.compile(r"\n|\r\n")
+
+
+def namespace_match(pattern: str, namespace: str):
+ """
+ Matches a namespace pattern against a namespace string. For example, `*tags` matches
+ `passage_tags` and `question_tags` and `tokens` matches `tokens` but not
+ `stemmed_tokens`.
+ """
+ if pattern[0] == "*" and namespace.endswith(pattern[1:]):
+ return True
+ elif pattern == namespace:
+ return True
+ return False
+
+
+class _NamespaceDependentDefaultDict(defaultdict):
+ """
+ This is a [defaultdict]
+ (https://docs.python.org/2/library/collections.html#collections.defaultdict) where the
+ default value is dependent on the key that is passed.
+ We use "namespaces" in the :class:`Vocabulary` object to keep track of several different
+ mappings from strings to integers, so that we have a consistent API for mapping words, tags,
+ labels, characters, or whatever else you want, into integers. The issue is that some of those
+ namespaces (words and characters) should have integers reserved for padding and
+ out-of-vocabulary tokens, while others (labels and tags) shouldn't. This class allows you to
+ specify filters on the namespace (the key used in the `defaultdict`), and use different
+ default values depending on whether the namespace passes the filter.
+ To do filtering, we take a set of `non_padded_namespaces`. This is a set of strings
+ that are either matched exactly against the keys, or treated as suffixes, if the
+ string starts with `*`. In other words, if `*tags` is in `non_padded_namespaces` then
+ `passage_tags`, `question_tags`, etc. (anything that ends with `tags`) will have the
+ `non_padded` default value.
+ # Parameters
+ non_padded_namespaces : `Iterable[str]`
+ A set / list / tuple of strings describing which namespaces are not padded. If a namespace
+ (key) is missing from this dictionary, we will use :func:`namespace_match` to see whether
+ the namespace should be padded. If the given namespace matches any of the strings in this
+ list, we will use `non_padded_function` to initialize the value for that namespace, and
+ we will use `padded_function` otherwise.
+ padded_function : `Callable[[], Any]`
+ A zero-argument function to call to initialize a value for a namespace that `should` be
+ padded.
+ non_padded_function : `Callable[[], Any]`
+ A zero-argument function to call to initialize a value for a namespace that should `not` be
+ padded.
+ """
+
+ def __init__(
+ self,
+ non_padded_namespaces: Iterable[str],
+ padded_function: Callable[[], Any],
+ non_padded_function: Callable[[], Any],
+ ) -> None:
+ self._non_padded_namespaces = set(non_padded_namespaces)
+ self._padded_function = padded_function
+ self._non_padded_function = non_padded_function
+ super().__init__()
+
+ def add_non_padded_namespaces(self, non_padded_namespaces: Set[str]):
+ # add non_padded_namespaces which weren't already present
+ self._non_padded_namespaces.update(non_padded_namespaces)
+
+
+class _TokenToIndexDefaultDict(_NamespaceDependentDefaultDict):
+ def __init__(self, non_padded_namespaces: Set[str], padding_token: str, oov_token: str) -> None:
+ super().__init__(non_padded_namespaces, lambda: {padding_token: 0, oov_token: 1}, lambda: {})
+
+
+class _IndexToTokenDefaultDict(_NamespaceDependentDefaultDict):
+ def __init__(self, non_padded_namespaces: Set[str], padding_token: str, oov_token: str) -> None:
+ super().__init__(non_padded_namespaces, lambda: {0: padding_token, 1: oov_token}, lambda: {})
+
+
+class Vocabulary:
+ def __init__(
+ self,
+ counter: Dict[str, Dict[str, int]] = None,
+ min_count: Dict[str, int] = None,
+ max_vocab_size: Union[int, Dict[str, int]] = None,
+ non_padded_namespaces: Iterable[str] = DEFAULT_NON_PADDED_NAMESPACES,
+ pretrained_files: Optional[Dict[str, str]] = None,
+ only_include_pretrained_words: bool = False,
+ tokens_to_add: Dict[str, List[str]] = None,
+ min_pretrained_embeddings: Dict[str, int] = None,
+ padding_token: Optional[str] = DEFAULT_PADDING_TOKEN,
+ oov_token: Optional[str] = DEFAULT_OOV_TOKEN,
+ ) -> None:
+ self._padding_token = padding_token if padding_token is not None else DEFAULT_PADDING_TOKEN
+ self._oov_token = oov_token if oov_token is not None else DEFAULT_OOV_TOKEN
+
+ self._non_padded_namespaces = set(non_padded_namespaces)
+
+ self._token_to_index = _TokenToIndexDefaultDict(
+ self._non_padded_namespaces, self._padding_token, self._oov_token
+ )
+ self._index_to_token = _IndexToTokenDefaultDict(
+ self._non_padded_namespaces, self._padding_token, self._oov_token
+ )
+
+ @classmethod
+ def from_files(
+ cls,
+ directory: Union[str, os.PathLike],
+ padding_token: Optional[str] = DEFAULT_PADDING_TOKEN,
+ oov_token: Optional[str] = DEFAULT_OOV_TOKEN,
+ ) -> "Vocabulary":
+ """
+ Loads a `Vocabulary` that was serialized either using `save_to_files` or inside
+ a model archive file.
+ # Parameters
+ directory : `str`
+ The directory or archive file containing the serialized vocabulary.
+ """
+ logger.info("Loading token dictionary from %s.", directory)
+ padding_token = padding_token if padding_token is not None else DEFAULT_PADDING_TOKEN
+ oov_token = oov_token if oov_token is not None else DEFAULT_OOV_TOKEN
+
+ if not os.path.isdir(directory):
+ raise ValueError(f"{directory} not exist")
+
+ # We use a lock file to avoid race conditions where multiple processes
+ # might be reading/writing from/to the same vocab files at once.
+ with FileLock(os.path.join(directory, ".lock")):
+ with codecs.open(os.path.join(directory, NAMESPACE_PADDING_FILE), "r", "utf-8") as namespace_file:
+ non_padded_namespaces = [namespace_str.strip() for namespace_str in namespace_file]
+
+ vocab = cls(
+ non_padded_namespaces=non_padded_namespaces,
+ padding_token=padding_token,
+ oov_token=oov_token,
+ )
+
+ # Check every file in the directory.
+ for namespace_filename in os.listdir(directory):
+ if namespace_filename == NAMESPACE_PADDING_FILE:
+ continue
+ if namespace_filename.startswith("."):
+ continue
+ namespace = namespace_filename.replace(".txt", "")
+ if any(namespace_match(pattern, namespace) for pattern in non_padded_namespaces):
+ is_padded = False
+ else:
+ is_padded = True
+ filename = os.path.join(directory, namespace_filename)
+ vocab.set_from_file(filename, is_padded, namespace=namespace, oov_token=oov_token)
+
+ return vocab
+
+ @classmethod
+ def empty(cls) -> "Vocabulary":
+ """
+ This method returns a bare vocabulary instantiated with `cls()` (so, `Vocabulary()` if you
+ haven't made a subclass of this object). The only reason to call `Vocabulary.empty()`
+ instead of `Vocabulary()` is if you are instantiating this object from a config file. We
+ register this constructor with the key "empty", so if you know that you don't need to
+ compute a vocabulary (either because you're loading a pre-trained model from an archive
+ file, you're using a pre-trained transformer that has its own vocabulary, or something
+ else), you can use this to avoid having the default vocabulary construction code iterate
+ through the data.
+ """
+ return cls()
+
+ def set_from_file(
+ self,
+ filename: str,
+ is_padded: bool = True,
+ oov_token: str = DEFAULT_OOV_TOKEN,
+ namespace: str = "tokens",
+ ):
+ """
+ If you already have a vocabulary file for a trained model somewhere, and you really want to
+ use that vocabulary file instead of just setting the vocabulary from a dataset, for
+ whatever reason, you can do that with this method. You must specify the namespace to use,
+ and we assume that you want to use padding and OOV tokens for this.
+ # Parameters
+ filename : `str`
+ The file containing the vocabulary to load. It should be formatted as one token per
+ line, with nothing else in the line. The index we assign to the token is the line
+ number in the file (1-indexed if `is_padded`, 0-indexed otherwise). Note that this
+ file should contain the OOV token string!
+ is_padded : `bool`, optional (default=`True`)
+ Is this vocabulary padded? For token / word / character vocabularies, this should be
+ `True`; while for tag or label vocabularies, this should typically be `False`. If
+ `True`, we add a padding token with index 0, and we enforce that the `oov_token` is
+ present in the file.
+ oov_token : `str`, optional (default=`DEFAULT_OOV_TOKEN`)
+ What token does this vocabulary use to represent out-of-vocabulary characters? This
+ must show up as a line in the vocabulary file. When we find it, we replace
+ `oov_token` with `self._oov_token`, because we only use one OOV token across
+ namespaces.
+ namespace : `str`, optional (default=`"tokens"`)
+ What namespace should we overwrite with this vocab file?
+ """
+ if is_padded:
+ self._token_to_index[namespace] = {self._padding_token: 0}
+ self._index_to_token[namespace] = {0: self._padding_token}
+ else:
+ self._token_to_index[namespace] = {}
+ self._index_to_token[namespace] = {}
+ with codecs.open(filename, "r", "utf-8") as input_file:
+ lines = _NEW_LINE_REGEX.split(input_file.read())
+ # Be flexible about having final newline or not
+ if lines and lines[-1] == "":
+ lines = lines[:-1]
+ for i, line in enumerate(lines):
+ index = i + 1 if is_padded else i
+ token = line.replace("@@NEWLINE@@", "\n")
+ if token == oov_token:
+ token = self._oov_token
+ self._token_to_index[namespace][token] = index
+ self._index_to_token[namespace][index] = token
+ if is_padded:
+ assert self._oov_token in self._token_to_index[namespace], "OOV token not found!"
+
+ def add_token_to_namespace(self, token: str, namespace: str = "tokens") -> int:
+ """
+ Adds `token` to the index, if it is not already present. Either way, we return the index of
+ the token.
+ """
+ if not isinstance(token, str):
+ raise ValueError(
+ "Vocabulary tokens must be strings, or saving and loading will break."
+ " Got %s (with type %s)" % (repr(token), type(token))
+ )
+ if token not in self._token_to_index[namespace]:
+ index = len(self._token_to_index[namespace])
+ self._token_to_index[namespace][token] = index
+ self._index_to_token[namespace][index] = token
+ return index
+ else:
+ return self._token_to_index[namespace][token]
+
+ def add_tokens_to_namespace(self, tokens: List[str], namespace: str = "tokens") -> List[int]:
+ """
+ Adds `tokens` to the index, if they are not already present. Either way, we return the
+ indices of the tokens in the order that they were given.
+ """
+ return [self.add_token_to_namespace(token, namespace) for token in tokens]
+
+ def get_token_index(self, token: str, namespace: str = "tokens") -> int:
+ try:
+ return self._token_to_index[namespace][token]
+ except KeyError:
+ try:
+ return self._token_to_index[namespace][self._oov_token]
+ except KeyError:
+ logger.error("Namespace: %s", namespace)
+ logger.error("Token: %s", token)
+ raise KeyError(
+ f"'{token}' not found in vocab namespace '{namespace}', and namespace "
+ f"does not contain the default OOV token ('{self._oov_token}')"
+ )
+
+ def get_token_from_index(self, index: int, namespace: str = "tokens") -> str:
+ return self._index_to_token[namespace][index]
+
+ def get_vocab_size(self, namespace: str = "tokens") -> int:
+ return len(self._token_to_index[namespace])
+
+ def get_namespaces(self) -> Set[str]:
+ return set(self._index_to_token.keys())
diff --git a/whisper_pipeline/gector/vocabulary/.lock b/whisper_pipeline/gector/vocabulary/.lock
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/whisper_pipeline/gector/vocabulary/d_tags.txt b/whisper_pipeline/gector/vocabulary/d_tags.txt
new file mode 100644
index 0000000000000000000000000000000000000000..56e05041ae1bcdee6b1b4c78fda114064a90de7d
--- /dev/null
+++ b/whisper_pipeline/gector/vocabulary/d_tags.txt
@@ -0,0 +1,4 @@
+CORRECT
+INCORRECT
+@@UNKNOWN@@
+@@PADDING@@
diff --git a/whisper_pipeline/gector/vocabulary/labels.txt b/whisper_pipeline/gector/vocabulary/labels.txt
new file mode 100644
index 0000000000000000000000000000000000000000..0de3942a59ce8cc0bf9c403afc3330da042f7dc1
--- /dev/null
+++ b/whisper_pipeline/gector/vocabulary/labels.txt
@@ -0,0 +1,15 @@
+$KEEP
+$TRANSFORM_CASE_CAPITAL
+$APPEND_,
+$APPEND_.
+$TRANSFORM_VERB_VB_VBN
+$TRANSFORM_CASE_UPPER
+$APPEND_:
+$APPEND_?
+$TRANSFORM_VERB_VB_VBC
+$TRANSFORM_CASE_LOWER
+$TRANSFORM_CASE_CAPITAL_1
+$TRANSFORM_CASE_UPPER_-1
+$MERGE_SPACE
+@@UNKNOWN@@
+@@PADDING@@
\ No newline at end of file
diff --git a/whisper_pipeline/gector/vocabulary/non_padded_namespaces.txt b/whisper_pipeline/gector/vocabulary/non_padded_namespaces.txt
new file mode 100644
index 0000000000000000000000000000000000000000..d5dee50c4400824e195a609940a9f9c9abad69b5
--- /dev/null
+++ b/whisper_pipeline/gector/vocabulary/non_padded_namespaces.txt
@@ -0,0 +1,2 @@
+*tags
+*labels
diff --git a/whisper_pipeline/infer.py b/whisper_pipeline/infer.py
new file mode 100644
index 0000000000000000000000000000000000000000..ead780a16e5cfedb000e2ee1786fde0b639ce94c
--- /dev/null
+++ b/whisper_pipeline/infer.py
@@ -0,0 +1,26 @@
+import os
+from pathlib import Path
+from gector import GecBERTModel
+from faster_whisper import WhisperModel, BatchedInferencePipeline
+from transformers.models.whisper.english_normalizer import BasicTextNormalizer
+from text_processing.inverse_normalize import InverseNormalizer
+import time
+inverse_normalizer = InverseNormalizer('vi')
+current_dir = Path(__file__).parent.as_posix()
+whisper_model = WhisperModel("pho_distill_q8", device="auto", compute_type="auto")
+batched_model = BatchedInferencePipeline(model=whisper_model, use_vad_model=True, chunk_length=15)
+gector_model = GecBERTModel(
+ vocab_path=os.path.join(current_dir, "gector/vocabulary"),
+ model_paths=[os.path.join(current_dir, "gector/Model_GECTOR")],
+ split_chunk=True
+)
+normalizer = BasicTextNormalizer()
+
+####start transcriptions#####
+start = time.time()
+segments, info = batched_model.transcribe("HA1.wav", language="vi", batch_size=32)
+transcriptions = [segment.text for segment in segments]
+normalized_transcriptions = [inverse_normalizer.inverse_normalize(normalizer(text)) for text in transcriptions]
+corrected_texts = gector_model(normalized_transcriptions)
+print(''.join(text for text in corrected_texts))
+print(time.time() - start)
diff --git a/whisper_pipeline/pho_distill_q8/config.json b/whisper_pipeline/pho_distill_q8/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..e5047537059bd8f182d9ca64c470201585015187
--- /dev/null
+++ b/whisper_pipeline/pho_distill_q8/config.json
@@ -0,0 +1,239 @@
+{
+ "alignment_heads": [
+ [
+ 5,
+ 3
+ ],
+ [
+ 5,
+ 9
+ ],
+ [
+ 8,
+ 0
+ ],
+ [
+ 8,
+ 4
+ ],
+ [
+ 8,
+ 7
+ ],
+ [
+ 8,
+ 8
+ ],
+ [
+ 9,
+ 0
+ ],
+ [
+ 9,
+ 7
+ ],
+ [
+ 9,
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+ "Ġf un",
+ "j ect",
+ "Ġimport ant",
+ "Ġs ur",
+ "e w",
+ "at es",
+ "Ġ 5",
+ "Ġd i",
+ "Ġm ade",
+ "Ġin s",
+ "Ġas k",
+ "Ġ et",
+ "Ġn um",
+ "Ġc ar",
+ "ĠO kay",
+ "Ġs im",
+ "i k",
+ "Ġl ast",
+ "ĠG o",
+ "Ġm us",
+ "Ġre l",
+ "ul ar",
+ "´ ì",
+ "ĠWe ll",
+ "pe ct",
+ "ĠTh ank",
+ "Ġth ree",
+ "Ã £",
+ "ã ĥ",
+ "Ġin v",
+ "Ġg en",
+ "l ic",
+ "Ġhapp en",
+ "ë Ĭ",
+ "i en",
+ "e ver",
+ "оР²",
+ "Ġst r",
+ "ĠA ll",
+ "Ġin st",
+ "Ġâ Ģ",
+ "Ġde f",
+ "Ġs l",
+ "Ġm ight",
+ "un g",
+ "Ġye ar",
+ "Ġo wn",
+ "Ġke ep",
+ "b ody",
+ "d er",
+ "Ġ ÑĤ",
+ "ĠÐ ´",
+ "Ġan other",
+ "Ġm od",
+ "Ġe v",
+ "Ġgu ys",
+ "Ġab le",
+ "ã o",
+ "qu e",
+ "id ent",
+ "ĠY es",
+ "Ġit s",
+ "Ġpl ace",
+ "Ġpro du",
+ "ar n",
+ "ĠÐ ¼",
+ "Ġre p",
+ "Ġex per",
+ "Ġf am",
+ "it ies",
+ "if ic",
+ "Ġh igh",
+ "i ed",
+ "o ol",
+ "ie w",
+ "е ÑĤ",
+ "re n",
+ "Ġdon e",
+ "Ġ ...",
+ "ëĬ Ķ",
+ "st em",
+ "ĠS e",
+ "Ġbet ter",
+ "c ome",
+ "Ġd el",
+ "Ġt y",
+ "Ġu m",
+ "Ġh o",
+ "ĠA n",
+ "Ġm on",
+ "ing s",
+ "Ġs k",
+ "Ġo b",
+ "c om",
+ "ble m",
+ "op e",
+ "st and",
+ "' d",
+ "ment s",
+ "Ġe le",
+ "ĠI s",
+ "Ġd a",
+ "Ġre g",
+ "le ase",
+ "i ke",
+ "al s",
+ "iz e",
+ "ê °",
+ "Ġc are",
+ "Ġne ver",
+ "ìĿ ´",
+ "es e",
+ "Ġm et",
+ "ol og",
+ "ĠWh en",
+ "u ck",
+ "е ÑĢ",
+ "Ġ é",
+ "Ġd at",
+ "Ã §",
+ "Ġex am",
+ "il ity",
+ "Ġd et",
+ "c ri",
+ "Ġus ed",
+ "ĠD o",
+ "Ġtr ans",
+ "e g",
+ "t en",
+ "Ñ İ",
+ "c us",
+ "Ġsec ond",
+ "Ġb est",
+ "Ġh ard",
+ "Ġ ide",
+ "Ġpro blem",
+ "ê ³",
+ "ĠU n",
+ "Ñ ħ",
+ "Ġ Î",
+ "Ġw atch",
+ "ĠS h",
+ "at ter",
+ "Ġpre t",
+ "Ġd er",
+ "Ġcour se",
+ "Å Ł",
+ "at ive",
+ "ic s",
+ "Ġquest ion",
+ "ut e",
+ "ì Ĺ",
+ "ĠF or",
+ "at her",
+ "Ġc ol",
+ "i end",
+ "Ġ í",
+ "Ġ Z",
+ "Ġdoes n",
+ "ar ch",
+ "Ġinter est",
+ "Ġp ol",
+ "Ġc or",
+ "i ence",
+ "Ġp res",
+ "Ġe ach",
+ "Ġsy stem",
+ "Ġf act",
+ "i el",
+ "ab ly",
+ "Ġ er",
+ "Ġr un",
+ "Ġì Ŀ",
+ "Ġto p",
+ "n er",
+ "Ġth ought",
+ "Ġe as",
+ "i ent",
+ "Ġc re",
+ "Ñ Ī",
+ "Ġcomm un",
+ "y e",
+ "re ady",
+ "ll ow",
+ "Ġevery thing",
+ "om m",
+ "Ġm ed",
+ "ļ Ķ",
+ "Ġc ount",
+ "it s",
+ "Ġcom pl",
+ "h ip",
+ "Ù Ħ",
+ "o ok",
+ "Ġto get",
+ "Ġtoget her",
+ "am p",
+ "Ġg ame",
+ "Ġal ready",
+ "аР»",
+ "Ġcall ed",
+ "al e",
+ "Å Ĥ",
+ "ĠM y",
+ "Ġunder stand",
+ "Ġd r",
+ "Ġm om",
+ "it ed",
+ "оР»",
+ "Ġus ing",
+ "z y",
+ "Ġnum ber",
+ "ãĢ ģ",
+ "c ed",
+ "Ġc le",
+ "н о",
+ "ëĭ ¤",
+ "in ce",
+ "Ġlook ing",
+ "Ġpret ty",
+ "Ġpro b",
+ "ĠS he",
+ "Ġ ve",
+ "Ġget ting",
+ "Ġwe ek",
+ "Ġe ff",
+ "u ff",
+ "a ir",
+ "u es",
+ "er n",
+ "Ġ Q",
+ "ou p",
+ "ent ion",
+ "Ġs ide",
+ "оР¼",
+ "Ġfor m",
+ "Ġb us",
+ "Ġas s",
+ "Ġ ed",
+ "as on",
+ "we en",
+ "âĢ ¦",
+ "Ġt urn",
+ "Ġc ur",
+ "Ġco ll",
+ "Ġd ire",
+ "ĠG od",
+ "Ġ1 0",
+ "Ġe qu",
+ "ĠÐ ±",
+ "Ġop en",
+ "Ġsu ch",
+ "ir d",
+ "аРº",
+ "Ġe ar",
+ "Ä Ļ",
+ "g an",
+ "Ġpart ic",
+ "Ġfr iend",
+ "Ġex p",
+ "Ġex t",
+ "Ġh ome",
+ "Ġw ater",
+ "ĠO n",
+ "ÑĤ ÑĮ",
+ "or k",
+ "Ġп ÑĢ",
+ "Ġmo ve",
+ "n ess",
+ "en se",
+ "h o",
+ "Ġch ar",
+ "c o",
+ "in s",
+ "Ġb oth",
+ "Ġ1 9",
+ "Ġg ra",
+ "Ġbet ween",
+ "á »",
+ "Ġì ķ",
+ "as h",
+ "ĠR e",
+ "a i",
+ "al th",
+ "u res",
+ "em ber",
+ "Ġa v",
+ "Ġ ver",
+ "Ã ª",
+ "one y",
+ "Ġth ank",
+ "Ġmay be",
+ "u c",
+ "im e",
+ "ê³ ł",
+ "Ġa way",
+ "Ġn ame",
+ "ou se",
+ "Ġac c",
+ "Ġmus ic",
+ "Ġch ange",
+ "Ġp ass",
+ "g er",
+ "Ġbu ild",
+ "Ġv al",
+ "in ess",
+ "an y",
+ "Ġfe w",
+ "´ ë",
+ "t a",
+ "Ġl ist",
+ "Ã ¥",
+ "Ġo ld",
+ "Ġì ŀ",
+ "Ġs ort",
+ "Ġme m",
+ "Ġc a",
+ "ce pt",
+ "Ġgen er",
+ "Ġye ah",
+ "Ġwh ile",
+ "Ġany thing",
+ "r ic",
+ "gr am",
+ "Ġe in",
+ "c y",
+ "ur ing",
+ "ĠD e",
+ "Ġp ower",
+ "Ġcom ing",
+ "Ġwor d",
+ "Ġ- -",
+ "Ġbel ie",
+ "Ġf ound",
+ "t o",
+ "Ð ¿",
+ "Ġme ans",
+ "Ġin form",
+ "Ġ Ø",
+ "Ġ Ñĩ",
+ "Ġsm all",
+ "00 0",
+ "Ġc ame",
+ "Ġ íķ",
+ "w h",
+ "Ġwork ing",
+ "Ġexam ple",
+ "Ġp os",
+ "Ġde p",
+ "ê ²",
+ "ä º",
+ "ot e",
+ "Ġde m",
+ "ì §",
+ "t s",
+ "Ġv ar",
+ "a ut",
+ "Ġt ri",
+ "ch n",
+ "Ġhe ad",
+ "Ġwho le",
+ "× Ļ",
+ "z e",
+ "Ġtry ing",
+ "Ġt em",
+ "Ġc ou",
+ "et s",
+ "Ġ 6",
+ "Ġf il",
+ "vel op",
+ "Ġc ase",
+ "à ¯",
+ "Ġprob ably",
+ "Ġo kay",
+ "Ġpl an",
+ "Ġs it",
+ "Ġsch ool",
+ "ĠTh en",
+ "¸ ë",
+ "m e",
+ "Ġpro cess",
+ "Ġf ar",
+ "Ġre ad",
+ "Ġp oss",
+ "Ġb re",
+ "Ġso l",
+ "ic ht",
+ "Ġsupp ort",
+ "ĠT o",
+ "ert ain",
+ "Ġstart ed",
+ "Ġc ap",
+ "Ġle ft",
+ "Ġdat a",
+ "Ġtim es",
+ "еР»",
+ "Ġwant ed",
+ "а н",
+ "Ġtalk ing",
+ "Ġis t",
+ "Ġha ving",
+ "um p",
+ "Ġcont in",
+ "Ġsu b",
+ "ĠÐ ·",
+ "p r",
+ "ëĭ Ī",
+ "in a",
+ "Å ¼",
+ "Ġc reat",
+ "od e",
+ "× ķ",
+ "æ ĺ",
+ "! !",
+ "Ġt erm",
+ "is m",
+ "оР´",
+ "ĠBe cause",
+ "Ġw ent",
+ "id er",
+ "Ġpro v",
+ "Ġch ild",
+ "Ġd en",
+ "Ġl ight",
+ "b r",
+ "³ о",
+ "o h",
+ "Ġbo ok",
+ "Ġ Ù",
+ "ut ion",
+ "ĠJ ust",
+ "en e",
+ "Ġf our",
+ "Ġv is",
+ "ê° Ģ",
+ "Ġh ope",
+ "Ġmak ing",
+ "ĠL e",
+ "ì ķ",
+ "Ġo pp",
+ "a u",
+ "Ġm oney",
+ "Ġpro gram",
+ "Ã ¨",
+ "Ġst and",
+ "I N",
+ "Ġs ign",
+ "Ġle arn",
+ "Ã ł",
+ "ĠD on",
+ "Ġte am",
+ "Ġн а",
+ "l ud",
+ "Ġre st",
+ "ic es",
+ "æ ľ",
+ "Ġ ÑĢ",
+ "Ġa ut",
+ "Ġle ad",
+ "ation al",
+ "d e",
+ "g y",
+ "Ġn ice",
+ "Ġd as",
+ "Ġd ist",
+ "Ġh um",
+ "ĠO ne",
+ "æ Ī",
+ "Ġcom es",
+ "Ġj o",
+ "Ġc ent",
+ "Ġex pl",
+ "Ġm ark",
+ "re en",
+ "l ed",
+ "g in",
+ "ì ļĶ",
+ "Ġle vel",
+ "Ġcon f",
+ "us h",
+ "Ġde velop",
+ "Ġt est",
+ "en g",
+ "v ious",
+ "at ure",
+ "еР¼",
+ "re t",
+ "Ġj e",
+ "Ġst uff",
+ "Ġcl ass",
+ "ow s",
+ "Ġê ·",
+ "Ġs i",
+ "Ġl es",
+ "ro p",
+ "ç ļ",
+ "Ġp or",
+ "Ġw ar",
+ "ìĹ IJ",
+ "Ġevery one",
+ "Ġg e",
+ "Ġche ck",
+ "ot t",
+ "Ġs ing",
+ "Ġar t",
+ "Ġfo llow",
+ "Ġ20 1",
+ "ĠF r",
+ "a is",
+ "ì ĸ",
+ "Î ±",
+ "å °",
+ "ĠÃ ł",
+ "im es",
+ "Ġre t",
+ "Ġch ang",
+ "Ġp ub",
+ "Ġin f",
+ "Ġte chn",
+ "ad a",
+ "iv es",
+ "Ġbe h",
+ "æĺ ¯",
+ "Ġlook s",
+ "ãĢ Ĥ",
+ "Ð ·",
+ "ĠWh y",
+ "çļ Ħ",
+ "Ġen ough",
+ "Ġb ra",
+ "it ch",
+ "ä »",
+ "Ġad v",
+ "Ð ±",
+ "Ġwith out",
+ "w er",
+ "mer ic",
+ "d en",
+ "Ġcompl et",
+ "Ġide a",
+ "ter s",
+ "o ck",
+ "Ġdef in",
+ "Ġe ver",
+ "Ġg l",
+ "Ġon ce",
+ "Ġbr ing",
+ "Ġsay ing",
+ "Ġan s",
+ "Ġhe ar",
+ "n ect",
+ "Ġl ess",
+ "g o",
+ "re am",
+ "ad o",
+ "ì ŀ",
+ "Ġm ind",
+ "ent e",
+ "Ġf ull",
+ "Ġb ad",
+ "Ġw om",
+ "Ġsome one",
+ "Ġd u",
+ "Ġw on",
+ "Ġcont ro",
+ "ort un",
+ "Ġhe alth",
+ "Ġch o",
+ "ĠA r",
+ "Ġcon c",
+ "Ġinform ation",
+ "Ġst op",
+ "at t",
+ "at ely",
+ "ä ½",
+ "Ġgr oup",
+ "Ġ Ñĥ",
+ "Ġqu ite",
+ "Ġres p",
+ "E R",
+ "ug ht",
+ "ê ¸",
+ "m an",
+ "iz ed",
+ "ĠB r",
+ "Ġrem ember",
+ "Ġfam ily",
+ "Ġbus iness",
+ "a w",
+ "Ġspe c",
+ "Ġa u",
+ "ĠO r",
+ "Ä ħ",
+ "Ġse en",
+ "Ġl ar",
+ "Ġ 7",
+ "g g",
+ "b ers",
+ "Ġd ra",
+ "Ġmon th",
+ "Ġsay s",
+ "Ġis s",
+ "Ġli ve",
+ "Ġl ine",
+ "Ġmom ent",
+ "Ġex c",
+ "el s",
+ "Ġs ound",
+ "Ġco ol",
+ "Ġlo c",
+ "Ġc ertain",
+ "Ġd ri",
+ "о ÑĤ",
+ "am es",
+ "Ġm ust",
+ "n y",
+ "и ÑĤ",
+ "Ġk id",
+ "Ġinc lud",
+ "ìĿ Ħ",
+ "at or",
+ "Ä Ł",
+ "h a",
+ "are d",
+ "Ġse em",
+ "Ð ¹",
+ "ì Ħ",
+ "Ġel se",
+ "Ġì ł",
+ "ir l",
+ "Ġ 8",
+ "Ġv o",
+ "Ġquest ions",
+ "in es",
+ "e e",
+ "æĪ ij",
+ "ü r",
+ "ĠA meric",
+ "Ġst ory",
+ "Ġser v",
+ "ver n",
+ "ag es",
+ "l and",
+ "ĠâĢ ĵ",
+ "er a",
+ "ĠC an",
+ "Ġp op",
+ "et her",
+ "Ġn a",
+ "Ġor der",
+ "Ġmak es",
+ "Ġs ince",
+ "c on",
+ "ct or",
+ "Ġth ough",
+ "Ġprodu ct",
+ "л и",
+ "Ġle g",
+ "Ġme et",
+ "al f",
+ "Ñģ Ñı",
+ "un ch",
+ "it er",
+ "o ve",
+ "×ķ ×",
+ "i et",
+ "аР¼",
+ "it al",
+ "Ġsu per",
+ "l ing",
+ "Ġp ay",
+ "Ġpar a",
+ "Ġj ob",
+ "ĠH ere",
+ "Ġs w",
+ "k s",
+ "pt ion",
+ "m a",
+ "Ġbelie ve",
+ "¬ ë",
+ "Ġw ait",
+ "оР¹",
+ "Ġun t",
+ "Ġqu ick",
+ "h r",
+ "ĠÑ į",
+ "ĠP ro",
+ "Ġm en",
+ "à ¹",
+ "Ġday s",
+ "Ġgo es",
+ "Ġspe ak",
+ "ĠA t",
+ "em ent",
+ "Ġm iss",
+ "Ġa w",
+ "Ġdes ign",
+ "Ġpro ject",
+ "о ÑĢ",
+ "i j",
+ "ant s",
+ "at s",
+ "ĠCh r",
+ "Ġ 9",
+ "Ġc ut",
+ "Ġre qu",
+ "Ġн е",
+ "ĠN ot",
+ "as ter",
+ "Ġm ill",
+ "Ġpartic ular",
+ "Ġp ie",
+ "Ġstud ents",
+ "Ġf ive",
+ "ou n",
+ "ĠN e",
+ "Ġg i",
+ "Ġp as",
+ "Ġf ree",
+ "ĠS p",
+ "l ich",
+ "Ġpro f",
+ "Ġen g",
+ "Ġpr ot",
+ "ĠL ike",
+ "os ed",
+ "Ġcon nect",
+ "a pp",
+ "Ġë §",
+ "it ing",
+ "Ġb lo",
+ "Ġl os",
+ "ist s",
+ "Ġexper ience",
+ "re nt",
+ "Ġst ay",
+ "Ġfo od",
+ "t on",
+ "ru ct",
+ "Ġh ist",
+ "v iew",
+ "in ing",
+ "m ost",
+ "i vers",
+ "b o",
+ "ãģ Ħ",
+ "ĠT r",
+ "g en",
+ "Ġp lease",
+ "Ġcommun ity",
+ "Ġc e",
+ "A N",
+ "n o",
+ "Ġb ody",
+ "Ġh our",
+ "Ġ vers",
+ "á º",
+ "c er",
+ "Ġê °",
+ "Ġre ason",
+ "ĠR ight",
+ "Ġl ater",
+ "Ï Ħ",
+ "Ġh ouse",
+ "Ġ X",
+ "оР½",
+ "Ġst ate",
+ "f ic",
+ "å ¤",
+ "Å Ľ",
+ "iel d",
+ "Ġp ri",
+ "Ġp ast",
+ "Ġw alk",
+ "olog y",
+ "er ing",
+ "an na",
+ "Ġt er",
+ "Ġho ld",
+ "Ġor gan",
+ "b en",
+ "Î ¿",
+ "ó n",
+ "Ġeff ect",
+ "Ġyour self",
+ "Ġpl us",
+ "a j",
+ "and o",
+ "ur al",
+ "Ġro om",
+ "le ct",
+ "ê² Į",
+ "? \"",
+ "s ide",
+ "Ġbe come",
+ "Ñ Ĩ",
+ "Ġ Â",
+ "o od",
+ "Ġcon st",
+ "Ġn ight",
+ "ut es",
+ "Ð ¶",
+ "Ġbre ak",
+ "Ġp ain",
+ "Ġst ep",
+ "ire d",
+ "Ġnot hing",
+ "Ġunt il",
+ "Ñ ĸ",
+ "аР²",
+ "Ù Ĭ",
+ "Ġd uring",
+ "ì§ Ģ",
+ "l ess",
+ "o ll",
+ "н Ñĭ",
+ "Î ¹",
+ "f ect",
+ "i ver",
+ "ı Ħ",
+ "ith er",
+ "y ing",
+ "Ġbe gin",
+ "×Ļ ×",
+ "iv id",
+ "ĠÃ §",
+ "Ġs al",
+ "Ġt a",
+ "Ġp ot",
+ "Ġ $",
+ "Ġm ar",
+ "Ġcle ar",
+ "Ġf ace",
+ "Ġgr ow",
+ "Ġ *",
+ "Ġins ide",
+ "Ġfriend s",
+ "Ġle ave",
+ "en n",
+ "Ġeas y",
+ "Ġare a",
+ "al ity",
+ "ou d",
+ "Ġe at",
+ "Ù Ĩ",
+ "Ġp ur",
+ "or n",
+ "Ġsa w",
+ "Ġans wer",
+ "Ġfr ont",
+ "Ġbe aut",
+ "¼ ë",
+ "Ġm atter",
+ "Ġs on",
+ "ĠN ew",
+ "Ġres ult",
+ "id es",
+ "ch e",
+ "Ġf ut",
+ "p s",
+ "Ġfo cus",
+ "Ġinterest ing",
+ "å ¥",
+ "Ġa p",
+ "\" .",
+ "Ġcre ate",
+ "о Ñģ",
+ "Ġp ress",
+ "r oss",
+ "Ġp ick",
+ "l ine",
+ "Ġto ok",
+ "ĠM ay",
+ "r ow",
+ "Ġ ich",
+ "ĺ ë",
+ "Ġre f",
+ "Ġm or",
+ "r act",
+ "are nt",
+ "A R",
+ "Ġex act",
+ "Ġsp ace",
+ "w ork",
+ "н и",
+ "Ġb ir",
+ "Ġde v",
+ "Ð ³",
+ "Ġto ld",
+ "Ġpub lic",
+ "ci ally",
+ "Ġv iew",
+ "ĠHe y",
+ "m ed",
+ "ll o",
+ "c c",
+ "Ġf ac",
+ "Ġcou ple",
+ "Ġhe art",
+ "l er",
+ "Ġre ady",
+ "Ġal most",
+ "ar ing",
+ "Ġh alf",
+ "ĠM e",
+ "av or",
+ "i que",
+ "Ġchar ac",
+ "Ġpr act",
+ "O N",
+ "an e",
+ "Ġ il",
+ "н а",
+ "Ġv i",
+ "l ish",
+ "he ad",
+ "Ġle ast",
+ "Ġbas ically",
+ "as ed",
+ "r ight",
+ "Ġy et",
+ "Ġtak ing",
+ "Ġcount ry",
+ "Ġw in",
+ "Ġis n",
+ "Ġposs ible",
+ "Ġc am",
+ "Ġinc re",
+ "Ġp at",
+ "Ġw anna",
+ "Ġcons ider",
+ "Ġab s",
+ "Ġwith in",
+ "Ġhum an",
+ "Ġthink ing",
+ "Ġo h",
+ "¡ ľ",
+ "Ġqu i",
+ "as es",
+ "Ġ 0",
+ "it ely",
+ "ä¸ į",
+ "Ġk ill",
+ "Ġm il",
+ "Ġinv est",
+ "is ter",
+ "Ġsu c",
+ "ion al",
+ "el f",
+ "Ġwh ether",
+ "Ġcontro l",
+ "Ġagain st",
+ "ot s",
+ "ëĭĪ ëĭ¤",
+ "i or",
+ "Ġpres ent",
+ "Ġ ا",
+ "Ġwatch ing",
+ "u be",
+ "er v",
+ "Ġn icht",
+ "Ġgo vern",
+ "ĠTh ese",
+ "Ġ :",
+ "u it",
+ "ug h",
+ "Ġwork s",
+ "o o",
+ "Ġw ir",
+ "Ġa ir",
+ "ĠT e",
+ "аР·",
+ "is ion",
+ "wh ere",
+ "Ġto t",
+ "j oy",
+ "ì ĭ",
+ "Ġv ol",
+ "ĠÐ µ",
+ "Ġcl ose",
+ "ĠA d",
+ "Ñ ī",
+ "in ed",
+ "Ġun a",
+ "Ġê· ¸ë",
+ "° ë",
+ "or ry",
+ "Ġb ro",
+ "Ġfil m",
+ "if t",
+ "2 0",
+ "Ġty pe",
+ "Ġhappen ed",
+ "ĠA m",
+ "Ġg irl",
+ "ĠA re",
+ "ward s",
+ "Ġp our",
+ "Ġcol or",
+ "el t",
+ "а Ñģ",
+ "Ġs ense",
+ "le x",
+ "ĠW ith",
+ "us s",
+ "ri b",
+ "Ġre se",
+ "Ġn orm",
+ "Ġfut ure",
+ "Ġde al",
+ "end ing",
+ "e y",
+ "Ġ x",
+ "er o",
+ "ĠC l",
+ "u k",
+ "Ġwhat ever",
+ "sel ves",
+ "Ġyou ng",
+ "ì Ĭ",
+ "ĠM ar",
+ "ĠChr ist",
+ "Ġgu ess",
+ "Ġper form",
+ "Ġen er",
+ "r on",
+ "Ġh it",
+ "Ġw ond",
+ "Ġdire ct",
+ "ĠE very",
+ "Ġof ten",
+ "Ġf a",
+ "Ġal ong",
+ "Ġcl ick",
+ "ĠL ook",
+ "Ġsit u",
+ "Ġhapp y",
+ "e ad",
+ "Ġag o",
+ "Ġen c",
+ "Ġmy self",
+ "Ġco ver",
+ "оР±",
+ "Ġm id",
+ "Ġc ost",
+ "Ġt en",
+ "ĠS ch",
+ "Ġex pect",
+ "Ġwas n",
+ "Ġstr ong",
+ "if ul",
+ "Ġopp ortun",
+ "in al",
+ "y le",
+ "Ġsh are",
+ "Ġtr ue",
+ "Ġapp ro",
+ "Ġch all",
+ "Ġmin utes",
+ "Ġch ann",
+ "Ġë Ĥ",
+ "Î µ",
+ "l i",
+ "Ġm ess",
+ "or ies",
+ "pe cially",
+ "Ġwr ong",
+ "Ġy es",
+ "Ġì Ĺ",
+ "ir on",
+ "Ġall ow",
+ "Ġsu bs",
+ "Ġf ore",
+ "Ġf ight",
+ "Ġso cial",
+ "Ġc ra",
+ "an a",
+ "Ġa ff",
+ "Ġ ess",
+ "Ġway s",
+ "Ġsh ort",
+ "Ġf all",
+ "Ġla w",
+ "ĠWh o",
+ "Ġen joy",
+ "Ġc al",
+ "Ġac cess",
+ "f e",
+ "Ġn on",
+ "Ġac ross",
+ "er y",
+ "vious ly",
+ "ĠE x",
+ "id ed",
+ "Ġl ink",
+ "ĠP r",
+ "Ġterm s",
+ "ac es",
+ "Ġl and",
+ "az ing",
+ "Ġ1 5",
+ "Ġm ult",
+ "Ġspe cial",
+ "å Ģ",
+ "iv ing",
+ "ìĿ Ģ",
+ "Ġty p",
+ "Ġst e",
+ "Ġ Ä",
+ "Ġfor ward",
+ "å ı",
+ "Ġf re",
+ "å¥ ½",
+ "Ġrese arch",
+ "௠į",
+ "а ÑĤ",
+ "Ġma in",
+ "Ġrec ord",
+ "Ġh u",
+ "Ġdefin itely",
+ "Ġe ither",
+ "Ġlist en",
+ "Ġke y",
+ "Ġmark et",
+ "ĠÑĩ ÑĤо",
+ "iz ation",
+ "Ġvide os",
+ "Ġgu y",
+ "Ġf ig",
+ "Ġst ra",
+ "ĠP l",
+ "ull y",
+ "am os",
+ "Ġm ention",
+ "Ġs ong",
+ "Ġinter n",
+ "r al",
+ "ur s",
+ "Ġh on",
+ "Ġval ue",
+ "Ġb ar",
+ "c le",
+ "оР¶",
+ "Ä ĩ",
+ "ľ ë",
+ "Ġz u",
+ "и м",
+ "ä½ ł",
+ "Ġsing le",
+ "Ġa uch",
+ "cus s",
+ "Ġget s",
+ "Ġsomet imes",
+ "å ¾",
+ "am b",
+ "m m",
+ "c ing",
+ "Ġper fect",
+ "ĠB l",
+ "out h",
+ "ì ł",
+ "Ġs ci",
+ "p ar",
+ "Ġre d",
+ "Ġp ost",
+ "Ġm ot",
+ "Ġele ct",
+ "ĠE u",
+ "it ive",
+ "ĠS ome",
+ "Ġdes cri",
+ "Ġcur rent",
+ "é s",
+ "Ġt re",
+ "ĠE n",
+ "Ġm it",
+ "E N",
+ "Ī ë",
+ "i um",
+ "Ġhe ard",
+ "Ġsim ple",
+ "l ar",
+ "Ġevery body",
+ "il ar",
+ "Ġneed s",
+ "Ġdif fic",
+ "ĠGo od",
+ "um ent",
+ "c ent",
+ "Ġo per",
+ "а ÑĤÑĮ",
+ "et y",
+ "Ġbl ack",
+ "Ġgi ven",
+ "on es",
+ "Ġwe l",
+ "é Ģ",
+ "Ġìķ Ħ",
+ "Ġ3 0",
+ "A T",
+ "Ġst at",
+ "ou ch",
+ "ĠM r",
+ "а ÑĢ",
+ "Ġsh o",
+ "Ġcon d",
+ "× Ķ",
+ "m y",
+ "Ġchild ren",
+ "Ġe u",
+ "еР´",
+ "ìķ Ħ",
+ "ter n",
+ "Ġu h",
+ "Ġh ar",
+ "Ġpr om",
+ "Ġp ull",
+ "re w",
+ "Ġcomp any",
+ "Ġbeaut iful",
+ "ust om",
+ "íķ ĺ",
+ "к и",
+ "Ġst re",
+ "Ġam azing",
+ "ri es",
+ "Ġsuc cess",
+ "Ġm ach",
+ "n ot",
+ "Ġdis cuss",
+ "Ġn at",
+ "¦ ¬",
+ "Ġun e",
+ "Ġdiffic ult",
+ "Ġr is",
+ "Î ½",
+ "Ġc amp",
+ "Ġbu y",
+ "ä¸ Ģ",
+ "Ġma g",
+ "p o",
+ "ĠY our",
+ "Ġbeh ind",
+ "ic a",
+ "ı n",
+ "ĠO K",
+ "Ġl ang",
+ "Ġwom en",
+ "Ġen v",
+ "Ġre ce",
+ "Ġchann el",
+ "i ally",
+ "u le",
+ "Ġ1 2",
+ "th ers",
+ "Ġb ott",
+ "Ġrep ort",
+ "ent ly",
+ "f ully",
+ "T he",
+ "Ġs ent",
+ "Ġev ent",
+ "Ġener gy",
+ "l t",
+ "Ġword s",
+ "ar r",
+ "d le",
+ "Ġa head",
+ "ard s",
+ "Ø ±",
+ "äº Ĩ",
+ "Ġto ol",
+ "con om",
+ "е Ñģ",
+ "Ġexact ly",
+ "Ġf avor",
+ "Ġl ow",
+ "Ġpro per",
+ "Ġìŀ Ī",
+ "Ġ !",
+ "Ġrel ations",
+ "Ġm as",
+ "Ġkid s",
+ "Ġent ire",
+ "ud e",
+ "Ù ħ",
+ "ĠWh ere",
+ "Ġon es",
+ "Ġc ity",
+ "ol ut",
+ "Ġs ix",
+ "ab ility",
+ "ö r",
+ "il i",
+ "ĠE s",
+ "Ġhapp ens",
+ "ain s",
+ "Ġmod el",
+ "Ġp ict",
+ "Ġes pecially",
+ "Ġ1 00",
+ "k t",
+ "Ġso on",
+ "b y",
+ "ro du",
+ "Ġan n",
+ "Ġsubs cri",
+ "ĠQ u",
+ "Ġav ail",
+ "im ent",
+ "Ġv oc",
+ "k a",
+ "Ġ2 00",
+ "ap er",
+ "ĠI nd",
+ "Ġì §",
+ "h or",
+ "į °",
+ "j or",
+ "и л",
+ "Ġs qu",
+ "A U",
+ "ar ning",
+ "ĠÐ ³",
+ "I S",
+ "ĠÐ »",
+ "еР¹",
+ "y es",
+ "å ħ",
+ "ĠÐ Ĵ",
+ "Ġor ig",
+ "оР³Ð¾",
+ "Ġask ed",
+ "il t",
+ "оР³",
+ "Ġcontin ue",
+ "Ġì ĺ",
+ "r am",
+ "Ġo thers",
+ "E S",
+ "oh n",
+ "Ġl ay",
+ "Ġbas ed",
+ "Ġp u",
+ "Ġapp e",
+ "Ġl im",
+ "Ġpro p",
+ "Ģ ë",
+ "m in",
+ "Ġh ot",
+ "ĠL a",
+ "Ġf ast",
+ "Ġprot ect",
+ "Ġam ount",
+ "Ġa qu",
+ "Ġf und",
+ "Ġc ustom",
+ "Ġc ult",
+ "Ġhand s",
+ "Ġha ven",
+ "Ġa ud",
+ "Ġout side",
+ "ĠA fter",
+ "ap s",
+ "Ġan im",
+ "pl oy",
+ "Ġh at",
+ "ĠF irst",
+ "Ġt reat",
+ "Ġe p",
+ "Ġm ater",
+ "Ġbuild ing",
+ "Ġë °",
+ "å IJ",
+ "ìĦ ľ",
+ "z a",
+ "ught er",
+ "ĠP e",
+ "ne y",
+ "et er",
+ "at ic",
+ "Ġed uc",
+ "ê¸ °",
+ "Ġmo v",
+ "ĵ ¤",
+ "am a",
+ "r ation",
+ "Ġs n",
+ "Ù Ī",
+ "Ġs um",
+ "Ġph ot",
+ "ĠÐ Ŀ",
+ "Ġ .",
+ "æľ ī",
+ "Ġfin ish",
+ "itt ing",
+ "å ®",
+ "Ġlar ge",
+ "Ġì ĸ",
+ "Ġwh ite",
+ "ar a",
+ "Ġma is",
+ "ĠH i",
+ "Ġd am",
+ "Ġا ÙĦ",
+ "Ġbo x",
+ "ĠHe llo",
+ "Ġs le",
+ "Ġo pt",
+ "ri ed",
+ "¥ ¼",
+ "Ġact iv",
+ "Ġn ão",
+ "ĠC om",
+ "Ġplay ing",
+ "T h",
+ "Ġavail able",
+ "Ġp ort",
+ "å Ī",
+ "ĠA h",
+ "Ġl as",
+ "Ġear ly",
+ "Ġwond er",
+ "± °",
+ "Ġ1 8",
+ "c ul",
+ "Ġfun ction",
+ "Ġmor ning",
+ "ll e",
+ "i ents",
+ "u x",
+ "Ġc ir",
+ "it ions",
+ "Ġde ep",
+ "Ġpol it",
+ "y or",
+ "m p",
+ "ak ing",
+ "Į ë",
+ "ĠM an",
+ "Ġmill ion",
+ "Ġ /",
+ "Ġind ivid",
+ "Ġp an",
+ "Ġgovern ment",
+ "Ġwr ite",
+ "ĠT od",
+ "am ent",
+ "Ġ Ï",
+ "Ġw ind",
+ "ĠE ng",
+ "ch en",
+ "W h",
+ "ì ľ",
+ "Ġ ident",
+ "ãģ §",
+ "v ent",
+ "ur ch",
+ "Ġh y",
+ "Ġy a",
+ "Ġtr ad",
+ "Ġrelations hip",
+ "Ã º",
+ "Ġd ou",
+ "O R",
+ "Ġs we",
+ "Ġne g",
+ "in ation",
+ "Ġte xt",
+ "i pp",
+ "Ġf ine",
+ "á s",
+ "ĠD r",
+ "ĠC ome",
+ "Ġmonth s",
+ ", \"",
+ "ен и",
+ "Ġhour s",
+ "Ġp od",
+ "ir t",
+ "Ġinv ol",
+ "Ġcoll ect",
+ "Ġau f",
+ "Ġp a",
+ "Ġhist ory",
+ "m b",
+ "if y",
+ "Ġ ?",
+ "Ġbel ow",
+ "as ure",
+ "ab y",
+ "Ġlang u",
+ "Ġan t",
+ "Ġcom b",
+ "at o",
+ "Ġex ist",
+ "Ġë ĭ",
+ "Ġtak es",
+ "Ġcharac ter",
+ "a ff",
+ "Ġf ield",
+ "Ġe conom",
+ "ie f",
+ "Ġpie ce",
+ "å ľ",
+ "Ġre ach",
+ "Ġê ²",
+ "on y",
+ "Ġmater ial",
+ "Ġd ig",
+ "Ġph ys",
+ "Ġimp ro",
+ "Ġsim ilar",
+ "I C",
+ "Ġn et",
+ "y n",
+ "Ġpos ition",
+ "Ã Ł",
+ "Ġb ene",
+ "re ad",
+ "Ġle arning",
+ "um e",
+ "Ġcle an",
+ "ÑĤо ÑĢ",
+ "Ġco ok",
+ "Ġseem s",
+ "Ġo l",
+ "ĠU S",
+ "ĠJ es",
+ "Ġ à®",
+ "ent ial",
+ "ivers ity",
+ "ac y",
+ "Ġ Ñı",
+ "olut ely",
+ "re ct",
+ "ĠP lease",
+ "Ġrep res",
+ "Ġt ouch",
+ "m en",
+ "ĠÐ °",
+ "i ón",
+ "ĠThank s",
+ "Ġan g",
+ "Ġma jor",
+ "Ġit self",
+ "ill s",
+ "\" ,",
+ "i ans",
+ "Ġsc reen",
+ "Ġh or",
+ "Ġknow n",
+ "Ġenv iron",
+ "Ġfin al",
+ "Ġfig ure",
+ "ĠT w",
+ "Ġe yes",
+ "Ġim ag",
+ "Ġsee ing",
+ "Ġha ir",
+ "re m",
+ "Ġapp lic",
+ "end s",
+ "p ut",
+ "Ġnew s",
+ "Ġcomplet ely",
+ "ugh s",
+ "Ġkn ew",
+ "if ied",
+ "ĠJ e",
+ "ĠD id",
+ "Ġsitu ation",
+ "Ġf lo",
+ "m s",
+ "Ġph one",
+ "Ġb all",
+ "d o",
+ "Ġp arent",
+ "Ġs orry",
+ "ur y",
+ "и н",
+ "ip s",
+ "аР´",
+ "Ġinst ead",
+ "Ġhu ge",
+ "Ġt u",
+ "Ġ ãģ",
+ "ĠG r",
+ "Ġdet ail",
+ "ĠÐ Ł",
+ "Ġindivid ual",
+ "Ġf ire",
+ "Ġcl os",
+ "Ġw er",
+ "un e",
+ "Ġrun ning",
+ "Ġcon vers",
+ "Ġrec omm",
+ "Ġcom o",
+ "Ġsome body",
+ "ĠJ ohn",
+ "ĠìĿ ´",
+ "ĠO ur",
+ "pl es",
+ "ĠP h",
+ "Ġan al",
+ "Ġ5 0",
+ "Ġof fer",
+ "Ġ <",
+ "ition al",
+ "g est",
+ "Ġv ous",
+ "l et",
+ "ic y",
+ "Ġfeel ing",
+ "L E",
+ "r os",
+ "Ġth ird",
+ "оРº",
+ "Ġser ies",
+ "ĠAn y",
+ "is ed",
+ "o ld",
+ "Ġdra w",
+ "Ġserv ice",
+ "Ġcan not",
+ "b al",
+ "ãģ Ĩ",
+ "Ġli ving",
+ "ı m",
+ "Ġdiffer ence",
+ "Ġopportun ity",
+ "Ġne ar",
+ "or th",
+ "k en",
+ "Ġloc al",
+ "Ø ª",
+ "ĠC on",
+ "Ġob ject",
+ "Ġd ass",
+ "ãģ Ļ",
+ "IJ ×",
+ "Ġquick ly",
+ "ra ph",
+ "Ġiss ues",
+ "éĢ Ļ",
+ "ĠAmeric an",
+ "Ġpre p",
+ "en ces",
+ "Ġprof ess",
+ "ll ing",
+ "o f",
+ "Ġfo ot",
+ "b re",
+ "Ġus ually",
+ "Ġgener al",
+ "d a",
+ "an ces",
+ "Ġd est",
+ "Ġo cc",
+ "Ġmem bers",
+ "Ġd ans",
+ "Ġequ al",
+ "z t",
+ "Ġbe com",
+ "Ġmo ving",
+ "Ġspec ific",
+ "ÃŃ a",
+ "Ġf ur",
+ "Ġne cess",
+ "Ġcomm on",
+ "Ġatt ack",
+ "ĠÑį ÑĤо",
+ "ĠTod ay",
+ "Ġun s",
+ "ĠG u",
+ "i od",
+ "Ġacc ount",
+ "Ġgra nd",
+ "Ġs elf",
+ "ĠE l",
+ "Ġt ast",
+ "Ġcont ent",
+ "Ġc u",
+ "Ħ ë",
+ "ĠMay be",
+ "ĠJes us",
+ "ore s",
+ "p ort",
+ "© ´",
+ "Ġg ives",
+ "Ġnorm al",
+ "ÑĢ Ñĥ",
+ "Ġimp act",
+ "ä r",
+ "Ġd ies",
+ "Ġl ab",
+ "s h",
+ "i os",
+ "ĠP res",
+ "ĠU nd",
+ "ĠO f",
+ "Ġfin ally",
+ "Ġdo ll",
+ "Ġvoc ê",
+ "p ly",
+ "ĠA g",
+ "Ġtak en",
+ "Ġgr ound",
+ "f ort",
+ "Ġg ave",
+ "ĠIn st",
+ "Ġl ost",
+ "Ġwork ed",
+ "Ġl iter",
+ "Ġiss ue",
+ "Ġind ust",
+ "Ġret urn",
+ "Ġhappen ing",
+ "Ġwant s",
+ "и в",
+ "Ġproblem s",
+ "ĠC ar",
+ "Ŀ ¼",
+ "ĠAl so",
+ "Ġs ize",
+ "Ġob viously",
+ "ĠS u",
+ "ĠS c",
+ "Ġrecomm end",
+ "our ces",
+ "ast ic",
+ ".. ..",
+ "Ġm i",
+ "l ier",
+ "ĠE ven",
+ "ci a",
+ "Ġh ur",
+ "v a",
+ "Ġm ass",
+ "Ġwould n",
+ "un t",
+ "ck s",
+ "Ġf elt",
+ "os p",
+ "l ight",
+ "ол ÑĮ",
+ "n ie",
+ "Ġbott om",
+ "Ġб Ñĭ",
+ "ore d",
+ "is on",
+ "Ġgr ad",
+ "Ġum a",
+ "Ġv a",
+ "Ġì Ĥ",
+ "ress ion",
+ "ul ation",
+ "I D",
+ "id ence",
+ "Ġb ur",
+ "Ġg one",
+ "l u",
+ "ìĸ ´ì",
+ "Ġre du",
+ "Ġj a",
+ "ìĿ ĺ",
+ "it a",
+ "Ġso ft",
+ "Ġç a",
+ "ic o",
+ "er al",
+ "Ã ±",
+ "a f",
+ "Ġpoint s",
+ "g u",
+ "Ġd é",
+ "ap t",
+ "a x",
+ "ĠAl right",
+ "Ġcam era",
+ "Ġa ch",
+ "Ġп о",
+ "Ġse ver",
+ "5 0",
+ "Ġs ie",
+ "Ï ģ",
+ "Ġm al",
+ "Ġcomp ut",
+ "Ġmid dle",
+ "Ġcould n",
+ "m ing",
+ "Ġì ĭ",
+ "ĠH is",
+ "Ġg ames",
+ "Ġint rodu",
+ "Ġc ell",
+ "p or",
+ "Ġsle ep",
+ "Ġë ³",
+ "id ing",
+ "Ġ ou",
+ "Ġde g",
+ "Ġdr ink",
+ "Ġenviron ment",
+ "ĠUn ited",
+ "Ġtalk ed",
+ "Ġcho ose",
+ "Ġj our",
+ "e ge",
+ "ĠM in",
+ "Ġint e",
+ "Ġr ather",
+ "Ġoff ic",
+ "к а",
+ "ac hing",
+ "Ġmention ed",
+ "Ġf ill",
+ "Ġtr ack",
+ "Ġn ie",
+ "Ġ ut",
+ "Ġв Ñĭ",
+ "ib ility",
+ "Ġv ac",
+ "Ġr ad",
+ "Ġp ack",
+ "Ġs end",
+ "ĠD as",
+ "ĠA b",
+ "Ġeng ine",
+ "ãģ Ĺ",
+ "Ġcomp et",
+ "Ã ´",
+ "Ġв Ñģ",
+ "Ġdo or",
+ "Ġlong er",
+ "å° į",
+ "Ġlangu age",
+ "Ġext ra",
+ "pl ay",
+ "Ġwe bs",
+ "um b",
+ "ro om",
+ "ç ľ",
+ "Ġbegin ning",
+ "Ġre fer",
+ "A M",
+ "n en",
+ "ig her",
+ "f ace",
+ "er c",
+ "Ġfor get",
+ "Ġcom ment",
+ "еРº",
+ "л Ñı",
+ "r or",
+ "ż e",
+ "ĠG e",
+ "Ġd ark",
+ "Ġany one",
+ "ant e",
+ "g es",
+ "ìĬ µ",
+ "Ñ ij",
+ "b ed",
+ "j e",
+ "ruct ure",
+ "Ġpr im",
+ "id a",
+ "è ¦",
+ "ãģ ¾",
+ "Ġm ix",
+ "Ġstart ing",
+ "ĠìĿ ´ë",
+ "Ġprov ide",
+ "act ion",
+ "Ġm other",
+ "Ġper iod",
+ "Ġst ick",
+ "ĠYou T",
+ "Ġtechn ology",
+ "ê ¹",
+ "Ġb ed",
+ "Ġg iving",
+ "Ġexpl ain",
+ "z en",
+ "im ate",
+ "Ġrepres ent",
+ "lo ad",
+ "ĠHow ever",
+ "Ġli ves",
+ "ut h",
+ "ir it",
+ "og n",
+ "Ġli k",
+ "Ġresp ons",
+ "Ġpri v",
+ "Ġto m",
+ "ç ão",
+ "i am",
+ "Ġexc ited",
+ "Ġc ard",
+ "gr ound",
+ "Ġ× Ķ",
+ "Ġs ens",
+ "Ġte ach",
+ "id o",
+ "h od",
+ "Ġep is",
+ "Ġwel come",
+ "Ġw all",
+ "ä ¹",
+ "Ġch ance",
+ "h en",
+ "ĠÐ ¡",
+ "ĠÄ ij",
+ "Ġsim ply",
+ "ĠÑĤ ак",
+ "r ing",
+ "j a",
+ "b ook",
+ "Ġsever al",
+ "st e",
+ "Ġcreat ed",
+ "Ġо ÑĤ",
+ "Ġp ush",
+ "= =",
+ "Ġh igher",
+ "u f",
+ "our ce",
+ "o ke",
+ "Ġon line",
+ "Ġre le",
+ "Ġt on",
+ "ens ive",
+ "Ġfavor ite",
+ "Ñĥ д",
+ "Ġlook ed",
+ "Ġv on",
+ "âĢ Ķ",
+ "Ġf ür",
+ "Ġbut ton",
+ "Ġb ill",
+ "Ġchang es",
+ "! \"",
+ "Ġsl ow",
+ "ab les",
+ "Ġde ath",
+ "and s",
+ "ate g",
+ "Ġthem selves",
+ "ãģ £",
+ "Ġc op",
+ "ãģ ®",
+ "Ġperson al",
+ "ug hing",
+ "Ġ1 1",
+ "g ar",
+ "ad es",
+ "Ġneed ed",
+ "Ġstud y",
+ "ag ed",
+ "ÑģÑĤ в",
+ "in o",
+ "Ġdis c",
+ "k i",
+ "Ġadd ress",
+ "× ¨",
+ "itt en",
+ "es ome",
+ "ĠÐ ¶",
+ "¤ ë",
+ "ur a",
+ "Ġm u",
+ "Ġcontin u",
+ "f or",
+ "Ġm atch",
+ "ãģ ¦",
+ "Ġstra ight",
+ "IJ ë",
+ "n ers",
+ "Ġdo g",
+ "Ġde b",
+ "ĠC O",
+ "Ġo s",
+ "g ed",
+ "c ame",
+ "Ġcor rect",
+ "et te",
+ "ĠSe e",
+ "Ġinclud ing",
+ "ĠEu ro",
+ "est er",
+ "Ġj ump",
+ "ĠWh ich",
+ "Ġк ак",
+ "s on",
+ "y a",
+ "IN G",
+ "Ġe ine",
+ "os h",
+ "en cy",
+ "Ġmed ia",
+ "Ġsubscri be",
+ "é Ĥ",
+ "Ġpr in",
+ "Ġha b",
+ "ĠP er",
+ "ĠW as",
+ "Ġp age",
+ "it or",
+ "Ġto wards",
+ "Ġtri ed",
+ "en ge",
+ "art ment",
+ "Ġvar i",
+ "Ġp aper",
+ "Ġpict ure",
+ "Ġvers ion",
+ "Ġbr ought",
+ "w are",
+ "ĠSt ates",
+ "Ġs ich",
+ "led ge",
+ "Ġper cent",
+ "Ġgo d",
+ "e c",
+ "ĠC omm",
+ "Ġdec ided",
+ "Ġse lect",
+ "íķ ľ",
+ ") .",
+ "ur ity",
+ "Ġfur ther",
+ "Ġcom ments",
+ "le ment",
+ "Ġd ream",
+ "Ġcent er",
+ "m i",
+ "Ġc as",
+ "Ġwom an",
+ "Ġro ad",
+ "Ġf ail",
+ "Ġbe came",
+ "l us",
+ "il ities",
+ "ãģ ¯",
+ "ĠC o",
+ "Ġman age",
+ "Ġrec ogn",
+ "Ġact ion",
+ "Ġbene f",
+ "Ġear lier",
+ "× ľ",
+ "Ġspe ed",
+ "Ġm ent",
+ "Ġso ci",
+ "Ġsho ot",
+ "u i",
+ "ĠÃ ¤",
+ "Ġapp ly",
+ "v o",
+ "x im",
+ "Ġca use",
+ "Ġsur pr",
+ "Ġha ben",
+ "D I",
+ "Ġf ather",
+ "ĠNe xt",
+ "ĠYouT ube",
+ "Ġc ode",
+ "Ġro le",
+ "g ress",
+ "Ġg reen",
+ "et t",
+ "Ġbu ilt",
+ "Ġfl ow",
+ "Ġb ase",
+ "Ġtra ining",
+ "Ġr ound",
+ "ĠW ill",
+ "Ġp ath",
+ "ĠR o",
+ "Ġinterest ed",
+ "ìĸ ´",
+ "Ġres pect",
+ "Ġchang ed",
+ "iss ion",
+ "Ġstud ent",
+ "og raph",
+ "Ġappro ach",
+ "Ġshow s",
+ "å° ±",
+ "Ġt ar",
+ "Ġcr it",
+ "Ġg lo",
+ "ìĬµ ëĭĪëĭ¤",
+ "Ġde ad",
+ "ĠPres ident",
+ "Ġth ous",
+ "Ġb al",
+ "st er",
+ "e x",
+ "Ġabs olutely",
+ "Ġm ic",
+ "Ġpract ice",
+ "Ġqu ality",
+ "Ġl ower",
+ "og le",
+ "Ġse par",
+ "b all",
+ "med i",
+ "Ġre view",
+ "ĠA pp",
+ "Ġo k",
+ "âĢ ĭ",
+ "Ġexper ien",
+ "Ġconc ern",
+ "ent ially",
+ "m ore",
+ "ĠJ o",
+ "ap an",
+ "ĠI ch",
+ "ist ic",
+ "Ġf air",
+ "Ġwebs ite",
+ "i res",
+ "ĠB y",
+ "Ġtra vel",
+ "Ġris k",
+ "Ġm ir",
+ "Ġbo ard",
+ "Ġs en",
+ "Ġparent s",
+ "ĠW ow",
+ "Ġfe ed",
+ "Ġsa ve",
+ "Ġser ious",
+ "Ġin it",
+ "E L",
+ "und red",
+ "A S",
+ "Ġv an",
+ "or row",
+ "Ġwor th",
+ "Ġse arch",
+ "Ġ1 6",
+ "Ġpart s",
+ "ÑģÑĤ ÑĮ",
+ "Ġcomp an",
+ "Ġmov ie",
+ "Ġmet hod",
+ "Ġ ill",
+ "Ġw ish",
+ "d y",
+ "Ġit em",
+ "Ġmin us",
+ "ang er",
+ "Ġvo ice",
+ "Ġsk in",
+ "Ġare as",
+ "Ġe ight",
+ "Ġo bs",
+ "Ġ ,",
+ "аР¹",
+ "Ġo il",
+ "Ġc y",
+ "Ġb aby",
+ "s y",
+ "Ġem ploy",
+ "ĠK e",
+ "Ġpl aces",
+ "Ġf ix",
+ "Ġest á",
+ "ãģ ¨",
+ "iv ed",
+ "Ġlot s",
+ "Ġse ason",
+ "un k",
+ "al t",
+ "Ġt able",
+ "ĠÐ ¢",
+ "Ã ¢",
+ "Ġatt ention",
+ "ãģ ª",
+ "ĠH er",
+ "Ġa ge",
+ "Ġp ra",
+ "b ack",
+ "c il",
+ "Ġnet work",
+ "r it",
+ "Ġdo c",
+ "Ġare n",
+ "ig en",
+ "Ġë Ħ",
+ "Ø ¯",
+ "end er",
+ "Ġtot al",
+ "Ġpr ice",
+ "Ġcra zy",
+ "ì ļ",
+ "i qu",
+ "th ough",
+ "Y ou",
+ "Ù ĩ",
+ "ãĤ ĵ",
+ "Ï ħ",
+ "Ġs at",
+ "Ġb i",
+ "ĠD ie",
+ "Ġsh a",
+ "Ġthank s",
+ "u h",
+ "Ġst age",
+ "аР¶",
+ "ĠF l",
+ "Ġle av",
+ "Ġbo y",
+ "Ġa f",
+ "ö n",
+ "ĠG et",
+ "Ġac cept",
+ "Ġent er",
+ "Ġt ur",
+ "Ġsi ÄĻ",
+ "Ġhon est",
+ "ãĢ Į",
+ "Ġs am",
+ "Ġre pl",
+ "g ing",
+ "Ġdevelop ment",
+ "ĠA ct",
+ "or a",
+ "ãĢ į",
+ "ä ¾",
+ "Ġknow s",
+ "Ġim age",
+ "ĠL ord",
+ "и ÑĤÑĮ",
+ "Ġweek s",
+ "Ġse x",
+ "Ķ ë",
+ "Ġh undred",
+ "Ġsound s",
+ "Ġlearn ed",
+ "Ġb ud",
+ "ĠÑģ ÑĤ",
+ "Ġinc red",
+ "â Ļ",
+ "Ġn os",
+ "Ġd rop",
+ "Ġb en",
+ "ĠÐ ĺ",
+ "Ġsa fe",
+ "at a",
+ "Ġf uck",
+ "so ci",
+ "Ġd an",
+ "Ġcr oss",
+ "1 0",
+ "m o",
+ "ver t",
+ "Ġ1 7",
+ "z ie",
+ "å ķ",
+ "Ġd om",
+ "ĠB o",
+ "Ġset ting",
+ "Ġinvol ved",
+ "ar ily",
+ "Ġs ind",
+ "Ġs us",
+ "Ġwor ry",
+ "et h",
+ "ê¹ Į",
+ "Ġs un",
+ "Ġh ier",
+ "Ġcertain ly",
+ "ou l",
+ "ort s",
+ "ĠE r",
+ "ĠU m",
+ "Ġca us",
+ "Ġnat ural",
+ "ĠÃ ¼",
+ "Ġc ry",
+ "ĠSe c",
+ "Ġs om",
+ "æ ²",
+ "Ġeduc ation",
+ "а еÑĤ",
+ "Ġmult ip",
+ "Ġal one",
+ "Ġe ye",
+ "Ġr ate",
+ "ĠEuro pe",
+ "è ¿",
+ "m on",
+ "Ġf it",
+ "iz ing",
+ "pp ed",
+ "Ġpress ure",
+ "th e",
+ "и Ñģ",
+ "it es",
+ "ĠA f",
+ "re ci",
+ "att le",
+ "Ġserv ices",
+ "ĠGo ogle",
+ "é ģ",
+ "Ġc ases",
+ "Ġdri ve",
+ "Ġchall eng",
+ "u z",
+ "ĠM o",
+ "ìľ ¼ë",
+ "v al",
+ "åĢ ĭ",
+ "Ġf ol",
+ "Ġì ¢",
+ "ff ic",
+ "Ġr a",
+ "Ġs in",
+ "Ġbl ue",
+ "Ġaff ect",
+ "Ġm is",
+ "Ġsh ot",
+ "Ġо б",
+ "as ing",
+ "Ġsign ific",
+ "ĠC he",
+ "Ġê ³",
+ "Ġpos itive",
+ "ì £",
+ "Ġw ie",
+ "Ġ4 0",
+ "ord ing",
+ "ĠFr om",
+ "ê µ",
+ "Ġbra nd",
+ "Ġtr ust",
+ "Ġp le",
+ "Ġcommun ic",
+ "Ġwe ight",
+ "Ġask ing",
+ "Ġta x",
+ "ĠJ apan",
+ "ãģ Ł",
+ "Ġíķ ĺ",
+ "op s",
+ "Ï Ĥ",
+ "Ġput ting",
+ "Ġro ll",
+ "ĠAmeric a",
+ "re g",
+ "ŀ ×",
+ "at ures",
+ "ens ion",
+ "ĠS omet",
+ "Ġorig inal",
+ "p ing",
+ "Ġ ÅŁ",
+ "Ġproduct s",
+ "ãĥ ¼",
+ "Ġcont act",
+ "ol ution",
+ "Ġgo al",
+ "Ġp ow",
+ "Ġperform ance",
+ "Ġblo od",
+ "at ors",
+ "ĠM ich",
+ "Ġtem per",
+ "ĠD an",
+ "Ġsu gg",
+ "ÑĤ и",
+ "Ġim m",
+ "Ġoff ice",
+ "Ġar ri",
+ "Ġcom fort",
+ "ĠÐ Ķ",
+ "Ġsugg est",
+ "Ġpl at",
+ "Ĥ ĺ",
+ "1 9",
+ "Ġo m",
+ "Ġse ven",
+ "ĠC ent",
+ "ill e",
+ "Ġcon cept",
+ "Ġb ag",
+ "ü n",
+ "ive ly",
+ "Ġd iv",
+ "m os",
+ "æ ī",
+ "Ġfeel s",
+ "Ġ ir",
+ "ak es",
+ "le y",
+ "Ġpartic ip",
+ "ĠÐ ļ",
+ "f l",
+ "j ust",
+ "Ġs il",
+ "ĠP a",
+ "A L",
+ "Ġgot ta",
+ "Ġf an",
+ "Ġchall enge",
+ "Ġcompan ies",
+ "ĠPe ople",
+ "< /",
+ "оР·",
+ "Ġp en",
+ "is ing",
+ "Ġa us",
+ "em ic",
+ "am ente",
+ "Ġmeet ing",
+ "Ġvis it",
+ "Ġsupp osed",
+ "ĠOn ce",
+ "д а",
+ "or ld",
+ "3 0",
+ "U S",
+ "Ġvi ol",
+ "Ġnot ice",
+ "ĠÐ IJ",
+ "h an",
+ "p ed",
+ "ì ĺ",
+ "h h",
+ "Ġtr ou",
+ "Ġmin ute",
+ "ĠP ar",
+ "r ay",
+ "Ġt it",
+ "Ġup d",
+ "Ġblo ck",
+ "Ġd ue",
+ "a ur",
+ "Ġfor ce",
+ "Ġcou n",
+ "ĠâĢ Ķ",
+ "Ġtyp es",
+ "ë §",
+ "Ġl ate",
+ "Ġimpro ve",
+ "Ġì Ī",
+ "Ġa ve",
+ "ul es",
+ "c l",
+ "am ed",
+ "Ġaw esome",
+ "ĠO k",
+ "Ġv ot",
+ "Ġmach ine",
+ "Ġfollow ing",
+ "Ġme asure",
+ "ac ión",
+ "u el",
+ "ch an",
+ "Ġab ility",
+ "Ġt out",
+ "Ġide as",
+ "Ġincre ase",
+ "Ġen s",
+ "ĠÑ ħ",
+ "Ġë ª",
+ "Ġj est",
+ "ĠÐ ľ",
+ "Ġtr uth",
+ "h y",
+ "Ġsp end",
+ "Ġsci ence",
+ "et e",
+ "Ġ1 4",
+ "Ġepis ode",
+ "Ġal g",
+ "end ed",
+ "ãģ ĵ",
+ "ar i",
+ "ll a",
+ "Ġf ish",
+ "Ġthr ow",
+ "m it",
+ "å ¹",
+ "Ġcir c",
+ "ĠC al",
+ "Ġt our",
+ "Ġdire ction",
+ "Ġno ch",
+ "еР²",
+ "é n",
+ "Ġcount ries",
+ "Ġindust ry",
+ "in y",
+ "ic le",
+ "Ġfe et",
+ "I t",
+ "Ġlead ers",
+ "et zt",
+ "Ġst aff",
+ "ç Ķ",
+ "Ġpur p",
+ "it o",
+ "? !",
+ "ĠJ a",
+ "Ġst ore",
+ "et ic",
+ "ĠCh ina",
+ "Ġë IJ",
+ "ĠUn iversity",
+ "Ġ #",
+ "Ġdec ision",
+ "Ġach ie",
+ "Ġact ual",
+ "u ly",
+ "Ġse ction",
+ "Ġresult s",
+ "Ġst ar",
+ "Ġm ist",
+ "ib ly",
+ "Ġd ad",
+ "Ġnum bers",
+ "om b",
+ "è ª",
+ "ĠS pe",
+ "Ġm er",
+ "Ġ2 5",
+ "Ġaut om",
+ "Ġco ld",
+ "Ø ¨",
+ "Ħ ľ",
+ "ag er",
+ "ĠT V",
+ "ĠS ie",
+ "ĠH ave",
+ "Ġ że",
+ "ug g",
+ "ain ed",
+ "Ġup on",
+ "Ġlo g",
+ "Ġcomplet e",
+ "Ġbra in",
+ "ag ing",
+ "ĠM us",
+ "o ver",
+ "Ġeas ier",
+ "Ġinte gr",
+ "Ġm ás",
+ "Ġturn ed",
+ "Ġst ri",
+ "iv al",
+ "Ġhe av",
+ "ĠT H",
+ "Ġwr iting",
+ "ÑĢ а",
+ "åľ ¨",
+ "å¤ §",
+ "Ġcl a",
+ "d ing",
+ "Ġtell ing",
+ "и д",
+ "ic ated",
+ "ä» ¥",
+ "ac ht",
+ "ãģ Ĥ",
+ "h aps",
+ "ĠSt e",
+ "Ġres ources",
+ "Ġd ann",
+ "Ġpart y",
+ "Ġ ÏĦ",
+ "Ġsa f",
+ "is es",
+ "t re",
+ "o int",
+ "Ġknow ledge",
+ "Ġany more",
+ "Ġf ly",
+ "Ġma int",
+ "и к",
+ "å ij",
+ "Ġse ll",
+ "la ughs",
+ "ĠY ork",
+ "Ġb ien",
+ "Ġo d",
+ "Ġeas ily",
+ "Ġr ange",
+ "Ġo ption",
+ "Ø ¹",
+ "Ġapp reci",
+ "oc r",
+ "Ġdet erm",
+ "Ñ Ħ",
+ "Ġmean ing",
+ "Ġs ite",
+ "Ġdis co",
+ "ver age",
+ "Ġl ose",
+ "Ġinst all",
+ "Ġem ot",
+ "ant ly",
+ "ä t",
+ "Ġt amb",
+ "ĠW ar",
+ "ĠH o",
+ "ĠG en",
+ "em y",
+ "еР·",
+ "ĠP ol",
+ "Ġmess age",
+ "Ġnot e",
+ "Į Ģ",
+ "Ġh et",
+ "Ġim medi",
+ "Ġav o",
+ "Ġbook s",
+ "Ġbecom es",
+ "res h",
+ "è s",
+ "as ons",
+ "Ġhim self",
+ "ut s",
+ "Ġj u",
+ "Ġaw are",
+ "Ġrequ ire",
+ "Ġsystem s",
+ "ĠH ar",
+ "Ġam ong",
+ "Ġh om",
+ "Ġb reat",
+ "Ġwe ird",
+ "Ġë ¶",
+ "Î »",
+ "Ø ©",
+ "if f",
+ "or ing",
+ "Ġplat form",
+ "ĠT ake",
+ "Ġhelp s",
+ "ut ions",
+ "Ġfor g",
+ "Ġl uck",
+ "ĠEng lish",
+ "Ġwe b",
+ "Ġneg ative",
+ "Ġt ut",
+ "Ġab ove",
+ "ng th",
+ "Ġê ±°",
+ "Ġst ories",
+ "Ġlo ad",
+ "Ġback ground",
+ "Ġsw itch",
+ "g a",
+ "Ġprin ci",
+ "Ġfin an",
+ "Ġvar ious",
+ "Ġl Ãł",
+ "Ġkind s",
+ "ain ing",
+ "Ġn ature",
+ "ĠÐ ŀ",
+ "c z",
+ "Ġpr ay",
+ "Ġg ar",
+ "ir m",
+ "Ġ &",
+ "Ġì ĥ",
+ "n s",
+ "ĠR ep",
+ "ĠF e",
+ "Ġre v",
+ "ra nd",
+ "Ġlike ly",
+ "Ġunderstand ing",
+ "ı r",
+ "ãģ ĭ",
+ "Ġf al",
+ "Ġ1 3",
+ "ÑĨ и",
+ "Ġsu d",
+ "Ġbr other",
+ "Ġpl ant",
+ "Ġthrough out",
+ "w ise",
+ "p re",
+ "Ġcult ure",
+ "ĠÙ ħ",
+ "Ġwonder ful",
+ "Ġa h",
+ "pp er",
+ "Ġso ld",
+ "Ġstart s",
+ "Ġwr itten",
+ "Î ¯",
+ "n i",
+ "Ġ×Ķ ×",
+ "ĠD av",
+ "Ġu lt",
+ "Ġar m",
+ "Ġro ck",
+ "Ġwe ar",
+ "ë į°",
+ "an o",
+ "ra g",
+ "Ġsqu are",
+ "ан и",
+ "c ast",
+ "le br",
+ "Ġliter ally",
+ "Ġplay ed",
+ "Ġhe at",
+ "on se",
+ "r ict",
+ "Ġins p",
+ "id s",
+ "Ġpop ular",
+ "ë ıĦ",
+ "Ġc atch",
+ "Ġm ount",
+ "Ġj ud",
+ "Wh at",
+ "еР±",
+ "R A",
+ "a ud",
+ "к о",
+ "Ġsur face",
+ "Ġcon v",
+ "Ġpie ces",
+ "O h",
+ "æ Ģ",
+ "Ġst yle",
+ "pp ing",
+ "Ġread ing",
+ "Ġconvers ation",
+ "оР¿",
+ "ä¾ Ĩ",
+ "ĠAg ain",
+ "Ġb ank",
+ "t ime",
+ "Ñĥ ÑĤ",
+ "er ve",
+ "ĠG reat",
+ "Ġcap t",
+ "аР±",
+ "ay s",
+ "ĠF in",
+ "ific ation",
+ "Ġä r",
+ "а Ñİ",
+ "Ġe gg",
+ "ĠW el",
+ "Ġtar get",
+ "ul a",
+ "ch es",
+ "an i",
+ "O O",
+ "ic ious",
+ "n ow",
+ "Ï ĥ",
+ "bo ard",
+ "Ġg ente",
+ "Ġd ro",
+ "ĠE t",
+ "Ġd in",
+ "Ġc os",
+ "Ġaut hor",
+ "Ø ³",
+ "Ġo ch",
+ "Ġem ail",
+ "Ġsp irit",
+ "Ġs itting",
+ "m as",
+ "Ġstre ngth",
+ "Ġbig ger",
+ "ĠW ait",
+ "Ġm at",
+ "Ġpol ice",
+ "ress ed",
+ "Ġwait ing",
+ "is hing",
+ "Ġdoll ars",
+ "ho od",
+ "s s",
+ "Ġimag ine",
+ "in i",
+ "Ġm es",
+ "Ġdis e",
+ "id ge",
+ "ab or",
+ "Ġp et",
+ "Ġh op",
+ "ĠK ing",
+ "Ġcomput er",
+ "Ġgo ld",
+ "Ġn u",
+ "Ġf ing",
+ ") ,",
+ "Ġsec urity",
+ "ru ction",
+ "Ġsol ution",
+ "e xt",
+ "Ġp atter",
+ "ick en",
+ "ure d",
+ "Ġstand ard",
+ "ìĭ ľ",
+ "Ġdou ble",
+ "Î ·",
+ "Ġw ife",
+ "is a",
+ "Ġdirect ly",
+ "ac ed",
+ "Ġb unch",
+ "ĠÂ ¿",
+ "ал ÑĮ",
+ "Ġreg ard",
+ "Ġswe et",
+ "Ġun ique",
+ "ĠâĻ «",
+ "Ġtra in",
+ "ĠG erm",
+ "Î ¬",
+ "R E",
+ "Ġbeh av",
+ "Ġpre d",
+ "ì ĥ",
+ "s et",
+ "Ġdescri ption",
+ "é e",
+ "Ġc at",
+ "å ĵ",
+ "Ġcoll ege",
+ "ì Ľ",
+ "Ġapplic ation",
+ "ĠS en",
+ "as k",
+ "Ġc red",
+ "ub lic",
+ "Ġmultip le",
+ "Ġn i",
+ "Ġpres ident",
+ "Ġadd ed",
+ "Ġro b",
+ "Ġaqu i",
+ "Ġh osp",
+ "Ġtool s",
+ "Ġg un",
+ "Ġbas ic",
+ "Ġl ines",
+ "Ġst ructure",
+ "ĠR uss",
+ "Ġtot ally",
+ "Ġbig gest",
+ "Ġe en",
+ "Ġar g",
+ "Ġ× ľ",
+ "Ġp ark",
+ "ĠD es",
+ "Ġce lebr",
+ "Ġf ait",
+ "ен ÑĮ",
+ "Ġsu ff",
+ "Ġreg ular",
+ "¨ ë",
+ "Ġm ine",
+ "ĠK ore",
+ "Ġpre vious",
+ "Ġp i",
+ "Ġse g",
+ "Ġpol icy",
+ "Ġк о",
+ "ĠTr ump",
+ "Ġvac c",
+ "ó w",
+ "ĠS y",
+ "и Ñĩ",
+ "it ter",
+ "Ġpolit ical",
+ "r as",
+ "Ġal s",
+ "ел ÑĮ",
+ "Ġsha pe",
+ "an z",
+ "Ġon to",
+ "Ġar ch",
+ "Ġam b",
+ "ag ram",
+ "ĠS m",
+ "ct ions",
+ "Ġjo in",
+ "b or",
+ "å Ľ",
+ "Ġfr ame",
+ "ł ĩ",
+ "Ġcho ice",
+ "௠ģ",
+ "Ñĥ Ñİ",
+ "ĠC or",
+ "ĠS w",
+ "I T",
+ "Ġt end",
+ "ĠE ar",
+ "Ġto r",
+ "Ġev ents",
+ "Ġcla im",
+ "ĠD a",
+ "ĠM ark",
+ "Ġgroup s",
+ "Ġe ating",
+ "ĠW orld",
+ "Ġrec ently",
+ "Ġtast e",
+ "Ġsur v",
+ "à ¤",
+ "Ġsk ills",
+ "Ġи з",
+ "itt ed",
+ "Ġsh op",
+ "ìĿ ´ì",
+ "Ġest ab",
+ "ĠëĤ ĺ",
+ "Ġsecond s",
+ "ĠTh ose",
+ "ĠE nt",
+ "Ġì Ħ",
+ "ers on",
+ "Ġto wn",
+ "Ġc and",
+ "Ġopt ions",
+ "Ġ ing",
+ "V ID",
+ "Ġenc our",
+ "Ġr é",
+ "âĻ ª",
+ "Ġent re",
+ "Ġmove ment",
+ "ĠB en",
+ "Ġbir th",
+ "Ġwh e",
+ "Ġh ang",
+ "ĠE m",
+ "ig e",
+ "ro ll",
+ "Ġun f",
+ "ì Ĥ",
+ "Ġr id",
+ "Ġsp read",
+ "Ġh ost",
+ "al d",
+ "ĠE d",
+ "Ġcons um",
+ "U N",
+ "Ġop in",
+ "it ar",
+ "ĠM ed",
+ "Ġsub ject",
+ "Ġp al",
+ "Ġcar ry",
+ "Ġag ree",
+ "ĠWh ile",
+ "Ġcare er",
+ "Ġsci ent",
+ "Ġsud den",
+ "Ġf ile",
+ "z i",
+ "Ġex cept",
+ "é º",
+ "Ġpot ential",
+ "ĠAn other",
+ "Ġcomp lex",
+ "ĠS im",
+ "end o",
+ "Ġr ais",
+ "Ġphys ical",
+ "Ġd ate",
+ "ak er",
+ "ĠC ol",
+ "Ġpower ful",
+ "Ġmem ber",
+ "ra p",
+ "Ġsp ot",
+ "Ġs ource",
+ "Ġf em",
+ "é m",
+ "Ġem p",
+ "j i",
+ "iet y",
+ "Ġinf lu",
+ "Ġd ry",
+ "Ġlo ck",
+ "Ġz ero",
+ "ĠU h",
+ "Ġr out",
+ "Ġpor que",
+ "Ġ2 4",
+ "Ġt al",
+ "Ġfol ks",
+ "Ġla unch",
+ "Ġcomp on",
+ "ĠWel come",
+ "Ġk ann",
+ "ä n",
+ "ĠÑį ÑĤ",
+ "e es",
+ "ĠÙ Ī",
+ "Ġany way",
+ "Ġaud ience",
+ "äº º",
+ "Ġsl ight",
+ "on a",
+ "Ġu r",
+ "Ġrel ig",
+ "Ġext rem",
+ "ı z",
+ "ĠM a",
+ "Î ¼",
+ "ĠÃ ¶",
+ "Ġall ows",
+ "Ġf at",
+ "ĠF ace",
+ "Ġn ational",
+ "Ġinter view",
+ "ĠM c",
+ "é t",
+ "Ġc ute",
+ "el a",
+ "Ġsec ret",
+ "ĠW est",
+ "ĠD ep",
+ "Ġex erc",
+ "Ġhist or",
+ "Ġpri or",
+ "Ġ6 0",
+ "av a",
+ "ac her",
+ "y ond",
+ "ĠH a",
+ "Ġest e",
+ "in ary",
+ "ĠN orth",
+ "on st",
+ "Ġsm art",
+ "am s",
+ "ал и",
+ "Ġd ar",
+ "er ed",
+ "Ġfun ny",
+ "ĠO b",
+ "ĠBl ack",
+ "Ġrel ated",
+ "ĠB u",
+ "Ġsome where",
+ "ĠR em",
+ "n es",
+ "ment e",
+ "ĠRe ally",
+ "Ġcreat ing",
+ "Ġfam il",
+ "Ġsoci ety",
+ "Ġg el",
+ "Ġtrans form",
+ "Ä ĥ",
+ "Ġinclud e",
+ "Ġh ol",
+ "l ike",
+ "k o",
+ "air s",
+ "Ġп од",
+ "Ġpers pect",
+ "Ġb es",
+ "Ġparticular ly",
+ "Ġshow ing",
+ "ĠP art",
+ "Ġqu al",
+ "lo ck",
+ "Ġreal ity",
+ "ho ld",
+ "ict ion",
+ "o on",
+ "Ġv ir",
+ "ãģ «",
+ "it ary",
+ "Ġdr ug",
+ "Ġfe ature",
+ "Ġre asons",
+ "Ġ× ©",
+ "Ġwr ote",
+ "Ġf ant",
+ "Ġb and",
+ "Ù ĥ",
+ "en a",
+ "ke y",
+ "Ġear th",
+ "d om",
+ "Ġfe atures",
+ "Ġflo or",
+ "Ġspeak ing",
+ "Ġt ip",
+ "ĠA ust",
+ "Ġst ock",
+ "Ġch urch",
+ "Ġr ac",
+ "ìľ¼ë ¡ľ",
+ "ภĻ",
+ "ãĤ Į",
+ "k y",
+ "Ġresp onse",
+ "Û Į",
+ "ul ations",
+ "Ġsl ide",
+ "Ġgrad u",
+ "ci ous",
+ "Ġme ant",
+ "Ġ ==",
+ "Ġ× IJ×",
+ "ã ħ",
+ "Ġkind a",
+ "Ġsc ene",
+ "Ġm uit",
+ "Ġê° Ģ",
+ "r ast",
+ "re st",
+ "Ġplay ers",
+ "w a",
+ "Ġbro ad",
+ "Ġtom orrow",
+ "oc ol",
+ "ĠÑģ в",
+ "ĠB ar",
+ "ı k",
+ "Ġse a",
+ "Ġrem ove",
+ "Ġrem ind",
+ "ом Ñĥ",
+ "ĠS ince",
+ "Ġave c",
+ "ce ll",
+ "и Ñħ",
+ "Ġdoc ument",
+ "Ġê·¸ë Ł",
+ "Ġne igh",
+ "be at",
+ "Ġp Ã¥",
+ "Ġas pect",
+ "Ġd ed",
+ "lish ed",
+ "il s",
+ "Ġour selves",
+ "u ce",
+ "Ġhe y",
+ "ĠпÑĢ о",
+ "ent y",
+ "Ġas soci",
+ "ad os",
+ "um ber",
+ "Ġ ]",
+ "éĤ £",
+ "no v",
+ "Ġì Ļ",
+ "Ñĥ Ñĩ",
+ "Ġcond ition",
+ "ëĬĶ ëį°",
+ "Ġval ues",
+ "Ġsc en",
+ "min ist",
+ "Ġc ast",
+ "Ġgrow ing",
+ "Ġus er",
+ "Ġresp ond",
+ "l im",
+ "é r",
+ "y m",
+ "çľ ĭ",
+ "os es",
+ "sy ch",
+ "ĠÑĢ аз",
+ "Ġappe ar",
+ "Ġpro gress",
+ "eng th",
+ "Ġj ak",
+ "ĠD is",
+ "Ġpat ients",
+ "ĠS er",
+ "Ġg as",
+ "è re",
+ "ìĸ´ì ļĶ",
+ "Ġre ci",
+ "ìĿ ¸",
+ "Ġs ca",
+ "ep end",
+ "Ñģ к",
+ "аР¿",
+ "Ġb atter",
+ "Ġve h",
+ "ð Ł",
+ "Ġac com",
+ "Ġbe at",
+ "Ġpain t",
+ "Ġcont rib",
+ "Ġs ad",
+ "Æ °",
+ "al es",
+ "Ġt ree",
+ "b a",
+ "Ġb orn",
+ "ic ed",
+ "à® ķ",
+ "b and",
+ "Ġme chan",
+ "ĠD et",
+ "Ġcap ital",
+ "Ġdel iver",
+ "Ġfe ar",
+ "ŀ ĺ",
+ "ĠS outh",
+ "Ġb ought",
+ "Ġst ress",
+ "Ġv or",
+ "? ?",
+ "i h",
+ "ìķ ¼",
+ "Ġer a",
+ "ìĿ´ ë",
+ "а Ñı",
+ "is ions",
+ "iv ity",
+ "Ġhelp ed",
+ "Ġass ist",
+ "Ġplay er",
+ "r an",
+ "Ġimmedi ately",
+ "Ġmo ved",
+ "c ie",
+ "ê ±",
+ "Ġann oun",
+ "å ¿",
+ "ìŀ IJ",
+ "Ġprodu ction",
+ "Ġsum mer",
+ "Ġt un",
+ "Ġprogram s",
+ "G H",
+ "al ing",
+ "ir a",
+ "el ess",
+ ". )",
+ "Ġa verage",
+ "è¦ ģ",
+ "Ġgl ass",
+ "om an",
+ "if ically",
+ "Ġëĭ ¤",
+ "ĠC ong",
+ "ĠV er",
+ "Ġtr ick",
+ "Ġbe gan",
+ "Ġv ill",
+ "ê ±°",
+ "h ow",
+ "æ Ń",
+ "Ġt ill",
+ "Ġ9 0",
+ "ber t",
+ "Ġê ¸",
+ "Ġtemper ature",
+ "Ã ²",
+ "๠Ī",
+ "Ġgra ph",
+ "Ġê· ¸",
+ "Ġr ot",
+ "Ġmo b",
+ "A Y",
+ "a el",
+ "Ġre pe",
+ "Ġdev ice",
+ "Ġ19 9",
+ "Ġte le",
+ "Ġke pt",
+ "p a",
+ "æ ĸ",
+ "ver se",
+ "Ġst ream",
+ "е Ñĩ",
+ "ess ion",
+ "Ġstr ugg",
+ "z z",
+ "Ġdeg ree",
+ "Ġhelp ing",
+ "Ġsm ell",
+ "Ġper haps",
+ "p ro",
+ "Ġcont ext",
+ "Ġi k",
+ "Ġп еÑĢ",
+ "Ġcal cul",
+ "éº ¼",
+ "b ing",
+ "Ġreal ize",
+ "l am",
+ "ĠCh ar",
+ "y t",
+ "ĠìĿ ´ì",
+ "Ġd anger",
+ "ĠI m",
+ "a a",
+ "Ġlo ved",
+ "Ġpurp ose",
+ "Ġfinish ed",
+ "Ġpe ace",
+ "Ġo t",
+ "Ġglo bal",
+ "Ï Ģ",
+ "Ġab er",
+ "ĸ Ī",
+ "Ġcharac ters",
+ "Ġn ur",
+ "Ġdam age",
+ "Ġem er",
+ "Ġpre c",
+ "ĠW ir",
+ "Ġinst it",
+ "ij ×",
+ "Ġallow ed",
+ "b on",
+ "Ġto d",
+ "еР³Ð¾",
+ "Ġj etzt",
+ "Ġmed ic",
+ "Ġsmall er",
+ "ce ed",
+ "Ġlevel s",
+ "Ġint ell",
+ "W e",
+ "Ġse m",
+ "Ġcurrent ly",
+ "Ġmod ern",
+ "Ġcont ract",
+ "Ġdetail s",
+ "ortun ately",
+ "O S",
+ "Ġst ates",
+ "Ġad just",
+ "ant age",
+ "e z",
+ "ĠV ery",
+ "Ġsc ale",
+ "Ġre lease",
+ "Ġf az",
+ "Ġ ic",
+ "it ude",
+ "A C",
+ "ĠP at",
+ "id en",
+ "Ń IJ",
+ "Ġpre fer",
+ "olog ical",
+ "ĠFace book",
+ "Ġê° Ļ",
+ "Ġ ..",
+ "ĠM ake",
+ "Ġко ÑĤоÑĢ",
+ "ĠDav id",
+ "ĠAf ric",
+ "Ġmod e",
+ "ĠC ity",
+ "Ġsh all",
+ "ĠÑ Ħ",
+ "im in",
+ "Ġз а",
+ "r om",
+ "u a",
+ "Ġbe yond",
+ "Ġdist rib",
+ "к Ñĥ",
+ "ĠDo es",
+ "Ġv ict",
+ "r ate",
+ "Ġv ai",
+ "Ġsuccess ful",
+ "Ġh ous",
+ "ah a",
+ "est s",
+ "ĠE st",
+ "Ġdisco ver",
+ "Ġthere fore",
+ "ch a",
+ "Ġc up",
+ "Ġpop ulation",
+ "ĠI l",
+ "s c",
+ "Ġsp ent",
+ "re l",
+ "Ġuse ful",
+ "Ġt ab",
+ "æ Ŀ",
+ "Ġ Å",
+ "Ġìł ľ",
+ "Ġcon se",
+ "Ġqu ant",
+ "ay a",
+ "Ġb on",
+ "åı ¯",
+ "ĠCh in",
+ "Ġê² ĥ",
+ "ound s",
+ "е ÑĪ",
+ "ell e",
+ "Ġ ice",
+ "2 1",
+ "Ġk ick",
+ "ä¸ ĭ",
+ "Ġstep s",
+ "Ġton ight",
+ "нÑĭ й",
+ "ren ch",
+ ". '",
+ "Ġgra b",
+ "Ġimp lement",
+ "ĠìĪ ĺ",
+ "Ġmiss ion",
+ "Ġclear ly",
+ "Ġappreci ate",
+ "è Ģ",
+ "Ġf resh",
+ "ar m",
+ "ĠTw o",
+ "Ġex ec",
+ "Ġproject s",
+ "Ġcommun ities",
+ "ri ble",
+ "Ġreg ion",
+ "Ġfre qu",
+ "ro y",
+ "Ġhow ever",
+ "Ġpart ners",
+ "an c",
+ "Ġmin im",
+ "Ġl at",
+ "Ġfamil ies",
+ "Ġev idence",
+ "Ġp un",
+ "ra ft",
+ "Ġl oss",
+ "Ġma p",
+ "Ġany body",
+ "Ġchang ing",
+ "Ġr ules",
+ "Ġorgan ization",
+ "Ġess entially",
+ "ĠR ed",
+ "Ġele ment",
+ "æ Ĺ",
+ "Ġv irt",
+ "r at",
+ "Ġpr int",
+ "and er",
+ "are n",
+ "em os",
+ "ο Ïħ",
+ "Ġcond itions",
+ "ab e",
+ "Ġd ance",
+ "и ÑĢ",
+ "Ġd os",
+ "о Ñĩ",
+ "ĠQ ue",
+ "Ġwalk ing",
+ "Ġt ro",
+ "Ġ id",
+ "Ġadd itional",
+ "Ġfull y",
+ "Ġf ans",
+ "Ġadd ition",
+ "Ġlik ed",
+ "Ġü ber",
+ "Ġb ow",
+ "d i",
+ "Ġm aster",
+ "o ff",
+ ") :",
+ "m ber",
+ "Ġë ¬",
+ "å ¯",
+ "åĪ °",
+ "la use",
+ "Ġo der",
+ "Ġsaf ety",
+ "Ġre act",
+ "à® ¿",
+ "b t",
+ "Ġdis app",
+ "Ġgirl s",
+ "S t",
+ "ĠA ng",
+ "Ġfa ith",
+ "Ġturn s",
+ "Ġt ight",
+ "Ġm outh",
+ "am i",
+ "z er",
+ "Ġwe ap",
+ "Ġб Ñĥд",
+ "Ġhosp ital",
+ "ra id",
+ "Ġmic ro",
+ "ĠSt ate",
+ "ĠM ost",
+ "ag n",
+ "Ġdec ide",
+ "Ġpat ient",
+ "Ġcor ner",
+ "Ġdi ed",
+ "N o",
+ "ĠSt ud",
+ "re nd",
+ "em pt",
+ "Ġli e",
+ "Ġl if",
+ "ĠBe fore",
+ "t ó",
+ "ĠSu per",
+ "Ġbe ll",
+ "6 0",
+ "Ġpriv ate",
+ "ĠPa ul",
+ "Ġg ib",
+ "Ġag re",
+ "´ì Ħľ",
+ "Ġs ig",
+ "Ġinvest ig",
+ "Ñı ÑĤ",
+ "en ing",
+ "Ġdist ance",
+ "Ġwar m",
+ "Ġdig ital",
+ "å¾ Ī",
+ "in er",
+ "Ġp and",
+ "ĠCO VID",
+ "Ð ³Ð¾",
+ "g n",
+ "Ġr ace",
+ "Ġpr oud",
+ "Ġte aching",
+ "Ġ ÑĤо",
+ "ìŀ ¥",
+ "ĠAll ah",
+ "I n",
+ "Ġw ood",
+ "Ġcol ors",
+ "Ġw ird",
+ "u j",
+ "id ad",
+ "Ġcustom ers",
+ "Ġconnect ed",
+ "Ġlay er",
+ "Ġachie ve",
+ "Ġperspect ive",
+ "ĠC oll",
+ "Ù Ĥ",
+ "Ġcl oud",
+ "!! !",
+ "Ġend ed",
+ "łĩ ê²Į",
+ "Ġmanage ment",
+ "Ġr ich",
+ "Ġsub st",
+ "Ġrem o",
+ "Ġser ve",
+ "Ġres ist",
+ "Ġthought s",
+ "Ġgrow th",
+ "ili ar",
+ "Ġright s",
+ "Ġchar ge",
+ "Ġcons ist",
+ "Ġwer den",
+ "Ġem b",
+ "and om",
+ "Ġhur t",
+ "Ġk an",
+ "i as",
+ "л о",
+ "Ġsh it",
+ "Ġbe g",
+ "Ġrece ived",
+ "it ation",
+ "Ġme at",
+ "Ġis so",
+ "ff ee",
+ "Ġfam ous",
+ "Ġcomfort able",
+ "I L",
+ "ĠB ye",
+ "èª ª",
+ "åĢ ij",
+ "oth es",
+ "Ġmed ical",
+ "Ġenjoy ed",
+ "Ġhealth y",
+ "Ġw y",
+ "c ies",
+ "Ġeff ort",
+ "Ġdo ctor",
+ "Ġmil itary",
+ "L AU",
+ "Ġg ro",
+ "Ġb attle",
+ "Ġf ed",
+ "Ġcap ac",
+ "Ġaf raid",
+ "iv il",
+ "ĠвÑģ е",
+ "Ġl ength",
+ "ys is",
+ "Ġbe i",
+ "¤ í",
+ "Ġorgan iz",
+ "or g",
+ "in c",
+ "Ġinter act",
+ "ĠChin ese",
+ "Ġacc ording",
+ "Ġincred ible",
+ "Ġkill ed",
+ "Ġda ughter",
+ "ĠÏ Ģ",
+ "Ñĭ в",
+ "Ġschool s",
+ "ĠÂ «",
+ "ll er",
+ "Ġshould n",
+ "n al",
+ "Ġcr is",
+ "Ġch icken",
+ "Ġf aster",
+ "Ġextrem ely",
+ "Ġopp os",
+ "Ġn ous",
+ "Ġ +",
+ "ri a",
+ "Ġfinan cial",
+ "Ġexc iting",
+ "Ġjour ney",
+ "×Ļ× Ŀ",
+ "ł ë",
+ "Ġdis play",
+ "Ġmem ory",
+ "Ġheav y",
+ "н е",
+ "Ġpass ed",
+ "ÑĢ и",
+ "il es",
+ "Ġp sych",
+ "Ġspec ifically",
+ "Ġeng age",
+ "Ġl ed",
+ "or ge",
+ "ĠD em",
+ "ord er",
+ "Ġ8 0",
+ "Ġcre am",
+ "ester day",
+ "Ġed ge",
+ "Ġп ол",
+ "Ġbu ll",
+ "Ġind ic",
+ "Ġk tó",
+ "Ġhope fully",
+ "um ents",
+ "ag en",
+ "н ого",
+ "Ġh ate",
+ "ch t",
+ "8 0",
+ "Ġeff ic",
+ "Ġì§ Ģ",
+ "Ġintern et",
+ "Ġbud get",
+ "Ġproper ty",
+ "id ay",
+ "Ġì ļ",
+ "Ġм ож",
+ "ol a",
+ "Ġshow ed",
+ "ĠM on",
+ "Ġthous and",
+ "A P",
+ "Ġpo or",
+ "us ed",
+ "ĠJ ack",
+ "Ġs Ã¥",
+ "ĥ ½",
+ "Ġes c",
+ "Ġsoft ware",
+ "Ġqu ar",
+ "ĠØ ¨",
+ "Ġnecess arily",
+ "om en",
+ "i y",
+ "Ġevent ually",
+ "ish ed",
+ "Ġbr ight",
+ "E D",
+ "Ġs pl",
+ "Ġdem and",
+ "Ġth reat",
+ "Ġs ir",
+ "Ġrele ased",
+ "ck et",
+ "ĠâĢ «",
+ "Ġrequ ired",
+ "Ġv ote",
+ "ì ¹",
+ "à® ¤",
+ "Ġdevelop ed",
+ "ĠìĤ ¬",
+ "at ory",
+ "Ġd ir",
+ "ca pe",
+ "Ġslight ly",
+ "Ã ¬",
+ "๠ī",
+ "re et",
+ "Ġdise ase",
+ "Ġcour t",
+ "Ġitem s",
+ "ĠEar th",
+ "ÑģÑĤ и",
+ "ж е",
+ "ì ²",
+ "Ġchalleng es",
+ "ĠBr it",
+ "Ġdesign ed",
+ "1 2",
+ "Ġhear ing",
+ "Ġlisten ing",
+ "z o",
+ "ĠÑģ л",
+ "ãģ§ ãģĻ",
+ "Ġper o",
+ "Ġwe aring",
+ "pl ic",
+ "Ġch em",
+ "Ġbal ance",
+ "Ġb a",
+ "Ġrece ive",
+ "im a",
+ "Ġsignific ant",
+ "Ġм Ñĭ",
+ "an ch",
+ "ĠC r",
+ "ĠC oun",
+ "ê¸ Ī",
+ "Ġjo bs",
+ "Ġoffic ial",
+ "Ġper m",
+ "om s",
+ "Ġopportun ities",
+ "Ġover all",
+ "Ġh us",
+ "od es",
+ "Ġn ation",
+ "ĠR eg",
+ "Ġor d",
+ "Ġrest aur",
+ "Ġì Ĩ",
+ "Ġm el",
+ "v in",
+ "Ġw enn",
+ "Ġk ön",
+ "æ ĥ",
+ "Ġopin ion",
+ "ãĤ Ĥ",
+ "è ¬",
+ "ĠSomet imes",
+ "ç Ĥ",
+ "Ñī е",
+ "as c",
+ "O U",
+ "Ġ20 20",
+ "Ġdel icious",
+ "ig er",
+ "Ġìķ Ī",
+ "o le",
+ "Ġhand le",
+ "Ġc it",
+ "Ġíķ ľ",
+ "Ġf ör",
+ "o oth",
+ "Ġnecess ary",
+ "Ġind epend",
+ "æ Ħ",
+ "ist en",
+ "h am",
+ "Ġé t",
+ "ãĥ ³",
+ "Ġmult i",
+ "Ï Į",
+ "? )",
+ "Ġcamp us",
+ "Ġtop ic",
+ "Ġr ain",
+ "Ġpan el",
+ "ĠS am",
+ "Ġlar ger",
+ "aud ience",
+ "Ġpa id",
+ "Ġeconom ic",
+ "ol t",
+ "Ġstre et",
+ "ĠC ont",
+ "Ġdri ving",
+ "Ġìł Ģ",
+ "Ġh ay",
+ "Ġprofess ional",
+ "ĠIn tern",
+ "å ¸",
+ "Ġin put",
+ "Ġc ateg",
+ "Ġc ro",
+ "Ġ ll",
+ "E T",
+ "Ñĭ й",
+ "* *",
+ "ĠZ e",
+ "B LE",
+ "Ġì ¤",
+ "re es",
+ "ĠÐ ¯",
+ "ed e",
+ "ier t",
+ "Ġfo ld",
+ "Ġd ur",
+ "ĠN ational",
+ "Ġìĸ ´ë",
+ "an ced",
+ "Ġfa ire",
+ "ut ed",
+ "Ġk ing",
+ "Ġw ild",
+ "o i",
+ "up beat",
+ "Ġpre vent",
+ "i us",
+ "ĠÃ ¨",
+ "Ġw ide",
+ "Ġr ing",
+ "Ġtit le",
+ "Ġstand ing",
+ "Ġal though",
+ "Ġh i",
+ "Ġsa uce",
+ "Ġs ides",
+ "Ġanim als",
+ "il ing",
+ "at ives",
+ "ìĹIJ ìĦľ",
+ "ĠO ver",
+ "Ġdes p",
+ "Ġconsider ed",
+ "ar ies",
+ "i ers",
+ "Ġein en",
+ "Ġs ister",
+ "Ġë ķ",
+ "ĠS ure",
+ "ãĤ ĭ",
+ "ri end",
+ "a ign",
+ "Ġsh own",
+ "Ġs ac",
+ "Ġs ont",
+ "Ġcent ury",
+ "Ġt ien",
+ "ĠÎ º",
+ "ĠS T",
+ "åķ Ĭ",
+ "Ġold er",
+ "ie m",
+ "Ġtr uly",
+ "ĠS i",
+ "Ġwind ow",
+ "iqu es",
+ "ar io",
+ "æ² Ĵ",
+ "Ġloc ation",
+ "Î º",
+ "Ġì ľ",
+ "v i",
+ "ag ue",
+ "ĠS orry",
+ "Ġdis p",
+ "Ġhe ll",
+ "ĠÃ ī",
+ "Ġtr ade",
+ "Ġcrit ical",
+ "Ġê ±",
+ "Ġn amed",
+ "Ġprep ared",
+ "ĠH ouse",
+ "al u",
+ "Ġt ough",
+ "Ġtri p",
+ "Ġs and",
+ "c el",
+ "ü z",
+ "ĠP ut",
+ "Ġap art",
+ "is f",
+ "v is",
+ "Ġli br",
+ "a ven",
+ "Ġv ie",
+ "Ġeffect ive",
+ "ภ²",
+ "Ġmag n",
+ "Ġmuit o",
+ "Ġê µ",
+ "h al",
+ "Ġlim it",
+ "Ġn ine",
+ "Ġwill ing",
+ "ı ÅŁ",
+ "s p",
+ "еР³",
+ "h i",
+ "Ġal t",
+ "ĠJ an",
+ "Ġorig in",
+ "ĠU s",
+ "Ġele ments",
+ "Ġus es",
+ "Ġhelp ful",
+ "Ġfl at",
+ "Ġfam iliar",
+ "ĠP ark",
+ "Ġc ore",
+ "Ġclos er",
+ "Ġact ive",
+ "Ġad minist",
+ "C E",
+ "нÑĭ е",
+ "ç Ħ",
+ "Ġrel ative",
+ "Ġment al",
+ "Ġr andom",
+ "Ġpart ner",
+ "Ġut il",
+ "ph one",
+ "Ġr ule",
+ "w w",
+ "Ġìł ķ",
+ "Ġsch on",
+ "Ġco ffee",
+ "H A",
+ "Ġconnect ion",
+ "Ġun it",
+ "la ughing",
+ "l og",
+ "Ġapp l",
+ "л а",
+ "us ic",
+ "ĠB ra",
+ "Ġany where",
+ "AU DI",
+ "Ġsepar ate",
+ "bo x",
+ "Ġd ivid",
+ "Ġtest ing",
+ "Ġs ick",
+ "Ġwer en",
+ "ä» ĸ",
+ "Ġ׾ ×",
+ "Ġadv antage",
+ "Ġtrans fer",
+ "' .",
+ "Ġë ¹",
+ "Ġfind ing",
+ "н ой",
+ "Ġì¢ ĭ",
+ "Ġfor t",
+ "Ġeconom y",
+ "Ġl ack",
+ "Ġleav ing",
+ "Ġd im",
+ "å İ",
+ "ĠR es",
+ "Ø Ń",
+ "Ġdiscuss ion",
+ "еР¿",
+ "Ġg es",
+ "du ct",
+ "Ġch ain",
+ "Ġus ers",
+ "e ch",
+ "ÅĤ a",
+ "Ġdis h",
+ "Ġcare ful",
+ "Ġte acher",
+ "Ġopt im",
+ "Ġfl u",
+ "at ically",
+ "Ġref lect",
+ "Ġtreat ment",
+ "e ed",
+ "i ÄĻ",
+ "Ã ¹",
+ "à® ¾",
+ "Ġequ ip",
+ "Ġplan ning",
+ "Ġsol ve",
+ "ãģ Ŀ",
+ "ĠT om",
+ "Ġavo id",
+ "Ġp ou",
+ "Ġgreat er",
+ "l in",
+ "O L",
+ "ĠL u",
+ "ĠM ore",
+ "Ġatt ract",
+ "ê n",
+ "un a",
+ "Ġphot o",
+ "er ation",
+ "Ġplan et",
+ "Ġcop y",
+ "Ġvis ual",
+ "ir ing",
+ "Ġintern ational",
+ "Ġla ughing",
+ "Ġth ick",
+ "Ġhold ing",
+ "Ġbring ing",
+ "Ġlet ter",
+ "Ġb urn",
+ "Ġeffect s",
+ "it é",
+ "our s",
+ "O T",
+ "ê me",
+ "ĠSch ool",
+ "×ķ× ª",
+ "rop ri",
+ "l ig",
+ "α ι",
+ "Ġad ult",
+ "Ġsu gar",
+ "Ġr ide",
+ "Ġhigh light",
+ "Ġno body",
+ "Ġ2 1",
+ "Ġch at",
+ "ĠпÑĢ и",
+ "Ġin nov",
+ "ung en",
+ "Ġatt ach",
+ "ed om",
+ "å Ĭ",
+ "y l",
+ "Ġleg al",
+ "Ġr ice",
+ "Ġcoll abor",
+ "k ing",
+ "d own",
+ "æ Ļ",
+ "ãĤ Ĭ",
+ "Ġi h",
+ "ĠA c",
+ "ous ly",
+ "Ġr ap",
+ "Ġsol id",
+ "Ġgener ally",
+ "Ġpatter n",
+ "al i",
+ "ภŃ",
+ "Ġtrans l",
+ "in ter",
+ "a ult",
+ "Ġë ¨",
+ "Ġexp ress",
+ "Ġexam ples",
+ "Ġch ose",
+ "Ġtell s",
+ "ÃŃ s",
+ "ain t",
+ "ĠT ell",
+ "ĠMich ael",
+ "æ ¨",
+ "ĠN umber",
+ "Ġt ap",
+ "Ġexper iment",
+ "Ġbenef it",
+ "Ġì °",
+ "Ġse qu",
+ "Ġexp ensive",
+ "Ġgener ation",
+ "ĠM any",
+ "Ġadd ing",
+ "Ġk il",
+ "Ġcamp aign",
+ "ĠA nt",
+ "ra w",
+ "omm en",
+ "Ġs oul",
+ "j o",
+ "ĠAct ually",
+ "am m",
+ "ê² ł",
+ "Ġma xim",
+ "Ġsal t",
+ "Ġc ru",
+ "Ġcall ing",
+ "ãģ Į",
+ "Ġbas is",
+ "b an",
+ "Ġkeep ing",
+ "ĠM or",
+ "ed s",
+ "ì Ĩ",
+ "Ġto do",
+ "ам и",
+ "н Ñı",
+ "Ġli ved",
+ "ĠD u",
+ "ãĤ ī",
+ "å® ¶",
+ "for ce",
+ "å¹ ´",
+ "fer ence",
+ "al a",
+ "Ġocc ur",
+ "s k",
+ "Ġrec ent",
+ "Ġc ars",
+ "Ġtrad itional",
+ "ent le",
+ "² Ī",
+ "Ġhel d",
+ "Ġn ach",
+ "ĠCent er",
+ "er en",
+ "Ġb in",
+ "Ù ģ",
+ "Ġcomm e",
+ "Ġre ve",
+ "Ġìĺ ¤",
+ "Ġexpect ed",
+ "ab il",
+ "Ġfocus ed",
+ "o v",
+ "Ġi P",
+ "or ial",
+ "i ro",
+ "Ġet c",
+ "am ing",
+ "ĠS on",
+ "Ġy esterday",
+ "Ġstr ate",
+ "ĠÑ Ĩ",
+ "Ġë ı",
+ "p es",
+ "Ġactiv ity",
+ "Ġadv ice",
+ "Ġopen ing",
+ "f in",
+ "Ġre la",
+ "é ĸ",
+ "Ġinst ance",
+ "ĠEvery one",
+ "b l",
+ "p en",
+ "Ġvis ion",
+ "ĠA lex",
+ "if orn",
+ "Ġt ick",
+ "H e",
+ "Ġstrate gy",
+ "Ġk om",
+ "P E",
+ "ĠG l",
+ "Ġelect ric",
+ "1 5",
+ "Ġda ily",
+ "Ġhus band",
+ "Ġst ation",
+ "Ġanal ysis",
+ "yn am",
+ "Ġatt empt",
+ "Ġbill ion",
+ "v ant",
+ "Ġfor th",
+ "Ġm ath",
+ "al y",
+ "Ġbehav ior",
+ "ĠM as",
+ "k an",
+ "ĠD ay",
+ "Ġbl ess",
+ "Ġg ut",
+ "ĠH igh",
+ "o x",
+ "Ġd ress",
+ "Ġj ed",
+ "è ¯",
+ "å ĸ",
+ "Ġexperien ces",
+ "ist a",
+ "Ġfight ing",
+ "å ·",
+ "ĠÑģ к",
+ "Ġmost ly",
+ "a use",
+ "Ġpict ures",
+ "ен ÑĤ",
+ "Ġm ad",
+ "Ġmod els",
+ "ÑĪ е",
+ "ĠC ount",
+ "Å Ħ",
+ "ÅĤ o",
+ "ep t",
+ "O M",
+ "ĠA N",
+ "Ġtrou ble",
+ "4 0",
+ "Ġb ird",
+ "ul ate",
+ "Ġm ur",
+ "Ġprodu ce",
+ "Ġmar ried",
+ "b it",
+ "Ġthe ory",
+ "í ĺ",
+ "Ġlead er",
+ "ĠL ast",
+ "A A",
+ "è µ",
+ "Ġim ages",
+ "Ġexp and",
+ "ĠP or",
+ "Ġpur ch",
+ "ĠS an",
+ "ĠChrist mas",
+ "ĠAust ral",
+ "Ġw id",
+ "ĠM iss",
+ "Ġknow ing",
+ "Ġz e",
+ "s hip",
+ "k u",
+ "Ñħ од",
+ "ĠInst agram",
+ "ĠInd ia",
+ "Ġest a",
+ "ĠCal iforn",
+ "Ġ7 0",
+ "Ġdra g",
+ "Ġbr ush",
+ "Ġn ames",
+ "A nd",
+ "Ġy o",
+ "ill a",
+ "Ġsch ed",
+ "Ġdest roy",
+ "ye ar",
+ "Ġv amos",
+ "Ġ ÙĦ",
+ "ç a",
+ "Ġforg ot",
+ "и е",
+ "Ġra ise",
+ "re me",
+ "íķ ´",
+ "ĠG ive",
+ "Ġcont ain",
+ "ra b",
+ "Ġg ift",
+ "ĠÑģ п",
+ "Ġrequ est",
+ "Ġsh ut",
+ "Ġdeg rees",
+ "Ġbenef its",
+ "Ñĭ е",
+ "Ġstud ies",
+ "Ġend s",
+ "Ġevery where",
+ "Ġher o",
+ "op h",
+ "er ry",
+ "Ġmaterial s",
+ "en ed",
+ "N A",
+ "å į",
+ "Ġmu y",
+ "Ġwor se",
+ "ä» Ģ",
+ "ĠM ad",
+ "Ġdec isions",
+ "ion e",
+ "Ġfore ign",
+ "la ughter",
+ "i ber",
+ "ени Ñı",
+ "ãħ ĭ",
+ "Ġreal ized",
+ "Ġ ign",
+ "Ġwe ak",
+ "ĠÎ ¼",
+ "Ġsca red",
+ "Ġass um",
+ "A K",
+ "ï ¿",
+ "ï¿ ½",
+ "Ġcover ed",
+ "ĠS at",
+ "Ġо н",
+ "Ġindividual s",
+ "Ġcomp ared",
+ "1 1",
+ "ĠAd d",
+ "ic les",
+ "Ġc ert",
+ "r ar",
+ "Ġbr ief",
+ "Ġactiv ities",
+ "Ġf ab",
+ "b ar",
+ "Ġa st",
+ "ĠO ther",
+ "Ġclass es",
+ "Ġo g",
+ "Ġmiss ing",
+ "ãģ ł",
+ "é Ŀ",
+ "w ers",
+ "× ©",
+ "Ġintrodu ce",
+ "Ġequ ation",
+ "ãģ¾ ãģĻ",
+ "Ġn om",
+ "Ġpain ting",
+ "us hing",
+ "ĠA P",
+ "Ġencour age",
+ "Ġsh ip",
+ "itt ee",
+ "iver se",
+ "ot a",
+ "n am",
+ "ãĥ »",
+ "Ġexerc ise",
+ "ĠÐ Ń",
+ "Ġn as",
+ "Ġthous ands",
+ "ĠCaliforn ia",
+ "Ġs es",
+ "Ġr ow",
+ "ŀ Ī",
+ "Ġpand emic",
+ "Ġsk ill",
+ "b el",
+ "Ġdire ctor",
+ "Ġmil k",
+ "Ġn ut",
+ "Ġmot ion",
+ "Ġcl osed",
+ "è ¨",
+ "Ġcred it",
+ "ah r",
+ "Ġche ese",
+ "Ġal tern",
+ "im ately",
+ "Ġs ust",
+ "ĠT ra",
+ "Ġgl ad",
+ "Ġhigh ly",
+ "Ġw a",
+ "Ġredu ce",
+ "Ġb le",
+ "ad or",
+ "in ated",
+ "ion es",
+ "ci ent",
+ "Ġdep ending",
+ "Ġsh aring",
+ "Ġca ught",
+ "ra el",
+ "Ġme hr",
+ "Ġpass ion",
+ "ç Ľ",
+ "Ġr u",
+ "Ġfar m",
+ "T I",
+ "av es",
+ "ĠR ob",
+ "ĠB ro",
+ "Ġmot iv",
+ "ret ch",
+ "ru pt",
+ "ĠB ig",
+ "Ġall e",
+ "Ġet t",
+ "ub s",
+ "ĠJapan ese",
+ "ĠH all",
+ "и ли",
+ "AUDI BLE",
+ "ç ¬",
+ "Ġcell s",
+ "ik a",
+ "el ine",
+ "il er",
+ "Ġì £",
+ "Ġsk y",
+ "IN AUDIBLE",
+ "end e",
+ "ap ter",
+ "Ġp in",
+ "Ġg ather",
+ "h ol",
+ "le ction",
+ "Ġsy n",
+ "Ġpl ug",
+ "r ound",
+ "Ġun iversity",
+ "h ib",
+ "Ġfant astic",
+ "k n",
+ "Ġho le",
+ "ĠRem ember",
+ "in ct",
+ "ak s",
+ "C H",
+ "Ġbro ken",
+ "Ġstr ateg",
+ "Ġal ive",
+ "Ġt ank",
+ "Ġc art",
+ "r ated",
+ "r ie",
+ "ĠSt ep",
+ "ĠEvery thing",
+ "Ġb ound",
+ "Ġso bre",
+ "Ġcustom er",
+ "¡ Į",
+ "ur g",
+ "ĠB ill",
+ "L a",
+ "wh at",
+ "Ġre action",
+ "Ġs ession",
+ "Ġpl ans",
+ "ĠìĿ´ë łĩê²Į",
+ "Ġdown load",
+ "ì Ļ",
+ "u er",
+ "Ġc ab",
+ "Ġinst r",
+ "if ying",
+ "ĠN ice",
+ "Ġteam s",
+ "ı l",
+ "Ġgo als",
+ "is ch",
+ "Ġtrans port",
+ "Ġanim al",
+ "Ġcost s",
+ "Ġcall s",
+ "Ġse hr",
+ "ì Ī",
+ "ri an",
+ "Ġd ial",
+ "Ġwe ather",
+ "๠Ģ",
+ "Ġв оÑĤ",
+ "ĠPl ay",
+ "Ġsh ared",
+ "Ġsm ooth",
+ "ab a",
+ "Ġleav es",
+ "à® ©",
+ "Ġconc ent",
+ "Ġsh ift",
+ "ĠëIJ ĺ",
+ "ĠGo vern",
+ "Ġdem onst",
+ "Ġbut ter",
+ "ĠìĹ ¬",
+ "Ġsat isf",
+ "Īë ¬",
+ "Ġrecogn ize",
+ "ĠF rench",
+ "Ġvol ume",
+ "ä nd",
+ "Ñĥ м",
+ "Ġì§ Ħ",
+ "ĠKe ep",
+ "ow a",
+ "ipp ed",
+ "ÑģÑĤ ÑĢ",
+ "Ġdet ect",
+ "ĠÏ ĥ",
+ "Ġl ift",
+ "Ġcl othes",
+ "ĠSt op",
+ "Ã µ",
+ "m et",
+ "Ġcl in",
+ "Ġar r",
+ "f riend",
+ "Ġst uck",
+ "Y e",
+ "h and",
+ "um a",
+ "Ġsc ri",
+ "Ġfuck ing",
+ "ct ors",
+ "× ª",
+ "Ġjo ining",
+ "Ġc ette",
+ "ĠØ £",
+ "ĠWh ite",
+ "Ġi hr",
+ "Î Ń",
+ "ãģ Ń",
+ "Ġinclud ed",
+ "ess o",
+ "Ġac ad",
+ "b um",
+ "Ġs ab",
+ "Ġд лÑı",
+ "è¿ Ļ",
+ "uf act",
+ "ĠRep ublic",
+ "r im",
+ "Ġye llow",
+ "Ġlim ited",
+ "T ER",
+ "ĠT y",
+ "Ġnot es",
+ "v est",
+ "и з",
+ "al ed",
+ "Ġph ase",
+ "and a",
+ "ĠM om",
+ "R I",
+ "Ġim mer",
+ "m al",
+ "Ġin j",
+ "Ġy ang",
+ "ud ible",
+ "аР³",
+ "Ġset t",
+ "Ġmag ic",
+ "Ġens ure",
+ "Ġsp ring",
+ "Ġsh ock",
+ "Ġwhe el",
+ "ог да",
+ "ãĤ Ī",
+ "Ġcan cer",
+ "Ġro ot",
+ "Ð IJ",
+ "gen cy",
+ "Ġë į",
+ "i i",
+ "Ġout put",
+ "Ġcomm it",
+ "Ġwork ers",
+ "ìķĦ ìļĶ",
+ "ĠÑģ ам",
+ "ve y",
+ "Ġpe u",
+ "Ġc ivil",
+ "is c",
+ "Ġbr ings",
+ "ÑĢ ав",
+ "an ia",
+ "Ä ģ",
+ "c raft",
+ "mb ol",
+ "Ġintell ig",
+ "b i",
+ "ac ing",
+ "y ou",
+ "Ġbecom ing",
+ "ĠD er",
+ "em a",
+ "å°± æĺ¯",
+ "Ġing red",
+ "Ġcomm and",
+ "Ġupd ate",
+ "Ġpre m",
+ "Ġopen ed",
+ "Ħ ¤",
+ "ени е",
+ "Ġg ard",
+ "Ġstat ement",
+ "Ġsc rew",
+ "Ġpr ote",
+ "Ġc ards",
+ "Ġt ask",
+ "Ġeven ing",
+ "Ġst itch",
+ "in en",
+ "ĠB er",
+ "m ark",
+ "ĠD ad",
+ "Ġе ÑģÑĤÑĮ",
+ "Ġ× ŀ×",
+ "ìĹ Ī",
+ "Ġb an",
+ "Ġcl im",
+ "Ġfre edom",
+ "Ġnorm ally",
+ "еÑģ ÑĮ",
+ "å ¦",
+ "Ġprov ided",
+ "Ġìŀ IJ",
+ "ĠìķĦ ëĭĪ",
+ "ĠK im",
+ "ied er",
+ "ìĿ Į",
+ "Ġcit iz",
+ "Ġb ike",
+ "Ġb ak",
+ "Ġno ise",
+ "Ġcl imate",
+ "iz es",
+ "å¾ Į",
+ "Ġincre asing",
+ "ĠTH E",
+ "Ġli qu",
+ "Ġperson ally",
+ "e f",
+ "res p",
+ "Ġleg s",
+ "ind er",
+ "Ġp ed",
+ "Ġë§ İ",
+ "Ġdep end",
+ "Ġvar iety",
+ "ĠIs rael",
+ "Ġwas h",
+ "å Ĩ",
+ "Ġqu iet",
+ "ĠJ ames",
+ "ĠJ ew",
+ "Ġfore ver",
+ "ĠI nt",
+ "Ġcoun ter",
+ "ur ance",
+ "ĠAny way",
+ "ca re",
+ "ĠOn ly",
+ "ci ón",
+ "ad i",
+ "ĠE v",
+ "ëĭĪ ê¹Į",
+ "ĠÎ ±",
+ "Ġslow ly",
+ "Ġо д",
+ "Ġnot iced",
+ "ier en",
+ "Ġfe ll",
+ "ĠÐ ij",
+ "Ġm ême",
+ "Ġwhen ever",
+ "! )",
+ "ĠH y",
+ "å ¼",
+ "ord s",
+ "us ion",
+ "ĠSt ar",
+ "Ġí ĺ",
+ "ĠM ac",
+ "ä¸ Ĭ",
+ "i ven",
+ "Ġìĭ ľ",
+ "ĠìĹ Ĩ",
+ "ĠT ur",
+ "Ġg er",
+ "r is",
+ "Ġve z",
+ "Ġл Ñİ",
+ "Ġvers us",
+ "ا Ø",
+ "ocol ate",
+ "Ġplan e",
+ "Ġz o",
+ "Ġsu it",
+ "Th is",
+ "Ġn erv",
+ "ĠA cc",
+ "Ñĥ ж",
+ "ìĤ ¬",
+ "n h",
+ "em e",
+ "Ġa uss",
+ "Ġme as",
+ "Ġtr ès",
+ "Ï ī",
+ "Ñģ ли",
+ "ĠAr t",
+ "ĠSec ond",
+ "олÑĮ ко",
+ "ch o",
+ "it ect",
+ "е ÑģÑĤ",
+ "Ġb oss",
+ "Ġinc ome",
+ "ł ¤",
+ "Ġsh ad",
+ "Ġapp ropri",
+ "ĠM al",
+ "op t",
+ "Ġart ist",
+ "Ġplay s",
+ "oth ers",
+ "ĠIn ter",
+ "Ġvir us",
+ "Ġh ung",
+ "Ġconst ant",
+ "Ġscri pt",
+ "Ġsn ow",
+ "ul f",
+ "k et",
+ "Ġdev ices",
+ "Ġmet al",
+ "ight s",
+ "ìĦ ¸",
+ "Ġsal es",
+ "Ġve get",
+ "Ġcollect ion",
+ "Ġv ia",
+ "k er",
+ "Ġgot ten",
+ "O W",
+ "i én",
+ "Ġacc ur",
+ "Ġw ave",
+ "ult y",
+ "ĠA ir",
+ "Ġlead ing",
+ "ic ing",
+ "Ġcent ral",
+ "ĠChrist ian",
+ "f r",
+ "ĠAl though",
+ "Ġsong s",
+ "Ġf if",
+ "нÑĭ Ñħ",
+ "Ġbel ong",
+ "oss ible",
+ "ì °",
+ "Ġphot os",
+ "is l",
+ "Ġrela x",
+ "s a",
+ "US IC",
+ "ê ·",
+ "Ġman ufact",
+ "ĠTw itter",
+ "Ġdanger ous",
+ "Ġhy d",
+ "le ar",
+ "i ant",
+ "ĠâĢ ¦",
+ "Ġsudden ly",
+ "Ġla ugh",
+ "Ġang le",
+ "ĠG ot",
+ "Ġwor ried",
+ "о е",
+ "Ġp ap",
+ "ĠM art",
+ "en o",
+ "Ġbatter y",
+ "Ġп оÑģ",
+ "Ġlight s",
+ "Ġar ms",
+ "ĠA bs",
+ "m es",
+ "âĢ ĵ",
+ "use um",
+ "Ġte a",
+ "ĠM ic",
+ "Ġfor mer",
+ "ograph y",
+ "Ġapplic ations",
+ "ĠD ire",
+ "çĦ ¶",
+ "Ġfeed back",
+ "itch en",
+ "yor um",
+ "u ed",
+ "ig t",
+ "Æ° á»",
+ "os ition",
+ "ĠD el",
+ "Ġíķ ĺë",
+ "ĠB ack",
+ "ad s",
+ "Ġpr ime",
+ "ì£ ¼",
+ "ì£ ł",
+ "× ij",
+ "Ġm ut",
+ "] .",
+ "ĠÐ Ĺ",
+ "lo c",
+ "k in",
+ "Ġexper t",
+ "Ġal right",
+ "ung s",
+ "Ġsupp ly",
+ "Ġleaders hip",
+ "ĠF ra",
+ "Ġtyp ically",
+ "Ġs el",
+ "Ġtre es",
+ "Ġ2 2",
+ "h ar",
+ "Ġwor st",
+ "Ġbus y",
+ "ant o",
+ "ĠU p",
+ "ĠB as",
+ "Ġpresent ation",
+ "Ġstr ange",
+ "Ġth in",
+ "ÑĤ е",
+ "Ġveh icle",
+ "Ġд о",
+ "cell ent",
+ "7 0",
+ "Ġt ired",
+ "Ġcris is",
+ "Ġt iny",
+ "as y",
+ "Ġr an",
+ "é ĩ",
+ "Ġfor ces",
+ "Ġо Ñĩ",
+ "Ġident ify",
+ "Ġass ess",
+ "иÑĤ е",
+ "S E",
+ "Ġcreat ive",
+ "ç Ł",
+ "Ġdep artment",
+ "Ġinit ial",
+ "æĪij åĢij",
+ "ĠD am",
+ "ak t",
+ "v ere",
+ "Ġinf ect",
+ "Ġp ump",
+ "Ạ¡",
+ "Ġv iel",
+ "Ġr are",
+ "Ġd ot",
+ "ash ion",
+ "em pl",
+ "Ġf lex",
+ "Ġk on",
+ "Ġtr uck",
+ "Ġle ct",
+ "Ġpl astic",
+ "la w",
+ "Ġlik es",
+ "Ġr ough",
+ "ĠM AT",
+ "í ŀĪ",
+ "Ġcomm er",
+ "Ġas se",
+ "Ġc ake",
+ "Ġact ions",
+ "Ġad m",
+ "Ġother wise",
+ "ĠHe alth",
+ "Ġcoll e",
+ "à¹Ģ à¸",
+ "Ġr ub",
+ "å¾ Ĺ",
+ "æ Ķ",
+ "Ġsc r",
+ "Ġz um",
+ "ĠH im",
+ "Ġch amp",
+ "Ġconcern ed",
+ "Ġ5 00",
+ "Ġpl ate",
+ "ĠO ut",
+ "Ġdon c",
+ "Ġequip ment",
+ "Ġta ught",
+ "ll ed",
+ "Ġí Ļ",
+ "iv a",
+ "Ġmot or",
+ "Â »",
+ "Ġgu ide",
+ "å ī",
+ "Ġstop ped",
+ "Ġr at",
+ "Ġlab or",
+ "Ġa im",
+ "Ġprep are",
+ "ĠÑ Ī",
+ "Ġshoot ing",
+ "ann ed",
+ "cri pt",
+ "Ġen emy",
+ "Ġdep ends",
+ "Ġn av",
+ "Ġb er",
+ "Ġland s",
+ "Ġun ivers",
+ "i u",
+ "Ġfact or",
+ "ok ing",
+ "Ġcar bon",
+ "b ut",
+ "ĠL ove",
+ "el d",
+ "ĠÎ µ",
+ "Ġg a",
+ "Ġé s",
+ "Ġbre ad",
+ "Ġvol t",
+ "í Ĭ",
+ "Ġwas te",
+ "Ġkeep s",
+ "æī Ģ",
+ "Ġst or",
+ "Ġhon or",
+ "Ġun less",
+ "Ġcol um",
+ "Ġë ĮĢ",
+ "Ġpl ants",
+ "Ye ah",
+ "Ġinclud es",
+ "ä¸ Ń",
+ "Ġo x",
+ "Ġpe ut",
+ "ë§ Į",
+ "ìĥ ģ",
+ "ist ry",
+ "ภ±",
+ "ĠDep artment",
+ "ant a",
+ "Ġfing er",
+ "Ġst retch",
+ "Ġsy mbol",
+ "Ġneigh bor",
+ "æ ¬",
+ "ê° Ħ",
+ "~ ~",
+ "ĠÑĤ Ñĭ",
+ "ĠA ber",
+ "k es",
+ "Ġmass ive",
+ "ĠC H",
+ "ĠS al",
+ "× ł",
+ "ãĤ Ĵ",
+ "Ġd ynam",
+ "ach e",
+ "ĠP re",
+ "Ġmon itor",
+ "ent ed",
+ "E O",
+ "Ġrais ed",
+ "ist ics",
+ "Ú ©",
+ "Ġv ou",
+ "it en",
+ "¡ °",
+ "Ġbusiness es",
+ "Ġe arn",
+ "Ġmob ile",
+ "id ade",
+ "Ġha be",
+ "y r",
+ "l ict",
+ "Ġcon duct",
+ "Ġfed eral",
+ "Ġw o",
+ "b u",
+ "Ġn one",
+ "Ġteach ers",
+ "ĠاÙĦ Ø",
+ "éģ ĵ",
+ "id ents",
+ "ا ÙĦ",
+ "Ġtre nd",
+ "еР¶",
+ "Ġal bum",
+ "Ġm ich",
+ "b ased",
+ "ภµ",
+ "Ġtrans ition",
+ "Ġн о",
+ "õ es",
+ "h ost",
+ "ed y",
+ "ĠPro f",
+ "p an",
+ "ij n",
+ "Ġcapac ity",
+ "und o",
+ "Ġ× ij×",
+ "Ġbreat h",
+ "Ġм ен",
+ "Ġm ü",
+ "í Ļ",
+ "ĠA ut",
+ "hing ton",
+ "Ġn or",
+ "Ġg ain",
+ "po int",
+ "Y es",
+ "ĠØ ª",
+ "ĠN a",
+ "Ã¥ r",
+ "Ġi ç",
+ "ĠM ary",
+ "Ġsp in",
+ "Ġant i",
+ "åIJ §",
+ "Ġsome how",
+ "Ġlaw s",
+ "Ġmom ents",
+ "Ġg re",
+ "Ġmo ves",
+ "ĠW ould",
+ "Ġpred ict",
+ "Ġv ra",
+ "Ġ201 9",
+ "¶ Ħ",
+ "Ġfund ament",
+ "2 5",
+ "Ġp ure",
+ "Ġw ow",
+ "Ġis land",
+ "Ġinvest ment",
+ "Ġb ath",
+ "ĠY a",
+ "Ġhard er",
+ "Ġt ips",
+ "å Ĺ",
+ "Ġelect ron",
+ "ĠB ob",
+ "Ġb ond",
+ "od ies",
+ "ĠA ug",
+ "Ġgib t",
+ "Ġch air",
+ "Ġtw ice",
+ "w ood",
+ "Ġcl ar",
+ "Ġmas k",
+ "Ġhonest ly",
+ "Ġ201 8",
+ "t ies",
+ "' ,",
+ "Ġp ens",
+ "Ġsurpr ised",
+ "Ġcommunic ation",
+ "ãģ£ ãģ¦",
+ "Ġsp r",
+ "Ġwh ose",
+ "Ġst ars",
+ "× IJ×",
+ "ĠâĢ ĭ",
+ "Ġproper ly",
+ "Ġg rew",
+ "os ing",
+ "Ġdi vers",
+ "A D",
+ "Ġem pt",
+ "Ġexp ression",
+ "Ạ¿",
+ "ĠP al",
+ "ãģ Ĭ",
+ "Ġjust ice",
+ "Ġp air",
+ "w o",
+ "Ġse at",
+ "or ter",
+ "Ġlink s",
+ "ĠM er",
+ "Ġre nd",
+ "но е",
+ "up id",
+ "ĠH el",
+ "ĠM arch",
+ "ĠL o",
+ "Ñģ ÑĮ",
+ "Ġhas n",
+ "Ġev alu",
+ "ãģ ı",
+ "å¤ ©",
+ "il os",
+ "Ġfund ing",
+ "Ġv en",
+ "u an",
+ "ĠM aster",
+ "ĠO l",
+ "ĠF re",
+ "Ġy ap",
+ "ĠS ir",
+ "s ch",
+ "Ġmist ake",
+ "am an",
+ "Ġdin ner",
+ "ĠWas hington",
+ "Ġorganiz ations",
+ "Ġж е",
+ "av ing",
+ "Ġv ÃŃ",
+ "Ġbirth day",
+ "Ġbe ar",
+ "ĠÙ ģ",
+ "Ġaff ord",
+ "Ġre ven",
+ "Ġrelationship s",
+ "r ough",
+ "ĠT ime",
+ "Ġt ag",
+ "ĠS un",
+ "u ary",
+ "ĠP o",
+ "c ar",
+ "ab ilities",
+ "Ġpr ison",
+ "Ġl ic",
+ "ìł ķ",
+ "id den",
+ "Ġspec ies",
+ "é »",
+ "Ġf irm",
+ "Ġsc ore",
+ "Ġd it",
+ "Ġspe ct",
+ "Ġp el",
+ "Ġcompl icated",
+ "æ¨ £",
+ "Ġr ank",
+ "Ġoppos ite",
+ "Ġpick ed",
+ "Ġк он",
+ "el er",
+ "Ġm ig",
+ "ĠS l",
+ "ĠN et",
+ "Ġne ck",
+ "ĠFr ance",
+ "Ġtechn ical",
+ "ภ¡",
+ "Ġmil es",
+ "Ġprim ary",
+ "Ġse in",
+ "s es",
+ "Ġla ughs",
+ "b ra",
+ "ÅĽ ci",
+ "ri age",
+ "Ġn ic",
+ "et ers",
+ "ĠÃ ª",
+ "olog ies",
+ "ĠI S",
+ "r ad",
+ "ud o",
+ "ı nd",
+ "m ar",
+ "Ġex ch",
+ "Ġcompet ition",
+ "Ġauss i",
+ "ĠS erv",
+ "Ġre nt",
+ "Ġch ocolate",
+ "Ġw ieder",
+ "Ġnear ly",
+ "Ġspe ech",
+ "Ġun c",
+ "Ġpar am",
+ "ĠBrit ish",
+ "Ġrem ain",
+ "ภģ",
+ "ur t",
+ "ĠØ ¹",
+ "Ġcr ack",
+ "ail s",
+ "Ġprom ise",
+ "Ġpay ing",
+ "i ÃŁ",
+ "Ġad apt",
+ "ал а",
+ "Ġmov ies",
+ "Ġw ire",
+ "Ł ¬",
+ "æľ ĥ",
+ "Ġter rible",
+ "Ġs ó",
+ "Ġperfect ly",
+ "åij ¢",
+ "ord in",
+ "Ġj á",
+ "Ġimp ossible",
+ "ĠTh ree",
+ "Ġn h",
+ "Ġtur ning",
+ "r um",
+ "ĠB el",
+ "ig g",
+ "Ġrespons ible",
+ "и й",
+ "Ġincred ibly",
+ "w i",
+ "ian o",
+ "Ġhum ans",
+ "ĠÃ ĩ",
+ "Ġsetting s",
+ "Ġj oy",
+ "o ot",
+ "Ġdeal ing",
+ "ill ed",
+ "Ġsur round",
+ "Ġfollow ed",
+ "Ġposs ibly",
+ "Ġinit i",
+ "st en",
+ "Ġpr os",
+ "Ġcand id",
+ "Ġass ign",
+ "Ġviol ence",
+ "W ell",
+ "Ġr ise",
+ "P S",
+ "Ġtamb ém",
+ "Ġë ĵ¤",
+ "i ance",
+ "y an",
+ "Ġaud io",
+ "ĠB et",
+ "ĠAmeric ans",
+ "ĠAs s",
+ "is chen",
+ "ìŀ ħ",
+ "Ġult imately",
+ "Ġpol ic",
+ "Ġmajor ity",
+ "éĢĻ åĢĭ",
+ "ĠFin ally",
+ "er ap",
+ "Ġgu ard",
+ "ĠMAT T",
+ "Ġbr own",
+ "м и",
+ "Ġch a",
+ "ĠHo ly",
+ "Ġnerv ous",
+ "ipp ing",
+ "ÄĻ d",
+ "ĠS a",
+ "ĵ ľë",
+ "¶ Ģ",
+ "l ie",
+ "çľ Ł",
+ "Ġn uc",
+ "ĠA pr",
+ "é Ľ",
+ "ĠKore a",
+ "eg o",
+ "ĠCan ada",
+ "Ġkön nen",
+ "Ġcomp ar",
+ "Ġg anz",
+ "ĠM ais",
+ "Ġthem e",
+ "Ġk i",
+ "Ġdraw ing",
+ "az on",
+ "ĠO ff",
+ "t t",
+ "ĠW ind",
+ "Ġtod os",
+ "Ġob vious",
+ "на Ñı",
+ "I M",
+ "ĠÐ ł",
+ "we ll",
+ "Ġbl ow",
+ "Ġho ok",
+ "Ġcir cle",
+ "Ġë³ ´",
+ "Ġarch itect",
+ "ĠK r",
+ "Ġc ó",
+ "Ġprotect ion",
+ "eg a",
+ "å ĩ",
+ "Ġwatch ed",
+ "Ġans wers",
+ "Ġdi et",
+ "iv o",
+ "Ġpow der",
+ "Ġyour s",
+ "Ġhigh est",
+ "çĤ º",
+ "F F",
+ "å º",
+ "Ġbo ys",
+ "ö yle",
+ "Ġl unch",
+ "è¬ Ŀ",
+ "ĠI I",
+ "Ġset s",
+ "Ġmo le",
+ "Û ģ",
+ "Ġwin ter",
+ "Ġluck y",
+ "Ġrespons ibility",
+ "Ġsign al",
+ "Ġwond ering",
+ "Ġa x",
+ "Ġcook ing",
+ "ов оÑĢ",
+ "le g",
+ "Ġп оÑĤ",
+ "Ġsurpr ise",
+ "Ġdem ocr",
+ "Ġlo op",
+ "Ġj ag",
+ "Ġcur ious",
+ "Ġmarket ing",
+ "Ð Ŀ",
+ "ar on",
+ "ĠApp le",
+ "Ġvirt ual",
+ "Ġ19 8",
+ "no on",
+ "ĠM et",
+ "оÑģ ÑĤо",
+ "об Ñĭ",
+ "it u",
+ "ĠA w",
+ "Ġbu ying",
+ "Ġrestaur ant",
+ "ĠB ud",
+ "Ġdou bt",
+ "Ġgr ant",
+ "Ġver d",
+ "Ġc ash",
+ "Ġfac ulty",
+ "Th at",
+ "ĠE in",
+ "å¤ ļ",
+ "Ġw ed",
+ "it ness",
+ "ĠM ag",
+ "n el",
+ "Ġn arr",
+ "Ġacc ident",
+ "Ġmed ium",
+ "em ents",
+ "Ġcr ow",
+ "n ight",
+ "ìĿ ¼",
+ "ä¹ Ł",
+ "Ġlibr ary",
+ "аÑİ ÑĤ",
+ "Ġtamb ién",
+ "Ġrefer ence",
+ "Ġfour th",
+ "h ouse",
+ "v ention",
+ "Ġfill ed",
+ "ĠC our",
+ "ib r",
+ "Ġn g",
+ "Ġdevelop ing",
+ "Ġprov ides",
+ "Ġpo ll",
+ "Ġtra ffic",
+ "arent ly",
+ "à® Ł",
+ "Ġform s",
+ "Ġcl ient",
+ "Ġg entle",
+ "Ġmus s",
+ "ĠCong ress",
+ "ĠInd ian",
+ "ce an",
+ "Ġp il",
+ "Ġc zy",
+ "st ood",
+ "ut y",
+ "Ġn ä",
+ "Ġsp ending",
+ "Ġconst ruction",
+ "ina udible",
+ "Ġë§ Ī",
+ "Īë¬ ´",
+ "Ġìĥ Ŀ",
+ "om a",
+ "os en",
+ "ag o",
+ "Ġlar gest",
+ "ãħĭ ãħĭ",
+ "Ġun iverse",
+ "b es",
+ "os a",
+ "Ġе го",
+ "Ġd ude",
+ "ĠM AR",
+ "Ġind eed",
+ "ε ι",
+ "Ġman aged",
+ "ĠSh ould",
+ "S o",
+ "Ġappl ied",
+ "Ġfair ly",
+ "ĠD en",
+ "Ġanal y",
+ "Ġconst antly",
+ "Ñģ п",
+ "H ow",
+ "ĠS ay",
+ "en cies",
+ "ĠP C",
+ "Ġegg s",
+ "à® °",
+ "Ġet h",
+ "ĠEnt ão",
+ "in ar",
+ "i ot",
+ "Ġc z",
+ "ĠEurope an",
+ "ãģ Ī",
+ "ĠA M",
+ "Ġc á",
+ "Ġrad io",
+ "§ Į",
+ "Ġh ide",
+ "ä» Ĭ",
+ "ĠSt art",
+ "Ġcl ub",
+ "ĠH ope",
+ "Ġeff orts",
+ "lus ion",
+ "Ġc ities",
+ "h one",
+ "Ġreach ed",
+ "Ġgu id",
+ "ro id",
+ "Ġhar m",
+ "Ġcut ting",
+ "Ġb ul",
+ "1 8",
+ "i est",
+ "ĠMe x",
+ "Ġ iron",
+ "çŁ ¥",
+ "Ġafter noon",
+ "Ġha ll",
+ "Ġpr zy",
+ "Ġg osh",
+ "Ġinflu ence",
+ "Ġв ид",
+ "Ġincre ased",
+ "ĠMin ister",
+ "Ġdis ci",
+ "ĠP eter",
+ "Ġver t",
+ "Ġmen u",
+ "Ġse lling",
+ "ur ally",
+ "Ġqu ote",
+ "ĠÂ ¡",
+ "Ġcontin ues",
+ "mp re",
+ "ĠÅŁ ey",
+ "it ution",
+ "Ġна Ñģ",
+ "c les",
+ "ĠGerm an",
+ "c zy",
+ "ĠÐ £",
+ "B e",
+ "Ġk itchen",
+ "ĠT ry",
+ "i pe",
+ "Ġic on",
+ "ar p",
+ "Ġprov iding",
+ "ĠTr ans",
+ "Ġtechn ique",
+ "Ġh är",
+ "Ġinf rast",
+ "Ġsus p",
+ "ü ck",
+ "ic ip",
+ "ĠÐ ķ",
+ "Ġc in",
+ "ìĸ ´ë",
+ "Ġpr z",
+ "Ġcompon ent",
+ "Ġby e",
+ "ĠB ible",
+ "iz er",
+ "C h",
+ "Ġsol utions",
+ "Ġaccom pl",
+ "Ġ201 6",
+ "I E",
+ "ĠT a",
+ "Ġass ume",
+ "Ġliqu id",
+ "Ġë¨ ¹",
+ "Ġquar ter",
+ "Ġfem ale",
+ "ĠTh ink",
+ "Ġstat us",
+ "it ute",
+ "Ġco ach",
+ "Ġre in",
+ "Ġcomb ination",
+ "è ·",
+ "ĠT er",
+ "Ġobject s",
+ "Ġdist rict",
+ "Ġmake up",
+ "Ġmur der",
+ "w as",
+ "f en",
+ "Ġbow l",
+ "Ġpub lished",
+ "Ġsp orts",
+ "ãģ ¡",
+ "Ġident ity",
+ "Ġseem ed",
+ "Ġact ing",
+ "л Ñİ",
+ "ri x",
+ "Ġup load",
+ "Ġh ast",
+ "Ġbo at",
+ "ĠM od",
+ "ri o",
+ "Ġ =",
+ "Ġcy cle",
+ "¯ ¸",
+ "Ġl oud",
+ "ust ed",
+ "com ing",
+ "Ġ201 7",
+ "Ġon t",
+ "Ġleg isl",
+ "Ġst ruct",
+ "ĠSomet hing",
+ "Ġconf lict",
+ "Ġu pper",
+ "Ġman ager",
+ "Ġm ort",
+ "Ġf ra",
+ "ĠÄ °",
+ "ĠM ike",
+ "ĠW ork",
+ "Ġn ó",
+ "ph ere",
+ "ĠìĤ ¬ë",
+ "ĠL and",
+ "Ġfil ter",
+ "Ġprom ot",
+ "æ °",
+ "æĻ Ĥ",
+ "ķ ¼",
+ "Ġrecord ing",
+ "× Ŀ",
+ "Ġassoci ated",
+ "Ġf uel",
+ "und er",
+ "Ġele ction",
+ "Ġemploy ees",
+ "ĠCom p",
+ "ÑĢÑĥ г",
+ "ĠW o",
+ "ro l",
+ "Ġsa ved",
+ "ĠH on",
+ "ĠV i",
+ "åĪ Ĩ",
+ "ac a",
+ "p ret",
+ "Ġw et",
+ "Ġst upid",
+ "Ġl ad",
+ "Ġf est",
+ "Ġw ake",
+ "Ġи н",
+ "Ġgreat est",
+ "ĠJ im",
+ "Ġserious ly",
+ "Ġì ¹",
+ "Ġfeel ings",
+ "Ġ3 00",
+ "i ation",
+ "Ġbeaut y",
+ "Ġìŀ ĺ",
+ "Ġs an",
+ "ĵ ł",
+ "Ġ- (",
+ "Ġcons cious",
+ "Ġд ел",
+ "b ye",
+ "ç Ļ",
+ "M an",
+ "Ġlet s",
+ "Ġsho es",
+ "y d",
+ "ä¹ Ī",
+ "Ġdisapp e",
+ "ĠCount y",
+ "ĠSc ott",
+ "Ġbut t",
+ "Ġaqu ÃŃ",
+ "Ġconf ig",
+ "resp ond",
+ "LAU GH",
+ "© ëĭĪëĭ¤",
+ "Ġdivid ed",
+ "Ġac qu",
+ "Ġz one",
+ "Ġk omm",
+ "a ção",
+ "ì§ ľ",
+ "c ut",
+ "Ġ2 3",
+ "Ġmaxim um",
+ "ro g",
+ "Ġrun s",
+ "Ġcompon ents",
+ "Ġarri ved",
+ "Ġconf ident",
+ "ÑĢ ов",
+ "Ġhe ight",
+ "Ġpro ced",
+ "E M",
+ "ĠÐŃ ÑĤо",
+ "ĠM en",
+ "Ġtalk s",
+ "Ġconf idence",
+ "ĠChr is",
+ "Ġlead s",
+ "Ġn ose",
+ "f all",
+ "b b",
+ "ĠNot hing",
+ "is er",
+ "Ġindepend ent",
+ "Ġmin or",
+ "Ġsy m",
+ "l en",
+ "ci ence",
+ "Ġf ashion",
+ "Ġsex ual",
+ "Ġb un",
+ "h ere",
+ "Ġso il",
+ "Ġdies e",
+ "Ġsh ap",
+ "Ġempt y",
+ "Ġjour nal",
+ "ag on",
+ "ĠThe ir",
+ "Ġweek end",
+ "ÃŃ t",
+ "Ġer ror",
+ "Ġn ar",
+ "Ã ¸",
+ "è ©",
+ "an cy",
+ "Ġìķ Ĭ",
+ "Ġfore st",
+ "Ġha cer",
+ "Ġmiss ed",
+ "ãģ ķ",
+ "åı¯ 以",
+ "Ġev il",
+ "Ġstor age",
+ "Ġsing ing",
+ "in ha",
+ "Ġkn ock",
+ "Ġimp ress",
+ "ĠоÑĩ енÑĮ",
+ "ĠGo ld",
+ "ĠS ur",
+ "ĠP ort",
+ "åİ »",
+ "ĠL ond",
+ "Ġfaz er",
+ "ot y",
+ "ot o",
+ "Ġan x",
+ "ĠWill iam",
+ "Ġexist ing",
+ "pl ace",
+ "ĠC D",
+ "Î ³",
+ "ĠColl ege",
+ "l or",
+ "ĠE ast",
+ "s en",
+ "f ach",
+ "o ft",
+ "Ġexperien ced",
+ "Ġlo ves",
+ "im m",
+ "Ġpo ly",
+ "Ġes se",
+ "ì ¤",
+ "ĠG rand",
+ "è §",
+ "ch er",
+ "Ġvict im",
+ "ĠG es",
+ "л ÑĮ",
+ "v ision",
+ "Ġt all",
+ "Ġl ens",
+ "Ġз на",
+ "ĠB oth",
+ "Ġì ²",
+ "Ġsust ain",
+ "Ġarg ument",
+ "Ġfact ors",
+ "Ġautom atically",
+ "Ġfr uit",
+ "Ġli ber",
+ "Ġa le",
+ "ĠP ress",
+ "ĠB a",
+ "ĠÐ ³Ð¾",
+ "Ġhundred s",
+ "th at",
+ "ĠR ich",
+ "Ġreci pe",
+ "ĠI T",
+ "è ĩ",
+ "Ạ¥",
+ "Ġdescri be",
+ "Ġdri ver",
+ "ĠO ct",
+ "ĠM at",
+ "д е",
+ "Ġme al",
+ "Ġlat est",
+ "Ġth erap",
+ "Ġcomp are",
+ "ĠAm azon",
+ "Ġì¢ Ģ",
+ "ĠRuss ia",
+ "Ġstr ing",
+ "Ġk a",
+ "ĠComm un",
+ "Ġd ia",
+ "I s",
+ "Ġmill ions",
+ "Ġcor por",
+ "Ġcor respond",
+ "Ġfix ed",
+ "ĠJo e",
+ "Ù İ",
+ "Ġview s",
+ "Ġr iver",
+ "Ġstud io",
+ "ig ger",
+ "Ġfl avor",
+ "Ġpres ence",
+ "Ġun its",
+ "Ġsa ving",
+ "av our",
+ "Ġp esso",
+ "or ith",
+ "Ġh ers",
+ "ĠN at",
+ "as ion",
+ "ĠFr ank",
+ "о ÑĪ",
+ "ÅĤ y",
+ "í Ħ",
+ "Ġein em",
+ "Ġfun ctions",
+ "um an",
+ "Ġn orth",
+ "Ġìł Ħ",
+ "Ġhor se",
+ "v id",
+ "Ġple asure",
+ "а ÑĪ",
+ "é es",
+ "ind a",
+ "Ġt ail",
+ "Ġexpl ore",
+ "S T",
+ "Ġcommer cial",
+ "ĠD uring",
+ "ar l",
+ "] :",
+ "f it",
+ "Ġr ates",
+ "æ ³",
+ "M USIC",
+ "Ġhous ing",
+ "Ġein er",
+ "Ġsitu ations",
+ "æ ĭ",
+ "Ġdec re",
+ "Ġappropri ate",
+ "ен но",
+ "% .",
+ "Ġb ac",
+ "Ġw at",
+ "ens ity",
+ "ä h",
+ "kn own",
+ "it z",
+ "Ġemot ional",
+ "erv ation",
+ "Ġbl ind",
+ "1 6",
+ "í ĥ",
+ "大 家",
+ "Ġjo ined",
+ "Ġloc ated",
+ "ĠÑģ м",
+ "ad as",
+ "ber g",
+ "Ġd ess",
+ "Ġde ar",
+ "ed en",
+ "c os",
+ "Ġad opt",
+ "1 00",
+ "ow e",
+ "ĠChe ck",
+ "ism o",
+ "Ġsim pl",
+ "Ġang ry",
+ "Ġмен Ñı",
+ "ĠC am",
+ "Ġp ad",
+ "Ġatt end",
+ "Ġsam ple",
+ "æĹ ¥",
+ "Ġì Ľ",
+ "ĠI N",
+ "ul ous",
+ "ĠS ar",
+ "ĠSh ow",
+ "Ġinfrast ructure",
+ "ĠAug ust",
+ "Ġless on",
+ "Ġn iet",
+ "æ İ",
+ "Ġfo i",
+ "Ġbro ke",
+ "t r",
+ "ç ķ",
+ "Ġ4 5",
+ "Ġg ew",
+ "Ñĥ п",
+ "at i",
+ "Ġmaint ain",
+ "Ġart ists",
+ "ing er",
+ "æĿ ¥",
+ "er ved",
+ "I A",
+ "Ġequ als",
+ "Ġoper ation",
+ "ill y",
+ "ĠëĤ ´",
+ "Ġcrow d",
+ "Ġintern al",
+ "Ġtest s",
+ "ĠR ock",
+ "ĠC ons",
+ "ĠëĦ Ī무",
+ "w ar",
+ "Ġs ou",
+ "Ġch art",
+ "ĠJ une",
+ "ĠApr il",
+ "g ent",
+ "Ġv ent",
+ "Ġqu and",
+ "ĠKore an",
+ "im o",
+ "ç ī",
+ "id ers",
+ "Ġmount ain",
+ "ÑģÑĤ ав",
+ "æľ Ī",
+ "ij k",
+ "Ġdiscover ed",
+ "ĠS und",
+ "ĠS il",
+ "Ġso lo",
+ "Â ´",
+ "Ġsch ol",
+ "ĠE ach",
+ "ç µ",
+ "Ġb are",
+ "Ġí Į",
+ "ĠvÃŃ de",
+ "Ġingred ients",
+ "ĠIt s",
+ "Ŀ¼ ê³ł",
+ "Ġì Ĭ",
+ "Ï į",
+ "ĠLe e",
+ "Ġsc ary",
+ "Ġprinci p",
+ "Ġspirit ual",
+ "ì ħ",
+ "ĠH old",
+ "æ²Ĵ æľī",
+ "Ġdef ine",
+ "ĠL es",
+ "ĠN or",
+ "ĠE nd",
+ "Ġbl og",
+ "ĠG reen",
+ "аеÑĤ ÑģÑı",
+ "p art",
+ "el es",
+ "äº ĭ",
+ "ĠUnd er",
+ "Ġpart e",
+ "Ġ3 5",
+ "Ġse ctor",
+ "ĠS ept",
+ "Ġaut h",
+ "à® ®",
+ "om in",
+ "Ġcl ients",
+ "Ġc i",
+ "ĠFr iday",
+ "er as",
+ "Ġtw e",
+ "ul ated",
+ "Ġcult ural",
+ "ĠÑģв о",
+ "Ġëį Ķ",
+ "ĠÃ º",
+ "Ġpar ce",
+ "à® ²",
+ "Ġtrad ition",
+ "Ġjud ge",
+ "ĠGen eral",
+ "Ġdeterm ine",
+ "ĠIs n",
+ "ĠP L",
+ "ne ath",
+ "Ġmatter s",
+ "íķ ´ì",
+ "! ]",
+ "а Ñħ",
+ "Ġpo ol",
+ "Ġvari able",
+ "Ġvacc ine",
+ "Ġcaus ed",
+ "Ġw est",
+ "ĠY ep",
+ "f ast",
+ "Ġph ilos",
+ "hor a",
+ "Ġcontinu ed",
+ "Ġunf ortunately",
+ "ãģ į",
+ "æ ķ",
+ "Ġfl ight",
+ "Ġw rap",
+ "Ġhu h",
+ "ĠAbs olutely",
+ "Ġp ink",
+ "Ġrem ains",
+ "Ġn é",
+ "Ġf le",
+ "ĠS ol",
+ "Ġlos ing",
+ "Ġalg orith",
+ "Ġrequ ires",
+ "Ġfound ation",
+ "ĠB ur",
+ "Ġprofess ion",
+ "ĠM id",
+ "Ġë ŃIJ",
+ "c an",
+ "ĠM il",
+ "Ġyoung er",
+ "Ġappe ars",
+ "ter m",
+ "íķĺ ê³ł",
+ "ac le",
+ "ĠLond on",
+ "Ġengine ering",
+ "ภ¢",
+ "Ġadv ent",
+ "ìĦ¸ ìļĶ",
+ "Ġê¸ °",
+ "ĠM aj",
+ "ÑĢ ем",
+ "ing u",
+ "ĠU K",
+ "u ro",
+ "s pe",
+ "Ġt ent",
+ "Ġreport ed",
+ "ĠA L",
+ "H ey",
+ "Ġë§ IJ",
+ "Ġd ent",
+ "ĠAustral ia",
+ "ĠJan uary",
+ "³ ´",
+ "ag ues",
+ "ars h",
+ "r ig",
+ "Ġtien e",
+ "ภ£",
+ "Î ®",
+ "Ġmach en",
+ "un te",
+ "Ñĥ Ñģ",
+ "Ġelect r",
+ "Ġtut orial",
+ "Ġpl aced",
+ "ĠìĿ´ ê±°",
+ "ĠCoun cil",
+ "í ĸĪ",
+ "°ë ¦¬",
+ "ah ren",
+ "Ġê·¸ë ŀĺ",
+ "Ġpro ve",
+ "f ol",
+ "Ġqu er",
+ "Ġche ap",
+ "ĠF ather",
+ "ĠP ower",
+ "ĵ ľ",
+ "Ġpur s",
+ "Ġes p",
+ "ĠB re",
+ "ê¸ °ë",
+ "om as",
+ "æĥ ³",
+ "ил ÑĮ",
+ "Ġge ht",
+ "os ter",
+ "ê³ ¼",
+ "Ġfil es",
+ "ĠÐ §",
+ "be ll",
+ "Ġwh om",
+ "Ġë ĺ",
+ "Ġex cellent",
+ "Ġdat ab",
+ "Ġg ö",
+ "Ġì§Ħ ì§ľ",
+ "Ġbelie f",
+ "j et",
+ "Ġj ack",
+ "Ġsw im",
+ "ri al",
+ "um in",
+ "a uc",
+ "Ġso ll",
+ "Ġess ential",
+ "íķĺ ëĬĶ",
+ "Ġev ol",
+ "cha ft",
+ "ain e",
+ "th let",
+ "Ġinc or",
+ "Ġreport s",
+ "Ġdefin ition",
+ "ke l",
+ "Ġcirc um",
+ "Ġprodu ced",
+ "Ġ× Ľ",
+ "ant ic",
+ "n et",
+ "Ġa ward",
+ "Ġd urch",
+ "Ġtrans p",
+ "Ġm ale",
+ "¦ ¬ë",
+ "Ġmo on",
+ "ĠGe orge",
+ "Ġfly ing",
+ "i ó",
+ "Ġs ources",
+ "Ġpl enty",
+ "ĠDem ocr",
+ "R O",
+ "Ġ 00",
+ "Ġsec ure",
+ "ĠB ir",
+ "ra in",
+ "Ġz ur",
+ "Ġeffic ient",
+ "Ġrepe at",
+ "Ġmethod s",
+ "Ġcal m",
+ "Ġdiscuss ed",
+ "ĠìŀĪ ëĬĶ",
+ "Ġser ver",
+ "an ie",
+ "ĠInst ead",
+ "Ġide al",
+ "Ġcon ven",
+ "Ġhop ing",
+ "ĠT or",
+ "Ġdep th",
+ "Ġhe aven",
+ "EN CE",
+ "Ġhab it",
+ "gr ad",
+ "Ġfl ag",
+ "Ġin e",
+ "Ġk h",
+ "ĠL I",
+ "Ġfac ing",
+ "ĠA U",
+ "ĠT im",
+ "Ġg em",
+ "ĠJ ul",
+ "Ġel a",
+ "iz za",
+ "Ġfe llow",
+ "Ġqu el",
+ "Ġsp oke",
+ "Ġcitiz ens",
+ "u ge",
+ "é ĥ½",
+ "Ġp ages",
+ "Ġf asc",
+ "Ġrelig ious",
+ "at en",
+ "Ġch apter",
+ "ĠV al",
+ "Ġcons ult",
+ "ĠM ill",
+ "g l",
+ "op er",
+ "Ġinf in",
+ "Ġmar riage",
+ "Ġmedic ine",
+ "Ġд в",
+ "Ġdog s",
+ "Ġinstr ument",
+ "ĠEx act",
+ "á n",
+ "Ġ20 21",
+ "Ġf er",
+ "Ġwe alth",
+ "Ġgr ade",
+ "Ñĭ Ñħ",
+ "Ġcr ime",
+ "Ġth read",
+ "Ġess a",
+ "Ġw ine",
+ "co hol",
+ "ph a",
+ "ภĩ",
+ "og ue",
+ "Ġins urance",
+ "arr ator",
+ "ĠSept ember",
+ "Ġv id",
+ "ĠSp irit",
+ "Ġg est",
+ "ĠRuss ian",
+ "Ġproper ties",
+ "Ġart icle",
+ "Ġunder neath",
+ "y er",
+ "Ġjo int",
+ "Ġrelative ly",
+ "Ġin ch",
+ "Ġdesp ite",
+ "ĠG ree",
+ "Ġclass ic",
+ "Ġsupport ing",
+ "Ġinst ruct",
+ "lus ive",
+ "Ġdi agn",
+ "æ Ĭ",
+ "Ġadminist ration",
+ "аб оÑĤ",
+ "ĠO pen",
+ "æīĢ 以",
+ "Ġп ок",
+ "Ġdoll ar",
+ "Ġconse qu",
+ "o ber",
+ "ĠGerm any",
+ "Ġter r",
+ "ĠQ U",
+ "ĠÐ ĵ",
+ "ç ¾",
+ "Ġstrong er",
+ "É Ļ",
+ "ĠÙ Ĭ",
+ "ĠiP hone",
+ "Ġfab ric",
+ "ü h",
+ "Ġen em",
+ "æ ¯",
+ "Ġsub t",
+ "E E",
+ "ond e",
+ "Ġcre w",
+ "Ġremo ved",
+ "Ġl ady",
+ "Ġpot entially",
+ "ĠÐĿ о",
+ "y al",
+ "Ġsym pt",
+ "Ġar my",
+ "Ġintrodu ced",
+ "t es",
+ "Ġaspect s",
+ "1 4",
+ "ĠL ou",
+ "Ġ )",
+ "Ġde ploy",
+ "p et",
+ "Ġh an",
+ "ĠW atch",
+ "Ġweap ons",
+ "Ġph en",
+ "Ġreg ister",
+ "Ġein fach",
+ "Ġsp ort",
+ "Ġbr idge",
+ "Ġin ner",
+ "Ġminim um",
+ "Ġw itness",
+ "Ġes o",
+ "Ġvill age",
+ "Ġown er",
+ "¦¬ ê³ł",
+ "Ġsc ream",
+ "il ed",
+ "Ġp itch",
+ "b ru",
+ "Ġadv ance",
+ "ä¸į æĺ¯",
+ "Ġsupp ose",
+ "ĠAt t",
+ "еÑĤ ÑģÑı",
+ "Ġdiffer ences",
+ "ak ed",
+ "Ġinter pret",
+ "Ã ¦",
+ "iend o",
+ "Ġabs ol",
+ "ĠбÑĥд еÑĤ",
+ "Ġë ²",
+ "Ġtri al",
+ "Ġthink s",
+ "ly ing",
+ "cept ion",
+ "ĠAfric an",
+ "Ġchem ical",
+ "Ġta pe",
+ "Ġconvers ations",
+ "Ġdistrib ution",
+ "t i",
+ "ĠA I",
+ "Ġfl ash",
+ "Ġunder stood",
+ "ĠGovern ment",
+ "å° ı",
+ "! ?",
+ "ĠS k",
+ "ê± °ë",
+ "ri er",
+ "T S",
+ "ĠAcc ording",
+ "Ñİ ÑĤ",
+ "Ġsp ons",
+ "ÑĤ обÑĭ",
+ "Ġval u",
+ "ere m",
+ "icht ig",
+ "Ġresist ance",
+ "ĠG al",
+ "ger y",
+ "Ġbeg ins",
+ "Ġadv anced",
+ "Ġrele vant",
+ "Ġpolit ics",
+ "ĠF am",
+ "Ġç ok",
+ "ĠN ever",
+ "ill ing",
+ "Ġfoot ball",
+ "и и",
+ "ĠI D",
+ "ĠAfric a",
+ "Ġfing ers",
+ "Ġб олÑĮ",
+ "ĠÃ ¡",
+ "Ġcl ip",
+ "ĠL at",
+ "ãĤ Ħ",
+ "Ġì§Ģ ê¸Ī",
+ "es se",
+ "Ġvo or",
+ "Ġas ide",
+ "æ ŀ",
+ "Ġto ward",
+ "Ġb at",
+ "Ġval id",
+ "ĠM ens",
+ "Ġcomplet ed",
+ "ı ģ",
+ "Ġpod cast",
+ "ĠB on",
+ "Û Ĵ",
+ "ĠJ uly",
+ "il a",
+ "Ġpack age",
+ "Ġpull ed",
+ "ch ar",
+ "ĠM el",
+ "o is",
+ "Ġs outh",
+ "Ġë Ķ",
+ "Ġimport ance",
+ "Ġp ushing",
+ "Ġis ol",
+ "Ġstand s",
+ "c ill",
+ "ä ¼",
+ "Ġ ðŁ",
+ "or i",
+ "ê° ģ",
+ "Ġhom es",
+ "Ġconcern s",
+ "Ġb iz",
+ "å ½",
+ "b ie",
+ "Ġb is",
+ "Ġge ar",
+ "ĠM S",
+ "Ġh un",
+ "ĠM att",
+ "Ạ£",
+ "se y",
+ "ĠSec ret",
+ "Ġod d",
+ "ĠM ax",
+ "oll y",
+ "f ord",
+ "ĠS H",
+ "Ġrepl ace",
+ "Ġnav ig",
+ "Ġin i",
+ "и Ñı",
+ "Ġgi ant",
+ "Ġma nd",
+ "ĠH app",
+ "TI ON",
+ "g un",
+ "iam o",
+ "ìŀħ ëĭĪëĭ¤",
+ "Ġg ap",
+ "Ġê tre",
+ "Ġclass room",
+ "Ġhy p",
+ "ak i",
+ "è ®",
+ "is ters",
+ "ack s",
+ "ĠÑģ о",
+ "Ġb ug",
+ "Ġgra v",
+ "am in",
+ "Ġevery day",
+ "Ġì ¡°",
+ "Ġgard en",
+ "ce mber",
+ "Ġest o",
+ "åĹ İ",
+ "Ø ¬",
+ "Ł °",
+ "å ģ",
+ "Ġr om",
+ "Ġìłľ ê°Ģ",
+ "Ġfall ing",
+ "Ġfa ult",
+ "ell y",
+ "Ġch est",
+ "Ġл и",
+ "Ġpot ato",
+ "Ġbuild ings",
+ "Ġoper ating",
+ "Ġp are",
+ "w r",
+ "D on",
+ "ĠF our",
+ "Ġv ul",
+ "Ġl á",
+ "Ġfr ust",
+ "ĠD ann",
+ "ol es",
+ "ny a",
+ "Ġì ¶",
+ "ĠÑĢ аÑģ",
+ "× Ľ",
+ "Ġa ÃŃ",
+ "w ord",
+ "Ġweap on",
+ "Ġob t",
+ "ĠF all",
+ "ĠSte ve",
+ "Ġmix ed",
+ "Ġp ode",
+ "ĠA S",
+ "ĠL eg",
+ "Ġdes c",
+ "Ġspl it",
+ "Ġemer gency",
+ "ĠS ing",
+ "Ġprof it",
+ "Ġtyp ical",
+ "ĠDon c",
+ "Ġannoun ce",
+ "ĠTe x",
+ "Ġsac r",
+ "tern al",
+ "Ġcomm ittee",
+ "ig o",
+ "Ġdi am",
+ "ph as",
+ "Ġdef e",
+ "ĠProf ess",
+ "Ġdec l",
+ "Ñĥ ÑĢ",
+ "2 2",
+ "ol f",
+ "ĠM ond",
+ "u y",
+ "Ġa y",
+ "Ġl em",
+ "Ġlove ly",
+ "ĠC ould",
+ "Ġgu ar",
+ "H H",
+ "Ġcare fully",
+ "ĠL isten",
+ "Ġк ÑĢ",
+ "Ġyou th",
+ "ĠThere fore",
+ "Ġdream s",
+ "ĠJe ff",
+ "? ]",
+ "Ġë Ī",
+ "D A",
+ "Ġb odies",
+ "au x",
+ "Ġtechn iques",
+ "Ġmechan ism",
+ "× ĵ",
+ "Ġо ни",
+ "Ġdes ire",
+ "Ã ®",
+ "ĠV o",
+ "qu es",
+ "ĠÑĥ же",
+ "ĠWho a",
+ "ĠG ame",
+ "Ġh al",
+ "an ish",
+ "Ġpract ices",
+ "5 00",
+ "Ġsort s",
+ "up s",
+ "ate ful",
+ "Ġhers elf",
+ "Ġgu itar",
+ "Ġprop os",
+ "Ġsit es",
+ "Ġbe ach",
+ "Ġ× ¢",
+ "ç¬ ¬",
+ "н Ñĥ",
+ "Ġdr am",
+ "ĠNo ve",
+ "V E",
+ "r ant",
+ "Ġpl ot",
+ "ĠìŬ 기",
+ "ĠC a",
+ "Ġestab lished",
+ "Ġ201 5",
+ "Ġinsp ired",
+ "Ġannoun ced",
+ "ä¸ ª",
+ "ĠÑĤ ÑĢ",
+ "Ġ2 6",
+ "Ġv oy",
+ "Ġte ch",
+ "ìł ģ",
+ "Ġprocess es",
+ "ont o",
+ "ĠP an",
+ "Ġrap id",
+ "ist an",
+ "Ġ19 7",
+ "Ġrelig ion",
+ "Ġ2 8",
+ "Ġsm ile",
+ "Ġb ab",
+ "Ġ Ú©",
+ "ĠV ir",
+ "Ġsched ule",
+ "Ġexec ut",
+ "Ġpr on",
+ "Ñ į",
+ "ĠÐĿ Ñĥ",
+ "m usic",
+ "ìĽ IJ",
+ "Ġg an",
+ "ìĭ ł",
+ "Ġdef ault",
+ "Ġbe m",
+ "Ù ī",
+ "Ġfor ced",
+ "ĠOb viously",
+ "Ġst one",
+ "Ġt ie",
+ "Ġdrink ing",
+ "Ġser ved",
+ "C ause",
+ "Ġcon ference",
+ "ĠExact ly",
+ "ãĥ Ī",
+ "ł ľ",
+ "ìĻ Ģ",
+ "ĠR a",
+ "Ġf ake",
+ "Ġdif f",
+ "ãģ ©",
+ "Ġchalleng ing",
+ "Ġì¤ ij",
+ "Ï ĩ",
+ "ä»Ģ 麼",
+ "Ġintellig ence",
+ "re te",
+ "Ġstud ying",
+ "Ġapp oint",
+ "Ġt an",
+ "Ġи м",
+ "Ġcur ve",
+ "ĠTe am",
+ "ĠA z",
+ "Ġз д",
+ "ĠMus ic",
+ "f ield",
+ "ir ation",
+ "Ġfail ed",
+ "Ġno vel",
+ "Ġdifferent ly",
+ "Ġes cape",
+ "ĠY o",
+ "ĠOct ober",
+ "ı yor",
+ "Ġdescri bed",
+ "Ġcon vert",
+ "ac ement",
+ "Ġhot el",
+ "is ation",
+ "Ġsu is",
+ "ãģ ij",
+ "å ŃIJ",
+ "æĢ İ",
+ "Ġwalk ed",
+ "2 00",
+ "Ġneighbor hood",
+ "is p",
+ "ĠL os",
+ "Ġh idden",
+ "Ġ2 7",
+ "л е",
+ "Ġph r",
+ "ĠIs land",
+ "ĠSt reet",
+ "end a",
+ "hip s",
+ "os ure",
+ "Ġdefin ed",
+ "ภ§",
+ "Ġv ida",
+ "Ġlab el",
+ "ĠEvery body",
+ "Ġjo ke",
+ "ia o",
+ "ا ÙĨ",
+ "Ġa thlet",
+ "... \"",
+ "ĠF ire",
+ "D o",
+ "Ġdef ense",
+ "Ġent ertain",
+ "á t",
+ "Ġpolic ies",
+ "Ġal cohol",
+ "ĠEng ine",
+ "Ġg al",
+ "ĠJ ud",
+ "Ġvol unte",
+ "ick s",
+ "et a",
+ "ag t",
+ "Ġ× ķ",
+ "Ġm ö",
+ "1 3",
+ "Ġenc oun",
+ "Ġe h",
+ "Ġor ange",
+ "Ġabs or",
+ "Ġsp aces",
+ "ĠNove mber",
+ "êµ ¬",
+ "i at",
+ "Ġt am",
+ "ck now",
+ "Ġst orm",
+ "ĠDire ctor",
+ "Ġpre gn",
+ "ĠìĿ ¼",
+ "Ġо п",
+ "Ġres ource",
+ "Ġb ard",
+ "ne w",
+ "ĠDe cember",
+ "u its",
+ "Ġwe il",
+ "Ġconst ruct",
+ "s i",
+ "n ic",
+ "Ġfl our",
+ "Ġrest rict",
+ "ü t",
+ "Ġentire ly",
+ "Ġbreak ing",
+ "ent lich",
+ "Ġtw enty",
+ "Ġcaus es",
+ "Ġele v",
+ "ĠS pr",
+ "ĠIntern et",
+ "Ġk iss",
+ "Ġoper ations",
+ "s zy",
+ "Ġë Ĭ",
+ "Ġscient ists",
+ "Ġgr own",
+ "Ġown ers",
+ "out s",
+ "Ġcour ses",
+ "Ġus ual",
+ "Ġin n",
+ "Ġtrans m",
+ "ñ o",
+ "Ġnu est",
+ "к ов",
+ "Ġcateg ory",
+ "ĠL ife",
+ "ĠPl us",
+ "Ġat mos",
+ "wh ile",
+ "Ġrecord s",
+ "Ġde ÄŁ",
+ "ëĭ¤ ê³ł",
+ "ĠìĤ¬ë ŀ",
+ "Ġrequire ments",
+ "in n",
+ "Ġimm ig",
+ "Ġdeep er",
+ "ç ´",
+ "Ġapp s",
+ "Ġcolle agues",
+ "ż y",
+ "Ġoff ers",
+ "Ġt á",
+ "Ġcolum n",
+ "la ud",
+ "I R",
+ "ĠM s",
+ "Ġexch ange",
+ "l as",
+ "ĠL aw",
+ "ĠJ on",
+ "is se",
+ "ro gen",
+ "Ġmo i",
+ "× Ĺ",
+ "Ġs ending",
+ "Ġhe llo",
+ "е е",
+ "ÅĽ Äĩ",
+ "Ġsuc ceed",
+ "Ġsuff ering",
+ "Ġad vert",
+ "Ġì£ ¼",
+ "çŁ¥ éģĵ",
+ "Ġrec o",
+ "ın ı",
+ "Ġк ом",
+ "all ey",
+ "Ġfail ure",
+ "ie j",
+ "Ġëķ Į",
+ "Ġdrug s",
+ "Ġcu ando",
+ "Ġìĸ´ë ĸ",
+ "ĠAb out",
+ "Ġqu ando",
+ "9 0",
+ "ĠF ed",
+ "1 7",
+ "S h",
+ "in ho",
+ "ĠSund ay",
+ "ĠPh il",
+ "Ġacad emic",
+ "ĠIn c",
+ "Ġmaint en",
+ "åĩ º",
+ "Ġre ward",
+ "er d",
+ "Ġcomm itted",
+ "ìĬ ¤",
+ "г ÑĢ",
+ "Ġstand ards",
+ "Ġk al",
+ "Ġint ention",
+ "ĠZ h",
+ "Ġa cknow",
+ "ä ¿",
+ "Ġ== =",
+ "og y",
+ "å §",
+ "Ġfilm s",
+ "is k",
+ "Ġte eth",
+ "Ġstrugg le",
+ "r d",
+ "u en",
+ "Ġdis s",
+ "ĠD ar",
+ "am y",
+ "Ġenem ies",
+ "Ġve loc",
+ "ĠC all",
+ "um bs",
+ "иÑĤ елÑĮ",
+ "Ġo cean",
+ "é d",
+ "ìļ °",
+ "Ġtre m",
+ "ient o",
+ "еÑĪ ÑĮ",
+ "ffic ient",
+ "Ġbott le",
+ "Ġinstit ution",
+ "est y",
+ "ĠH an",
+ "h ab",
+ "ëĬ ĺ",
+ "Ġar rest",
+ "éĤ Ħ",
+ "Ġlet ters",
+ "oun ce",
+ "í Į",
+ "A n",
+ "Ġcreat es",
+ "Ġcl ock",
+ "Ġdeb t",
+ "Ġan cient",
+ "ific ations",
+ "g i",
+ "B ut",
+ "ĠT u",
+ "k l",
+ "Ġb order",
+ "Ġo ok",
+ "ĠB ay",
+ "est a",
+ "Ġë³ ´ì",
+ "Ġw ra",
+ "pre ne",
+ "Ġê² Į",
+ "ang le",
+ "Ġbelie ved",
+ "ien cy",
+ "ak a",
+ "Ġcrit ic",
+ "Ġb omb",
+ "Ġha m",
+ "ĠÐ Ľ",
+ "êµ Ń",
+ "ĠGu ys",
+ "ros oft",
+ "Ġcr im",
+ "et ch",
+ "AR R",
+ "Ġs ight",
+ "и на",
+ "Ġa in",
+ "á» ij",
+ "is che",
+ "Ġau x",
+ "Ġnum er",
+ "Ġsurv ive",
+ "A ll",
+ "B C",
+ "Ġs z",
+ "Ł ¬ë",
+ "Ġj am",
+ "ĠCour t",
+ "Ġall es",
+ "Ġtr igger",
+ "Ð ŀ",
+ "Ġform at",
+ "Ġdec ades",
+ "Ġc es",
+ "Ġsign s",
+ "Ġrob ot",
+ "ĠCh urch",
+ "Ġa z",
+ "Ġs oup",
+ "ĠTex as",
+ "ut en",
+ "ĠÑĩ ÑĤобÑĭ",
+ "Ġneigh b",
+ "ĸ ×Ķ",
+ "Ġcommunic ate",
+ "Å ¡",
+ "Ġel imin",
+ "Ġfrequ ency",
+ "her n",
+ "id os",
+ "Ġem phas",
+ "Ġmess ages",
+ "Ġg ender",
+ "ĠW enn",
+ "Ġв о",
+ "Ġpr ices",
+ "ol o",
+ "Ġп он",
+ "w ing",
+ "ĠF il",
+ "а ем",
+ "ĠC ur",
+ "Ġfal se",
+ "Ġfield s",
+ "Ġs é",
+ "2 4",
+ "Ġm ac",
+ "u ÅŁ",
+ "Ġlay ers",
+ "Ġadv oc",
+ "w an",
+ "Ġk ar",
+ "ĠÅ ŀ",
+ "Ġdec or",
+ "Ġwall s",
+ "o e",
+ "iss ions",
+ "Ġres ol",
+ "× ¢",
+ "ĠCar ol",
+ "ĠV ide",
+ "le ep",
+ "ĠY OU",
+ "Ġfl ip",
+ "Ġsur gery",
+ "Ġch op",
+ "U R",
+ ". ,",
+ "Ġag ency",
+ "Ġwant ing",
+ "Ġsol ar",
+ "Ġhor iz",
+ "ĠAd am",
+ "Ġstay ing",
+ "ol ic",
+ "Ġgr ateful",
+ "Ġrem ark",
+ "Ġtechn ologies",
+ "Ġprote in",
+ "å¿ ĥ",
+ "д ел",
+ "ĠM ont",
+ "Ġshould er",
+ "Ġz a",
+ "re y",
+ "ĠO oh",
+ "Ġst y",
+ "ic ar",
+ "оÑĤ ÑĢ",
+ "Ġrout e",
+ "ĠT urn",
+ "Ġb om",
+ "Ġdeb ate",
+ "Ġposs ibility",
+ "Ġíķ ´ì",
+ "ap a",
+ "Ġinv ent",
+ "ür lich",
+ "Ġprof ile",
+ "Ġsen ior",
+ "pp y",
+ "v as",
+ "Ġm undo",
+ "ate ver",
+ "Ġapp arently",
+ "en er",
+ "× IJ",
+ "ç Ń",
+ "Ġprec is",
+ "Ġal ign",
+ "Ġkn ife",
+ "ĠRo bert",
+ "å ĭ",
+ "Ġfo ol",
+ "Ġinv ite",
+ "us ing",
+ "Ġcircum st",
+ "Ġcapt ure",
+ "Ġd ough",
+ "ĠS and",
+ "Ġse u",
+ "ĠNew s",
+ "Ġb ite",
+ "Ġne ut",
+ "w ide",
+ "Ġlect ure",
+ "Ġëĺ IJ",
+ "Ġorigin ally",
+ "Ġcho ices",
+ "ĠG ar",
+ "Ġver se",
+ "Ġl it",
+ "Ġ19 6",
+ "íķ ł",
+ "Ġmeas ures",
+ "ç ões",
+ "w ater",
+ "ri ve",
+ "Ġz ijn",
+ "í ģ",
+ "ĠB us",
+ "Ġhe b",
+ "е Ñħ",
+ "ĠK ar",
+ "ĠN ão",
+ "Ġkill ing",
+ "à® ª",
+ "Ġmir ror",
+ "m od",
+ "Ġm ol",
+ "Ġcre ation",
+ "Ġest im",
+ "Ġatmos phere",
+ "Ġg am",
+ "Ġt ables",
+ "is i",
+ "ĠL ittle",
+ "Ġt as",
+ "ĠE le",
+ "é l",
+ "Ġscen es",
+ "Ġt one",
+ "Ġaffect ed",
+ "ĠAU DI",
+ "ĠBr own",
+ "I f",
+ "ĠÙ ĩ",
+ "ĠDan iel",
+ "羣 çļĦ",
+ "qu er",
+ "ch i",
+ "íķ ĺë",
+ "Ġmist akes",
+ "Ġs la",
+ "ãĤ ¤",
+ "Ġent r",
+ "Ġе Ñģли",
+ "Ġsh out",
+ "Ġport ion",
+ "Ñ Ĺ",
+ "Ġpre viously",
+ "á» Ļ",
+ "ĠпÑĢ ед",
+ "оÑģ ÑĮ",
+ "Ġhead s",
+ "ç İ",
+ "å Ń",
+ "åľ ĭ",
+ "Ġgr ass",
+ "ภ°",
+ "cri be",
+ "Ġqu é",
+ "ĠSp anish",
+ "Ġoffer ed",
+ "ĠбÑĭ ло",
+ "ĠCl oud",
+ "Ġve ctor",
+ "ĠH uh",
+ "Ġk ad",
+ "if ts",
+ "ĠÎ ½",
+ "Ġhung ry",
+ "Ð ¡",
+ "Ġpar all",
+ "AN D",
+ "ĠvÃŃde o",
+ "iz z",
+ "Ġocc up",
+ "Ġí Ķ",
+ "Ġsee k",
+ "h es",
+ "Ġdo ors",
+ "Ġhous es",
+ "Ġconsider ing",
+ "Ġgradu ate",
+ "Ġf ulf",
+ "è ¡Į",
+ "è £",
+ "Ġext reme",
+ "Ġflow ers",
+ "it ate",
+ "ĠP ri",
+ "Ġfundament al",
+ "Ñĩ аÑģ",
+ "è¯ ´",
+ "Ġtext ure",
+ "į ĺ",
+ "ĠAN D",
+ "à® ±",
+ "ĠT em",
+ "Ġn ada",
+ "ì§ Ħ",
+ "Ġcelebr ate",
+ "um s",
+ "Ġp ill",
+ "Ġи ли",
+ "go ing",
+ "Ġh ip",
+ "Ġsupport ed",
+ "Ġper man",
+ "Ġagre ement",
+ "Ġty m",
+ "Ġë ij",
+ "ĵ¤ ìĿ´",
+ "Ġpurch ase",
+ "í Ķ",
+ "ĠPl an",
+ "eg en",
+ "Ġrec over",
+ "P U",
+ "ĠMic rosoft",
+ "du c",
+ "Ġhol es",
+ "Ġdro pped",
+ "Ġp ig",
+ "Ġend ing",
+ "Ġattack s",
+ "be c",
+ "Ġre n",
+ "Ġr app",
+ "Ġìļ °ë¦¬",
+ "Ġter ror",
+ "Ġ× Ļ",
+ "Ġed it",
+ "Ġa o",
+ ". ",
+ "Ġhero es",
+ "ĠB oston",
+ "Ġdepend ent",
+ "Ġmotiv ation",
+ "fl ix",
+ "Ġse am",
+ "ки е",
+ "Ġdra in",
+ "od ed",
+ "Ġgu ilty",
+ "ĠJ enn",
+ "ing en",
+ "Ġgrant ed",
+ "ĠK elly",
+ "ĠS av",
+ "ĠUn cle",
+ "ĠHon estly",
+ "EL I",
+ "Ġnavig ate",
+ "Ġbless ed",
+ "c ore",
+ "Ġear ning",
+ "Ġsign als",
+ "Ġdis k",
+ "ial s",
+ "Ġag es",
+ "æ ħ",
+ "Ġpartic le",
+ "ĠÑĩ еÑĢ",
+ "Ġcan n",
+ "Ġt ier",
+ "Ġstat ements",
+ "ê³ł ìļĶ",
+ "ĠëķĮ문 ìĹIJ",
+ "ĠCh o",
+ "Ġpol ar",
+ "an ç",
+ "ĠK enn",
+ "ĠN i",
+ "ĠF ight",
+ "or gan",
+ "é ķ",
+ "ĠCh a",
+ "ĠS ÃŃ",
+ "ãĥ ª",
+ "Ġs lic",
+ "Ġcert ific",
+ "Ġtempl ate",
+ "ĠFed eral",
+ "Ġconsider ation",
+ "Ġexpl o",
+ "ĠM ain",
+ "ĠN E",
+ "Ġalong side",
+ "Ġd ressed",
+ "ĠP oint",
+ "Ġenviron ments",
+ "Ġpró xim",
+ "Ġda ar",
+ "Ġprom pt",
+ "Ġpurs ue",
+ "Ġentertain ment",
+ "Ġth roat",
+ "Ġproblem a",
+ "Ġm art",
+ "ì ¼",
+ "Ġprov ider",
+ "Ø Į",
+ "Ġ× Ĺ",
+ "int e",
+ "m aking",
+ "Ġstro ke",
+ "Ġtiss ue",
+ "U n",
+ "Ġpre cious",
+ "ĠAr ts",
+ "ink ing",
+ "ĠÐŀ н",
+ "Ġи Ñģ",
+ "n ah",
+ "ĠÐķ Ñģли",
+ "Ġcor ners",
+ "Ġtrick y",
+ "in ch",
+ "l ijk",
+ "Ġpress ing",
+ "le vel",
+ "AN G",
+ "Ġrad iation",
+ "ìĦ ł",
+ "Ġconf ront",
+ "Ġv et",
+ "Ġrepresent ative",
+ "Ġprop ag",
+ "Ġcra p",
+ "ĠDe c",
+ "Ġr amp",
+ "еп еÑĢÑĮ",
+ "u és",
+ "ess en",
+ "cri ption",
+ "Ġb ills",
+ "ĠMatth ew",
+ "Ġan ime",
+ "ấ t",
+ "Ġlow est",
+ "h as",
+ "sc reen",
+ "og rap",
+ "ал о",
+ "int on",
+ "ĠJ ah",
+ "èĢ ħ",
+ "it Ãł",
+ "Ġk ay",
+ "Ġrot ation",
+ "ĠW ere",
+ "abe i",
+ "Ġtri als",
+ "Ġle ver",
+ "ight y",
+ "Ġsp oon",
+ "Ġh unt",
+ "c ling",
+ "Ġdis m",
+ "ĠболÑĮ ÑĪ",
+ "Ġass ault",
+ "Ġíĺ ķ",
+ "Ġweek ly",
+ "Ġm ismo",
+ "Ġgen etic",
+ "ul pt",
+ "ĠStud ent",
+ "Ġreal istic",
+ "Ġauthent ic",
+ "æī ĵ",
+ "ast a",
+ "Ġarrest ed",
+ "Ġguid elines",
+ "Ġ×ľ× IJ",
+ "Ġд ав",
+ "ĠCom ing",
+ "f ür",
+ "Ġrequ ests",
+ "ĥ IJ",
+ "Ġanaly ze",
+ "Ġinter ess",
+ "Ġh alt",
+ "ĠO per",
+ "on om",
+ "Ġd uck",
+ "Ġwith d",
+ "s er",
+ "ĠÏ Į",
+ "ĠHist ory",
+ "Ġyout ube",
+ "ãĤ į",
+ "Ġsab er",
+ "w alk",
+ "f ont",
+ "Ġover view",
+ "3 9",
+ "ü y",
+ "ett i",
+ "Ġfro zen",
+ "Ġf lesh",
+ "ÄŁ i",
+ "ĠP M",
+ "ĠìĻ Ģ",
+ "é ¢",
+ "ÑĨи и",
+ "Ġê¸ °ë",
+ "íģ ¬",
+ "Ġpr ose",
+ "oo oo",
+ "r ates",
+ "W S",
+ "Ġautom atic",
+ "Ġcollect ing",
+ "Å ij",
+ "Ġneighb ors",
+ "» .",
+ "ĠEx pl",
+ "Ġcir cul",
+ "co ver",
+ "we g",
+ "Ġstick s",
+ "Ġe ller",
+ "Ġw ww",
+ "Ġd orm",
+ "ĠEx per",
+ "Ġstat istics",
+ "Ġemail s",
+ "Ġgra ve",
+ "im iz",
+ "H S",
+ "Ġu it",
+ ", '",
+ "Ġlas er",
+ "è ī",
+ "ĠÑĤ ем",
+ "Ñĭ ÑĪ",
+ "Ñī Ñij",
+ "Ġgen au",
+ "Ġtien en",
+ "Ġmed itation",
+ "ĠOr gan",
+ "Ġest imate",
+ "Ġë¬ ´ì",
+ "l ets",
+ "Ġn Ãły",
+ "Ġmind set",
+ "Ġres on",
+ "Ġm és",
+ "Ġnumer ous",
+ "Ġvie lleicht",
+ "ĠTh ird",
+ "u ous",
+ "ĠDe ad",
+ "ан д",
+ "H N",
+ "Ġrac ing",
+ "Ġag ents",
+ "ĠU t",
+ "Ġte ar",
+ "ĠH P",
+ "Ġchem istry",
+ "Ġsurv ival",
+ "æĸ °",
+ "Ġconvin ced",
+ "Ġ ;",
+ "Ġreg ulations",
+ "ĠE S",
+ "åĴ Į",
+ "3 00",
+ "Ġen se",
+ "Ġì µ",
+ "Ġd ict",
+ "G A",
+ "Ġah ÃŃ",
+ "åĭ ķ",
+ "Ġte j",
+ "Ġо ÑģÑĤ",
+ "ĠE lect",
+ "Ġintellect ual",
+ "Ġbi as",
+ "Ġbur den",
+ "çĤ ¹",
+ "Ġìĸ´ëĸ »",
+ "Ġche er",
+ "Ġso ph",
+ "Ġportfol io",
+ "ub a",
+ "Ġest os",
+ "T V",
+ "F or",
+ "Ġas h",
+ "Ġkom mer",
+ "Ġcollect ive",
+ "Ġw rest",
+ "ĠJ etzt",
+ "ĠW at",
+ "re ich",
+ "Ġprim er",
+ "act ive",
+ "Ġm ie",
+ "ick ed",
+ "Ġhun ting",
+ "Ġtest im",
+ "Ġcompass ion",
+ "ĠØ ±",
+ "Ġbr ut",
+ "Ġsal ad",
+ "об Ñīе",
+ "Ġsol ving",
+ "Ġflo ating",
+ "ç ·",
+ "Ġattract ive",
+ "ÙĪ ÙĦ",
+ "Ġper d",
+ "if fer",
+ "Ġsc ulpt",
+ "hh h",
+ "ĠWe ek",
+ "Ġent hus",
+ "Ġn ad",
+ "Ġmer ch",
+ "ĠíĻ ķ",
+ "Ġm ile",
+ "好 äºĨ",
+ "ĠÎ ¸",
+ "ĠëĤ ĺë",
+ "éĩ į",
+ "3 8",
+ "Ġch ains",
+ "ĠAl most",
+ "Ġtick ets",
+ "r in",
+ "ĠC C",
+ "Ġdistrib uted",
+ "abet es",
+ "Ġtemper atures",
+ "Ġg ained",
+ "Ġflex ibility",
+ "Ġscream ing",
+ "Ġab road",
+ "un o",
+ "Ġentreprene urs",
+ "ĠNet work",
+ "ĠCanad ian",
+ "Ġpre v",
+ "Ġs ö",
+ "ĠÑĤеб Ñı",
+ "ĠP oke",
+ "ĠP od",
+ "ĠTur key",
+ "çı¾ åľ¨",
+ "Ġabst ract",
+ "Ġsn ake",
+ "ĠAm y",
+ "ĠëĬIJëĤ Į",
+ "Ġbra ve",
+ "ĠìŀĪ ìĸ´ìļĶ",
+ "ĠK al",
+ "Ġ200 7",
+ "á rio",
+ "Ġmark ed",
+ "gin es",
+ "Ġall oc",
+ "ON G",
+ "Ġscient ist",
+ "Ġes ca",
+ "Ġrac ism",
+ "× ij×",
+ "ĠS ams",
+ "ĠP enn",
+ "Ġload s",
+ "Ġà® ¨",
+ "ü ber",
+ "M e",
+ "ix ò",
+ "Ġper ò",
+ "an ne",
+ "Ġexp ressed",
+ "м еÑĢ",
+ "Ġmo et",
+ "Ġret urning",
+ "n ia",
+ "Ġexp on",
+ "P ro",
+ "Ġlo yal",
+ "M L",
+ "Ġl amp",
+ "Ġsh y",
+ "Ġcomp osition",
+ "ĠL y",
+ "Ġmagn etic",
+ "Ġprem ier",
+ "Ġmeasure d",
+ "Ġsumm ary",
+ "Ġattack ed",
+ "Ġfin ishing",
+ "Ð Ĺ",
+ "ç ¥",
+ "Ġs its",
+ "Ġhyd rogen",
+ "Ġma i",
+ "ĠDeuts ch",
+ "as ı",
+ "Ġobt ain",
+ "v ie",
+ "Ġso it",
+ "Ġë° Ķ",
+ "Ġl ane",
+ "Ġconse gu",
+ "в о",
+ "Ġe ase",
+ "ak in",
+ "ĠF a",
+ "Ġunt uk",
+ "Ġbur st",
+ "Ġc um",
+ "al ım",
+ "ú blic",
+ "id i",
+ "ĠRoy al",
+ "ĠK on",
+ "Ġcommon ly",
+ "Ġremo ving",
+ "Ġj ur",
+ "il ib",
+ "Ġan ch",
+ "íĸ ī",
+ "Æ°á» £",
+ "ĠÐľ Ñĭ",
+ "ĠAn th",
+ "ĠS Ã¥",
+ "Ġinter rupt",
+ "Ġst ere",
+ "ĠO S",
+ "ony m",
+ "ter y",
+ "ĠMar ia",
+ "ê² ĥ",
+ "Ġexpl oring",
+ "Ġtransp arent",
+ "Ġf ate",
+ "ĠJ ung",
+ "Ġgr up",
+ "Ġdark er",
+ "ĠD oug",
+ "Ġman e",
+ "æĶ ¾",
+ "ạ i",
+ "d ri",
+ "lo ok",
+ "ĠDes ign",
+ "Ġtut aj",
+ "Ġhorizont al",
+ "re on",
+ "ort e",
+ "ĠCor rect",
+ "ĠSte ven",
+ "Ġv ine",
+ "0 2",
+ "i Äĩ",
+ "Ġsie mpre",
+ "ĠK ey",
+ "åĥ ı",
+ "ĠG ames",
+ "Ġna ar",
+ "Ġshock ed",
+ "el ve",
+ "ĠR ose",
+ "ìĭ ¬",
+ "Ġstop ping",
+ "oh l",
+ "ĠM ix",
+ "Ġsuff ered",
+ "Ġsig ma",
+ "Ġweak ness",
+ "ĠO w",
+ "ี à¹Ī",
+ "I F",
+ "Ġà® ħ",
+ "ad ed",
+ "ĠNet flix",
+ "an es",
+ "Ġrem ained",
+ "ir y",
+ "Ġr ip",
+ "ell t",
+ "Ġsil ent",
+ "Ġpro ven",
+ "Ġtox ic",
+ "Ġal umin",
+ "Ġmulti pl",
+ "al and",
+ "Ġ3 4",
+ "0 6",
+ "ĠB ru",
+ "Ġìłķ ë§IJ",
+ "J ust",
+ "b oy",
+ "Ġsho e",
+ "Ġcreat ure",
+ "Ġhead ed",
+ "ĠоÑĤ к",
+ "æ ±",
+ "Ġess ence",
+ "Ġremark able",
+ "Ġnú mer",
+ "Ġd rew",
+ "Ġpu zzle",
+ "ĠLibr ary",
+ "ĠF u",
+ "ash es",
+ "k k",
+ "ĠI st",
+ "¦ °",
+ "ĠB ry",
+ "Ġc eremony",
+ "Ġà® İ",
+ "Ġc ri",
+ "e qu",
+ "ãĤ ¢",
+ "Ġpri ze",
+ "Ġdim ensions",
+ "og ram",
+ "Ġle ather",
+ "Ġpop ulations",
+ "u um",
+ "Ġve gan",
+ "Ñı д",
+ "Ġcó mo",
+ "å Ħ",
+ "Ġstri p",
+ "å £",
+ "Ġvac ation",
+ "ħ ķ",
+ "Ġme als",
+ "ili pp",
+ "Ġ ents",
+ "ar am",
+ "ric ht",
+ "Ġgra in",
+ "ĠSp ain",
+ "Ġche ek",
+ "ĠA ff",
+ "I ON",
+ "ĠBr ing",
+ "Ġ3 8",
+ "iel en",
+ "ul u",
+ "ĠболÑĮ ÑĪе",
+ "Ġannounce ment",
+ "ĠÑĤ ÑĥÑĤ",
+ "ĠPro phet",
+ "ard o",
+ "3 7",
+ "Ġw oke",
+ "Ġtransl ation",
+ "ĠN OT",
+ "ĠC L",
+ "Ġd Ã¼ÅŁ",
+ "ÑĨ Ñĸ",
+ "ac er",
+ "ĠL oc",
+ "Ġper ception",
+ "N O",
+ "Ġdies en",
+ "L ook",
+ "he art",
+ "av ed",
+ "Ġbound ary",
+ "Ġfl ows",
+ "Ñij м",
+ "Ġarg uments",
+ "Ġelect ions",
+ "ı s",
+ "Ġhe ck",
+ "Ġsuit able",
+ "Ġf iber",
+ "ĠSt ra",
+ "x y",
+ "ĠH um",
+ "Ġmonth ly",
+ "u per",
+ "Ġgol f",
+ "Ġl ately",
+ "ĠG ard",
+ "ĠR en",
+ "ĠA st",
+ "ĠF ant",
+ "аÑģ Ñģ",
+ "Ġobs er",
+ "ë ¡ľ",
+ "Ġeas iest",
+ "į Ķë",
+ "Ġwebs ites",
+ "p ol",
+ "Ġco con",
+ "Ġà® ĩ",
+ "ĠV eg",
+ "Ġwalk s",
+ "Ġint ro",
+ "Ġdirect ed",
+ "ĠAn na",
+ "Ġëĵ¤ ìĸ´",
+ "ĠEaster n",
+ "ĠS aint",
+ "ĠB ow",
+ "Ġro ast",
+ "ĠU RL",
+ "Ġjed en",
+ "ur as",
+ "aj a",
+ "Ġse mi",
+ "Ġrapid ly",
+ "Ġtarget s",
+ "ĠCont rol",
+ "Ġb ah",
+ "Ġref lection",
+ "Ġcreat ivity",
+ "hold ers",
+ "Ġìĺ ¬ë",
+ "Ġamong st",
+ "Ġfeed ing",
+ "ÑįÑĤ омÑĥ",
+ "Ġвид е",
+ "Ġë§Įë ĵ¤",
+ "ĠSm art",
+ "Ġrel iable",
+ "Ġvez es",
+ "Ġ× ¨",
+ "ch uckles",
+ "az ione",
+ "ĠWilliam s",
+ "Ġa ç",
+ "Ġsle e",
+ "е Ñī",
+ "Ġtim eline",
+ "Ġthor ough",
+ "á» į",
+ "ĠO t",
+ "ạ n",
+ "Ġimag ination",
+ "Ġmechan ics",
+ "r ist",
+ "Ġclaim ed",
+ "ÏĦ η",
+ "ê te",
+ "ĠHur ry",
+ "ĠiP ad",
+ "Ġconst ru",
+ "ĠC la",
+ "ĠAl s",
+ "ä¼ ļ",
+ "ut z",
+ "Ġcult ures",
+ "Ġìĸ´ëĸ» ê²Į",
+ "Ġbelong s",
+ "Ġy er",
+ "ĠDoes n",
+ "Ġge omet",
+ "Ġb id",
+ "Ġfo am",
+ "Ġh ob",
+ "ĠBrit ain",
+ "Ġsubst ance",
+ "Ġann iversary",
+ "ĠëĦ Ī",
+ "Ġnot ed",
+ "Ġgovern or",
+ "Ġstock s",
+ "3 1",
+ "Ġdi ye",
+ "ìĬ ¤ë",
+ "Ġre b",
+ "z el",
+ "Ġmultip ly",
+ "Ġoper ator",
+ "Ħ¤ ìļĶ",
+ "Ġwat ers",
+ "Ġd är",
+ "Ġuns er",
+ "ĠEliz abeth",
+ "é« ĺ",
+ "Ġincreasing ly",
+ "ĠG ro",
+ "Ġen gines",
+ "ir s",
+ "Ø «",
+ "Ġtre asure",
+ "P C",
+ "in ction",
+ "ir i",
+ "Ġacc um",
+ "Ġvari ation",
+ "Ġp om",
+ "Ġtit les",
+ "ĠF est",
+ "ó s",
+ "Ġeld er",
+ "ny m",
+ "r un",
+ "Ñı в",
+ "Ġinnov ative",
+ "Ġnom bre",
+ "Ġco inc",
+ "Ġfr anch",
+ "Ġent onces",
+ "Ġnicht s",
+ "Ġexc lusive",
+ "ĠChe ers",
+ "ĠB i",
+ "u je",
+ "æŃ ¡",
+ "Ġp ok",
+ "ĠP rem",
+ "Ġrock et",
+ "ELI PE",
+ "Ġhosp itals",
+ "ri um",
+ "Ġjust e",
+ "Ġham mer",
+ "Ġquant um",
+ "Ġrespons es",
+ "ll y",
+ "end i",
+ "Ġact ively",
+ "Ġfr idge",
+ "i ate",
+ "l ong",
+ "Ġqu em",
+ "Ġdeath s",
+ "Ġsuper ior",
+ "ck en",
+ "ìĿ´ì ĹIJ",
+ "kt op",
+ "Ġgather ed",
+ "£ ¨",
+ "Ġd azu",
+ "Ġreci pes",
+ "Ġbu zz",
+ "c en",
+ "Ġany time",
+ "ons ense",
+ "Ġcirc les",
+ "Ġsol ved",
+ "Ġìĭ ł",
+ "Ġcoron avirus",
+ "ĠLu ke",
+ "Ġbu bb",
+ "Ġcont empor",
+ "r zy",
+ "ĠJ ane",
+ "Ġд ом",
+ "Ġscrew s",
+ "Ġhy brid",
+ "Ġcas ual",
+ "Ġsel bst",
+ "be ing",
+ "ĠÄ IJ",
+ "ĠCol umb",
+ "ĠÑħ оÑĩ",
+ "Ġbu cket",
+ "Ġevalu ate",
+ "Ġid ol",
+ "Ġrep utation",
+ "ĠìĨ Įë",
+ "ÙĪ ر",
+ "Ġhe cho",
+ "Ġpo em",
+ "Ġsubject s",
+ "pl ant",
+ "ĠBe h",
+ "ĠSpe aking",
+ "Ġbatter ies",
+ "Ġfollow ers",
+ "ö l",
+ "Ġg ently",
+ "Ġsi xt",
+ "Ġparam eter",
+ "Ġik ke",
+ "ĠT our",
+ "ĠD J",
+ "ot te",
+ "ĠJ ahren",
+ "Ġprepar ation",
+ "Ġд Ñĥм",
+ "Ġ8 00",
+ "c op",
+ "ik ing",
+ "Ġë¬ ¸",
+ "Ġн Ñĥ",
+ "Ġл еÑĤ",
+ "åIJ Į",
+ "ĠI de",
+ "Ġì¡° ê¸Ī",
+ "Ġla ughter",
+ "Ġmole cules",
+ "ĠR est",
+ "Ġobs erved",
+ "d zie",
+ "Ġadvert ising",
+ "ert o",
+ "Ġmo ins",
+ "ĠM IT",
+ "Ġexc it",
+ "Ġt um",
+ "Ġty l",
+ "Ġinvest ed",
+ "Ġph arm",
+ "Ġunex pected",
+ "Ġph i",
+ "oty pe",
+ "we ise",
+ "Ġge ç",
+ "jour d",
+ "Ġhors es",
+ "n Äħ",
+ "= \"",
+ "ĠS M",
+ "Ġf ib",
+ "Ġcl ips",
+ "çķ ¶",
+ "å¦Ĥ æŀľ",
+ "Ġreg ime",
+ "Ġrot ate",
+ "r ou",
+ "n ik",
+ "Ġarm or",
+ "ðŁ ĺ",
+ "еÑĢ а",
+ "åº ¦",
+ "ĠO ch",
+ "Ġr ichtig",
+ "üz el",
+ "ane ously",
+ "m ek",
+ "éĮ ¯",
+ "ĠX iao",
+ "Ġexist ed",
+ "w orth",
+ "ãģ£ ãģ¨",
+ "Ġna ught",
+ "Ġhe iÃŁt",
+ "ĠB al",
+ "Ġres id",
+ "iv ot",
+ "om atic",
+ "Ġh ired",
+ "Ġgrad ually",
+ "Ġon ions",
+ "Ġcomp at",
+ "Ġint im",
+ "Ġj ew",
+ "Ġcontrib ution",
+ "ĠI re",
+ "ac ji",
+ "Ġsl ice",
+ "Ġimm un",
+ "ĠR us",
+ "Ġgr ows",
+ "ĠSimilar ly",
+ "Ġhard est",
+ "Ġst ruck",
+ "Ġmeasure ment",
+ "... ]",
+ "th ey",
+ "Ġìł Ģë",
+ "Ġsne ak",
+ "Ġappl ies",
+ "Ġн ем",
+ "æ ĵ",
+ "×ij ר",
+ "ĠЧ ÑĤо",
+ "Ġout ro",
+ "Ġinnoc ent",
+ "Ġm og",
+ "ĠSams ung",
+ "Ġmer cy",
+ "Ġhand ling",
+ "Ġinter vention",
+ "id ays",
+ "g ot",
+ "Ġcur ric",
+ "Ġbound aries",
+ "Ġconf using",
+ "Ŀ¼ ëĬĶ",
+ "æ ĩ",
+ "Ġstitch es",
+ "ÃŃ vel",
+ "Ġtun nel",
+ "it ä",
+ "Ġg ost",
+ "im y",
+ "Ġcz as",
+ "Ġm é",
+ "Ġcat al",
+ "ĠSim on",
+ "ĠLI AM",
+ "m ic",
+ "ĠÐ ¤",
+ "Ġey el",
+ "is as",
+ "ĠC PU",
+ "ĠD ou",
+ "Ġnä ch",
+ "Ġinfin ity",
+ "Ġr if",
+ "ĠPe ace",
+ "ĠC u",
+ "Ġminim al",
+ "Ġlisten ed",
+ "Ġpo le",
+ "hal b",
+ "Ġload ed",
+ "Ġste ady",
+ "ĠBes ides",
+ "ê m",
+ "Ġl ap",
+ "Ġco op",
+ "Ġfriends hip",
+ "w orld",
+ "Ġge h",
+ "Ġtyl ko",
+ "ĠLa ura",
+ "Ġsurround ed",
+ "ĠE vent",
+ "Ġch ap",
+ "ĠW onder",
+ "bre ak",
+ "Ġdro ve",
+ "Ġbroad er",
+ "Ġch i",
+ "F i",
+ "Ġge hen",
+ "Ġwest ern",
+ "Ġintellig ent",
+ "Ġpers ist",
+ "Ġfound ed",
+ "ãģĵ ãģ¨",
+ "Ġhistor ic",
+ "Ġfr Ã¥",
+ "cks å",
+ "Ġhand y",
+ "Ġsy mp",
+ "Ġr ows",
+ "Ġnut ri",
+ "b ur",
+ "ĠLe on",
+ "Ġsist ema",
+ "Ġext ensive",
+ "ĠÑĥ в",
+ "í ı",
+ "Ġnight s",
+ "Ġcá c",
+ "Ġcount ing",
+ "ĠM ust",
+ "all ow",
+ "еÑģ Ñģ",
+ "M om",
+ "Ġнад о",
+ "Ġbar rel",
+ "ãĥ ŀ",
+ "AR D",
+ "Ġinstall ation",
+ "Ġin sect",
+ "Ġëħ ¸ë",
+ "uj Äħ",
+ "ĠÄij i",
+ "Ġpack ed",
+ "Ġf iction",
+ "N ow",
+ "ĠY ay",
+ "Ġper t",
+ "r ons",
+ "und e",
+ "ach es",
+ "Ġsty les",
+ "Ġapr ès",
+ "ok u",
+ "ĠV ice",
+ "ın ız",
+ "com m",
+ "Ġassign ed",
+ "Ġinteract ions",
+ "Ġac ab",
+ "F ELIPE",
+ "Ġresc ue",
+ "Ġindust ries",
+ "ĠAnd y",
+ "Ġpra ise",
+ "Ġfl ame",
+ "Ġsn ack",
+ "í Ĥ",
+ "ç ģ",
+ "Ġsw o",
+ "rend er",
+ "Ġbo ards",
+ "ĠÑĤ ом",
+ "en ne",
+ "Ġpast a",
+ "Ġdev il",
+ "ĠF el",
+ "Ġhat te",
+ "Ġcoll eg",
+ "e h",
+ "ì »",
+ "ãģĵ ãģ®",
+ "Ġproduct ive",
+ "for ward",
+ "и п",
+ "Ġsmart phone",
+ "Ġinv is",
+ "Ġb um",
+ "Ġwho a",
+ "ìŀ Ħ",
+ "Ġo cksÃ¥",
+ "ĠL ang",
+ "ĠSy ria",
+ "Ġses i",
+ "ί α",
+ "Ġappro val",
+ "4 8",
+ "Ġод ин",
+ "Ġë ĸ",
+ "ĠH arr",
+ "ĠAd minist",
+ "Ġ× ¤",
+ "ĠDe an",
+ "f i",
+ "Ġcitiz en",
+ "Ġsh ark",
+ "0 5",
+ "Ġbo il",
+ "Ġindic ate",
+ "å ¡",
+ "A re",
+ "Ġlay out",
+ "Ġref r",
+ "ĠPac ific",
+ "AA AA",
+ "ĠAustral ian",
+ "g ression",
+ "V oice",
+ "ал ÑģÑı",
+ "Ġshel ter",
+ "T o",
+ "au pt",
+ "Ġevalu ation",
+ "ap or",
+ "Ġcur rency",
+ "Ġм ного",
+ "ig os",
+ "ãģ °",
+ "Ġo ct",
+ "Ġro yal",
+ "è ³",
+ "as il",
+ "ĠChild ren",
+ "Ġr ien",
+ "Ġë ĵľë",
+ "Ġbar rier",
+ "Ġej emplo",
+ "Ġe k",
+ "N D",
+ "es p",
+ "ен а",
+ "Ġp ic",
+ "Ġkill er",
+ "Ġintegr ate",
+ "Ġfew er",
+ "Ġdis abilities",
+ "Ġ ....",
+ "Ġtri angle",
+ "Ġfe es",
+ "Ġwid ely",
+ "em i",
+ "Ġoverwhel ming",
+ "Ġz omb",
+ "Ġb ere",
+ "Ġho od",
+ "ĠA ye",
+ "ĠHar vard",
+ "e v",
+ "ĠÏĦ οÏħ",
+ "Ġcup s",
+ "ĠA uch",
+ "z ona",
+ "Ġ199 0",
+ "Ġwe iÃŁ",
+ "Ġcr unch",
+ "æ ¥",
+ "Ġз ав",
+ "Ġmeas uring",
+ "Ġst ations",
+ "ĠStep hen",
+ "Ġshort ly",
+ "Ġsig ning",
+ "Ġcom edy",
+ "om o",
+ "Ġsuggest ions",
+ "Ġsign ature",
+ "ĠпÑĢ ив",
+ "Ġdis order",
+ "as ka",
+ "Ġworld s",
+ "Ġprecis ely",
+ "n orm",
+ "ra v",
+ "ĠC ivil",
+ "In ter",
+ "ĠC ertain",
+ "Ġinj ured",
+ "Ġsuggest s",
+ "ĠGold en",
+ "Ġcy ber",
+ "ĠØ ´",
+ "Ġtempor ary",
+ "Ġco oper",
+ "Ġvot ed",
+ "Ġ ought",
+ "ấ y",
+ "x ual",
+ "Ġpan els",
+ "Ġ9 5",
+ "Ġhands ome",
+ "ĠпÑĢ ов",
+ "Ġper mit",
+ "Ġke in",
+ "Ġbad ly",
+ "Ġnot ifications",
+ "iz a",
+ "ĠNot ice",
+ "Ġinc lusive",
+ "Ġanswer ing",
+ "Ġí Ĺ",
+ "u ld",
+ "íħ Į",
+ "Ġnow adays",
+ "Ġ3 7",
+ "Ġb olt",
+ "Ġstat ic",
+ "ĠH op",
+ "Ġav ant",
+ "aj o",
+ "Ġ맼 ìŀĪ",
+ "Ġfif ty",
+ "ĠF inal",
+ "Ġsc ores",
+ "ĠT ap",
+ "Ġcy l",
+ "Ġconv ince",
+ "Ġany ways",
+ "od a",
+ "Ġìķ ¼",
+ "Ġser ves",
+ "ĠÑĤак ой",
+ "ĠZo om",
+ "Ġsaving s",
+ "ul o",
+ "Ġs outhern",
+ "view er",
+ "Ġho je",
+ "Ġse ja",
+ "Ġrepresent ing",
+ "Īë įĺ",
+ "l ik",
+ "ĠSome body",
+ "Ġbe ast",
+ "Ġstick ing",
+ "Ġins ist",
+ "Ġtal ented",
+ "Ġexplain ing",
+ "Ġatt orney",
+ "éĥ ¨",
+ "Ġst airs",
+ "ĠD og",
+ "í ĭ",
+ "Ġc ig",
+ "Ġshap ed",
+ "Ġs ons",
+ "Ïģ ι",
+ "ut t",
+ "Ġì Ķ",
+ "Ġpar ad",
+ "ìĿ¸ë į°",
+ "Ġh orn",
+ "ĠJ our",
+ "ann o",
+ "Ġworld wide",
+ "åĬ Ľ",
+ "Ġparticip ation",
+ "¦ Ħ",
+ "Ġm ów",
+ "Ġburn ed",
+ "Ġwrit ers",
+ "all ah",
+ "ĠF und",
+ "Ġcle ver",
+ "ĠLe ute",
+ "b in",
+ "Ġbe ating",
+ "f oot",
+ "ĠìĽ IJ",
+ "ĠStud io",
+ "Ġv ag",
+ "be y",
+ "r ze",
+ "Ġoppos ition",
+ "Ġж из",
+ "w ho",
+ "Ġê± ´",
+ "Ġtr ace",
+ "Ġд енÑĮ",
+ "Ġep id",
+ "Ġges ch",
+ "ĠN ar",
+ "ĠB E",
+ "Ñĥ й",
+ "ĠS ign",
+ "ed ly",
+ "Ġcl ay",
+ "Ġinst antly",
+ "Ġgather ing",
+ "ĠGal axy",
+ "Ġb ored",
+ "ĠBudd h",
+ "c é",
+ "Ġm am",
+ "Ġsl ope",
+ "Ġëĭ¤ ìĿĮ",
+ "Ġsch ön",
+ "Ġp ir",
+ "ge f",
+ "am er",
+ "Ġh ö",
+ "Ġcolle ague",
+ "Ġpres ents",
+ "ad ium",
+ "Ġà® µ",
+ "Ġfal ar",
+ "be ep",
+ "Ġdri ed",
+ "ism s",
+ "Ġro pe",
+ "Ġworks hop",
+ "Ġest ud",
+ "Ġb ands",
+ "Ġthem es",
+ "åħ ¬",
+ "ÙĬ ر",
+ "åIJ İ",
+ "Ġremind er",
+ "ÑĤ Ñĥ",
+ "ĠB h",
+ "Ġcocon ut",
+ "ĠÑģ ÑĤо",
+ "ĠCh annel",
+ "Ġimmig ration",
+ "ä s",
+ ".. ...",
+ "ä¸ »",
+ "çĻ ½",
+ "st op",
+ "Ġк аÑĢ",
+ "Ġco ins",
+ "ĠÑĩ аÑģ",
+ "Ġdest ruction",
+ "l ined",
+ "Ġbar riers",
+ "ant ine",
+ "Ġprint ed",
+ "Ġcongrat ulations",
+ "ĠHe art",
+ "Ġin qu",
+ "th a",
+ "Ġhard ly",
+ "ĠA ven",
+ "Ġt inha",
+ "ĠS ony",
+ "ĠN F",
+ "Ġgradu ates",
+ "Ġsque eze",
+ "ere my",
+ "ÏĦ ι",
+ "Ġep ic",
+ "ĠJ u",
+ "Ġol m",
+ "ĠLa ughter",
+ "Ġbelief s",
+ "ĠC ru",
+ "ĠTr ue",
+ "ĠS oul",
+ "owe en",
+ "Ġrom antic",
+ "Ġз в",
+ "Ġan os",
+ "ĠY up",
+ "éĺ ¿",
+ "d im",
+ "Ġin fer",
+ "Ġз ам",
+ "Ġso c",
+ "uk a",
+ "Ġprec ise",
+ "Ġdro pping",
+ "Ġcl ue",
+ "Ġer rors",
+ "char ge",
+ "ĠP u",
+ "omet er",
+ "Ġlamb da",
+ "ac ional",
+ "ĠD ong",
+ "Ġcham ber",
+ "Ġthank ful",
+ "ĠN u",
+ "ĠHaw ai",
+ "Ġinf o",
+ "Ġactiv ate",
+ "ĠQ ual",
+ "Ġqu ed",
+ "Ñĥ лÑĮ",
+ "Ġcl oth",
+ "åĸ ľ",
+ "Ġw ichtig",
+ "5 5",
+ "Ġot ra",
+ "ograp her",
+ "Ġcur ios",
+ "Ġ19 80",
+ "Ġemp res",
+ "d ess",
+ "e ur",
+ "Ġcl uster",
+ "ar ter",
+ "ob ile",
+ "ĠY an",
+ "ĠAd v",
+ "Ġdiscipl ine",
+ "Ġìłķ ëıĦ",
+ "ĠPl ace",
+ "ĠSe lect",
+ "T E",
+ "ĠбÑĭ ла",
+ "Ġwh is",
+ "Ġb ay",
+ "ĠD or",
+ "en cing",
+ "Ġrep et",
+ "Ġf icar",
+ "p ad",
+ "Ġf og",
+ "u yor",
+ "Ġsn ap",
+ "ib t",
+ "Ġso bie",
+ "Ġappoint ment",
+ "ĠR y",
+ "Ġce iling",
+ "our se",
+ "Ġwr ites",
+ "ĠAfghan istan",
+ "Ġm os",
+ "az e",
+ "Ġpen al",
+ "Ġcry stal",
+ "IC E",
+ "ê° IJ",
+ "é Ł",
+ "ĠTes la",
+ "Ġthe ories",
+ "Ġappe al",
+ "Ġnewsp aper",
+ "Ġcook ies",
+ "æ ©",
+ "ĠاÙĦ ÙĦ",
+ "Ġma j",
+ "ĠGet ting",
+ "k ommen",
+ "ĠHe aven",
+ "ell s",
+ "Ġdiv ine",
+ "Ä «",
+ "Ġa kt",
+ "Ġhop es",
+ "ĠCh en",
+ "we gen",
+ "** *",
+ "ĠFra ge",
+ "Ġн и",
+ "ภ¹",
+ "min ister",
+ "nes ota",
+ "wh ich",
+ "Ġexpl icit",
+ "Ġverd ad",
+ "Ġgradu ated",
+ "ĠPh ilipp",
+ "Q L",
+ "ĠM I",
+ "Ġdev ot",
+ "Ġc ure",
+ "Ġclos est",
+ "ĠÃ Ħ",
+ "Ġsex y",
+ "ãģ Ľ",
+ "ĠDe ath",
+ "ok o",
+ "ug u",
+ "ĠAn ne",
+ "itar ian",
+ "es a",
+ "ег од",
+ "ĠD ur",
+ "Ġ 000",
+ "ze it",
+ "Ġtour nament",
+ "Ġmel hor",
+ "ภª",
+ "Ġin du",
+ "Ġf law",
+ "Ġw ars",
+ "ĠM ind",
+ "ĠI ron",
+ "ÑĤ ак",
+ "ĠV R",
+ "Ġs iz",
+ "ĠS outhern",
+ "Ġê·¸ëŁ ¬ë",
+ "Ġaw ak",
+ "Ġìķ ŀ",
+ "Ġc ube",
+ "believ able",
+ "if all",
+ "d is",
+ "Ġabandon ed",
+ "m ind",
+ "Ġpar l",
+ "Ġclass ical",
+ "è ĭ",
+ "á»Ļ t",
+ "ĠAut o",
+ "ĠB or",
+ "ç ©",
+ "4 00",
+ "ĠSoci ety",
+ "Ġsubt le",
+ "Ġmiss ions",
+ "Ġremember ed",
+ "ĠE ither",
+ "Ġda für",
+ "OR D",
+ "Ġint ensity",
+ "ES IN",
+ "ĠC up",
+ "Ġrare ly",
+ "Ġto ys",
+ "ĠChar lie",
+ "á» Ł",
+ "Ġgla ube",
+ "Ġround s",
+ "T IN",
+ "Ġcap ability",
+ "Ġderiv ative",
+ "Ġrefer ring",
+ "Ġd Ã¥",
+ "ĠT ALI",
+ "Ġcott on",
+ "Ġcon fer",
+ "Ġcolum ns",
+ "Ġliber al",
+ "Ġnun ca",
+ "Ġμ ε",
+ "Ġind o",
+ "ib en",
+ "ĠBe ispiel",
+ "Ġê·¸ë łĩ",
+ "ĠÑĥ Ñĩ",
+ "Ġh oy",
+ "Ġfr y",
+ "ĠScott ish",
+ "è Ĭ",
+ "Ġc iv",
+ "Ġconserv ative",
+ "Ġair pl",
+ "Ġs ar",
+ "r us",
+ "Ġinvest ments",
+ "Ġinfin ite",
+ "Ġà® ķ",
+ "ĠTALI ESIN",
+ "ĠG ary",
+ "ue ll",
+ "Ġа к",
+ "ĠC ir",
+ "Ġrit ual",
+ "Ġ>> >",
+ "Ġtem pt",
+ "ĠTe ch",
+ "ĠPoke mon",
+ "Ġimprove ments",
+ "Ġsp are",
+ "Ġtransl ate",
+ "Ġson ra",
+ "ĠFil m",
+ "w ort",
+ "Ġм и",
+ "Ġperiod s",
+ "Ġje alous",
+ "ãģĦ ãģĦ",
+ "Ġt ir",
+ "M I",
+ "Ġconduct ed",
+ "ĠìķĪë ħķ",
+ "0 9",
+ "ĠPol it",
+ "ĠWhere as",
+ "Ġmoist ure",
+ "Ġs ins",
+ "Ġk ap",
+ "ĠÑį к",
+ "Ġben im",
+ "Ġelimin ate",
+ "Ġathlet es",
+ "ĠMan ager",
+ "Ġfeature d",
+ "ap ore",
+ "äº Ľ",
+ "Ġë° ľ",
+ "Ġper f",
+ "ĠTh us",
+ "Ġdeb ut",
+ "об ÑĢ",
+ "Ġse ñ",
+ "Ġmyster ious",
+ "w ords",
+ "Ķ ê°Ģ",
+ "Ġcheck s",
+ "Ġvolunte er",
+ "Ġwas hing",
+ "ĠMar vel",
+ "ĠA B",
+ "iss ors",
+ "! '",
+ "ĠF ull",
+ "ye on",
+ "Ġwe igh",
+ "ĠJO HN",
+ "Ġv os",
+ "Ġproced ures",
+ "Ġaddress ed",
+ "ĠBer lin",
+ "put er",
+ "ĠB an",
+ "Ġmedic ation",
+ "Ġdr one",
+ "ĠÑĥ б",
+ "ĠJe an",
+ "Ġcap s",
+ "Ġdisappoint ed",
+ "Ġw ore",
+ "Ġêµ Ń",
+ "Ġorgan ize",
+ "ĠHall oween",
+ "Ġfant asy",
+ "y ard",
+ "Ġnos otros",
+ "Ġjump ed",
+ "Ġphot ography",
+ "ĠN ame",
+ "re c",
+ "A B",
+ "Ġbless ing",
+ "ĠSh ut",
+ "Ġbit ter",
+ "p op",
+ "ãģĿ ãĤĮ",
+ "Ġde i",
+ "Ġfulf ill",
+ "çIJ Ĩ",
+ "Ġden gan",
+ "Ġbe lo",
+ "ĠMean while",
+ "Ġdep ois",
+ "Ġdi abetes",
+ "Ġbu nd",
+ "ĠZe aland",
+ "Ġdig est",
+ "Ġt ires",
+ "Ġdo d",
+ "ag ne",
+ "ế t",
+ "Ġpe el",
+ "Ġз аб",
+ "Ġn odes",
+ "Ġtrend s",
+ "ĠSw itch",
+ "ĠA ward",
+ "ĠOr ig",
+ "ĠH al",
+ "Ġest as",
+ "Ġ3 60",
+ "Ġsim ult",
+ "Ġcom ic",
+ "Ġm Ãł",
+ "Ġbal anced",
+ "ĠPrin cess",
+ "Ġkilomet ers",
+ "á» ©",
+ "Ġpart ir",
+ "ì¤ ij",
+ "so ft",
+ "ĠV iew",
+ "Ġbi ological",
+ "in st",
+ "4 4",
+ "Ġman era",
+ "Ġcompreh ensive",
+ "ĠS ab",
+ "Ġcr imes",
+ "y ers",
+ "ĠComp any",
+ "ĠPh ot",
+ "Ġpou co",
+ "i ac",
+ "Ġbe im",
+ "in ate",
+ "Ġsub sequ",
+ "ĠMay or",
+ "Ġcent uries",
+ "è res",
+ "ìŀĸ ìķĦìļĶ",
+ "Ġê·¸ëŁ ¼",
+ "ĠFra u",
+ "ĠO H",
+ "Ġëģ Ŀ",
+ "ĠN ah",
+ "ĠSer ies",
+ "Ġover night",
+ "íĴ Ī",
+ "ĠâĢ ¢",
+ "Ġtra ve",
+ "atter ed",
+ "Ġwar ri",
+ "ĠGru nd",
+ "ĠInd ones",
+ "Ġsc ra",
+ "ob y",
+ "ĠBro ok",
+ "Ġcur s",
+ "Ġë ¸",
+ "Ġexpl ains",
+ "ram atic",
+ "Ġparticip ating",
+ "Ġmin ut",
+ "Ġcontract s",
+ "Ġg egen",
+ "Ġdisappe ared",
+ "ĠS N",
+ "Ġrob ust",
+ "ap h",
+ "Ġsh rim",
+ "Ġdev ast",
+ "c ope",
+ "Ġme ets",
+ "Ġpeace ful",
+ "m ate",
+ "Ġwe ld",
+ "Ġ× ª",
+ "d on",
+ "Ñĥ ÑĤÑĮ",
+ "Ġregister ed",
+ "ĠN ik",
+ "j in",
+ "Ġc av",
+ "Ġe cht",
+ "io x",
+ "Ġflow ing",
+ "но ÑģÑĤи",
+ "Ġto e",
+ "Ġent ity",
+ "ов а",
+ "f its",
+ "ĠPat rick",
+ "ÑĤ ÑĢ",
+ "Ġle verage",
+ "Ġcor rel",
+ "i ah",
+ "Ġstr ings",
+ "ist inct",
+ "Ġg ue",
+ "arch y",
+ "Ġteng o",
+ "ım ız",
+ "Ġor bit",
+ "ä¸ º",
+ "Ġе ÑīÑij",
+ "ca ke",
+ "Ġ׾ ×Ķ",
+ "ĠMin nesota",
+ "Ġbra ke",
+ "ow ie",
+ "Ġcra w",
+ "ê¸°ë ¥¼",
+ "Ġprogram me",
+ "ĠÑģл ÑĥÑĩ",
+ "åı ª",
+ "ien ces",
+ "ĠO ui",
+ "ĠP ers",
+ "im iento",
+ "ĠIn vest",
+ "Ġsl ower",
+ "æĻĤ åĢĻ",
+ "ĠB eth",
+ "Ġnur se",
+ "ĠSpr ing",
+ "S p",
+ "Ġun employ",
+ "д и",
+ "Ġgen ius",
+ "ĠA aron",
+ "Ġê·¸ëŁ ¬",
+ "Ġe i",
+ "ãģĹ ãĤĩ",
+ "Ġtank s",
+ "Ġau jourd",
+ "Ġcomplex ity",
+ "ĠÑĢ еÑĪ",
+ "Ġold est",
+ "Ġlet z",
+ "åħ ¥",
+ "Ġphenomen on",
+ "pr int",
+ "ĠBund es",
+ "it at",
+ "ê» ĺ",
+ "Ġ4 2",
+ "ĠW i",
+ "Ġinc om",
+ "Ġg ek",
+ "Ġembr ace",
+ "Ġt ies",
+ "out e",
+ "Ġd ose",
+ "ĠF riends",
+ "Ñĭ ÑĤ",
+ "егод нÑı",
+ "Ġor g",
+ "Ħë ¡ľ",
+ "ó g",
+ "Ġex ceed",
+ "Ġgod s",
+ "Ġê±° ìĺĪìļĶ",
+ "Ġsoci et",
+ "ĠUn ivers",
+ "it ät",
+ "Ġword en",
+ "Ġsm oking",
+ "Ġint ens",
+ "ab ul",
+ "em ia",
+ "è ij",
+ "4 7",
+ "f ly",
+ "Ġ200 6",
+ "ĠSer iously",
+ "Ġprze z",
+ "æ ¼",
+ "c re",
+ "Ġn an",
+ "Ġmod es",
+ "ов аÑĤÑĮ",
+ "ĠH ang",
+ "em en",
+ "Ġbenefic ial",
+ "Ġvot ers",
+ "ĠBro ad",
+ "Ġb ent",
+ "W ow",
+ "Ġm ul",
+ "åĵ ¥",
+ "ĠU C",
+ "Ġdam aged",
+ "ĠUk raine",
+ "Ġw ipe",
+ "Ġst ones",
+ "Ġman agers",
+ "Ġr ab",
+ "ÑģÑĤÑĢ о",
+ "l at",
+ "Ġde ce",
+ "Ġgraph ic",
+ "Ġf oss",
+ "Ġdisag ree",
+ "ĠAm en",
+ "Ġsec rets",
+ "ho le",
+ "ink le",
+ "Ġfortun ate",
+ "Ġì ±",
+ "ìľ Ħ",
+ "èIJ ¬",
+ "Ġhab its",
+ "Ġbur ied",
+ "Ġh in",
+ "Ġvirt ually",
+ "ol as",
+ "ĠR P",
+ "ĠT ab",
+ "l ow",
+ "Ġsacr ific",
+ "Ġestim ated",
+ "ol n",
+ "Ù ĭ",
+ "c ur",
+ "ĠFe el",
+ "Ġcast le",
+ "Ġus eless",
+ "Ġdis g",
+ "ĠJac ob",
+ "Ġga an",
+ "Ġup side",
+ "Ġpare ce",
+ "ãĥ³ ãĥ",
+ "Ġsh ipping",
+ "ĠC R",
+ "Ġdis rupt",
+ "ac ter",
+ "UN D",
+ "f u",
+ "å® Į",
+ "ĠP ick",
+ "ĠChar l",
+ "ĠB ull",
+ "Ġenter prise",
+ "Ġpunish ment",
+ "ack ing",
+ "Ġfr action",
+ "Ġtab let",
+ "Ġch ord",
+ "Ġsimilar ly",
+ "åħ¶ 實",
+ "ĠTor onto",
+ "Ġcour ts",
+ "ÄŁ l",
+ "esz cze",
+ "Ġpron oun",
+ "ĠS ister",
+ "ĠM P",
+ "Ġgreat ly",
+ "ĠD ank",
+ "ic op",
+ "Ġgar bage",
+ "Ġresol ve",
+ "ĠS af",
+ "ĠG un",
+ "Ġcomp ound",
+ "Ġë° °",
+ "ĠMus ik",
+ "âĻ «",
+ "Ġcha os",
+ "ĠWhen ever",
+ "Ġe uros",
+ "Ġor chest",
+ "Ġrefr iger",
+ "al an",
+ "ภ·",
+ "ĠAm azing",
+ "Ġp ud",
+ "ag an",
+ "Ġj eszcze",
+ "is y",
+ "Ġaccur acy",
+ "ĠA ma",
+ "is ode",
+ "ë ĮĢ",
+ "Ġinterpret ation",
+ "ĠL iber",
+ "æ ·",
+ "c am",
+ "Ġevol ved",
+ "ĠK ay",
+ "ÑĨ Ñĭ",
+ "Ġcreat or",
+ "it as",
+ "Ġal arm",
+ "Ġcelebr ation",
+ "z ent",
+ "Ġfun cion",
+ "Ġo v",
+ "umb ling",
+ "Ġ %",
+ "ภĪ",
+ "Ġrestrict ions",
+ "Ġн ав",
+ "ĠK inder",
+ "Ġban ana",
+ "ÑĮ Ñı",
+ "Ġdiam eter",
+ "Ġnor thern",
+ "ur ers",
+ "ĠP as",
+ "æĪij çļĦ",
+ "Ġwork force",
+ "Ġj ung",
+ "Ġguar ante",
+ "Ġequ ilib",
+ "Ġsu ite",
+ "Ġeu ro",
+ "Ġdel iber",
+ "S te",
+ "Ġdownt own",
+ "Ġch in",
+ "Ġc odes",
+ "ed ia",
+ "Ġshe ep",
+ "res hold",
+ "wn ie",
+ "ó b",
+ "Ġunder lying",
+ "l ia",
+ "j er",
+ "ÏĢ ÏĮ",
+ "ç Ŀ",
+ "th rop",
+ "Ġz ap",
+ "Ġvac uum",
+ "ĠH ab",
+ "Ġwra pped",
+ "ì ¢",
+ "Ġinvent ory",
+ "м а",
+ "Ġco ord",
+ "Ġpl ates",
+ "Ġsy mm",
+ "T e",
+ "ĠwÅĤa ÅĽnie",
+ "Ġreach es",
+ "Ġlon ely",
+ "S cript",
+ "le e",
+ "ess er",
+ "Ġê± ¸",
+ "ĠGes ch",
+ "ĠMo ving",
+ "Ġré p",
+ "ĠV ill",
+ "åIJ Ī",
+ "ĠR achel",
+ "Ġtem os",
+ "ON E",
+ "Ġstra in",
+ "Ġang el",
+ "Ġf Ã¥",
+ "T r",
+ "Ġach o",
+ "Ġhighlight s",
+ "ĠW er",
+ "ĠCar l",
+ "Ġbl ur",
+ "Ġreg ards",
+ "Â ·",
+ "ил ÑģÑı",
+ "Ġrec re",
+ "ĠY ani",
+ "U CK",
+ "ł ¸",
+ "Ġelectr ons",
+ "ĠSp iel",
+ "Ġv ed",
+ "Ú ¾",
+ "Ġbe am",
+ "Ġid iot",
+ "ë ĵ¤",
+ "на Ñĩ",
+ "id d",
+ "Ġsk i",
+ "it ative",
+ "Ġhyp othes",
+ "ãģ§ãģĻ ãģŃ",
+ "ent er",
+ "ĠìķĦëĭĪ ë",
+ "Ġih re",
+ "Ġpre view",
+ "ang el",
+ "Ġdem on",
+ "Ġd us",
+ "Ġd ic",
+ "ĠK om",
+ "LE Y",
+ "... !",
+ "Ġsie ht",
+ "ĠSon ic",
+ "Ġten ho",
+ "an as",
+ "Ġdig it",
+ "ĠMa ar",
+ "Ġunder grad",
+ "oun cer",
+ "uff y",
+ "Ġconvers ion",
+ "Ġdis connect",
+ "Ġe cho",
+ "om er",
+ "Ġcurric ulum",
+ "Ġper ché",
+ "Ġw and",
+ ".. ?",
+ "Ġroll ed",
+ "Ġentreprene ur",
+ "Ġtheore t",
+ "ĠÑī о",
+ "Ġins ights",
+ "Ġzus ammen",
+ "o in",
+ "ret t",
+ "p rodu",
+ "Ġvisit ors",
+ "e ous",
+ "Ġgrand mother",
+ "Ġhum or",
+ "Ġн иÑħ",
+ "zen ia",
+ "ins on",
+ "Ġres et",
+ "Ġbase ball",
+ "Ġmatch ing",
+ "ëĭ¤ ê°Ģ",
+ "Ġpun to",
+ "ì ¡",
+ "Ġre de",
+ "Ġaddress ing",
+ "Ġfore cast",
+ "ĠB ol",
+ "Ġcol ored",
+ "Ġdocument ation",
+ "Ġexpect ation",
+ "ĠNor thern",
+ "Ġcre o",
+ "Ġà® ļ",
+ "f on",
+ "Ġuns ere",
+ "U M",
+ "Ġcop ies",
+ "Ġexpand ed",
+ "Ġveter ans",
+ "ĠAl m",
+ "Ġво обÑīе",
+ "Ġpsych ological",
+ "Ġnos so",
+ "Ġpay ments",
+ "im eters",
+ "Ġ-- >",
+ "ĠJenn ifer",
+ "Ġvolunte ers",
+ "os se",
+ "or ious",
+ "ĠбÑĭ ли",
+ "è Ĥ",
+ "ĠEs s",
+ "w s",
+ "ĠB C",
+ "ĠI C",
+ "W oman",
+ "Ġv ont",
+ "Ġeth nic",
+ "EN N",
+ "им о",
+ "Ġlo b",
+ "Ġou i",
+ "c s",
+ "Ġre he",
+ "Ġìł ģ",
+ "Ġch ick",
+ "ús ica",
+ "Ġk ont",
+ "ĠDist rict",
+ "Ġp ile",
+ "Ġа в",
+ "ей ÑģÑĤв",
+ "ĠÂ £",
+ "Ġiss ued",
+ "Ġком п",
+ "Ġpros per",
+ "Ġprof ound",
+ "ĠDe ar",
+ "Ġãģ ĵ",
+ "Ġfund ed",
+ "Ġb isa",
+ "ŀ ĺë",
+ "× Ł",
+ "ĠìĿ ĺ",
+ "Ġtw elve",
+ "ĠChamp ions",
+ "éĿŀ 常",
+ "Ñģ л",
+ "Ġ200 5",
+ "p m",
+ "Ġon de",
+ "Ġdiff é",
+ "ĠCh all",
+ "Ġdifficult ies",
+ "Ġgar age",
+ "Ġd á",
+ "ün k",
+ "Ġë¬ ¼",
+ "Ġtr an",
+ "Ġsubm itted",
+ "z w",
+ "ÙĪ ا",
+ "Ġar k",
+ "ĠìĦ ±",
+ "Ġgrocer y",
+ "он а",
+ "i ere",
+ "Ġa est",
+ "Ġexhib ition",
+ "Ġr és",
+ "Ġconsist ency",
+ "Ġcook ie",
+ "н ей",
+ "Ġrepl acement",
+ "æ² ¹",
+ "ĠS em",
+ "ĠìĤ¬ ìļ©",
+ "8 00",
+ "Ġgen es",
+ "Ġtrans action",
+ "ĠE L",
+ "Ġdur ante",
+ "ib les",
+ "ĠE at",
+ "t ail",
+ "iss ance",
+ "Ġto ss",
+ "Ġsurv ived",
+ "Ġoff ices",
+ "Ġsupport ive",
+ "Wh ere",
+ "Ġtout es",
+ "Ġë§ ī",
+ "Ġj okes",
+ "ier on",
+ "ap ers",
+ "Ġm ature",
+ "ĠM arsh",
+ "Ġs ido",
+ "k ind",
+ "Ġreal mente",
+ "ĠChe f",
+ "Ġquel que",
+ "Ġjud ges",
+ "e ft",
+ "ER S",
+ "Ġj et",
+ "Ġpers ons",
+ "è »",
+ "iz ations",
+ "ri k",
+ "Ġsh ops",
+ "ĠW y",
+ "Ġele g",
+ "qu è",
+ "qu oi",
+ "Ġjug a",
+ "Ġíķľë ²Ī",
+ "ĠQuest ion",
+ "ĠGlo bal",
+ "Ġìķ½ ê°Ħ",
+ "ĠSt ation",
+ "æİ ¥",
+ "ĠOh io",
+ "Ġstick y",
+ "Ġst ressed",
+ "Ġg ün",
+ "Ġí Ŀ",
+ "ÑģÑĤ Ñĥп",
+ "é ¡Į",
+ "ĠPh D",
+ "im mer",
+ "Ġment or",
+ "Ġinv ented",
+ "Ġre un",
+ "Ġine vit",
+ "Ġpol ÃŃt",
+ "Ġexec ute",
+ "ĠSt ory",
+ "Ġout standing",
+ "Ġgu er",
+ "ĠR ain",
+ "Ġch oses",
+ "ĠT it",
+ "ĠÑģ еÑĢ",
+ "ĠSing apore",
+ "ĠN one",
+ "Ġch ronic",
+ "°ë į°",
+ "Ġe go",
+ "æł ·",
+ "ES T",
+ "ãģĤ ãĤĬ",
+ "ĠW ang",
+ "ĠN AT",
+ "Ġa ug",
+ "Ġdes ktop",
+ "Ġetern al",
+ "ĠìĤ¬ ìĭ¤",
+ "ĠConst itution",
+ "ìĤ ¬ë",
+ "×Ļ× ľ",
+ "p res",
+ "ĠТ Ñĭ",
+ "Ġinter f",
+ "Ġlist s",
+ "Ġfight s",
+ "ft en",
+ "ĠI owa",
+ "Ġmotiv ated",
+ "ĠH osp",
+ "Ġelse where",
+ "Ġpath s",
+ "Ġinst ances",
+ "B l",
+ "r ange",
+ "á» ±",
+ "ĠS it",
+ "man a",
+ "Ġìĭľ ìŀij",
+ "Ġm ình",
+ "ans as",
+ "Ġs na",
+ "Ġphilos oph",
+ "Ġpas se",
+ "Æ°á» Ŀi",
+ "ak h",
+ "ent al",
+ "Ġih n",
+ "ru ctor",
+ "Ġв аÑĪ",
+ "Ġgener ous",
+ "Ġp ivot",
+ "п ол",
+ "Ġjam ais",
+ "Ġcom ent",
+ "ĠL ew",
+ "od zi",
+ "ĠX box",
+ "Ġв од",
+ "Ġcons ent",
+ "ī ìŀ¥",
+ "Ġdis par",
+ "l ass",
+ "ĠGovern or",
+ "Be ifall",
+ "Ġê° ľ",
+ "Ġbelo ved",
+ "׳ ×ķ",
+ "se ll",
+ "Ġhon ored",
+ "le h",
+ "Ġw äre",
+ "un ting",
+ "Ġfra ud",
+ "ĠR AM",
+ "ê± ¸",
+ "Ġkill s",
+ "Ġeconom ics",
+ "0 4",
+ "п еÑĢ",
+ "Ġco isas",
+ "Ġи гÑĢ",
+ "ÃŃ m",
+ "Ġmö chte",
+ "Ġìµ ľ",
+ "Ġstim ul",
+ "Ġfast est",
+ "l v",
+ "Ġg én",
+ "ĠS ounds",
+ "Ġ19 70",
+ "Ġhome work",
+ "spe aking",
+ "Ġencour aging",
+ "Ġqu ery",
+ "Ġre vers",
+ "pro fit",
+ "Ġd y",
+ "Ġìŀ ij",
+ "ëĬĶëį° ìļĶ",
+ "Ġso ap",
+ "ĠG all",
+ "ĠC N",
+ "ĠAn s",
+ "Ġf ic",
+ "ank s",
+ "Ġdess ert",
+ "ĠìłĢ íĿ¬",
+ "ĠM aking",
+ "Ġcome ç",
+ "ê³ Ħ",
+ "Ġassoci ation",
+ "D ad",
+ "he e",
+ "Ġh ogy",
+ "Ġap ro",
+ "Ġinvis ible",
+ "Americ an",
+ "í İ",
+ "Ġvi be",
+ "Ġem issions",
+ "Ġadvoc ate",
+ "Ġkick ed",
+ "Ġ vel",
+ "Ġsum mar",
+ "Ġfre aking",
+ "ch ron",
+ "Ġpin ch",
+ "Ġwszyst k",
+ "isc al",
+ "Ġpro ved",
+ "Ġmind ful",
+ "Ġt ä",
+ "Ġno ises",
+ "Ġisol ated",
+ "Ġcross ed",
+ "Ġê° ķ",
+ "Ġvo ilÃł",
+ "Ġch ore",
+ "ĠR A",
+ "C om",
+ "Ġrelax ed",
+ "at ro",
+ "Ġpre vention",
+ "Voice over",
+ "O D",
+ "ĠCo vid",
+ "Ġsepar ation",
+ "Ġ- [",
+ "иÑĩ его",
+ "çĻ ¼",
+ "ĠS D",
+ "ble ep",
+ "Ġindepend ence",
+ "Ġpart ial",
+ "Ġalgorith ms",
+ "ĠAny one",
+ "Ġassoci ate",
+ "h um",
+ "ic ular",
+ "Ġb ạn",
+ "Ġbatt les",
+ "G ood",
+ "App lause",
+ "Ġbast ante",
+ "Ġadv ant",
+ "ĠS weet",
+ "Ġref used",
+ "ãĤ ¸",
+ "ĠÑĤеб е",
+ "pl et",
+ "Ġencour aged",
+ "åĵ ¦",
+ "Ġmir acle",
+ "ĠB un",
+ "ĠV ar",
+ "rim ination",
+ "e lect",
+ "ĠM ult",
+ "Ġdeliver ing",
+ "e ing",
+ "Ġc m",
+ "ne hmen",
+ "ĠL ine",
+ "Ġë§ Į",
+ "en ced",
+ "ĠS ound",
+ "ĠCont in",
+ "ij d",
+ "UN G",
+ "k le",
+ "Ġth reshold",
+ "Ġcomp act",
+ "ad t",
+ "Ġto es",
+ "ĠP ur",
+ "own ed",
+ "ment ed",
+ "Ġdes igning",
+ "Ġvacc inated",
+ "Ġexha ust",
+ "Ġbas ics",
+ "Ġcons ists",
+ "ĠGu y",
+ "ac zy",
+ "Ġm ÃŃ",
+ "w on",
+ "å® ³",
+ "Ġ8 5",
+ "æ Ĥ",
+ "Ġm um",
+ "Ġign or",
+ "Ġprint ing",
+ "ac ular",
+ "p ow",
+ "Ġexpand ing",
+ "Ġg ir",
+ "ĠC ab",
+ "íĺ ¸",
+ "ÑĤÑĮ ÑģÑı",
+ "ĠìĹ¬ëŁ¬ë ¶Ħ",
+ "Ġang les",
+ "Ġterm inal",
+ "ĠW on",
+ "ĠInter esting",
+ "Ġcross ing",
+ "Ġbond s",
+ "Ġpu eden",
+ "Ġor b",
+ "lar ın",
+ "Ġcreep y",
+ "Ġnutr ition",
+ "Ġall ies",
+ "Ġwire less",
+ "Ġdes ired",
+ "Ġcomp ute",
+ "ĠAri zona",
+ "ĠBeaut iful",
+ "Ġprodu ces",
+ "Ġnuest ro",
+ "t ed",
+ "Ġel igible",
+ "ĠÑģ оз",
+ "ic ial",
+ "ĠH ero",
+ "Ġcons ume",
+ "Ġrob ots",
+ "Ġpurch ased",
+ "c ción",
+ "Ġ iz",
+ "ượ c",
+ "ίν αι",
+ "ĠØ£ ÙĨ",
+ "Ġshad ows",
+ "ĠMed ia",
+ "Ġprin cess",
+ "Ġk lar",
+ "Ġwood en",
+ "Ġus ar",
+ "Ġg üzel",
+ "Ġsl ot",
+ "r ade",
+ "Ġë Ĵ",
+ "Ġhar mon",
+ "Ġingred ient",
+ "ors hip",
+ "ek i",
+ "Ġgrand father",
+ "Ġexcit ement",
+ "Ġpolit icians",
+ ".. !",
+ "Ġout s",
+ "Ġsepar ately",
+ "ĠÑı к",
+ "ĠW elt",
+ "ĠP ow",
+ "j an",
+ "Ġorient ation",
+ "åı ĭ",
+ "L C",
+ "age m",
+ "ÛĮ Úº",
+ "åIJ Ĺ",
+ "Ġbran ches",
+ "ad en",
+ "rent e",
+ "ĠI hr",
+ "as m",
+ "Ġest ão",
+ "ĠN ic",
+ "Ġsla ve",
+ "Ġcomp ress",
+ "c rowd",
+ "Ġclim bing",
+ "ĠMan agement",
+ "ĠB ah",
+ "Ġpan ic",
+ "Ġk or",
+ "Ġcool ing",
+ "Ġb ind",
+ "Ġз ад",
+ "Ġr ack",
+ "Ġent it",
+ "Ġs ends",
+ "Ġyour selves",
+ "d es",
+ "ĠMuslim s",
+ "Ġí ļ",
+ "ism a",
+ "cy cle",
+ "un kt",
+ "ĠC ore",
+ "Ġinj uries",
+ "Ġident ical",
+ "ка Ñı",
+ "ĠDeutsch land",
+ "Ġе е",
+ "is an",
+ "Ġtr uc",
+ "let on",
+ "Ġback up",
+ "Ġult ra",
+ "Ġab und",
+ "ille urs",
+ "Ġby ÅĤo",
+ "åħ ĥ",
+ "ort ed",
+ "Ġearth qu",
+ "Ġк л",
+ "Ġobs ervation",
+ "Ġmainten ant",
+ "el en",
+ "Ġsett led",
+ "Ġp ela",
+ "ĠE conom",
+ "Ġ Õ",
+ "Ġste ering",
+ "ĠAL L",
+ "ĠC her",
+ "Ġpat ience",
+ "ĠS now",
+ "Ġb or",
+ "Ġworth y",
+ "Ġcá i",
+ "Ġ× §",
+ "Ġκ α",
+ "d og",
+ "ĠK aren",
+ "ill es",
+ "Î ²",
+ "Ġagric ulture",
+ "×ķ× Ł",
+ "ĠSe an",
+ "Ġsens ors",
+ "íķ ´ë",
+ "ag h",
+ "Ġpublic ly",
+ "Ġpe ux",
+ "ĠAlex ander",
+ "Ġprior it",
+ "Ġla zy",
+ "ard on",
+ "atter ing",
+ "Ġcost ume",
+ "س ت",
+ "è¿ ĺ",
+ "Ġun w",
+ "Ð Ľ",
+ "Ġthick ness",
+ "qu ito",
+ "g unt",
+ "ist as",
+ "ne ys",
+ "ĠëIJĺ ê²Į",
+ "ĠBr asil",
+ "Ġto ken",
+ "Ġaff ili",
+ "l on",
+ "Ġf Ã¥r",
+ "ĠBe ach",
+ "Ġw itch",
+ "ĠSe ven",
+ "Ġp ant",
+ "λ λ",
+ "Ġcapt ain",
+ "å Ŀ",
+ "Ġve ut",
+ "Ġpou voir",
+ "ac z",
+ "ĠBar b",
+ "Ġut ility",
+ "Ġcontempor ary",
+ "Ġobt ained",
+ "Ġpainting s",
+ "e ar",
+ "Ġpe an",
+ "ĠO g",
+ "Ġc ust",
+ "л ем",
+ "Ĥ ĺë",
+ "ĠIs so",
+ "Ġac onte",
+ "ĠTe le",
+ "ĠAss istant",
+ "Ã ī",
+ "íĸĪ ìĬµëĭĪëĭ¤",
+ "Ġcount s",
+ "Ġbu ck",
+ "ĠDe ep",
+ "Ġtack le",
+ "Ġh arsh",
+ "Ġdec ides",
+ "éĹ ľ",
+ ". âĢĭ",
+ "éĤ Ĭ",
+ "ĠAng el",
+ "Ġlay ing",
+ "Ġcal ories",
+ "Ġcontro lling",
+ "Ġadvant ages",
+ "ĠÑįÑĤ ой",
+ "Ġappro aching",
+ "Ġthreat s",
+ "ak an",
+ "em atic",
+ "m ann",
+ "ê³ µ",
+ "m umbles",
+ "ac ió",
+ "Ġmaint aining",
+ "Ġfound er",
+ "l ah",
+ "f ight",
+ "Ġadm itted",
+ "âĢ¦ .",
+ "ķ Į",
+ "ab ol",
+ "Ġus age",
+ "Ġn onsense",
+ "ĠPal est",
+ "Ġcont re",
+ "ĠDemocr atic",
+ "ĠE R",
+ "j ekt",
+ "Ġar bit",
+ "Ġг ол",
+ "ĠMich elle",
+ "ich er",
+ "es h",
+ "ĠP ho",
+ "к ом",
+ "4 9",
+ "ĠEner gy",
+ "ο Ïį",
+ "Ġc ents",
+ "Ġref ers",
+ "Ġg ospel",
+ "ĠSh a",
+ "ĠSh are",
+ "×Ļ× ł",
+ "Ġclin ic",
+ "ĠëĦ £",
+ "Ġequ ality",
+ "ug s",
+ "Ġsh ed",
+ "Ġplan es",
+ "Ġtout e",
+ "re ck",
+ "Ġstra nd",
+ "Ġbi ology",
+ "Ġle ague",
+ "ĠP ok",
+ "Ġnúmer o",
+ "ĠCo ast",
+ "Ġconsist ently",
+ "Ġnuc le",
+ "OO OO",
+ "Ġob jet",
+ "Ġch or",
+ "Ġg inger",
+ "Ġd abei",
+ "Ġcoop eration",
+ "à¯į .",
+ "nt en",
+ "ç ¤",
+ "l Ãł",
+ "ìĸ ij",
+ "r ado",
+ "Ġpass ive",
+ "Ġglo ves",
+ "Ġunder ground",
+ "Ġlog ical",
+ "Ġk et",
+ "Ġfunction ality",
+ "¸ë ¦¬",
+ "Ġport al",
+ "ell er",
+ "×Ļ× ¨",
+ "ĠT ed",
+ "ĠG re",
+ "IJ ľ",
+ "Ġperson nel",
+ "Ġemer ging",
+ "ĠF ür",
+ "Ġmeant ime",
+ "usal em",
+ "ĠC lear",
+ "Ġtra pped",
+ "Ġìļ °",
+ "Ġdis pl",
+ "Ġmet tre",
+ "Ġmun icip",
+ "Ġwithd raw",
+ "Ġsp at",
+ "un es",
+ "Ġaccess ibility",
+ "æĪij 们",
+ "Ġap are",
+ "Ġpros pect",
+ "Ġн аз",
+ "Ġcop per",
+ "ĠP RO",
+ "Ïħ ÏĦ",
+ "Ġattack ing",
+ "ĠV in",
+ "ĠSt one",
+ "Ġinvestig ate",
+ "st yle",
+ "ĠÎ »",
+ "ë ¡Ŀ",
+ "ë§ Ī",
+ "Ġins pect",
+ "Ġli ver",
+ "ал иÑģÑĮ",
+ "Ġser a",
+ "hal ten",
+ "em an",
+ "Ġmin istry",
+ "' '",
+ "Ġd ots",
+ "ãħĭãħĭ ãħĭãħĭ",
+ "Ñĥ ÑģÑĤ",
+ "ĠJ ak",
+ "AK E",
+ "Ġg aps",
+ "uck er",
+ "ĠинÑĤеÑĢ еÑģ",
+ "ĠEm ily",
+ "Ġinter val",
+ "Ġt ender",
+ "ĠTechn ology",
+ "g ame",
+ "Ġtri b",
+ "ÙĦ ا",
+ "ĠDevelop ment",
+ "Ùħ ا",
+ "Ġwr ist",
+ "Ġf ires",
+ "Ġtarget ed",
+ "ìł IJ",
+ "Ġso d",
+ "íļ Į",
+ "Ġoldu ÄŁ",
+ "Ġse asons",
+ "vent ions",
+ "Ġн его",
+ "Ġsomet ime",
+ "ли в",
+ "n é",
+ "Ġt ú",
+ "ĠDe us",
+ "Ġexec ution",
+ "á p",
+ "ĠCh ange",
+ "ĠInd eed",
+ "Ġreg ulation",
+ "ĠH ung",
+ "é is",
+ "Ġwish es",
+ "Ġj azz",
+ "Ġstruct ural",
+ "Ġblow ing",
+ "Ġby Äĩ",
+ "Ġtherm al",
+ "ph ant",
+ "ÑĢÑĥ з",
+ "ан ÑĤ",
+ "ĠP ull",
+ "Ġconf usion",
+ "нÑĭ ми",
+ "Ġscen arios",
+ "ìłģ ìľ¼ë¡ľ",
+ "Ġд еÑĤ",
+ "Ġtatto o",
+ "Ġaut re",
+ "Ġhe ating",
+ "Ġtreat ing",
+ "Ġпон им",
+ "Ġexc lus",
+ "ĠL OL",
+ "we ar",
+ "ag le",
+ "Ġzur ück",
+ "Ġr ational",
+ "s u",
+ "Ġdet er",
+ "ĠN ative",
+ "à®ķ ள",
+ "ach ed",
+ "Ġ ãĥ",
+ "ĠEnt onces",
+ "Ġhor a",
+ "ìĿ´ìĹIJ ìļĶ",
+ "Ġl ite",
+ "Ã «",
+ "Ġsix th",
+ "Ġбол ее",
+ "act or",
+ "Ġpsych ology",
+ "çĽ ¸",
+ "Ġdem ands",
+ "Ġpe er",
+ "Ġnew ly",
+ "ĠWW E",
+ "Don ald",
+ "ĠBo x",
+ "Ġp ine",
+ "Ġload ing",
+ "ĠN ico",
+ "Ġs ÅĤ",
+ "omm e",
+ "AR T",
+ "Ġrecru it",
+ "Ġbug s",
+ "arent s",
+ "ĠпÑĢ об",
+ "ĠIn side",
+ "ipp er",
+ "d ramatic",
+ "Ġplan ets",
+ "ord e",
+ "Ġy oga",
+ "ch ild",
+ "ĠMar ie",
+ "Ġãģ Ĥ",
+ "ĠB L",
+ "Ġfil med",
+ "Ġref resh",
+ "Ġtomato es",
+ "Ġf et",
+ "Qu é",
+ "Ġ !!",
+ "ĠëĤ ´ë",
+ "r ine",
+ "Ġinteract ive",
+ "s al",
+ "ann ah",
+ "pe z",
+ "ç¶ ĵ",
+ "Ġunderstand s",
+ "ĠTok yo",
+ "Ġlibr aries",
+ "Ġread er",
+ "ij IJ",
+ "o z",
+ "ĠEnd e",
+ "ĠF lo",
+ "Ġm ild",
+ "Ġpo etry",
+ "Ġж ив",
+ "æĦ Ľ",
+ "Ġbeh ave",
+ "Ġdo en",
+ "ĠSus an",
+ "p age",
+ "ra ham",
+ "Ġcommunic ations",
+ "Ġtun ing",
+ "Ġp ac",
+ "Ġanx ious",
+ "I O",
+ "M ark",
+ "Ġhi ç",
+ "book s",
+ "Ġp iss",
+ "Ġen abled",
+ "achel or",
+ "ĠF OR",
+ "Ġé c",
+ "ĠT R",
+ "il st",
+ "h at",
+ "ĠìĿ Į",
+ "Ġty ch",
+ "Ġj ar",
+ "Ġbuild s",
+ "ĠAr gent",
+ "Ġinter medi",
+ "Ġl ou",
+ "Ġa ra",
+ "Ġassign ment",
+ "Ġcabin et",
+ "Ġretire ment",
+ "ãģ »",
+ "Ġdis abled",
+ "ric a",
+ "Ġa wards",
+ "Ġbo ots",
+ "Ġacknow led",
+ "Ġth y",
+ "Ġêµ ¬",
+ "Ġsy nd",
+ "ни й",
+ "il ton",
+ "Ġprob l",
+ "ĠF al",
+ "Ġverd ade",
+ "Ġ7 00",
+ "ĠLe arning",
+ "oc us",
+ "Ġpal ace",
+ "N ot",
+ "t ain",
+ "c m",
+ "Ġmagn et",
+ "inc oln",
+ "Ġfig uring",
+ "ĠL yn",
+ "ĠB oss",
+ "ĠV O",
+ "Ġdiagn osis",
+ "Ġequ ipped",
+ "w atch",
+ "in os",
+ "ad ers",
+ "Ġsh elf",
+ "Ġorgan is",
+ "Ġn od",
+ "Ġk ız",
+ "pp ers",
+ "Ġrest ore",
+ "Ġart ic",
+ "ĠVo ice",
+ "ı yorum",
+ "ê² ©",
+ "Ġspread ing",
+ "Ġh ips",
+ "Ġw ard",
+ "ure au",
+ "Ġinter section",
+ "6 6",
+ "Ġ3 9",
+ "ç ³",
+ "Ġwait ed",
+ "ì ´",
+ "hh hh",
+ "Ġd ys",
+ "ĠE N",
+ "Ġb atch",
+ "Ġca f",
+ "Ġmark er",
+ "大家 好",
+ "or able",
+ "ó ria",
+ "Ġste pped",
+ "Ġcelebr ating",
+ "ан а",
+ "Ġwor n",
+ "ĠF ol",
+ "Ġpl a",
+ "Ġattempt s",
+ "Ġtwe et",
+ "Ġr ust",
+ "g ence",
+ "í Ĩµ",
+ "Ġre vel",
+ "Ġre cept",
+ "en ess",
+ "Ġ( (",
+ "ãĥ¼ ãĥ",
+ "! âĢĭ",
+ "ĠìĨ IJ",
+ "Ġinfluen ced",
+ "и ж",
+ "Ġкон еÑĩно",
+ "Ġcolleg es",
+ "ion i",
+ "Ġs ag",
+ "An n",
+ "ol ar",
+ "Ġexpress ions",
+ "Ġsu its",
+ "Ġowners hip",
+ "el and",
+ "pie ce",
+ "æĢİ ä¹Ī",
+ "Ġdesp ués",
+ "Ġt el",
+ "Ġins ult",
+ "Ġêµ īìŀ¥",
+ "ĠSm all",
+ "ĠF R",
+ "ok a",
+ "ber ries",
+ "ĠAnt on",
+ "ел Ñı",
+ "Ñı Ñģ",
+ "Ġval ve",
+ "act s",
+ "Ġwood s",
+ "à® £",
+ "Ġcult iv",
+ "Ġf á",
+ "ãģ¨ ãģĦãģĨ",
+ "Ġche ers",
+ "Ġassum ption",
+ "Ġfit ness",
+ "ÃŃ cul",
+ "Ġpod r",
+ "Ġwe it",
+ "ĠH ind",
+ "Ġd ign",
+ "Ġз н",
+ "Ġsqu ad",
+ "Ġdest ro",
+ "c ere",
+ "sh irt",
+ "imm t",
+ "eng ers",
+ "Ġs ä",
+ "k ÅĤad",
+ "Ġ ÈĻ",
+ "Ġocc as",
+ "Ġì¤ Ħ",
+ "Ġprocess or",
+ "ĠD M",
+ "ĠDad dy",
+ "Ġsoon er",
+ "Ġstraight forward",
+ "Ġdepart ments",
+ "ĠChr ome",
+ "Ġwork place",
+ "ĠPy thon",
+ "Ġm eng",
+ "ĠD AN",
+ "ĠI ce",
+ "ĠëĪ Ī",
+ "ĠG i",
+ "Ġh iring",
+ "Ġland ed",
+ "Ġdemocr atic",
+ "ied z",
+ "ãģĺ ãĤĥ",
+ "Ġse v",
+ "ic ia",
+ "Ġespe cial",
+ "ĠN ous",
+ "Ġh ät",
+ "Ġb ou",
+ "per t",
+ "ies z",
+ "åij Ģ",
+ "Ġv il",
+ "ÅĽ li",
+ "Ġî n",
+ "Ġloss es",
+ "éķ ·",
+ "Ġto ast",
+ "Ġreal m",
+ "ĠAust in",
+ "ĠIn formation",
+ "Ġres ume",
+ "Ġch ase",
+ "Ġsal ary",
+ "Ġë¶ Ħ",
+ "ли Ñĩ",
+ "ĠÑģл ед",
+ "ĠFur ther",
+ "Ġcar ing",
+ "Ġv ig",
+ "Ġval or",
+ "è¿Ļ 个",
+ "ĠÑĩ а",
+ "Ġanalyt ics",
+ "Ġglo be",
+ "ĠM AN",
+ "Ġn el",
+ "ìĿ´ì ķ¼",
+ "Ł ¼",
+ "Ġo y",
+ "íķĺ ìĦ¸ìļĶ",
+ "j en",
+ "Ġtrou bles",
+ "ah aha",
+ "Ġchurch es",
+ "u et",
+ "Ġmeasure ments",
+ "b il",
+ "ì ½",
+ "if ully",
+ "ин Ñĥ",
+ "ĠWil son",
+ "¦ ´",
+ "ĠíĮ Į",
+ "Ġì° ¨",
+ "Ġp úblic",
+ "ĠJer usalem",
+ "Ġn ails",
+ "Ġsp ine",
+ "Ġhe mos",
+ "Ġz n",
+ "qu is",
+ "ĠLe ben",
+ "Ġrefer ences",
+ "IT H",
+ "i per",
+ "ĠÑģеб Ñı",
+ "ì ģ",
+ "ĠW a",
+ "st ate",
+ "§ Ŀ",
+ "åħ ±",
+ "ĠGen er",
+ "Ġact ress",
+ "ĠEn joy",
+ "๠ĥ",
+ "Ġ× Ĵ",
+ "Ġinfect ed",
+ "Ġsh aking",
+ "Ġn ick",
+ "ภ¸",
+ "Ġf ot",
+ "Ġaccompl ished",
+ "u ke",
+ "Ġshe ets",
+ "Ġf ence",
+ "Ġnurs ing",
+ "Ġintrodu cing",
+ "Ġfe at",
+ "O ne",
+ "T O",
+ "Ġcl ubs",
+ "ĠBru ce",
+ "on ge",
+ "ch ange",
+ "ĠBat man",
+ "åı °",
+ "ĠOffic er",
+ "Ġhyd ro",
+ "Ġsupp lement",
+ "Ġc ela",
+ "Ġlong est",
+ "Ġcompet ing",
+ "Ġcon he",
+ "g iving",
+ "Ġbra ins",
+ "Ġlo ans",
+ "Ġw age",
+ "ĠCl inton",
+ "Ġs Äĥ",
+ "ane ous",
+ "Ġl ord",
+ "ÑĢÑĥ ж",
+ "Ġqu iz",
+ "Ġst iff",
+ "ĠL GB",
+ "s z",
+ "M E",
+ "m are",
+ "th ere",
+ "Ġn är",
+ "ĠM and",
+ "l ast",
+ "Ġd ag",
+ "Ġhalf way",
+ "ĠB and",
+ "Ġëĭ¤ ìĭľ",
+ "ĠA ren",
+ "Ġi le",
+ "P N",
+ "ent o",
+ "Ġalg um",
+ "Ġsoc cer",
+ "Ġblock ed",
+ "ĠJon athan",
+ "Ġse w",
+ "ĠTest ament",
+ "Ġv ale",
+ "Ġbehav i",
+ "å§ ĭ",
+ "Ġcon na",
+ "IC H",
+ "Ġaud iences",
+ "m l",
+ "amm ad",
+ "ĠìĤ ´ì",
+ "I GH",
+ "Ġr aces",
+ "em ed",
+ "Ġm á»Ļt",
+ "Ã ¯",
+ "Ġover s",
+ "Ġdecl ared",
+ "Ġs ana",
+ "ĠU na",
+ "ĠÑĢ е",
+ "uck s",
+ "Ġp airs",
+ "Ġan ge",
+ "N e",
+ "Ġup s",
+ "av y",
+ "ø r",
+ "ree k",
+ "Ġbehav iors",
+ "Ġreflect ed",
+ "Ġprior ities",
+ "Ġcon du",
+ "Ġret reat",
+ "Ġexp enses",
+ "Ġë´ IJ",
+ "Ġtri ple",
+ "Ġêµīìŀ¥ íŀĪ",
+ "ä lt",
+ "Ġind igenous",
+ "Ġmin ing",
+ "Ġaccept able",
+ "Ġru in",
+ "C A",
+ "u ine",
+ "Ġpip eline",
+ "ct ic",
+ "ê t",
+ "ĠвÑģ его",
+ "Ġb oun",
+ "ĠDig ital",
+ "ĠBo om",
+ "ÑĨ е",
+ "Ġл ÑĥÑĩ",
+ "Ġas c",
+ "ĮĢë ¡ľ",
+ "ĠGood bye",
+ "Ġrend er",
+ "ene z",
+ "ar re",
+ "ĠTH AT",
+ "b our",
+ "ic ión",
+ "ãĤ Ń",
+ "E very",
+ "Ġw ires",
+ "ĠPar liament",
+ "n ung",
+ "ate ur",
+ "ĠS ave",
+ "ĠPh ys",
+ "Ġam or",
+ "ĠE ve",
+ "Ġfr ight",
+ "Ġgam ma",
+ "Ġmic ros",
+ "m itt",
+ "ĠC ode",
+ "ĠBe y",
+ "pl ed",
+ "ĠиÑģп олÑĮз",
+ "ç Ĺ",
+ "ìĥ ī",
+ "å¥ ¹",
+ "Ġmon et",
+ "ĠJah re",
+ "Ġlux ury",
+ "Ġde af",
+ "Ġbet ray",
+ "Ġê² °",
+ "и ки",
+ "Ġdefe ated",
+ "Ġunder t",
+ "Ġwe g",
+ "Ġcool er",
+ "ãģķ ãĤĵ",
+ "iam i",
+ "éĤĦ æľī",
+ "ĠJess ica",
+ "ĠJ oy",
+ "Ġsoph istic",
+ "ени и",
+ "ðĿ ĺ",
+ "Ġch ili",
+ "ĠTy pe",
+ "Ġprote ins",
+ "Ġpresent ing",
+ "al ia",
+ "ìļ ¸",
+ "ĠMaj or",
+ "Ġmolec ule",
+ "um er",
+ "Ġcoll apse",
+ "ĠAny ways",
+ "ĠMount ain",
+ "ant ed",
+ "ãĢ IJ",
+ "Ġвиде о",
+ "æ° ´",
+ "A ud",
+ "Ġcon qu",
+ "Ġvo ll",
+ "Ġkn it",
+ "Ġmem br",
+ "ĠMark et",
+ "Ġd ari",
+ "Ġcalcul ated",
+ "г и",
+ "Ġshrim p",
+ "ĠM u",
+ "ĠпÑĢ оÑĤ",
+ "Ġìĺģ ìĥģ",
+ "Ġproduct ivity",
+ "Ġcogn itive",
+ "ĠHe b",
+ "ict ions",
+ "ê² ½",
+ "Ġcr é",
+ "f ör",
+ "Ġpray ing",
+ "ash i",
+ "ĠT ik",
+ "ó r",
+ "w en",
+ "ÑĮ Ñİ",
+ "ix o",
+ "Ġ( \"",
+ "ĠÑĤ ел",
+ "Ġìĸ´ëĸ ¤",
+ "ĠпеÑĢ ед",
+ "ĠD rive",
+ "ãĢ ij",
+ "ĠE qu",
+ "Ġequilib rium",
+ "Ġdescri bes",
+ "не е",
+ "4 2",
+ "ĠCur rent",
+ "y y",
+ "Ġabsor b",
+ "Ġsold ier",
+ "d ers",
+ "Ġtestim ony",
+ "Ġdec line",
+ "ľë ¡ľ",
+ "g age",
+ "Ġinsp ire",
+ "la pping",
+ "Ġspin ning",
+ "Ġsla very",
+ "Ġfac ial",
+ "Ġtrad itions",
+ "ári os",
+ "ĠHosp ital",
+ "Ġn est",
+ "ĠëĪ Ħ",
+ "Ġto i",
+ "Ġfe ars",
+ "ìħ ¨",
+ "ĠM uh",
+ "Ġgradu ation",
+ "Ġimpact ed",
+ "Ġa unt",
+ "ĠLet s",
+ "Ġalumin um",
+ "Ġdomin ant",
+ "ĠDav is",
+ "ĠNav y",
+ "Ġcom pt",
+ "op les",
+ "Ġest ava",
+ "è ¥",
+ "Ġsc al",
+ "Ġpres erve",
+ "ĠO pp",
+ "Ġpract ically",
+ "Ġmagn itude",
+ "Ġf itting",
+ "Ġcoordin ate",
+ "Ġfurn iture",
+ "ĠFam il",
+ "Ġexplos ion",
+ "Ġdocument ary",
+ "ĠS cript",
+ "Ġport ray",
+ "m at",
+ "Ġschedul ed",
+ "Ġdynam ics",
+ "ph y",
+ "ak y",
+ "ĠU I",
+ "C he",
+ "Ġcontinu ously",
+ "ĠPro v",
+ "å° ij",
+ "Ñĥ з",
+ "ra h",
+ "Ġger ne",
+ "pro of",
+ "Ġsecret ary",
+ "ĠPat reon",
+ "sc ream",
+ "ĠK ids",
+ "á»ĵ i",
+ "Ġk g",
+ "Ġuncertain ty",
+ "Ġк ажд",
+ "Ġmit ig",
+ "Ġread s",
+ "å· ²",
+ "ĠR u",
+ "Ġpri est",
+ "Ġн ед",
+ "Ġlimit ations",
+ "Ġflo at",
+ "6 00",
+ "ĠT oy",
+ "ĠJim my",
+ "Ġoff ensive",
+ "en i",
+ "ĠX i",
+ "Ġeye br",
+ "ĠTur k",
+ "Ġaccident ally",
+ "Ġoh ne",
+ "ĠS aud",
+ "9 5",
+ "ĠD utch",
+ "ан Ñģ",
+ "ĠSe attle",
+ "Ġëĵ ±",
+ "che ck",
+ "k ÄĻ",
+ "Ġcontrib utions",
+ "Ġbes ide",
+ "Ġqu indi",
+ "Ġfle w",
+ "æĹ ¶",
+ "ذ ا",
+ "ĠL O",
+ "Ġwa ist",
+ "ĠE V",
+ "Ġhol idays",
+ "j on",
+ "Ġmis under",
+ "Ñı н",
+ "Ġb out",
+ "Ġd imin",
+ "Ạ½",
+ "ó l",
+ "ĠGr ace",
+ "Ġinput s",
+ "Ġden y",
+ "Ġform ing",
+ "ĠB ild",
+ "Ġad equ",
+ "Ġfol k",
+ "Ġreject ed",
+ "se mb",
+ "Ġfrust rated",
+ "op en",
+ "ĠBet ter",
+ "il on",
+ "Ġtow el",
+ "Ġdifferent ial",
+ "Ġsac red",
+ "Ġsa il",
+ "éĩ Į",
+ "ent imes",
+ "Ġgentle man",
+ "Ġicon ic",
+ "Ġcomp aring",
+ "Ġs agt",
+ "Ġtext s",
+ "Ġgrand ma",
+ "Ġroll s",
+ "Ġcont ents",
+ "ä¸į 好",
+ "оÑģ Ñģ",
+ "Ġsusp ension",
+ "ro it",
+ "¦ ¼",
+ "Ġasse z",
+ "Ġd ort",
+ "ĠM ath",
+ "ĠVict or",
+ "ĠJava Script",
+ "ä¸į å°į",
+ "Ġen han",
+ "Å Ļ",
+ "ĠB ush",
+ "Ġpromot ion",
+ "Ġk in",
+ "Ġmon sters",
+ "ĠColor ado",
+ "ĠÎ ²",
+ "íķ´ì ļĶ",
+ "æŃ £",
+ "iffer ent",
+ "Ġn aked",
+ "Ġpro d",
+ "et ics",
+ "ĠW oman",
+ "Ġtreat ments",
+ "Ġest oy",
+ "v é",
+ "Ġlif ting",
+ "Ġy apt",
+ "ĠRo ber",
+ "Ġì¹ ľ",
+ "Ġsubst itute",
+ "ak u",
+ "r idge",
+ "Ġê± °ë",
+ "Ġrespond ed",
+ "Ġb é",
+ "ĠEngine er",
+ "Ġtransfer red",
+ "ë ²",
+ "Ġha ber",
+ "o op",
+ "ĠW E",
+ "Ġv est",
+ "Ġfor ty",
+ "ĠD S",
+ "Ġ200 4",
+ "Ġco aching",
+ "n om",
+ "ĠB ab",
+ "Ġn ossa",
+ "ĠJ ake",
+ "Ġg y",
+ "Ġde leg",
+ "Ġìŀ ł",
+ "ĠкÑĢ аÑģ",
+ "Ġstand point",
+ "Ġdis ad",
+ "Ġart work",
+ "A d",
+ "ill o",
+ "ĠÄij ược",
+ "ĠPr om",
+ "ĠL ib",
+ "Ġcritic ism",
+ "Ġcontact s",
+ "ÑĢ ам",
+ "Ġachieve ment",
+ "ÐĶ а",
+ "Ġdiss ol",
+ "ĠVeg as",
+ "Ġstream s",
+ "ĠK ent",
+ "ĠعÙĦ Ùī",
+ "Ġrad ius",
+ "Ġsu cks",
+ "ĠA ch",
+ "Ġf i",
+ "ou st",
+ "ĠлÑİд и",
+ "Ġpal ette",
+ "ĠH az",
+ "ĠAnth ony",
+ "Ġtem a",
+ "ĠC os",
+ "Ġsa fer",
+ "α ÏĤ",
+ "Ġcont rad",
+ "Ġma ior",
+ "Ġinfl ation",
+ "ĠSil ver",
+ "Ġatt ending",
+ "íķľ íħĮ",
+ "art o",
+ "Ġapplaud ing",
+ "Ġcomput ing",
+ "ĠH at",
+ "æ »",
+ "k now",
+ "mak ers",
+ "Ġcon oc",
+ "Ġeduc ated",
+ "Ġmod ified",
+ "Ġinc lusion",
+ "ment al",
+ "ŀ IJ",
+ "is ia",
+ "ĠÏĢ οÏħ",
+ "Ġa un",
+ "ĠIre land",
+ "Ġk ö",
+ "Ġcompl iance",
+ "Ġinsp iring",
+ "иÑĤелÑĮ но",
+ "Ġdisp os",
+ "ì° ¨",
+ "Ġw ip",
+ "r ical",
+ "raw d",
+ "Ġt res",
+ "Ġmob il",
+ "olut ions",
+ "B O",
+ "Ġb ounce",
+ "Ġassum ed",
+ "ĠMed ical",
+ "Ġf iscal",
+ "Ġng Æ°á»Ŀi",
+ "ition ally",
+ "Ġst olen",
+ "ĠB M",
+ "Ġmechanism s",
+ "ε ί",
+ "Ġqual ified",
+ "Ġìŀ IJë",
+ "ught ers",
+ "ĠH IV",
+ "ĠL ots",
+ "Ġser vers",
+ "Ġcar r",
+ "ĠT ogether",
+ "Ġattract ed",
+ "Ġk r",
+ "æĪij æĺ¯",
+ "th ur",
+ "in in",
+ "ĠH alf",
+ "È Ľ",
+ "ĠP ap",
+ "Ġremind ed",
+ "AL L",
+ "Ġhel met",
+ "Ġbott les",
+ "Ġprofess ors",
+ "Ġse ine",
+ "ÅĤ Äħ",
+ "ãĥ ı",
+ "Ġê±° ìķ¼",
+ "Ġ×¢ ׾",
+ "f un",
+ "ĠB ird",
+ "Ġfight er",
+ "ĠëĶ °ë",
+ "ĠT ool",
+ "Ġt in",
+ "ino is",
+ "ë ¶Ħ",
+ "×Ļ× Ł",
+ "ĠC AR",
+ "åIJ į",
+ "irst y",
+ "Ġout door",
+ "ĠN S",
+ "ãħ İ",
+ "ff en",
+ "Ġl ud",
+ "H ello",
+ "Ġroll er",
+ "ie le",
+ "ĠPol and",
+ "Ġap a",
+ "ex p",
+ "Ġcertific ate",
+ "ĠT own",
+ "аÑİÑĤ ÑģÑı",
+ "ild e",
+ "Ġdeterm in",
+ "P R",
+ "Ġfree ze",
+ "Ġmain stream",
+ "Ġobject ives",
+ "b lo",
+ "Ġtak ie",
+ "åĵĪ åĵĪ",
+ "Ġë°Ķë ¡ľ",
+ "el et",
+ "ĠI V",
+ "ĠF ast",
+ "Ġd ere",
+ "em p",
+ "ĠD ra",
+ "ĠìŀĪ ìĹĪ",
+ "Ġdisc rimination",
+ "Ġε ίναι",
+ "ne cess",
+ "æ ®",
+ "ıģ ı",
+ "Ġpost ing",
+ "wi ÅĽcie",
+ "Ġl ub",
+ "Ġol ive",
+ "Ġr im",
+ "Ġmodel ing",
+ "Ġa ño",
+ "ĠPak istan",
+ "Ġover l",
+ "Ġinf lam",
+ "N E",
+ "ìĹIJ ê²Į",
+ "Ġatt ended",
+ "Ġdeal t",
+ "ĠAl t",
+ "ĠL incoln",
+ "Ġaw ake",
+ "Ġfil ters",
+ "ĠWith in",
+ "czy wiÅĽcie",
+ "Ġs û",
+ "ĠJohn ny",
+ "Ġintegr ity",
+ "Ġisol ation",
+ "ĠE asy",
+ "ĠпÑĢ ин",
+ "ĠAl ice",
+ "Ġsm iling",
+ "en ix",
+ ", ...",
+ "Î ¶",
+ "Ġbeg un",
+ "Ġjew el",
+ "Ġconvention al",
+ "Ġstat ist",
+ "Ġhand ed",
+ "Ġir re",
+ "Ġpro hib",
+ "Ġsatell ite",
+ "é¦ Ļ",
+ "ĠInd ust",
+ "Ġtra ged",
+ "Ġtra va",
+ "Ġih m",
+ "Ġcru el",
+ "ĠAg ora",
+ "ĠD oc",
+ "Ġz ones",
+ "Ġm all",
+ "Ġtr ay",
+ "×ķ× ł",
+ "Ġir rit",
+ "Ġk ans",
+ "ĠBe at",
+ "ud ge",
+ "ie lle",
+ "Ġtrust ed",
+ "Ġb ikes",
+ "ĠÑĥ п",
+ "ĠM ember",
+ "w ick",
+ "Ġcreat ors",
+ "Ġher itage",
+ "ind istinct",
+ "Ġres ur",
+ "enn en",
+ "C ome",
+ "Ġf iring",
+ "ĠBu eno",
+ "ĠТ о",
+ "ik an",
+ "ett es",
+ "Ġk es",
+ "Ġtri ps",
+ "Ġdivor ce",
+ "ĠK l",
+ "Ġcons ol",
+ "ke ep",
+ "기 ê°Ģ",
+ "ĠRep ort",
+ "Ġhost ing",
+ "Ġdiam ond",
+ "Ġcompl ic",
+ "Ġhel icop",
+ "Ġdep uis",
+ "d s",
+ "ĠCh an",
+ "Ñı л",
+ "Ġsc issors",
+ "il ation",
+ "Ġprop ortion",
+ "ER E",
+ "ĠÙĪ اÙĦ",
+ "int a",
+ "Ġmuch as",
+ "u ation",
+ "it is",
+ "æĬ Ĭ",
+ "Ñı Ñī",
+ "Ġni in",
+ "Ġemphas ize",
+ "uel a",
+ "Ġprodu cers",
+ "Ġr ze",
+ "änd er",
+ "ET H",
+ "æ º",
+ "Ġconst itu",
+ "åĽ ½",
+ "Ġperform ances",
+ "ist le",
+ "go v",
+ "ĠL iter",
+ "Ġincorpor ate",
+ "Ġeduc ate",
+ "ĠN in",
+ "ì ª½",
+ "Ùĩ Ùħ",
+ "el eration",
+ "×ķ× ij",
+ "Ġya ÅŁ",
+ "or ous",
+ "ĠC as",
+ "Ġgr ants",
+ "ëĬ ¥",
+ "am el",
+ "Ġê·¸ë łĩê²Į",
+ "ĠE ste",
+ "Ñħод иÑĤ",
+ "ĠпоÑģ ле",
+ "Ġg ent",
+ "Ġfocus es",
+ "al ities",
+ "ĠR h",
+ "ë ³´",
+ "æ° ij",
+ "ĠD ance",
+ "r r",
+ "Ġam er",
+ "Ġutil ize",
+ "Ġl ÃŃ",
+ "ĠAm ong",
+ "Ġpregn ancy",
+ "Ġlo ops",
+ "ал оÑģÑĮ",
+ "ĠM oh",
+ "Ġcatch ing",
+ "Ġglo b",
+ "Ġa jud",
+ "Ġ[ ?",
+ "ĠAn al",
+ "lo oking",
+ "Ġsurf aces",
+ "Ġprogress ive",
+ "Ġvir al",
+ "0 8",
+ "Î ¾",
+ "K A",
+ "Ġ ży",
+ "Ġpick s",
+ "ann on",
+ "Ġbul k",
+ "ĠR oss",
+ "Ġdescri bing",
+ "ĠG el",
+ "Ġloc ally",
+ "Ġend less",
+ "Ġmass age",
+ "Ġclean ed",
+ "Ġtravel ed",
+ "ен Ñĭ",
+ "Ġsent iment",
+ "ig ma",
+ "ĠN as",
+ "Ġchemical s",
+ "Ġright eous",
+ "ĠMag ic",
+ "Ġrel ates",
+ "Ġtruck s",
+ "Ġ19 60",
+ "åĪ ¥",
+ "Ġapp et",
+ "Ġsn acks",
+ "ĠSum mer",
+ "Ġy üz",
+ "Ġpr is",
+ "ĠMex ican",
+ "Ġtransp aren",
+ "Ġminor ity",
+ "Ġver te",
+ "Ġl assen",
+ "4 6",
+ "л ек",
+ "é p",
+ "ĠÑĦ илÑĮ",
+ "Ġi yi",
+ "Ġsp an",
+ "íķĺ ì§Ģ",
+ "Ġind icated",
+ "qu ar",
+ "Ġscholars hip",
+ "ĠLGB T",
+ "Ġhistor ically",
+ "ó ÅĤ",
+ "Ġmin ist",
+ "Ġpen et",
+ "ĠR ap",
+ "Ġcons ervation",
+ "çĽ ´",
+ "ĠH oney",
+ "ĠBe i",
+ "id el",
+ "Ġrespons ibilities",
+ "Ġmess y",
+ "ĠEx cept",
+ "OR E",
+ "Ġiniti atives",
+ "Ġjun ior",
+ "Ġdesign ers",
+ "Ġexpl oration",
+ "Ġspons or",
+ "Ġmob ility",
+ "Ġint eg",
+ "land o",
+ "Ġb ark",
+ "Ġindic ates",
+ "à ¶",
+ "Ġemploy er",
+ "å® ī",
+ "Ġcous in",
+ "Ġbo iling",
+ "Ġch rom",
+ "Ġç al",
+ "Ġper pet",
+ "Ġcont ained",
+ "Ġpark s",
+ "Ð «",
+ "ĠEngine ering",
+ "P lease",
+ "ĠStart ing",
+ "her o",
+ "Ġlaw yers",
+ "è¥ ¿",
+ "Ġz d",
+ "Ġfranch ise",
+ "ra ge",
+ "Ġint uit",
+ "ĠG L",
+ "re ach",
+ "ĠE lle",
+ "Ġnh Æ°",
+ "ĠN ord",
+ "Ġbe an",
+ "0 7",
+ "Ġple asant",
+ "å½ ĵ",
+ "v iron",
+ "Ġgrad ient",
+ "z us",
+ "ĠE M",
+ "Ġess ay",
+ "ìĹIJ ìļĶ",
+ "ế n",
+ "n u",
+ "á» «",
+ "ĠÃī s",
+ "Ġden omin",
+ "ĠGirl s",
+ "Ġperson nes",
+ "ĠاÙĦØ £",
+ "b ild",
+ "ĠSt at",
+ "Ġcompl iment",
+ "ĠK ate",
+ "Ġoptim al",
+ "Ġh id",
+ "د ÙĬ",
+ "Ġquick er",
+ "w all",
+ "E n",
+ "IN E",
+ "?? ?",
+ "ì² ´",
+ "ĠA ction",
+ "å Ł",
+ "Ġpenal ty",
+ "ĠK az",
+ "' ?",
+ "Ġc ried",
+ "Ġcan vas",
+ "ft e",
+ "Ġexc lud",
+ "¸ë ¡ľ",
+ "Ġemphas is",
+ "Ġen zy",
+ "ĠH ou",
+ "Ġoverse as",
+ "ÃŃ amos",
+ "å¸ «",
+ "ö glich",
+ "Ġhead phones",
+ "c n",
+ "ĠA ge",
+ "Ġa kan",
+ "Ġcharacter istic",
+ "íķĺë ©´",
+ "get s",
+ "Ġë¶ Ī",
+ "Ġr ival",
+ "Ġb orders",
+ "em ente",
+ "em ás",
+ "Ġy ol",
+ "Ġcom pe",
+ "end ers",
+ "ınd an",
+ "Ġmö glich",
+ "Ġbubb les",
+ "nat ural",
+ "Ġar med",
+ "Ġel abor",
+ "ĠìĿ´ë ²Ī",
+ "Ġwash ed",
+ "οÏħ με",
+ "è« ĭ",
+ "Ġfl avors",
+ "Ġexist e",
+ "Ġpre st",
+ "ĠThe ma",
+ "оп ÑĢоÑģ",
+ "er on",
+ "U E",
+ "er i",
+ "Ġconc er",
+ "Ġa ixò",
+ "åħ ©",
+ "Ġprotect ive",
+ "Ġзна Ñİ",
+ "ĠëĤ ł",
+ "ĠII I",
+ "Ġme er",
+ "ĠSh op",
+ "ll i",
+ "ĠOr der",
+ "ĠM Y",
+ "ĠG host",
+ "ãĤĤ ãģĨ",
+ "ad el",
+ "Ġst ole",
+ "Ġrele asing",
+ "ĠCom ment",
+ "Ġtra ins",
+ "ë ªħ",
+ "Ġw issen",
+ "ens ed",
+ "Ġdesc end",
+ "Ġf ier",
+ "Ġrad i",
+ "Ġpers u",
+ "ç ¢",
+ "Ġм н",
+ "ĠD est",
+ "Ġwor ries",
+ "it et",
+ "b as",
+ "Ġst ab",
+ "n ame",
+ "or ic",
+ "ĠCl ose",
+ "Ġalum ni",
+ "ĠS elf",
+ "ff e",
+ "it ating",
+ "ather ine",
+ "ĠRight s",
+ "Ġell os",
+ "Ġwar rant",
+ "Ġn erve",
+ "Ġveget able",
+ "ĠTe il",
+ "Ġê°Ļ ìĿ´",
+ "R Y",
+ "Ġsustain ability",
+ "Ġste ht",
+ "Ġbr id",
+ "ada ÅŁ",
+ "Ġt v",
+ "Ġdur ation",
+ "Ġpesso a",
+ "Ġmet rics",
+ "Ġad am",
+ "c as",
+ "аÑĢ и",
+ "Ġev ident",
+ "Ġdisplay ed",
+ "Ø§Ø ¦",
+ "Ġre ck",
+ "ĠBudd ha",
+ "Ġde le",
+ "ĠDie go",
+ "os ph",
+ "Ġb la",
+ "ĠM ik",
+ "ul ator",
+ "Ġ200 1",
+ "Ġpromot ing",
+ "y ch",
+ "ĠE X",
+ "Ġlast ly",
+ "Ġout line",
+ "Ġspir its",
+ "Ġve ux",
+ "Ġsubt ract",
+ "ĠÅŁ imdi",
+ "Ġp ins",
+ "Ġbur ger",
+ "Ġmol to",
+ "Ġhab ÃŃa",
+ "Ġë° ĺ",
+ "ig u",
+ "er st",
+ "Ġn en",
+ "Ġbac on",
+ "it ious",
+ "Ġcar ries",
+ "Ġprom ises",
+ "nd e",
+ "ĠLe ft",
+ "ĠL im",
+ "æ £",
+ "Ġ4 4",
+ "Ġcare ers",
+ "Ġì£ ¼ë",
+ "Ġspeed s",
+ "qu é",
+ "m ad",
+ "mark et",
+ "is me",
+ "Ġ200 3",
+ "Ġre cess",
+ "ĠJ UD",
+ "Ġrac ist",
+ "ĠSch l",
+ "Ġpar ler",
+ "Ġot ros",
+ "ish es",
+ "Ġconvert ed",
+ "aa aa",
+ "ани и",
+ "ĠAr k",
+ "ĠCh ance",
+ "Ġelement ary",
+ "ε ν",
+ "ink s",
+ "Inter viewer",
+ "Ġfre ely",
+ "al ah",
+ "Ġëĭ¤ë ¥¸",
+ "Ġrequest ed",
+ "Ġtor que",
+ "no ÅĽci",
+ "ou red",
+ "ĠSt aff",
+ "Ġst ain",
+ "ĠAl an",
+ "Ġv ere",
+ "ĠW inter",
+ "Ġdef ect",
+ "ied y",
+ "Ġbe ats",
+ "Ġh á",
+ "um n",
+ "o ons",
+ "it udes",
+ "Ġse it",
+ "o ly",
+ "Ġres erv",
+ "Ġext r",
+ "Ġphys ician",
+ "vis or",
+ "Ġhand ful",
+ "ĠN ations",
+ "Ġì¢ĭ ìĿĢ",
+ "uc cess",
+ "Ġup stairs",
+ "ĠSqu are",
+ "Ġhe in",
+ "ĠSe ason",
+ "ol is",
+ "Ġpr ince",
+ "Ġdef ensive",
+ "ç ½",
+ "Ġм еÑģÑĤ",
+ "Ñĸ й",
+ "Ġا ÙĨ",
+ "um ble",
+ "ê¹Į ìļĶ",
+ "Ġass ass",
+ "Ġcirc ular",
+ "Ġqual ities",
+ "Ġh mm",
+ "Ġbl own",
+ "ĠL iz",
+ "ĠK ur",
+ "ĠS A",
+ "Ġfind ings",
+ "Ġcol ours",
+ "Ġde lle",
+ "ĠI R",
+ "ĠA th",
+ "ĠD ub",
+ "ĠO x",
+ "ĠØ ®",
+ "Ġpo ckets",
+ "Ġgr ill",
+ "Ġswitch ing",
+ "Ġprefer red",
+ "ĠW ales",
+ "Ġex emplo",
+ "Ġchop ped",
+ "Ġvacc ination",
+ "Ġne uro",
+ "Ġspec ify",
+ "iv os",
+ "Ġser á",
+ "Ġz ie",
+ "Ġà® ®",
+ "Ġresult ing",
+ "ĠU gh",
+ "Ġmess ed",
+ "C D",
+ "Ġpa ar",
+ "Ġcom er",
+ "Ġcou ch",
+ "ĠFest ival",
+ "Ġ4 9",
+ "v ous",
+ "z ens",
+ "ç¨ ®",
+ "ĠKenn edy",
+ "ĠT s",
+ "Ġë³´ì Ĺ",
+ "Ġdemonst ration",
+ "Ġun to",
+ "Ġfrust rating",
+ "Ġlabor atory",
+ "Ġe gy",
+ "Ġbeaut ifully",
+ "Ġìŀ ¬ë",
+ "Ġal gu",
+ "Ġö yle",
+ "ä½ł çľĭ",
+ "ĠP H",
+ "Ġfort une",
+ "Ġclean er",
+ "ĠRob in",
+ "Ġsa us",
+ "ĠG eld",
+ "Ġk at",
+ "o bs",
+ "Ġol ur",
+ "Ġm att",
+ "Ġquest a",
+ "Ġsuggest ion",
+ "en cer",
+ "о ÑģÑĤ",
+ "Ġrad ar",
+ "Ġìŀ ¡",
+ "ish a",
+ "à® ¨",
+ "ãĤĵ ãģª",
+ "j es",
+ "Ġve el",
+ "ìĤ °",
+ "Ġauth ors",
+ "ãĢ İ",
+ "pl an",
+ "Ġcollabor ative",
+ "Ġinst inct",
+ "Ġfar ming",
+ "au ge",
+ "E du",
+ "Ġmembers hip",
+ "Ġsimult aneously",
+ "Ġb ake",
+ "Ġk ä",
+ "Ġlect ures",
+ "Ñĩ еÑģ",
+ "Ġprend re",
+ "Ġcoll aps",
+ "ĠS aya",
+ "ĠF ut",
+ "Ġy og",
+ "ĠR ather",
+ "ر ÙĬ",
+ "Ġcamp s",
+ "ол од",
+ "Ġsim ulation",
+ "ĠM ak",
+ "La ughs",
+ "Ġgre y",
+ "Ġsent ences",
+ "y en",
+ "ĠUn less",
+ "J e",
+ "ĠSat an",
+ "ĠÑĤак же",
+ "ĠN A",
+ "Ġbr on",
+ "Ġ? ]",
+ "Ġsoul s",
+ "Ġlight ning",
+ "Ġimag ined",
+ "Ġczy li",
+ "ps ilon",
+ "et ta",
+ "Ġbelie ving",
+ "Ġstrong est",
+ "ĠC ON",
+ "Ġquel ques",
+ "Ġimmig rants",
+ "Ġwall et",
+ "éĢĻ æĺ¯",
+ "ĠJer sey",
+ "Ġimplic ations",
+ "Ġfor b",
+ "ãĢ ı",
+ "Ġun believable",
+ "Ø§Ø ¡",
+ "Ġoper ational",
+ "ü s",
+ "ĠG M",
+ "Ġê·¸ëŁ °ëį°",
+ "Ġgrac ias",
+ "Ġent end",
+ "ĠReg ard",
+ "ro b",
+ "ĠÑĤ еÑħ",
+ "è ı",
+ "ĠRev olution",
+ "Ġwa ar",
+ "ĠB iz",
+ "th eless",
+ "Ġspons ored",
+ "qu ier",
+ "ĠìĿ ¼ë",
+ "Ġte k",
+ "ĠëIJ ł",
+ "ig keit",
+ "ĠL uck",
+ "ĠCertain ly",
+ "Ġto ll",
+ "Ġн иÑĩего",
+ "ĠM oney",
+ "ĠÑģ ÑĤоÑĢ",
+ "ĠDou ble",
+ "ĠW olf",
+ "Ġch unk",
+ "ά ν",
+ "it és",
+ "on ing",
+ "M ar",
+ "Ġgrand es",
+ "Ġcollect ions",
+ "ĠEurop a",
+ "Ġа ÑĢ",
+ "ĠâĢĭâĢĭ âĢĭ",
+ "Ġê·¸ëŁ¬ë ©´",
+ "Ġоб ÑĬ",
+ "Ġãģ ª",
+ "Ġìĭľ ê°Ħ",
+ "ĠC ustom",
+ "Ġì² ĺ",
+ "Ñĸ лÑĮ",
+ "Ġindivid ually",
+ "í Ĺ",
+ "Ġdo zen",
+ "Ġo we",
+ "ĠVict oria",
+ "åı¯ èĥ½",
+ "Ġbe et",
+ "ur b",
+ "Ġanal og",
+ "i ção",
+ "Ĥ ľ",
+ "so ever",
+ "Ġmod o",
+ "Ġsubscri bed",
+ "ìŀ ¬",
+ "Ġent ities",
+ "çī ĩ",
+ "Ġclos et",
+ "Ġrespond ing",
+ "Ġprin ter",
+ "ĠStep han",
+ "Ġby ÅĤ",
+ "ĠD om",
+ "ĠF ern",
+ "ĠP ier",
+ "ĠwiÄĻ c",
+ "Ġh ence",
+ "Ġmod ules",
+ "ãĥ ¬",
+ "ĠëĶ ±",
+ "ĠDann y",
+ "ĠÑģеб е",
+ "Ġv ad",
+ "ĠìĹ Ħ",
+ "Ġs ous",
+ "Ġsp here",
+ "B Y",
+ "ĠP ed",
+ "ign ed",
+ "Ġwhe at",
+ "Ġund ers",
+ "Ġevol ve",
+ "Ġdec lar",
+ "Ġlight ly",
+ "Ġident ifying",
+ "æĦı æĢĿ",
+ "Ġlegend ary",
+ "Ġgen uine",
+ "Ġgr ind",
+ "ĠU ne",
+ "ge ben",
+ "Ġb icy",
+ "Ġjump s",
+ "Ġprov ince",
+ "zi ÄĻ",
+ "Ġ×IJ× ł×Ļ",
+ "Ġh oc",
+ "Ġб л",
+ "ĠGr ad",
+ "Ġreven ge",
+ "ĠاÙĦ ت",
+ "o oh",
+ "æĭ ľ",
+ "аÑĨи и",
+ "å¹ ³",
+ "Ġelect ro",
+ "ĠëIJ IJ",
+ "ãģ§ ãģ¯",
+ "Ġf als",
+ "ri el",
+ "ok er",
+ "ĠEx cellent",
+ "ĠMor gan",
+ "Ġbr ick",
+ "Ġsubstant ial",
+ "Ġpoll ution",
+ "ĠT ür",
+ "ĠEv et",
+ "Ġl ung",
+ "ãģ ĸ",
+ "×Ļ× ©",
+ "omm es",
+ "Ġreal izing",
+ "Ġhum ble",
+ "ĠL ock",
+ "Ġb od",
+ "Ġìĸ ¸",
+ "Ġpe ers",
+ "uz z",
+ "Ġembed ded",
+ "Ġclar o",
+ "Ġag greg",
+ "Ġemploy ers",
+ "ĠR aj",
+ "Ġãģ ¨",
+ "ĠY i",
+ "Ġje u",
+ "at ers",
+ "Ġstri kes",
+ "n os",
+ "aut res",
+ "d r",
+ "op her",
+ "ĠApp arently",
+ "íĺ Ħ",
+ "Ġinf ant",
+ "ا ب",
+ "ÑĤ Ñĭ",
+ "í Ľ",
+ "Ú ¯",
+ "Ġred es",
+ "acaģ ım",
+ "ĠDA VID",
+ "ĠCh icken",
+ "Ġperspect ives",
+ "Ġview er",
+ "Ġsh ar",
+ "ĠпÑĢо из",
+ "lig t",
+ "er os",
+ "it able",
+ "ил оÑģÑĮ",
+ "Ġdif ÃŃ",
+ "´ë į°",
+ "Ġret ired",
+ "Ġthat s",
+ "zen ie",
+ "be iten",
+ "Ġmy cket",
+ "ĠR ab",
+ "Ġinflam m",
+ "ì° ®",
+ "Ġd um",
+ "Ġdad dy",
+ "æľ Ł",
+ "Ġimm ers",
+ "Ġplay list",
+ "௠Ĩ",
+ "Ġtra um",
+ "Ġref use",
+ "st ep",
+ "à® ļ",
+ "c up",
+ "Ġpop s",
+ "r imin",
+ "ay ım",
+ "Ġa ld",
+ "Ġun necess",
+ "Ġd ah",
+ "ĠIr ish",
+ "Ġcomp r",
+ "la ÅŁ",
+ "T P",
+ "Ġtransl ated",
+ "S c",
+ "ce ÄŁim",
+ "´ IJ",
+ "Ġd rei",
+ "ĠлÑİд ей",
+ "Ġqu iero",
+ "Ġhe le",
+ "z lich",
+ "Ġapp les",
+ "Ġdistrict s",
+ "Ġcred its",
+ "Ġas p",
+ "Ġëĭ ¨",
+ "or al",
+ "å½ ±",
+ "Ġste pping",
+ "ĠV a",
+ "Ġg ains",
+ "6 5",
+ "Ġnuest ra",
+ "ed ay",
+ "ass ador",
+ "ĠL ind",
+ "Ġcrop s",
+ "ci endo",
+ "ig ue",
+ "Ġb ana",
+ "A m",
+ "Ġp ent",
+ "Ġadd iction",
+ "Ġpack aging",
+ "ä d",
+ "ª ¨",
+ "Ġper què",
+ "Ġcampaign s",
+ "Ġste ep",
+ "Ġne ue",
+ "Ġembarrass ed",
+ "Ġdist inction",
+ "it zer",
+ "åij Ĭ",
+ "Ġregist ration",
+ "Ġll am",
+ "ĠAlm ighty",
+ "li est",
+ "Ġu z",
+ "n ak",
+ "ç º",
+ "Ġter az",
+ "iam ente",
+ "Ġtrans actions",
+ "Ġc ôt",
+ "Ġswitch ed",
+ "Ġcom bo",
+ "Ġpray ers",
+ "Ġintern ship",
+ "Ġaddress es",
+ "Ġchar ity",
+ "ĠW OO",
+ "Ġb ait",
+ "è¿ ĩ",
+ "Ġ �",
+ "Ġf ica",
+ "ĠTy ler",
+ "ar u",
+ "Ġat oms",
+ "ĠLe vel",
+ "ĠпоÑĤ ом",
+ "Ġf ame",
+ "ul k",
+ "Ġteach es",
+ "Ġre build",
+ "ед ÑĮ",
+ "ĠIndones ia",
+ "ush i",
+ "ĠSh ort",
+ "Ġens uring",
+ "f s",
+ "e le",
+ "Ġmargin al",
+ "Ġconclud e",
+ "am t",
+ "Ġver ify",
+ "ĠMc Donald",
+ "Ġsk al",
+ "Ġrec onst",
+ "ĠM ann",
+ "Ġbas ement",
+ "Ġtransform ed",
+ "Ġoccasion ally",
+ "z one",
+ "ĠD ans",
+ "Ġкак ой",
+ "Ġdiagn osed",
+ "ĠÏĦ α",
+ "Ġcomm ands",
+ "Ġpresident ial",
+ "Ġab b",
+ "Ġbrack et",
+ "ĠL em",
+ "Ã¥ ng",
+ "Ġfavor ites",
+ "Ġrev ol",
+ "ĠíĬ ¹",
+ "Ġhar ass",
+ "é ħ",
+ "Ġcle ans",
+ "st änd",
+ "Ġknock ed",
+ "Ġpe oples",
+ "Ġmusic ians",
+ "Ġmut ual",
+ "ĠC old",
+ "8 8",
+ "ze j",
+ "at ie",
+ "ĠHon or",
+ "Ġobs essed",
+ "ĠM USIC",
+ "ĠBre ak",
+ "ú ng",
+ "Ġmod ify",
+ "Ġs öyle",
+ "Ġ×ŀ ×Ķ",
+ "ĠOn line",
+ "f o",
+ "ĠMill er",
+ "Ġlik ing",
+ "Ġin hab",
+ "Ġgrat itude",
+ "ĠJour nal",
+ "arn ess",
+ "J ohn",
+ "ĠG it",
+ "åī Ľ",
+ "Ġsin cere",
+ "ĠS ci",
+ "ĠE li",
+ "Ġsymbol s",
+ "Ġman ually",
+ "ε ÏĤ",
+ "Ġв Ñĸд",
+ "ĠF at",
+ "Ġlab els",
+ "Ġsophistic ated",
+ "ump s",
+ "Ġrele ases",
+ "Ġ4 7",
+ "ĠO M",
+ "ê°Ģ ë",
+ "ĠB ien",
+ "ĠRe f",
+ "è¨ ĺ",
+ "ĠSt a",
+ "ĠE gg",
+ "Ġindic ator",
+ "ps on",
+ "Ġnas ıl",
+ "R ight",
+ "Ġcon vey",
+ "Ġkn ot",
+ "Ġconnect s",
+ "ul as",
+ "Ġpre ced",
+ "Ġine quality",
+ "am iento",
+ "Ġrep ly",
+ "O Y",
+ "Ġdism iss",
+ "ĠëIJ ľ",
+ "çĦ ¡",
+ "ĠÑħоÑĢоÑĪ о",
+ "Ġm éd",
+ "Ġrandom ly",
+ "ĠO nt",
+ "u ard",
+ "Ġpull s",
+ "ĠÑĤ епеÑĢÑĮ",
+ "ĠNe ed",
+ "ĠSo ft",
+ "Ġstrength s",
+ "Ġgo ed",
+ "um en",
+ "æŃ »",
+ "Ġíİ ¸",
+ "Ġд об",
+ "Ġclar ity",
+ "ĠA i",
+ "Ġball oon",
+ "ĠP and",
+ "ĠìķĦ ëĭ",
+ "Ġsh iny",
+ "Ġsmall est",
+ "on ia",
+ "h ill",
+ "ot ing",
+ "Ġe ing",
+ "Ġmere ly",
+ "Ġse us",
+ "Ġн еп",
+ "Ġí Ĩµ",
+ "Ġgu ides",
+ "Ġspecial ist",
+ "Ġste ak",
+ "ãĤĪ ãģĨ",
+ "Ġmig ration",
+ "que le",
+ "Ġru ined",
+ "Ġpu pp",
+ "å¥ ³",
+ "Ġk end",
+ "ang an",
+ "Ġpal m",
+ "Ġunf air",
+ "Ġz m",
+ "ĠD V",
+ "ch ester",
+ "и Ñİ",
+ "Ġo oh",
+ "er g",
+ "AT H",
+ "° ©",
+ "åĵ ª",
+ "r ison",
+ "Ġinvol ving",
+ "Ġpart ly",
+ "anç ais",
+ "Ġv ow",
+ "Ġprom inent",
+ "Ġcry st",
+ "ib a",
+ "Ġdes erves",
+ "Ġover t",
+ "Ġsens it",
+ "ĠWh e",
+ "Ġtight en",
+ "Ġintim id",
+ "Ġal iment",
+ "w ill",
+ "Ġstrength en",
+ "ĠT an",
+ "åı Ī",
+ "ãģĹ ãģ¾ãģĻ",
+ "on i",
+ "ĠM un",
+ "Ġpro ph",
+ "Ġrehe ars",
+ "ĠK le",
+ "Ġve ces",
+ "Ġwonder ed",
+ "ok i",
+ "Ġsens es",
+ "´ì ĭ",
+ "Æ°á» Ľ",
+ "ĠÈĻ i",
+ "Ġmuch os",
+ "Ġwatch es",
+ "ortun ate",
+ "ĠJ uan",
+ "ìŀĸ ìķĦ",
+ "ÑĢ е",
+ "e i",
+ "ion en",
+ "Ġexperiment al",
+ "Ġda ughters",
+ "ภĽ",
+ "Ġment ally",
+ "bec ca",
+ "aw are",
+ "ìĦ Ŀ",
+ "Ġwhat soever",
+ "Ġen ables",
+ "ĠL ow",
+ "o id",
+ "ภĬ",
+ "ó d",
+ "Ø º",
+ "Ġconstruct ed",
+ "ĠLad ies",
+ "Ġaccus ed",
+ "Ġа н",
+ "D an",
+ "Ġsp awn",
+ "Ġcontain ers",
+ "Ġart istic",
+ "ı p",
+ "Ġdisc l",
+ "Ġaut res",
+ "in as",
+ "ĠN ation",
+ "Ġn ag",
+ "be an",
+ "w he",
+ "ľë ıĦ",
+ "ĠSe oul",
+ "Ġíı ¬",
+ "ĠN ich",
+ "Ġcomp lement",
+ "Ġinter ven",
+ "ĠMod el",
+ "ĠOr ange",
+ "nam on",
+ "Ġcalcul ation",
+ "se e",
+ "Ġusted es",
+ "Ġle b",
+ "Ġdo ct",
+ "Ñĸ н",
+ "Ġf oster",
+ "Ġel astic",
+ "ĠAh h",
+ "Ġa ce",
+ "ĠP ink",
+ "ĠJ eg",
+ "Ġde er",
+ "ãģĹ ãģĦ",
+ "s is",
+ "Ġjak o",
+ "ĠEm ma",
+ "ÑģÑĤв енно",
+ "Ġport rait",
+ "Ġmak er",
+ "Ġa ument",
+ "ÑĢ об",
+ "Ġairpl ane",
+ "Ġtransparen cy",
+ "Ġadjust ment",
+ "ĠCD C",
+ "ç on",
+ "Ġupload ed",
+ "Ġд ейÑģÑĤв",
+ "Ġго ÑĤов",
+ "Ġit er",
+ "Ġcur se",
+ "ô n",
+ "mer ce",
+ "ar an",
+ "Ġle ak",
+ "çµ IJ",
+ "Ġabs ence",
+ "Ñģ кий",
+ "Ġread ers",
+ "al er",
+ "Ġbene ath",
+ "ang o",
+ "h etic",
+ "Ġfin ns",
+ "Ġpo op",
+ "Ġdu plic",
+ "H i",
+ "ig s",
+ "olog ically",
+ "op p",
+ "Ġd izer",
+ "ĠAll en",
+ "Ġgl i",
+ "Ġacc eleration",
+ "Ġvit amin",
+ "ãĥ Ń",
+ "v ä",
+ "ĠAc cess",
+ "à® Ļ",
+ "r ás",
+ "Ġappreci ated",
+ "Ġn ah",
+ "Ġpos ter",
+ "Ġt ale",
+ "Ġhighlight ed",
+ "æĸ ĩ",
+ "ż eli",
+ "Ġblock chain",
+ "Ġmic row",
+ "Ġcin ema",
+ "ĠCh ang",
+ "ĠSe arch",
+ "ust ers",
+ "ĠZ ero",
+ "ĠDiv ision",
+ "ÑĢ аÑģ",
+ "Ġsca re",
+ "Ġj elly",
+ "ĠAdminist ration",
+ "S O",
+ "Ġl ined",
+ "Ġê° Ħ",
+ "Ġge ben",
+ "Ġso da",
+ "Ġwin ners",
+ "³ ¼",
+ "Ù Ĵ",
+ "ĠAm b",
+ "åķı é¡Į",
+ "å Ķ",
+ "Ġpe g",
+ "å· ±",
+ "4 3",
+ "Ġra us",
+ "Ġre wards",
+ "Ġinc lus",
+ "Ġhigh way",
+ "Ġha h",
+ "Ġmultipl ied",
+ "Ġs ẽ",
+ "Ġdisci ples",
+ "Ġn ing",
+ "Ġdress ing",
+ "Ġattrib utes",
+ "ĠM osc",
+ "ĠGree ce",
+ "Ġse k",
+ "ĠLe arn",
+ "Ġj us",
+ "rend re",
+ "Ġperson ne",
+ "pl ete",
+ "Ġpl acing",
+ "Ġl uego",
+ "ill ance",
+ "Ġоб Ñī",
+ "Ġprov ision",
+ "Ġl ion",
+ "t ra",
+ "bo ards",
+ "Ġbehavi our",
+ "he y",
+ "Ġsubscri ption",
+ "Ġprot agon",
+ "ãĥ £",
+ "Ġvar a",
+ "ĠÅŁ u",
+ "Ġha ha",
+ "Ġteas poon",
+ "æ Ł",
+ "av oir",
+ "Ġcrypt o",
+ "ĠÑģÑĤ аÑĢ",
+ "ĠSt ore",
+ "ab s",
+ "ĠStud ents",
+ "Ġla und",
+ "int o",
+ "Ġapproach ed",
+ "° ľ",
+ "ÑĥÑİ Ñī",
+ "ĠL abor",
+ "ot es",
+ "iat ric",
+ "Ġgro ÃŁ",
+ "ut ive",
+ "Ġи д",
+ "ĠG ib",
+ "Ġpl acement",
+ "ĠdifÃŃ cil",
+ "Ġf rog",
+ "ĠвÑģе Ñħ",
+ "ĠJ r",
+ "az ed",
+ "Ñĥ Ñī",
+ "Ġê ¼",
+ "fr ame",
+ "а еÑĪÑĮ",
+ "Ġlock down",
+ "åij ³",
+ "Ġmed i",
+ "Ġ×Ķ× ŀ×",
+ "ени й",
+ "em ale",
+ "ì¢ ħ",
+ "ater al",
+ "Ġdist ant",
+ "Ġbe ars",
+ "Ġjournal ist",
+ "è§ £",
+ "ĠMarsh all",
+ "ĠIh nen",
+ "uet ooth",
+ "b ag",
+ "ĠÄij ã",
+ "ĠHigh ness",
+ "Ġì° į",
+ "и ка",
+ "ĠW u",
+ "ĠFr an",
+ "Ġp eng",
+ "Ġf on",
+ "Ġhypothes is",
+ "ĠÑĢ Ñĥ",
+ "Ġl y",
+ "× ļ",
+ "ìĽ Ķ",
+ "ĠRad io",
+ "ภŀ",
+ "D av",
+ "Ġembarrass ing",
+ "ĠìŀĪ ìĸ´",
+ "Ġcast ing",
+ "Ġc age",
+ "ĠP sych",
+ "ĠìĿ¼ ëĭ¨",
+ "ĠÅ ¾",
+ "im b",
+ "Ġdirect ors",
+ "S H",
+ "ĠÏĦη ν",
+ "á»ģ u",
+ "Ġkon uÅŁ",
+ "Ġoption al",
+ "quar ters",
+ "ik er",
+ "ĠS ant",
+ "Ġvers es",
+ "ë ¶Ģ",
+ "Ġo lar",
+ "ĠÏ ĩ",
+ "ãĥ ķ",
+ "Ġγ ια",
+ "ĠI mm",
+ "Ġcontrovers ial",
+ "Ġer sten",
+ "Ġreci p",
+ "ĠChristian ity",
+ "Ġê´ ľ",
+ "ord on",
+ "×ķ× ©",
+ "Ġsl ash",
+ "ĠP f",
+ "Ñĥд ÑĮ",
+ "×ķ× Ŀ",
+ "ĠPer ry",
+ "Ġm amy",
+ "Ġbackground s",
+ "Ġà®İ ன",
+ "Ġpend ant",
+ "ĠColumb ia",
+ "Ġin verse",
+ "ĠÑĩеÑĢ ез",
+ "Ġs v",
+ "Ġdig ging",
+ "4 1",
+ "ch em",
+ "Ġnavig ation",
+ "ĠSh in",
+ "ĠFr ont",
+ "P D",
+ "Ġbe aring",
+ "ĠW asser",
+ "Ġw ax",
+ "ĠCH RIS",
+ "ch ing",
+ "Ġpress ed",
+ "E l",
+ "ĠD al",
+ "ons in",
+ "Ġb inding",
+ "Ñģк ой",
+ "po ons",
+ "Ġmo ck",
+ "are st",
+ "к ÑĢа",
+ "M M",
+ "Ġcor rupt",
+ "st orm",
+ "Ġref res",
+ "ĠCo ach",
+ "ll ä",
+ "ĠTH IS",
+ "Ġpar ag",
+ "Ġìĵ °",
+ "p ool",
+ "Ġbill ions",
+ "Ġê¹ Ģ",
+ "gr oup",
+ "Ġwel coming",
+ "cell ence",
+ "ĠDu ke",
+ "ê¸ ´",
+ "Ġprim era",
+ "ìł ¸",
+ "Ġp ond",
+ "Ġstat ue",
+ "Ġêµ ¬ë",
+ "Ġh atch",
+ "Ġinstrument al",
+ "Ġresident ial",
+ "ì» ¤",
+ "Ġaccept ing",
+ "osh i",
+ "d ate",
+ "ĠìĶ ¨",
+ "Ġplant ed",
+ "Ġj oking",
+ "Ġì Ħľ",
+ "Ġh ated",
+ "ĠÑĢаÑģ Ñģк",
+ "Ġsle pt",
+ "Ġpack ages",
+ "Ġisland s",
+ "es en",
+ "ģ ı",
+ "Ġdi agon",
+ "ĠO sc",
+ "Ġmes h",
+ "Ġsc ales",
+ "ar ity",
+ "ĠDef ense",
+ "ãģ¡ ãĤĩ",
+ "ĠLew is",
+ "ĠÑģ егоднÑı",
+ "Ġfl ies",
+ "uin ely",
+ "ĠCons ider",
+ "Ġst ark",
+ "he w",
+ "ĠAs ÃŃ",
+ "³ ´ë",
+ "Ġprop ose",
+ "Ġíķĺë ©´",
+ "od o",
+ "ĠNorm ally",
+ "Ġhe eft",
+ "ĠHarr is",
+ "g ro",
+ "ĠBlo od",
+ "b ase",
+ "Ġi OS",
+ "Ġtouch es",
+ "Ġinsp ir",
+ "Ġ× ĵ",
+ "Ġb inary",
+ "Ġì¶ Ķ",
+ "Ġser ial",
+ "Ġ ion",
+ "Ġunemploy ment",
+ "Ġodd s",
+ "ĠF ab",
+ "ĠF BI",
+ "BR UN",
+ "Ġweight s",
+ "ν ο",
+ "at ile",
+ "Ġnurs es",
+ "Ġinvolve ment",
+ "ĠíĶ ¼",
+ "Ġgovern ance",
+ "Ġâ Ĥ¬",
+ "ÑĢÑĥ п",
+ "ier ra",
+ "íĺ ķ",
+ "ĠJ erry",
+ "Ġbe ard",
+ "Ġsal vation",
+ "ĠAl ong",
+ "g entle",
+ "ĠK i",
+ "b ol",
+ "ĠPl at",
+ "Ġhas ht",
+ "è¿ ij",
+ "Ġw are",
+ "Ġpart ie",
+ "y cz",
+ "Ġint r",
+ "F ih",
+ "n ent",
+ "Ġche at",
+ "il en",
+ "Ġë ¯",
+ "or ie",
+ "Ġfá cil",
+ "et ric",
+ "Ġaffect ing",
+ "unci ation",
+ "Ġaff airs",
+ "Ġbe e",
+ "Ġview ing",
+ "Ġor ang",
+ "ĠL an",
+ "ĠС ÑĤ",
+ "ä¸ ĸ",
+ "ĠM es",
+ "ĥ ģ",
+ "er ie",
+ "Ġes pa",
+ "Ġinter pre",
+ "Ġposs ess",
+ "Ġpure ly",
+ "rit o",
+ "f ound",
+ "as ma",
+ "ìłģ ìĿ¸",
+ "Ġexam ine",
+ "ĠÑĥ м",
+ "Ġbes ch",
+ "ĠTom orrow",
+ "ĠB lock",
+ "Ġvari ant",
+ "Ġprefer ence",
+ "Ġcoach es",
+ "Ġmedic ations",
+ "Ġíĺ Ħ",
+ "Ġemp ire",
+ "ë Ħ¤",
+ "ĠIll inois",
+ "Ġcris py",
+ "Ġth ì",
+ "Ġbe es",
+ "7 7",
+ "Ġgl ow",
+ "è º",
+ "ĠStud ies",
+ "åIJ Ħ",
+ "ĠChall enge",
+ "Ġunlike ly",
+ "Ð §",
+ "ıy orsun",
+ "DI E",
+ "Ġminim ize",
+ "iz ard",
+ "Ġú n",
+ "Ġencont rar",
+ "ĠK ill",
+ "å »",
+ "Ġvan illa",
+ "ĠGr ant",
+ "ĠG T",
+ "se a",
+ "Ġs ought",
+ "в од",
+ "Ġnä m",
+ "ĠA unt",
+ "OW N",
+ "Ġpump kin",
+ "st ellen",
+ "Ġr ag",
+ "ег да",
+ "Ġstory t",
+ "Ġfor um",
+ "æ© Ł",
+ "Ġestab a",
+ "uch e",
+ "Ġcon gress",
+ "ĠRe y",
+ "Ġdram atically",
+ "ĠSp ort",
+ "ĠYe llow",
+ "Ġê³Ħ ìĨį",
+ "Ġdisg usting",
+ "ĠRe cent",
+ "Ġacqu ired",
+ "Ġc ables",
+ "çĶ ļ",
+ "d in",
+ "Ġv isto",
+ "Ġcommunic ating",
+ "ÑģÑĤав лÑı",
+ "еÑģ ÑĤо",
+ "ãĥ»ãĥ» ãĥ»",
+ "Ġré g",
+ "Ġso cks",
+ "Ġpro ces",
+ "be cause",
+ "Ġut ter",
+ "Ġcoloc ar",
+ "Ġnew est",
+ "Ġgr amm",
+ "è¡ ¨",
+ "ä¸į çŁ¥éģĵ",
+ "Ġsh ifting",
+ "Ġcar rier",
+ "ĠÑģк оÑĢ",
+ "ĠSch w",
+ "Ġexec uted",
+ "Ġmaint ained",
+ "ĠÏ Ĩ",
+ "ĠM oses",
+ "Ġdis se",
+ "Ġhor r",
+ "ãĢ ľ",
+ "Ġr ally",
+ "Ġall em",
+ "ĠEvent ually",
+ "Ġdi yor",
+ "lv ania",
+ "Ġsch nell",
+ "Ġê³ ¼",
+ "Ġë§ ¤",
+ "Ġstrugg les",
+ "l ate",
+ "Ġclar ify",
+ "é ment",
+ "Ġmulti plic",
+ "иб о",
+ "Ġjour n",
+ "Ġfra gr",
+ "Ġsurprising ly",
+ "Ġdesper ate",
+ "5 2",
+ "Ġs ul",
+ "ĠRe ad",
+ "ĠF ried",
+ "Ġm ond",
+ "w oo",
+ "Ġorgan izing",
+ "ãģĹãĤĩ ãģĨ",
+ "ĠSo on",
+ "Ġв опÑĢоÑģ",
+ "ĠN ur",
+ "ĠÐĹ Ð´",
+ "Ġsp ider",
+ "е ÑģÑı",
+ "Ġtutorial s",
+ "Ġnutri ents",
+ "or er",
+ "Ġcoe fficient",
+ "Ġarrange ment",
+ "Ġpr icing",
+ "n an",
+ "y u",
+ "B L",
+ "Ġtri be",
+ "ĠHow ard",
+ "un ks",
+ "Ġnew er",
+ "Ġprov in",
+ "Ġpred iction",
+ "h os",
+ "Ġol sun",
+ "ĠAr ound",
+ "Ġv ier",
+ "ĠÑģÑĤоÑĢ он",
+ "Ġv alley",
+ "ĠE la",
+ "if i",
+ "Ġgal axy",
+ "Ġtran qu",
+ "Ġad vers",
+ "ĠTem ple",
+ "iff s",
+ "ig ence",
+ "èĩª å·±",
+ "Ġkön nte",
+ "ĠÄij ó",
+ "D id",
+ "Ġphotograph s",
+ "ĠA WS",
+ "ÑĨи Ñı",
+ "Ġgu ards",
+ "Ġappoint ed",
+ "ĠG il",
+ "Ġм ом",
+ "Ġc od",
+ "ĠUn like",
+ "Ġeven ly",
+ "isc onsin",
+ "Ġest ou",
+ "Ġm nie",
+ "ĠEx ec",
+ "ĠM V",
+ "ĠE ine",
+ "ä¿ ¡",
+ "ĠRog er",
+ "ĠF ac",
+ "ĠL ist",
+ "Ġf uer",
+ "аеÑĤ е",
+ "om ed",
+ "Ġattract ion",
+ "èī ²",
+ "Ġter rain",
+ "ĠD rop",
+ "Ġcorpor ations",
+ "Ġsci ences",
+ "Ġthr one",
+ "ãģĦ ãģŁ",
+ "Ġa j",
+ "ĠR ot",
+ "çī ¹",
+ "Ġsupp orters",
+ "ĠB ere",
+ "H ere",
+ "Ġdifer entes",
+ "Ġsignific ance",
+ "Ïĥ η",
+ "æĪij 覺å¾Ĺ",
+ "Ġcl amp",
+ "Ġë ĮĢë",
+ "Ġfab ulous",
+ "re z",
+ "æĮ ģ",
+ "Ġassum ptions",
+ "ut her",
+ "w id",
+ "p ot",
+ "è¿ İ",
+ "Ġy an",
+ "ul in",
+ "ÑĢ Ñĭв",
+ "ĠSl ow",
+ "ĠPenn sy",
+ "Ġíķ ´ìĦľ",
+ "Ġme io",
+ "Ġwealth y",
+ "ĠE ight",
+ "Ġpul se",
+ "Ġfr iction",
+ "id ity",
+ "ĠH oll",
+ "i yorum",
+ "Ġsound ed",
+ "ĠC arr",
+ "Ġfor k",
+ "â ĺ",
+ "ĠP A",
+ "Ġcons pir",
+ "Ġc oding",
+ "r t",
+ "ĠTy p",
+ "Ġìĸ ij",
+ "Ġп ог",
+ "Ġmis er",
+ "ĠÑģм оÑĤÑĢ",
+ "ĠSw eden",
+ "Ġolar ak",
+ "ĠZh ang",
+ "ĠCh i",
+ "ĠT itan",
+ "Ġscreen ing",
+ "ĠSp ider",
+ "ĠÅŀ imdi",
+ "Ġobst acles",
+ "lar a",
+ "Ġchalleng ed",
+ "p se",
+ "T ON",
+ "á» ¥",
+ "ĠP i",
+ "Ġlag i",
+ "ie urs",
+ "Ġhur ting",
+ "Ġneg lect",
+ "Ġgener ating",
+ "Ġyoung est",
+ "Ġaud it",
+ "ĠÑĢ ез",
+ "Ïģ ά",
+ "Ġdon ate",
+ "ĠPD F",
+ "Ġvis its",
+ "Ġcru ise",
+ "P P",
+ "as er",
+ "Ġw sp",
+ "back s",
+ "iv als",
+ "ãģĨ ãĤĵ",
+ "Ġde ve",
+ "Ġprop ort",
+ "Ġc ath",
+ "ĠE ffect",
+ "Ġwind s",
+ "ĠìĻ Ķ",
+ "Ġchart s",
+ "Ġs ama",
+ "Ġautom ation",
+ "Ġпок а",
+ "Ġol an",
+ "Ġbo ats",
+ "Ġca fe",
+ "Ġden ied",
+ "ĠM ama",
+ "Ġblock ing",
+ "ĠTh or",
+ "Ġphenomen al",
+ "Ġstake holders",
+ "Ġun os",
+ "Ñĥ еÑĤ",
+ "ĠAb raham",
+ "ãģ§ ãĤĤ",
+ "Ġdetect ion",
+ "Ġjur is",
+ "Ġpower ed",
+ "z ial",
+ "Ġwel fare",
+ "Ġup grad",
+ "Ġmoż na",
+ "ĠC ase",
+ "c ular",
+ "Ķ ìĿ´",
+ "ãĥ ģ",
+ "ĠGu ess",
+ "Ġcy cles",
+ "ä¾ ĭ",
+ "çµ ¦",
+ "ro ck",
+ "um i",
+ "Ġel ite",
+ "Ġqu è",
+ "åł ±",
+ "ÑĤ ом",
+ "Ġsh ore",
+ "gun ta",
+ "Ġk u",
+ "Ġfaith ful",
+ "ĠJ eremy",
+ "a id",
+ "à ·",
+ "ug al",
+ "å°į åķĬ",
+ "ĠV el",
+ "Ġvra i",
+ "st ell",
+ "¨ ¸",
+ "Ġk ol",
+ "è ½",
+ "Ġquant o",
+ "Ġз аÑĢ",
+ "Ġ200 2",
+ "es y",
+ "Ġres erve",
+ "Ġмом енÑĤ",
+ "Ġdeploy ed",
+ "Ġdefin ing",
+ "Ġsa u",
+ "Ġga at",
+ "\" )",
+ "Ġtrans mit",
+ "Ġpubl ishing",
+ "Ġrank ing",
+ "Ġoff ense",
+ "Ġ4 6",
+ "p in",
+ "ĠT aking",
+ "Ġentit led",
+ "Ġgen uinely",
+ "Ġvari ations",
+ "Ġfind e",
+ "Ġt au",
+ "Ġunf ortunate",
+ "ĠR ah",
+ "port s",
+ "Ġc Å",
+ "Ġmon key",
+ "Ġbr ac",
+ "we i",
+ "l ung",
+ "Ġart if",
+ "Ġsy rup",
+ "ĠÐĶ ав",
+ "Ġlift ed",
+ "Ġche z",
+ "ĠAd vent",
+ "ĠSt ock",
+ "Ġdo l",
+ "м ен",
+ "иÑĪ ÑĮ",
+ "Ġy n",
+ "g io",
+ "d et",
+ "Ġdes se",
+ "Ġg ri",
+ "ĠChair man",
+ "ç ħ",
+ "Ġcu enta",
+ "an im",
+ "Ġcra b",
+ "Ġesc al",
+ "Ġpremi ère",
+ "ĠGe f",
+ "Ġd ining",
+ "Ġsevent h",
+ "Ġch asing",
+ "ĠT ower",
+ "Ġbrut al",
+ "Ġfundament ally",
+ "ãģ¨ ãģĨ",
+ "л ениÑı",
+ "st age",
+ "Ġacqu is",
+ "Ġcyl inder",
+ "Ġcomm ander",
+ "m em",
+ "ĠU V",
+ "ha ppy",
+ "Ġe psilon",
+ "Ġinv itation",
+ "Ġfar mer",
+ "ch air",
+ "Ġdest iny",
+ "Ġso vere",
+ "ĠHeb rew",
+ "Ġserv ant",
+ "Ġbe w",
+ "Ġg ast",
+ "ut ies",
+ "Ġadministr ative",
+ "ĠComm and",
+ "é ta",
+ "Ġnit rogen",
+ "ê· ¼",
+ "Ġab i",
+ "Ġvill ain",
+ "Ġblank et",
+ "ĠS end",
+ "Ġbeat en",
+ "² Ħ",
+ "Ġvol unt",
+ "Ġschol ar",
+ "ĠEm peror",
+ "Ġ4 3",
+ "v able",
+ "ĠD us",
+ "ĠG U",
+ "Ġtarget ing",
+ "ww w",
+ "Ġamend ment",
+ "ìĨ Įë",
+ "Ġt ing",
+ "Ġn asty",
+ "Ġg auge",
+ "ĠÑĢ од",
+ "ĠH ans",
+ "Y our",
+ "α ν",
+ "Ġpro jet",
+ "ĠHawai i",
+ "Ġsusp icious",
+ "Ġsch w",
+ "Ġremo val",
+ "Ġint rig",
+ "ĠM U",
+ "Ġp onto",
+ "ठ¾",
+ "Ġоб ÑĢаз",
+ "Ġguess ing",
+ "p ace",
+ "Ġm others",
+ "Ġmill imeter",
+ "л ение",
+ "没 æľī",
+ "Ġavail ability",
+ "ic z",
+ "æŃ ¤",
+ "Ġfr act",
+ "Ġbas es",
+ "k m",
+ "ĠB TS",
+ "ĠF ield",
+ "Ġd zie",
+ "Ġseg undo",
+ "ĠëĤĺ ëĬĶ",
+ "Ġlegit imate",
+ "im as",
+ "Ġв н",
+ "Ġcor ruption",
+ "Ġsm ash",
+ "ĠVal ent",
+ "Ġalign ed",
+ "ĠPennsy lvania",
+ "Ġg ab",
+ "ĠE un",
+ "ent h",
+ "ĠMor ning",
+ "Ġcand le",
+ "Ġback pack",
+ "ĠIslam ic",
+ "a ções",
+ "Ġenc ry",
+ "Ġmushroom s",
+ "íĮ Į",
+ "d it",
+ "Ġtrans it",
+ "ĠW isconsin",
+ "Ġparticip ated",
+ "ĠIl s",
+ "Ġunf old",
+ "¶ Ģë",
+ "Ġprof its",
+ "Ġwar ming",
+ "ĠG ang",
+ "Ġnetwork ing",
+ "Ġme ga",
+ "Ġthorough ly",
+ "le ments",
+ "ĠH m",
+ "Ġdec iding",
+ "Ġemotion ally",
+ "Ġexha usted",
+ "ĠÐŁ оÑĤ",
+ "c ido",
+ "ĠHT ML",
+ "Ġcopy right",
+ "Ġmel ody",
+ "y im",
+ "Ġand ers",
+ "osh op",
+ "Ġë³ ¼",
+ "Ġathlet e",
+ "ĠG E",
+ "Ġfrequ ent",
+ "Ġdes ires",
+ "Ġneed ing",
+ "ĠY un",
+ "Ġrif le",
+ "Ġlo ver",
+ "' T",
+ "Ġd ense",
+ "Ġt ão",
+ "Ġnot ified",
+ "Ġid i",
+ "ìĹ Ń",
+ "í Ĩ",
+ "Ġinteract ing",
+ "Ġrapp ort",
+ "еÑĢ и",
+ "s ki",
+ "Ġb esser",
+ "Ġmanufact urer",
+ "ĠK yle",
+ "Ġaccount able",
+ "ĠS ak",
+ "ĠP il",
+ "ĠD omin",
+ "Ġpres um",
+ "ĠÐĴÑģ е",
+ "Ġvine gar",
+ "Ġguarante ed",
+ "çľĭ åĪ°",
+ "Ġhand led",
+ "éŁ ³",
+ "c at",
+ "Ġcivil ization",
+ "Ġaccom p",
+ "ĠV M",
+ "é mon",
+ "Ġde ze",
+ "Ġgrad es",
+ "Ġsoll te",
+ "Ġst aring",
+ "×IJ× ª",
+ "ar nt",
+ "Ġhoriz on",
+ "Ġtrav ail",
+ "h our",
+ "第 ä¸Ģ",
+ "ĠE D",
+ "ĠD ak",
+ "Ġn y",
+ "Ġcon ve",
+ "ĠCh am",
+ "Ġfir ms",
+ "ĠL iu",
+ "ĠÑģÑĤ ÑĢан",
+ "Ġli bert",
+ "Ġlens es",
+ "Ġint ake",
+ "ĠвÑĭ б",
+ "Ġmens en",
+ "h el",
+ "Ġpract ition",
+ "Ġ3 50",
+ "ãĤ ³",
+ "F O",
+ "Ġbed s",
+ "Ġancest ors",
+ "ĠìĹĦ ì²Ń",
+ "Ġdistur b",
+ "ĠLast ly",
+ "ĠSupp ort",
+ "ี à¹ī",
+ "ĠCor ona",
+ "Ġenthus i",
+ "Ġвоз м",
+ "ĠìĤ¬ëŀ Įë",
+ "Ġ5 2",
+ "b ird",
+ "Ġredu ces",
+ "ĠìŀĪ ìĿĦ",
+ "ĠG ene",
+ "êµ IJ",
+ "ÄĻ p",
+ "ĠÃľ ber",
+ "Ġconcer ning",
+ "us er",
+ "Ġconcent rate",
+ "ĠWH AT",
+ "ish op",
+ "onym ous",
+ "no ld",
+ "Ġsuggest ing",
+ "© °",
+ "ĠF ish",
+ ".... ....",
+ "Ġvess el",
+ "Ġtrabaj o",
+ "ãģ µ",
+ "ĠO cean",
+ "å§ IJ",
+ "y g",
+ "Ġtown s",
+ "d el",
+ "Ġterr ifying",
+ "Ġçal Ä±ÅŁ",
+ "Ġs ino",
+ "Ġe ats",
+ "Ġge z",
+ "Ġg eme",
+ "ĠìĻ Ħ",
+ "Ġcomp art",
+ "Ġimplement ing",
+ "ĠPot ter",
+ "ĠGerm ans",
+ "Ġg ÅĤ",
+ "Ġt ennis",
+ "Ġcar pet",
+ "au er",
+ "ĠSaud i",
+ "ye ong",
+ "Ġcur ry",
+ "ĠFore st",
+ "Ñĭ л",
+ "Ġfif teen",
+ "Ġbol ts",
+ "Ġ{ \\",
+ "¬ ´",
+ "Ġsett lement",
+ "Ġl ange",
+ "Ġb am",
+ "G et",
+ "íķ Ļ",
+ "Ġsw ap",
+ "ĠK han",
+ "Ġcomm ence",
+ "Ġquar antine",
+ "Ġsc ored",
+ "ç ĸ",
+ "Ġ19 50",
+ "Ġthick er",
+ "Ġsû r",
+ "åı £",
+ "ĠLar ry",
+ "Ġall ez",
+ "ìĭľ ëĬĶ",
+ "Ġg ü",
+ "Ġspect acular",
+ "/ /",
+ "b oth",
+ "Ġst ats",
+ "å¦ ³",
+ "ĠN ancy",
+ "Ġbun u",
+ "Ġcr ust",
+ "Ġactiv ated",
+ "Ġê·¸ë ŀ",
+ "out he",
+ "Ġport s",
+ "Ġne ural",
+ "Ġj aw",
+ "Ġobserv ations",
+ "Ġvo it",
+ "ab an",
+ "ả i",
+ "¦¬ë ¥¼",
+ "om es",
+ "௠ĭ",
+ "qu i",
+ "Ġkind ness",
+ "Ð ij",
+ "Ġ4 1",
+ "Ġmoder ate",
+ "Ġang els",
+ "ĠT amb",
+ "è t",
+ "Ġch lor",
+ "ĠBill y",
+ "ì² ĺë",
+ "ac on",
+ "Ġselect ing",
+ "ĠDel ta",
+ "Ġn ull",
+ "den ly",
+ "Ġci ud",
+ "Ġtend ency",
+ "Ġbreak down",
+ "Ġm int",
+ "ÑĦ оÑĢм",
+ "or ph",
+ "Ġda wn",
+ "s pr",
+ "ĠW ILL",
+ "äch lich",
+ "Ġpu ppy",
+ "7 00",
+ "Ġà® ¤",
+ "Ġfail s",
+ "ĠCon c",
+ "Ġrel atives",
+ "Ġinv iting",
+ "Ġaut onom",
+ "Ġcomp osed",
+ "Ġun ity",
+ "Ġdec is",
+ "Ġaccess ories",
+ "ĠC ass",
+ "Ġb ist",
+ "ĠT ip",
+ "ì§ ¸",
+ "Ġp unt",
+ "Ġr áp",
+ "éĢ ²",
+ "AN K",
+ "ãģ ļ",
+ "ex ist",
+ "Ġcompat ible",
+ "Ġn er",
+ "Ġе мÑĥ",
+ "Ġa plic",
+ "Ġb apt",
+ "Ġfail ing",
+ "ĠTam am",
+ "Ġos cill",
+ "Ġletz ten",
+ "Ġrepeated ly",
+ "Ġjung le",
+ "ĠP ush",
+ "h ai",
+ "ĠÎ ·",
+ "Ġdead ly",
+ "Ñı ж",
+ "wi Äħ",
+ "ĠComm on",
+ "ĠÎ ķ",
+ "Ġsk ate",
+ "T C",
+ "ĠMin i",
+ "Ġhob by",
+ "ầ n",
+ "Ġrout es",
+ "Ġam igos",
+ "Ġcon jun",
+ "Ġpartners hips",
+ "Ġno vo",
+ "Ġa ver",
+ "Ġpou vez",
+ "br idge",
+ "Ġpre oc",
+ "h im",
+ "Ġtur b",
+ "Ġso b",
+ "ĠSn ap",
+ "Ġì° ¸",
+ "min ute",
+ "Ġtra ject",
+ "uj ÄĻ",
+ "Ġe ager",
+ "Ġregul atory",
+ "Ġbank ing",
+ "b ling",
+ "ÑĪ ÑĮ",
+ "a ż",
+ "Ġbiz arre",
+ "it ated",
+ "d ire",
+ "Ġthreat ened",
+ "Ġsh ining",
+ "Ġn esse",
+ "Ġcor ps",
+ "ĠÑģ Ñĥ",
+ "Ġt eles",
+ "Ġtem p",
+ "t em",
+ "Ġк ан",
+ "Ġfe ver",
+ "N ew",
+ "Ġheav ier",
+ "ĠS ah",
+ "b ud",
+ "Ġout ros",
+ "Ġì° ¾",
+ "Ġëª ħ",
+ "arr ing",
+ "Ġê´ľ ì°®",
+ "ĠN ap",
+ "Ġse min",
+ "ĠTh an",
+ "if s",
+ "Ġdes en",
+ "ĠÑĤак ое",
+ "Ġlos es",
+ "ĠB alt",
+ "k on",
+ "Ġнап ÑĢ",
+ "Ġvo is",
+ "ĠMosc ow",
+ "Ġch airs",
+ "h is",
+ "Ġrefuge es",
+ "k g",
+ "Ġk ole",
+ "į ¨",
+ "аÑģ ибо",
+ "¦ ½",
+ "ĠUn iverse",
+ "ĠDire ct",
+ "Ġche ating",
+ "ĠC in",
+ "Ġpat ri",
+ "Ġadv ise",
+ "ĠN ether",
+ "Ġprime iro",
+ "Ġmention ing",
+ "n ut",
+ "5 6",
+ "ar ı",
+ "Ġpet ite",
+ "b led",
+ "Ġpens ar",
+ "ic io",
+ "IN D",
+ "Ġveter an",
+ "Ġlad der",
+ "Ġconsequ ence",
+ "ож ал",
+ "ĠB urn",
+ "Ġr ug",
+ "ĠM ade",
+ "Ġg it",
+ "\" ...",
+ "Ġcompet itors",
+ "Ġprz ed",
+ "Ġapp arent",
+ "ĠArgent ina",
+ "ĠWork ing",
+ "Ġcollabor ate",
+ "w oman",
+ "Ġret ain",
+ "Ġle urs",
+ "Ġdash board",
+ "×Ļ× ĵ",
+ "ĠEar ly",
+ "B M",
+ "Ġе Ñij",
+ "ол ог",
+ "Ġsatisf ying",
+ "Ġoft entimes",
+ "Ġma pping",
+ "ünk ü",
+ "ar th",
+ "f old",
+ "Ġlaunch ing",
+ "Ġa ura",
+ "Ġprec ision",
+ "work s",
+ "G od",
+ "Ġstra p",
+ "ĠIm per",
+ "Ġr ivers",
+ "Ġ |",
+ "Ġcu er",
+ "reg on",
+ "Ġarri val",
+ "ка Ñħ",
+ "ĠM iami",
+ "ан Ñĭ",
+ "Ġsurviv ors",
+ "ĠSen ior",
+ "Dav id",
+ "Ġest ado",
+ "Ġse ctors",
+ "Ġpop ping",
+ "Ġch im",
+ "ay ı",
+ "Ġkun nen",
+ "Ġgall ery",
+ "Ġsun light",
+ "ese hen",
+ "Ġye lling",
+ "ĠMe in",
+ "ĠPho enix",
+ "Ġman o",
+ "Ġhistor ia",
+ "Ġoccur ring",
+ "æ¬ ¸",
+ "ì ¸",
+ "ад и",
+ "å¾ ħ",
+ "Ġinstitution al",
+ "ĠT ut",
+ "ç ²",
+ "Ġsl aves",
+ "ãģ© ãģĨ",
+ "Ġforg iveness",
+ "Ġtw in",
+ "ĠHy un",
+ "н ÑĮ",
+ "ĠK omm",
+ "and ra",
+ "sh ot",
+ "ss ä",
+ "ĠÑĨ е",
+ "at ta",
+ "Ġexp ense",
+ "ĠG PU",
+ "ĠP ast",
+ "rib ly",
+ "ĠëŃIJ ìķ¼",
+ "Ġгод а",
+ "Ġresp ir",
+ "æĿ ±",
+ "ĠQue ens",
+ "h ops",
+ "Ġs érie",
+ "Ġpre f",
+ "Ġcom ed",
+ "Ġpl ut",
+ "ĠOver all",
+ "Ġãģ Ŀ",
+ "Ġc ush",
+ "Ġring ing",
+ "Ġincor rect",
+ "ĠÑģÑĤ ÑĢ",
+ "Ġgeomet ry",
+ "Ġadvert is",
+ "ĠÐ ¨",
+ "Ġreview ed",
+ "ãģĤ ãģĤ",
+ "Ġdo zens",
+ "Ġdeterm ination",
+ "ĠPh ill",
+ "Ġcontrib uted",
+ "ĠC it",
+ "Ġpass engers",
+ "Ġcôt é",
+ "Ġre ver",
+ "Ġtechn ological",
+ "Ġall en",
+ "Ġr aining",
+ "av i",
+ "Ġsal ty",
+ "Ġtyp ing",
+ "ĠÑĤ е",
+ "Ġt ilt",
+ "Ġì¹ ĺ",
+ "Ġо ÑĢ",
+ "ĠпÑĢ Ñıм",
+ "Ġr ou",
+ "Ġare na",
+ "ar at",
+ "åĪ «",
+ "HH HH",
+ "Ġmanufact urers",
+ "ĠEd ward",
+ "Ġt uck",
+ "Ġbl ows",
+ "ing o",
+ "ĠMar c",
+ "ìķĦ ìĦľ",
+ "M ich",
+ "ĠCle an",
+ "è ´",
+ "est o",
+ "ĠP ack",
+ "Ġsha ft",
+ "BRUN O",
+ "Ġa ven",
+ "u ur",
+ "Ñģк олÑĮко",
+ "ê´ Ģ",
+ "Ġautom ated",
+ "Ġvent ure",
+ "Ġsurve illance",
+ "ĠG row",
+ "ĠE mer",
+ "Ġд оÑĢ",
+ "Ġinvest or",
+ "ĠY ok",
+ "Ġl atter",
+ "ĠN I",
+ "Ġfunction ing",
+ "ĠHam ilton",
+ "Ġ5 1",
+ "Ġmurder ed",
+ "Ġanch or",
+ "Ġc uc",
+ "ĠSC P",
+ "ĠMad am",
+ "Ġconstra ints",
+ "Ġb arn",
+ "ank en",
+ "Ġë§İ ìĿĢ",
+ "ĠMot or",
+ "ĠDo ing",
+ "Ġam en",
+ "et ts",
+ "Ġinst ructor",
+ "eg t",
+ "ak o",
+ "Ġpost ure",
+ "iv ia",
+ "ĠPol ish",
+ "Ġдв а",
+ "Ġcolor ful",
+ "Ġel bow",
+ "Ġpar le",
+ "Ġpass er",
+ "Ġcond em",
+ "ort al",
+ "Ġfert il",
+ "ا د",
+ "ĠCol omb",
+ "Ġalign ment",
+ "Ġastron aut",
+ "ĠM ut",
+ "Ġsal mon",
+ "Ġstructure d",
+ "ŀ ר",
+ "Ġclick s",
+ "Ġm iej",
+ "æĶ ¿",
+ "ãģĦ ãĤĦ",
+ "ĠR ound",
+ "Ġrain bow",
+ "ĠV A",
+ "ãģĶ ãģĸ",
+ "ì§ Ī",
+ "ot z",
+ ", ",
+ "Ġch ords",
+ "ĠSand ers",
+ "Ġë¶ Ħë",
+ "B en",
+ "Ġdar über",
+ "ili ans",
+ "Ġorder ing",
+ "ĠMan h",
+ "Ġkil ogram",
+ "Ġkar ÅŁ",
+ "Ġgr asp",
+ "Ġghost s",
+ "al en",
+ "ĠJ edi",
+ "Ġб ли",
+ "Ġdownload ed",
+ "Ġconduct ing",
+ "ĠH ak",
+ "Ġresearch er",
+ "il an",
+ "go od",
+ "ĠH annah",
+ "ĠdÃ¼ÅŁ ün",
+ "ĠMess iah",
+ "u ity",
+ "ion a",
+ "Ġprob able",
+ "ĠY E",
+ "Ġindepend ently",
+ "Ġbuff er",
+ "b urn",
+ "our d",
+ "ĠMc K",
+ "Ġl ingu",
+ "uj emy",
+ "еÑĢ ÑĤ",
+ "Ġintuit ive",
+ "Ġcrack s",
+ "app ropri",
+ "nt y",
+ "Ġge en",
+ "Ġl end",
+ "Ġcert ification",
+ "ID S",
+ "un ter",
+ "pe es",
+ "Ġtr ump",
+ "Ġbank rupt",
+ "Ġfe as",
+ "è Ĺ",
+ "Ġdu ż",
+ "æ¸ ħ",
+ "Ġvirus es",
+ "Ġ5 8",
+ "g od",
+ "Ġж ел",
+ "Ġst alk",
+ "I nd",
+ "ach i",
+ "ĠC F",
+ "ĠC ond",
+ "Ġsan ct",
+ "Ġcont en",
+ "Ġfre ed",
+ "ĠR T",
+ "Ġment ors",
+ "ì¡ ±",
+ "Ġport able",
+ "ĠPaul o",
+ "r ane",
+ "HA HA",
+ "ĠS ection",
+ "ç Ĩ",
+ "hy un",
+ "ĠÎŃ Ïĩ",
+ "ĠP ub",
+ "ĠInd epend",
+ "Ġcomp ounds",
+ "ĠÑģ Ñĭ",
+ "Ġmess aging",
+ "Ġded ication",
+ "Ġnot icing",
+ "Ġdevot ed",
+ "ÑİÑĤ ÑģÑı",
+ "Ġsn akes",
+ "Ġbattle field",
+ "p ers",
+ "Ġdel a",
+ "9 2",
+ "Ġha i",
+ "ill ä",
+ "ér er",
+ "e very",
+ "Ġrespons ive",
+ "×Ļ ×ķ",
+ "op f",
+ "é ī",
+ "Ĭ ¸",
+ "Be cause",
+ "Ġtour ism",
+ "Ġê·¸ ê²Į",
+ "×ķ× ¦",
+ "Ġcan s",
+ "st üt",
+ "Ġdon ne",
+ "ĠD ios",
+ "ĠU ber",
+ "act ory",
+ "Ġorient ed",
+ "ĠH erm",
+ "Ġpat ron",
+ "ur f",
+ "be i",
+ "Ġprogram a",
+ "ĠOh h",
+ "gen er",
+ "Ġf ist",
+ "ĠW endy",
+ "Ġand a",
+ "Ġguess ed",
+ "Ġfre ak",
+ "ä¸Ń åľĭ",
+ "ĠK ings",
+ "ch ool",
+ "Ġoff line",
+ "ĠIndian a",
+ "ĠAll iance",
+ "Ġ5 3",
+ "Ġpartic ul",
+ "ĠF ocus",
+ "Ġinhab it",
+ "Ġê°ĻìĿĢ ëį°",
+ "ĠMc G",
+ "ows ki",
+ "ĠìĿ´ ê±´",
+ "Ġpa ÅĦst",
+ "он и",
+ "itt a",
+ "Ġconfirm ation",
+ "ĠBrook lyn",
+ "Ġnood le",
+ "f und",
+ "it ud",
+ "Ġgrand parents",
+ "Ġbar becue",
+ "ει ÏĤ",
+ "Ġ á",
+ "Ġball ot",
+ "ĠV eter",
+ "Ġpip es",
+ "ig ious",
+ "ĠG raph",
+ "est ed",
+ "Ġë¸ Įë",
+ "ĠK E",
+ "ãģ¡ãĤĩ ãģ£ãģ¨",
+ "Ġe ins",
+ "Ġhat red",
+ "ãģij ãģ©",
+ "Ġd ang",
+ "ee ee",
+ "Ġarch ae",
+ "ĠJes se",
+ "Ġdetect ed",
+ "Ġsen i",
+ "burg h",
+ "Ġdispl acement",
+ "Ġdo p",
+ "Ġcondition ing",
+ "Ġне ÑģколÑĮко",
+ "Ġdistur bing",
+ "P H",
+ "Ġthin ner",
+ "Ġwound ed",
+ "ĠCu ando",
+ "Ġcush ion",
+ "Ġwh ites",
+ "Ġprefer ences",
+ "Ġì¤Ģë ¹Ħ",
+ "Ġka ż",
+ "ĠG ate",
+ "ĠP ath",
+ "d les",
+ "à¸Ħ ร",
+ "im ore",
+ "Ġë³´ìĹ ¬",
+ "Ġdiscipl ines",
+ "á» ı",
+ "Ġmes ma",
+ "Ġìĥ Īë",
+ "Ġìĭ ¬",
+ "Ġg ing",
+ "Ġumbre lla",
+ "IGH T",
+ "Ġp ension",
+ "Ġcomb ining",
+ "S S",
+ "Ġrect angle",
+ "á»ĩ t",
+ "Ġpro xim",
+ "ĠC ow",
+ "¸ Į",
+ "Ġintention al",
+ "æķ Ļ",
+ "Ġdec id",
+ "ĠÑģк аж",
+ "ĠU ma",
+ "ias m",
+ "b uz",
+ "Ġdebr is",
+ "Ġc ass",
+ "ĠP rop",
+ "is ka",
+ "ë ł¥",
+ "ester ol",
+ "uss ian",
+ "ìĿ´ë ŀij",
+ "Ġun limited",
+ "Ġadm ire",
+ "Ġtight ly",
+ "Ġgen ome",
+ "ĠJun ior",
+ "ven ir",
+ "g us",
+ "Ġc Äĥ",
+ "ĠV lad",
+ "Ġí Ĥ",
+ "Ġrel ativ",
+ "in ci",
+ "Ġaun que",
+ "ĠBo ys",
+ "ÑĨи он",
+ "ĠSw iss",
+ "Ġphys icians",
+ "Ġíı ī",
+ "ĠP ET",
+ "Ġw ounds",
+ "ab out",
+ "Ãł i",
+ "on z",
+ "ur ities",
+ "ĠÑĥв ид",
+ "å· ¦",
+ "Ġment ality",
+ "Ġvari ance",
+ "Ġseg unda",
+ "Ġvol cano",
+ "al ie",
+ "ॠĩ",
+ "Ġt iles",
+ "ĠT erry",
+ "ĠاÙĦÙĦ Ùĩ",
+ "Ġcan on",
+ "Ġsc attered",
+ "pt on",
+ "Ġdefin itions",
+ "Ġal gebra",
+ "ot en",
+ "ab lo",
+ "ij uana",
+ "Ġwra pping",
+ "Ġses ame",
+ "ĠнаÑĩ ина",
+ "ĠAl f",
+ "ĠÐł оÑģÑģ",
+ "or no",
+ "Ġan kle",
+ "Ġspecial ty",
+ "Ġattempt ing",
+ "ili ation",
+ "Ġ19 20",
+ "Ġphen omena",
+ "ĠPro duct",
+ "ĠB uck",
+ "ĠA ww",
+ "se en",
+ "Ġvo id",
+ "ĠFrank lin",
+ "Ġadvoc acy",
+ "ĠS ep",
+ "Ġcool est",
+ "ĠÑģ ÑĢазÑĥ",
+ "ĠQu and",
+ "Ġ9 00",
+ "ĠTr ad",
+ "d ies",
+ "Ġhas h",
+ "æĪij å°±",
+ "ä¹Ł æĺ¯",
+ "Ġpot s",
+ "Ġsad ly",
+ "Ġvi able",
+ "ĠT iger",
+ "ĠON E",
+ "Ġneur ons",
+ "ow anie",
+ "Ä Ĺ",
+ "ĠSh ar",
+ "ĠLand es",
+ "Ġconfer ences",
+ "è© ²",
+ "Ġcred ential",
+ "Ġl ime",
+ "ine e",
+ "x it",
+ "p ay",
+ "Ġinc ons",
+ "Ġ>> :",
+ "èª į",
+ "Ġí ŀĺë",
+ "Ġless er",
+ "Ġsp ill",
+ "Ġprem ise",
+ "Ġ36 5",
+ "ĠH ost",
+ "Ġtom ar",
+ "×IJ× ľ",
+ "ë ²Ī",
+ "ĠWhat s",
+ "Ġlight weight",
+ "ĠM ap",
+ "f ia",
+ "ells chaft",
+ "Ġvend ors",
+ "uest o",
+ "ĠM ister",
+ "ĠÐŁ ÑĢи",
+ "åı ³",
+ "h ma",
+ "Ġintention ally",
+ "ĠT ang",
+ "éĹ ®",
+ "Ġident ification",
+ "Ġetc etera",
+ "ĠN ee",
+ "ĠÑĤ ÑĢи",
+ "ê· ¸",
+ "Ġcrypt ocur",
+ "Ġin hale",
+ "Ġadd ict",
+ "åIJĦ ä½į",
+ "Ġma u",
+ "ĠÑĤак аÑı",
+ "Ġë² Ħ",
+ "Ġcomp rar",
+ "ied zieÄĩ",
+ "ĠоÑĤ но",
+ "Ġbegin ner",
+ "Ġм Ñĥж",
+ "Ġobs c",
+ "Ġlim iting",
+ "asc ular",
+ "Ġins pection",
+ "ac i",
+ "Ġre jo",
+ "M us",
+ "Ġz aten",
+ "Ġsz cz",
+ "ĠMad rid",
+ "Ġvar ieties",
+ "Ġest Ãł",
+ "ĠSh akes",
+ "Ġk its",
+ "Ġad minister",
+ "Ġla va",
+ "Ġg Ã¥",
+ "è© ¦",
+ "ת ×Ļ",
+ "ĠWay ne",
+ "Ġinst agram",
+ "Ġr ated",
+ "p aper",
+ "Ġb ild",
+ "Ġpret ending",
+ "Ġobser ving",
+ "ĠÑģам ом",
+ "Ġtr or",
+ "Ġorgan isms",
+ "Ġfal ta",
+ "Ġh ometown",
+ "ç ±",
+ "Ġí ĭ",
+ "Ġche g",
+ "Ġì ¡",
+ "Ġcomm a",
+ "is é",
+ "Ġlike lihood",
+ "av ored",
+ "Ġgel di",
+ "ни ков",
+ "Ġmed io",
+ "Ġjak ie",
+ "ĠJ up",
+ "Ġgreen house",
+ "Ġsp it",
+ "ко е",
+ "Ġк аж",
+ "ĠG ram",
+ "ĠCon ference",
+ "Ġdef icit",
+ "s ın",
+ "in se",
+ "u ÄŁ",
+ "Ġr icht",
+ "Ġcoinc idence",
+ "åı į",
+ "Ġeu rop",
+ "Ġbutter fly",
+ "p read",
+ "Ġìĸ ¼",
+ "èĢ ¶",
+ "Ġwa vel",
+ "ĠIn fin",
+ "ĠPlan et",
+ "Ġself ie",
+ "ient ras",
+ "Ġar rog",
+ "os er",
+ "id al",
+ "ł×Š׳×ķ",
+ "üt ün",
+ "Ġfresh man",
+ "ĠMach ine",
+ "Ïĥ ÏĦ",
+ "ĠD ia",
+ "ìĿ´ ëĭ¤",
+ "ãģĵ ãģĨ",
+ "ne a",
+ "Ġlist ing",
+ "Ġconfig ure",
+ "ut or",
+ "U p",
+ "ts chaft",
+ "ri ère",
+ "Ġup wards",
+ "ĠÑħоÑĩ Ñĥ",
+ "Ġswe ep",
+ "B r",
+ "Ġexpress ing",
+ "Ġun happy",
+ "Ġmand atory",
+ "g ender",
+ "ĠA ÃŃ",
+ "Ġindic ators",
+ "Ġoil s",
+ "n ote",
+ "Ġseg ur",
+ "ож еÑĤ",
+ "yn asty",
+ "Ġdist ances",
+ "Ġmer ge",
+ "BER T",
+ "Ġsur render",
+ "Ġbu at",
+ "ĠA wards",
+ "Ġseñ or",
+ "od ox",
+ "Ġfl avour",
+ "Ġab dom",
+ "Ġconfig ur",
+ "8 6",
+ "ĠDI Y",
+ "Ġrig id",
+ "° ĺ",
+ "Ġcorpor ation",
+ "Ġg room",
+ "j aw",
+ "ĠNe ar",
+ "ил о",
+ "Ġoper a",
+ "ĠIn nov",
+ "и ÑĢа",
+ "ĵ ±",
+ "Ġspec ified",
+ "Ġcos m",
+ "ĠFre edom",
+ "Ġcl own",
+ "ĠN em",
+ "Ġв ол",
+ "Ñij н",
+ "Ġchar ger",
+ "à¹ģ ล",
+ "Ġinflu ential",
+ "äs ident",
+ "é ¤",
+ "ĠìĦ łë",
+ "Ġvol umes",
+ "æ IJ",
+ "Ġout ras",
+ "ĠTw itch",
+ "Ġfound ing",
+ "Ġa while",
+ "Ġco il",
+ "ê° Ļ",
+ "Ġc ả",
+ "ĠTh row",
+ "ĠH ence",
+ "omm t",
+ "ĠBen jamin",
+ "глÑı д",
+ "T ime",
+ "ob ic",
+ "Ġm our",
+ "Ġd read",
+ "ĠL Ãł",
+ "ĠCh ile",
+ "Ġpre val",
+ "Ġv ain",
+ "Ġart ık",
+ "Ġpres erved",
+ "ĠоÑĤ д",
+ "Ġware house",
+ "Ġbest e",
+ "ĠSever al",
+ "ĠS ituation",
+ "Ġcard board",
+ "T od",
+ "er na",
+ "Ġgar ant",
+ "Ġgest ure",
+ "Ġh en",
+ "Ġspe lling",
+ "ose xual",
+ "Ġan ne",
+ "Ġm ice",
+ "ĠMe ine",
+ "c ard",
+ "Ġre bell",
+ "Ġcert o",
+ "Ġìľ łë",
+ "Ġvers chied",
+ "ĠB os",
+ "Ġinv ention",
+ "Ġtr ze",
+ "Ġman ière",
+ "ĠCh ad",
+ "Ġsp re",
+ "Ġorganis ations",
+ "Ġpoor ly",
+ "Ġan terior",
+ "Ġst air",
+ "к ÑĢ",
+ "Ġatom ic",
+ "Ġsymp ath",
+ "Ġcontin ually",
+ "Ġkle ine",
+ "è te",
+ "и Ñī",
+ "ο ÏĤ",
+ "pe ut",
+ "Ġrep osit",
+ "Ġent ra",
+ "E m",
+ "Ġfinan cing",
+ "Ġмн ог",
+ "Ġthe sis",
+ "ĠCom puter",
+ "e au",
+ "ĠT ree",
+ "Ġbr ide",
+ "ons ieur",
+ "sh ire",
+ "w ic",
+ "D E",
+ "ĠìĪ ĺë",
+ "Ġac om",
+ "ĠP O",
+ "ers ch",
+ "Ġпом оÑī",
+ "ĠAr men",
+ "Ġì£ ½",
+ "Ġz or",
+ "Ġprint s",
+ "ĠD ass",
+ "æ¸ ¯",
+ "Ġdur able",
+ "ĠTrans port",
+ "ìŀIJ ê°Ģ",
+ "Ġл ег",
+ "Ġdé t",
+ "ô le",
+ "am ous",
+ "Y N",
+ "Ġcl iff",
+ "Ġgramm ar",
+ "ĠÐŁÐ¾ ÑįÑĤомÑĥ",
+ "ĠlÃł m",
+ "es ch",
+ "Ġmiser able",
+ "Ġvol ts",
+ "ĠC ad",
+ "uk an",
+ "ÑĤ ив",
+ "r ust",
+ "Ġìĺ¬ë Ŀ¼",
+ "Ġver k",
+ "Ġchick ens",
+ "ĠY oo",
+ "Ġout fits",
+ "c ode",
+ "Ġhier archy",
+ "net es",
+ "Ġcounter part",
+ "Ġt ôi",
+ "Ġt ed",
+ "ĠB art",
+ "Ġë Ŀ¼",
+ "ĠGen au",
+ "Ġinc oming",
+ "ĠA BC",
+ "ri que",
+ "ĠоÑĤ п",
+ "qu al",
+ "Ġincent ive",
+ "Ġih ren",
+ "׳ ×Ļ",
+ "lo e",
+ "Ġ19 30",
+ "Ġbar g",
+ "Ġd iction",
+ "Ġön ce",
+ "IN S",
+ "Ġre h",
+ "isia j",
+ "m outh",
+ "Ġsc oring",
+ "l ık",
+ "ĠìķĦ 주",
+ "OR IA",
+ "ĠEst ados",
+ "Ġcompan ion",
+ "Ġasse mble",
+ "Ġpun ished",
+ "Ġit al",
+ "Ġprev ents",
+ "ist es",
+ "ĠKent ucky",
+ "Ġloc ate",
+ "Ġfast ing",
+ "ãģ¨ æĢĿ",
+ "ĥ Ģ",
+ "ĠSe b",
+ "ĠCr own",
+ "op ia",
+ "Ġwh ip",
+ "us z",
+ "к ами",
+ "Ġdatab ases",
+ "åŃ Ĺ",
+ "Ġprose c",
+ "Ġ199 7",
+ "ĠìĤ´ì §Ŀ",
+ "ĠSol ar",
+ "ĠP ues",
+ "ĠZ en",
+ "oll o",
+ "ĠG uru",
+ "Ġsque ez",
+ "ĠÐĹ Ð°",
+ "ĠÄ į",
+ "cept ions",
+ "c ca",
+ "iz able",
+ "m and",
+ "Ġbreak through",
+ "Ġtables poon",
+ "ĠS EC",
+ "ik h",
+ "ĠS ão",
+ "Ġп ло",
+ "am en",
+ "Ġpr ac",
+ "Ġdar ling",
+ "Ġtall er",
+ "Ġrend ering",
+ "Ġìļ°ë¦¬ ê°Ģ",
+ "ĠÏĦη ÏĤ",
+ "Ġm ã",
+ "Ġes os",
+ "uer do",
+ "ĠÑģ ÑĩиÑĤ",
+ "all er",
+ "ìĹĪ ìĸ´ìļĶ",
+ "Ġmill ones",
+ "ler in",
+ "Ġpe gar",
+ "on ne",
+ "Ġenroll ment",
+ "Ġli egt",
+ "Ġbo a",
+ "w iÄĻ",
+ "bs p",
+ "Ġcy cling",
+ "ĠBern ie",
+ "Ġ198 9",
+ "Ġд алÑĮ",
+ "ĠDak ota",
+ "ĠÑģв Ñıз",
+ "ĠC P",
+ "Ġst are",
+ "íĤ ¤",
+ "Ġprosper ity",
+ "Ġarrange ments",
+ "Ġarri ving",
+ "m ä",
+ "Ġkay ak",
+ "ip t",
+ "Ġp ardon",
+ "Ġrel at",
+ "Ġver ste",
+ "ĠF ig",
+ "Ġfo il",
+ "ĠTalk ing",
+ "pe are",
+ "Ġno i",
+ "ĠпÑĢи ÑĪ",
+ "Ġhoc key",
+ "Ġad o",
+ "ĠO UT",
+ "6 7",
+ "Ġhorm ones",
+ "ĠAven ue",
+ "ĠSuper man",
+ "Ġpres cription",
+ "uber netes",
+ "C L",
+ "ot ive",
+ "N IS",
+ "ien en",
+ "Ġsad ness",
+ "ĠV it",
+ "T y",
+ "Ġstar ter",
+ "Ġbed e",
+ "Ġfound ations",
+ "Ġso re",
+ "åº Ĺ",
+ "Ñīе ÑģÑĤв",
+ "ìļ °ë",
+ "ĠÑĩ Ñĥв",
+ "l ink",
+ "Ġmane u",
+ "work ing",
+ "Ãł n",
+ "ĠAtt ack",
+ "ĠC art",
+ "ve is",
+ "ĠRes p",
+ "ens ing",
+ "Ġì¢ĭ ìķĦìļĶ",
+ "Ġesc uch",
+ "ĠR NA",
+ "Ĥ ´",
+ "Ġad op",
+ "Ġb ending",
+ "ع د",
+ "Ġman ages",
+ "us p",
+ "Ġt art",
+ "Ġrout er",
+ "B o",
+ "Ġestab lishing",
+ "Ġbal ancing",
+ "Ġathlet ic",
+ "ĠS lo",
+ "Ġf ills",
+ "Ġн аб",
+ "Ġд ал",
+ "Ġpos so",
+ "ĠV ielen",
+ "Ġcrit ics",
+ "Ġlaws uit",
+ "ĠIsa ac",
+ "ĠÑĦилÑĮ м",
+ "Ġtr as",
+ "Ġpra w",
+ "ĠCra zy",
+ "Ġne u",
+ "Ġk ull",
+ "Ġtum or",
+ "ĠAP P",
+ "g ate",
+ "ĠA RE",
+ "9 8",
+ "ĠSte am",
+ "Ġfuck ed",
+ "l age",
+ "ĠâĻ ¬",
+ "ĠM D",
+ "f y",
+ "Ġshell s",
+ "ĠSe ems",
+ "iz ers",
+ "Ġr anges",
+ "ĠAnton io",
+ "AT ION",
+ "ĠB aba",
+ "Ġìĥ ī",
+ "k un",
+ "Ġpray ed",
+ "ÑĢ Ñı",
+ "ĠпÑĢоÑĤ ив",
+ "Ġse as",
+ "b ury",
+ "Ġ×Ķ× ©",
+ "Ġtra it",
+ "ĠDep ending",
+ "Ġd re",
+ "Ġkön nt",
+ "ÑĨ Ñĥ",
+ "Ġlip stick",
+ "ee z",
+ "ĠпÑĢ имеÑĢ",
+ "Ġassign ments",
+ "B ob",
+ "Ġmet als",
+ "Ġspe cially",
+ "å°į ä¸įå°į",
+ "Ġìĺ Īë",
+ "ĠÅ ¡",
+ "Ġv ista",
+ "ĠÎ ¬",
+ "Ġtw ins",
+ "Ġnot able",
+ "ĠS au",
+ "Ġdé velop",
+ "Ġç ek",
+ "Ġpoly nom",
+ "av am",
+ "Ġtamb é",
+ "он ом",
+ "Ġpl asma",
+ "Ġe fect",
+ "Ġlä ng",
+ "Ġcas i",
+ "Ñģ а",
+ "ım ı",
+ "ãģĻ ãĤĭ",
+ "ĵ¤ ìĿĢ",
+ "Ġlab our",
+ "oss en",
+ "ĠP un",
+ "r if",
+ "Ġd oses",
+ "Ġoper ates",
+ "ил ли",
+ "Ġja ar",
+ "st aw",
+ "ĠìĤ¬ëŀ ij",
+ "Ġat m",
+ "Ġprotect s",
+ "Ġimp ed",
+ "H O",
+ "Ġc ima",
+ "Ġto ch",
+ "ab is",
+ "Ġsend o",
+ "la us",
+ "Ġcur l",
+ "ĠN um",
+ "Ġspons ors",
+ "Ġdé but",
+ "ĠAlex a",
+ "ĠB ür",
+ "ĠA mer",
+ "Ġc ope",
+ "Ġиз в",
+ "j al",
+ "Ġ199 5",
+ "ap at",
+ "res se",
+ "ĠPri ze",
+ "ĠCla ire",
+ "ĠBrand on",
+ "Ġwszyst ko",
+ "Ġval ued",
+ "à¸Ļ ะ",
+ "Ġse ct",
+ "Ġsecret ly",
+ "Ġdiam onds",
+ "ĠEv an",
+ "ĠRP G",
+ "ãģ« ãģª",
+ "Īë ıĦ",
+ "ĠUnivers al",
+ "Ġdoub ts",
+ "ĠP in",
+ "wiÄħ z",
+ "ļ ©",
+ "Ġal bo",
+ "Ġbra ucht",
+ "AU L",
+ "ĠM obile",
+ "gr ades",
+ "Ġsch em",
+ "wh y",
+ "ĠN icht",
+ "p i",
+ "g le",
+ "Ġchor us",
+ "Ġg ly",
+ "Ġrein force",
+ "Ġm uff",
+ "ĠSh en",
+ "ĠH ola",
+ "Ñĥ г",
+ "vid emment",
+ "v ial",
+ "ac ious",
+ "laim ed",
+ "ĠR ico",
+ "Ġve gg",
+ "Ġillust ration",
+ "ĠBut ter",
+ "ow ad",
+ "Ġeu x",
+ "Ġenf ants",
+ "ĠLe ader",
+ "ĠVill age",
+ "et ically",
+ "ÙĨ ÙĬ",
+ "Ġst ew",
+ "Ġsurpr ises",
+ "Ġc ue",
+ "ĠGrand ma",
+ "ĠC elsius",
+ "ĠR icht",
+ "en c",
+ "Ġpet ition",
+ "Ġher b",
+ "Ġw icked",
+ "Ġsch le",
+ "oc aly",
+ "Ġtrans f",
+ "Ġtok ens",
+ "ĠGr ay",
+ "ĠB BC",
+ "I K",
+ "Ġ15 00",
+ "z n",
+ "ĠNe v",
+ "Ġk oy",
+ "Ġz ar",
+ "Ġbull shit",
+ "ĠColomb ia",
+ "ul ative",
+ "Ġwides pread",
+ "y ect",
+ "k it",
+ "Ġempres a",
+ "Ġn our",
+ "Ġburn s",
+ "at in",
+ "a ired",
+ "Ġrevolution ary",
+ "Ġгод Ñĥ",
+ "ĠLog an",
+ "Ġ199 6",
+ "ĠGra ham",
+ "re b",
+ "ĠN HS",
+ "æľ Ľ",
+ "Ġcost umes",
+ "Ġnaw et",
+ "Ġlo vers",
+ "ĠLuc y",
+ "ĠInd igenous",
+ "íķĺ 기",
+ "Ġimmun ity",
+ "¥ ´ë",
+ "uit o",
+ "Ġexcess ive",
+ "Ġdon ations",
+ "Ġ×Ķ ר",
+ "Ġì² «",
+ "éī Ħ",
+ "Ġdry ing",
+ "mel on",
+ "Ġsurve ys",
+ "Ġ무ì Ĭ¨",
+ "é¢ ¨",
+ "aa a",
+ "Ġpro be",
+ "an cial",
+ "Ġlou der",
+ "Ġhot els",
+ "ü ÄŁ",
+ "ag ner",
+ "Ġorig ins",
+ "Ġë§Ī ì§Ģë§ī",
+ "Ġ* *",
+ "Ġstr angers",
+ "ĠHa us",
+ "com ed",
+ "Ġan throp",
+ "Ġus o",
+ "ĠìķĦ ì§ģ",
+ "ĠY uan",
+ "ĠíķĦ ìļĶ",
+ "pl er",
+ "ress ive",
+ "Ġsp raw",
+ "ĠSt ew",
+ "Ġ199 4",
+ "Ġeld ers",
+ "Ġme inen",
+ "Ġj unt",
+ "Ġac oust",
+ "ĠW ohn",
+ "Ġban anas",
+ "Ġproject ion",
+ "ĠSt ick",
+ "leg t",
+ "spe ed",
+ "ĠcÅ ©ng",
+ "ĠW ort",
+ "ĠBalt imore",
+ "ĠÑĨ ел",
+ "Ġdun no",
+ "å¼ ·",
+ "? ,",
+ "ãĥī ãĥ³",
+ "ĠLoc al",
+ "ost o",
+ "Ð Ń",
+ "од а",
+ "ĠPort uguese",
+ "Ġtheir s",
+ "Ġdé m",
+ "åı ¦",
+ "Ġdra uf",
+ "ĠBuddh ist",
+ "ert a",
+ "G e",
+ "Ġcar rot",
+ "ĠWonder ful",
+ "Ġso ak",
+ "Ġchair man",
+ "gg i",
+ "IC A",
+ "f ried",
+ "Ġfl ick",
+ "ĠThrough out",
+ "Ġìļ °ë",
+ "Ġc ough",
+ "Ġfl uffy",
+ "sch ool",
+ "Ġr ipped",
+ "---- ----",
+ "ĠZuk unft",
+ "Ġн еб",
+ "Ġst o",
+ "ĠB O",
+ "p ent",
+ "ĠLaw rence",
+ "Ïī ÏĤ",
+ "st icks",
+ "ĠE ins",
+ "ĠÑĢ Ñĭ",
+ "ĠStr ong",
+ "Ġcar amel",
+ "Ġsp ite",
+ "az ar",
+ "éĥ½ æĺ¯",
+ "Ġcrit ically",
+ "Ġob ra",
+ "ow itz",
+ "ĠZ one",
+ "ĠÑĢ ек",
+ "Ġsu g",
+ "ard ed",
+ "Ġg ì",
+ "ff entlich",
+ "an che",
+ "Ø Ł",
+ "ast ically",
+ "ìĿ ¼ë",
+ "л ав",
+ "Ġsimpl est",
+ "ĠF riend",
+ "Ġque llo",
+ "Ġamb ition",
+ "Ġabb iamo",
+ "åº ķ",
+ "ĠÑĦ оÑĢм",
+ "ĠEs sa",
+ "Ġeduc ators",
+ "Ġstatist ical",
+ "éĢĻ éĤĬ",
+ "Ġchang er",
+ "Ġat au",
+ "éta is",
+ "ĠShakes peare",
+ "ë IJĺ",
+ "Ġtr iggers",
+ "Ġreal iz",
+ "Ġcel ui",
+ "whe el",
+ "Ġloyal ty",
+ "Ġscream s",
+ "ke hr",
+ "ĠM ega",
+ "e ast",
+ "Ġtop s",
+ "ĠTot ally",
+ "ount ain",
+ "l ord",
+ "Ġviol ation",
+ "ĠG A",
+ "Ġnic er",
+ "ĠF resh",
+ "ĠMel issa",
+ "fun ction",
+ "Ġra pe",
+ "Ġexcept ions",
+ "Ġsil icon",
+ "Ġliber ty",
+ "Ġhousehold s",
+ "ãģį ãģ¾ãģĻ",
+ "ĠC A",
+ "ĠÐŀ б",
+ "Ġli b",
+ "ŀ Į",
+ "c ific",
+ "Ġtrop ical",
+ "Ġinvestig ating",
+ "H D",
+ "Ġad apter",
+ "ĠP itt",
+ "an cia",
+ "ĠShe ll",
+ "friend ly",
+ "Ġconclus ions",
+ "Ġtur tle",
+ "Ġdec omp",
+ "Ġanim ations",
+ "ĠÑģ ек",
+ "ins i",
+ "Ġret ention",
+ "k ie",
+ "Ġinject ion",
+ "ĠMad ison",
+ "ì° °",
+ "Ġv ient",
+ "Ġvar ied",
+ "Ġviol in",
+ "ĠB il",
+ "Ġluck ily",
+ "Ġh tt",
+ "l ä",
+ "Ġr anch",
+ "çľĭ çľĭ",
+ "Ġsó lo",
+ "ìķ ħ",
+ "ĠD erek",
+ "ĠScript ure",
+ "оÑĢ а",
+ "Ġclassroom s",
+ "av il",
+ "form ed",
+ "Ġbefore hand",
+ "ĠG em",
+ "pre ch",
+ "Ġl in",
+ "Ġgre ens",
+ "ÑĨ ев",
+ "ĠMer cedes",
+ "Ġdr ought",
+ "gas ps",
+ "Ġab ortion",
+ "Ġter ribly",
+ "Ġspos ób",
+ "Ġsec ured",
+ "Ġat rás",
+ "Ġwavel ength",
+ "Ġgra ins",
+ "ect ive",
+ "Ġspace craft",
+ "Ġtour s",
+ "Ġprof es",
+ "Ġsur geon",
+ "ĠP ie",
+ "Ġide ally",
+ "arn er",
+ "U P",
+ "op ard",
+ "s ce",
+ "Ġimm ense",
+ "ĠOr t",
+ "roll er",
+ "ĠD allas",
+ "ĠNich olas",
+ "Ġs ulf",
+ "ĠToy ota",
+ "Ġquant ities",
+ "ce ans",
+ "Ġcu i",
+ "an ça",
+ "ĠC AN",
+ "itzer land",
+ "åĦ ¿",
+ "Ġz ou",
+ "ĠCy ber",
+ "le gen",
+ "ĠIn it",
+ "ed u",
+ "Ġa pert",
+ "Ġad jac",
+ "ou v",
+ "èĢĮ ä¸Ķ",
+ "r s",
+ "Ġcab bage",
+ "Ġwheel chair",
+ "iny l",
+ "ĠD ynam",
+ "ĠìķĦëĭĪë Ŀ¼",
+ "Ġl ing",
+ "h l",
+ "Ġмог Ñĥ",
+ "Ġcris p",
+ "Ġm ij",
+ "Ġd ug",
+ "n in",
+ "Ġbl oss",
+ "Ġbelong ing",
+ "Ġloud ly",
+ "Ġminer als",
+ "Ġconclud ed",
+ "Ġsearch ed",
+ "9 6",
+ "ĠMe et",
+ "ĠS EO",
+ "ĠС к",
+ "ĠH ob",
+ "ot ta",
+ "Ġpropag anda",
+ "Ġcin namon",
+ "Ġhun ter",
+ "Ġgeme ins",
+ "Ġsculpt ure",
+ "uls ion",
+ "Ġv äl",
+ "Ġmagaz ines",
+ "Ġcontrovers y",
+ "ä¸Ģ 樣",
+ "Ġsequ ences",
+ "ãģĦ ãĤĭ",
+ "Ġíļ Į",
+ "Ġdel eted",
+ "ä½ ¿",
+ "IJë ıĦ",
+ "Ġvary ing",
+ "ãĥ Ĩ",
+ "Ġmount ing",
+ "Ġaff air",
+ "Ġpath ways",
+ "æ ¦",
+ "Ġdig o",
+ "äº ®",
+ "Ġд ок",
+ "A lex",
+ "Ġtob acco",
+ "ĠC V",
+ "Ġbother ed",
+ "Ġamb ient",
+ "ink y",
+ "ĠS L",
+ "Ġh ates",
+ "Ġje żeli",
+ "Ġcon greg",
+ "Ġel as",
+ "Ġde uts",
+ "ĠStud ios",
+ "ch ÄĻ",
+ "Ġdocument ed",
+ "ĠCru z",
+ "ĠL en",
+ "ĠDoug las",
+ "ĠPort ugal",
+ "ent i",
+ "Ġsp ouse",
+ "Ġanal ys",
+ "av ia",
+ "Ġed ited",
+ "Ġl ại",
+ "bu ilt",
+ "Ġv ille",
+ "ad ora",
+ "Ġbrac elet",
+ "Ġs ushi",
+ "Ġp m",
+ "Ġtra ils",
+ "Ġl ug",
+ "Ġö ver",
+ "Ġs orrow",
+ "Ġcol ony",
+ "ado x",
+ "Ġser ie",
+ "any ak",
+ "ĠØ ·",
+ "ĠG ulf",
+ "æĺ¯ ä¸įæĺ¯",
+ "ĠP V",
+ "ĠSam uel",
+ "ĠK it",
+ "ĠR al",
+ "ont in",
+ "ex pl",
+ "Ġent ries",
+ "Ġactiv ists",
+ "P s",
+ "Ġs ant",
+ "ĠÑĤо Ñĩ",
+ "ĠBr uno",
+ "ke ley",
+ "Ġtut to",
+ "é Ķ",
+ "Ġv intage",
+ "Ġterr ified",
+ "Ġпо Ñħ",
+ "us ive",
+ "ow ers",
+ "ай ÑĤ",
+ "ë ıĻ",
+ "Ġtwist ed",
+ "ĠTh ought",
+ "Ġt ah",
+ "Ġshr ink",
+ "Ġshe er",
+ "l it",
+ "Ġdal am",
+ "Ġd ib",
+ "Ġv ard",
+ "ow ane",
+ "Ġdo br",
+ "ĠR ena",
+ "ĠÑģво Ñİ",
+ "ĠpaÃŃs es",
+ "ĠE ra",
+ "ãģ® ãģ§",
+ "ĠB UT",
+ "s ighs",
+ "Ġê·¸ ê±°",
+ "Ġgro ÃŁen",
+ "Ġë¹ ¨ë¦¬",
+ "Ġn erves",
+ "Ġconst it",
+ "Ġpreoc up",
+ "ĠG ay",
+ "ĠX u",
+ "keep er",
+ "he ure",
+ ".. )",
+ "ĠCal m",
+ "ĠUn idos",
+ "ĠìĿ´ ê²ĥ",
+ "ĠAqu i",
+ "Ġìłľ ìĿ¼",
+ "d ır",
+ "ì¦ ĺ",
+ "y our",
+ "ĠÑįÑĤ им",
+ "20 20",
+ "Ġr und",
+ "ĠH O",
+ "ĠC atherine",
+ "iel i",
+ "Ġf usion",
+ "Ġide ology",
+ "Ġfor am",
+ "sh aped",
+ "ĠíĽ Ħë",
+ "Ġw t",
+ "Ġret r",
+ "Ġpr éc",
+ "Ġê° ij",
+ "Ġopen ly",
+ "v ity",
+ "구 ìļĶ",
+ "Ġobst acle",
+ "Ġbo o",
+ "Ġse iner",
+ "ic orn",
+ "Ġeigen lijk",
+ "Ġhead er",
+ "are mos",
+ "Ġso fter",
+ "ĠÐŁ од",
+ "Ġpre jud",
+ "Ġdefin es",
+ "ier te",
+ "Ġbl ending",
+ "Ġbelie vers",
+ "ĠWo chen",
+ "Ġник ак",
+ "ĠÐļ огда",
+ "ĠTyp ically",
+ "Ġíģ ¬",
+ "ç® ¡",
+ "ci os",
+ "Ġmiss iles",
+ "Ġsp onge",
+ "ĠK itchen",
+ "Ġt ren",
+ "ning en",
+ "Ġsc rap",
+ "Ġser ait",
+ "´ì ł",
+ "ç ¹",
+ "Ġë° ĺë",
+ "Ġrest ored",
+ "Ġprzy kÅĤad",
+ "ĠK ubernetes",
+ "Ġsa it",
+ "Ġu w",
+ "Ġen abling",
+ "Ġtra vers",
+ "amp s",
+ "åı Ĺ",
+ "ĠOM G",
+ "ens or",
+ "Ġz osta",
+ "Ġpronoun ced",
+ "A ng",
+ "norm al",
+ "Ġeconom ies",
+ "t in",
+ "ĠChamp ion",
+ "iz en",
+ "Ġar beiten",
+ "ĠG ospel",
+ "ĠZ u",
+ "ng a",
+ "Ġliter acy",
+ "ĠM ans",
+ "Ġcircul ation",
+ "Ġad ap",
+ "ĠTot al",
+ "Ġmere ka",
+ "Ġol acak",
+ "ÑģÑĤ аÑĤи",
+ "J ack",
+ "Ġm und",
+ "Ġth ief",
+ "b ies",
+ "Ġê² ģ",
+ "a que",
+ "ĠÚ© ÛĮ",
+ "ĠSc ar",
+ "å ²",
+ "Ġab ol",
+ "Ġdev ote",
+ "Ġ0 1",
+ "Ġs itten",
+ "ĠVis ual",
+ "we ek",
+ "s ome",
+ "ing t",
+ "Ġjournal ism",
+ "ĠH ir",
+ "ĠB achelor",
+ "in ery",
+ "Ãľ ND",
+ "ãĥ Ł",
+ "ç» Ļ",
+ "Ġcolor ing",
+ "ĠCr ist",
+ "Ġcelebr ities",
+ "ĠÑĩ иÑģ",
+ "ĠC rit",
+ "Ġdifferent iate",
+ "ĠÐľ не",
+ "el im",
+ "Ġse afood",
+ "Ġalgum as",
+ "otherap y",
+ "æĪ °",
+ "Ġgla ub",
+ "Ġarbitr ary",
+ "g ens",
+ "ĠбÑĥд ем",
+ "Ġt av",
+ "Ġcream y",
+ "ĠCount ry",
+ "a ñ",
+ "м еÑĤ",
+ "Ġh inter",
+ "Ġm ism",
+ "Ġillust rate",
+ "ÃľND NIS",
+ "Ġdecre asing",
+ "Ġwen iger",
+ "AK I",
+ "ix on",
+ "Ġн ей",
+ "Ġfat to",
+ "Ġn erd",
+ "ç ł",
+ "Ġb itte",
+ "P er",
+ "Ġt ane",
+ "Ġgö z",
+ "Ġfor te",
+ "ĠE y",
+ "Ġнав еÑĢ",
+ "è¢ «",
+ "ĠWord Press",
+ "ĠM is",
+ "Å ¯",
+ "z äh",
+ "Ġinté ress",
+ "osa urs",
+ "ĠFall s",
+ "Ġn essa",
+ "9 7",
+ "Ġmuseum s",
+ "Ġcorrespond s",
+ "Ġs ings",
+ "f our",
+ "Ġed er",
+ "ĠCommun ist",
+ "o a",
+ "ne k",
+ "ĠWH O",
+ "Ġcor po",
+ "Ġmess ing",
+ "ÏĦ αι",
+ "Ġbrush es",
+ "Ġb isc",
+ "ĠAr beits",
+ "ĠT ax",
+ "Ġse le",
+ "Ġflag s",
+ "ou pe",
+ "Ġanticip ated",
+ "ãĥ ij",
+ "ĠN ad",
+ "Ġpou red",
+ "Ġm l",
+ "Ġll ama",
+ "Ġvisual ize",
+ "Ġlisten ers",
+ "ÙĦ Ùĥ",
+ "al ten",
+ "Mich ael",
+ "Ġcos ì",
+ "Õ¡ Õ",
+ "op us",
+ "Ġíķ´ì £¼",
+ "Ġh ike",
+ "ĠAtt orney",
+ "ĠHill ary",
+ "ud ed",
+ "Ġíķĺ ì§Ģë§Į",
+ "Ġdo ve",
+ "Ġstorm s",
+ "ак Ñģ",
+ "Ġdoct rine",
+ "Ġhe x",
+ "ik s",
+ "no ÅĽÄĩ",
+ "Ġscript s",
+ "Ġδ εν",
+ "ĠÑįÑĤи Ñħ",
+ "ĠÐ Ĩ",
+ "ab er",
+ "ĠV as",
+ "Ġcent imeters",
+ "×ŀ ×Ķ",
+ "ни б",
+ "Ġrid ers",
+ "ĠT rib",
+ "åĮ ħ",
+ "Ġtak że",
+ "Ġn oun",
+ "Ġic ons",
+ "Ġsole ly",
+ "mind ed",
+ "Ġdisp on",
+ "ĠSw itzerland",
+ "Ġcl usters",
+ "Ġqu eda",
+ "ail ing",
+ "Ġman ga",
+ "Ġ6 8",
+ "Ħ Ī",
+ "Ġt et",
+ "g ins",
+ "ha us",
+ "ç© º",
+ "å· ¥",
+ "ĠO P",
+ "ot ed",
+ "Ġnouve au",
+ "AL LY",
+ "ÙĪ د",
+ "ò n",
+ "Ġmort ality",
+ "ĠGit Hub",
+ "d rop",
+ "Ġdis gu",
+ "Ġrec om",
+ "Ġloc als",
+ "Ġhome made",
+ "amb a",
+ "Ġpron unciation",
+ "Ġal phabet",
+ "ан ÑĮ",
+ "ow any",
+ "ir as",
+ "id ency",
+ "OM E",
+ "ĠÑĢаÑģ Ñģ",
+ "ar ak",
+ "v iamente",
+ "Ġnon profit",
+ "ĠYouT uber",
+ "Ġp arenth",
+ "ĠB oo",
+ "v at",
+ "ĠSt ir",
+ "Ġpre cip",
+ "Ġan ts",
+ "Ġall y",
+ "ĠMa ori",
+ "ĠëĮĢ íķľ",
+ "åı¯ æĺ¯",
+ "og ene",
+ "ĠLab our",
+ "aret te",
+ "Ġrecy cling",
+ "ens a",
+ "Ġpurs uit",
+ "Ġs ak",
+ "ĠÐĹд еÑģÑĮ",
+ "Ġtoler ance",
+ "Ġsa at",
+ "Ġclick ed",
+ "âĻ ¥",
+ "Ġface book",
+ "ĠInt o",
+ "Ġincent ives",
+ "기 ëĬĶ",
+ "ĠD ennis",
+ "ĠW ik",
+ "ges ch",
+ "à¹ĢภĽ",
+ "ĠÏĢ α",
+ "ĠWh oo",
+ "Ġround ed",
+ "Ġdo pe",
+ "Ġcapt uring",
+ "ĠWar ri",
+ "Ġcivil ian",
+ "Ġchar ming",
+ "Ġes as",
+ "Ġsust ained",
+ "Ġle aning",
+ "Ġabund ance",
+ "ÃŃ lia",
+ "алÑĮ нÑĭй",
+ "Ġph ải",
+ "ac ja",
+ "Ġê°Ļ ìķĦ",
+ "act iv",
+ "า ย",
+ "Ġ9 7",
+ "Ġм ой",
+ "c ro",
+ "ĠJack ie",
+ "itt ees",
+ "br acht",
+ "ul ent",
+ "Ġìł ľë",
+ "Ġplug in",
+ "v antage",
+ "part y",
+ "Ġsu as",
+ "Ġan te",
+ "Ñĥ л",
+ "ÐĿ ÐIJ",
+ "æĤ ¨",
+ "ĠÏĥ Ïħ",
+ "Ġmet h",
+ "Ġenthus iasm",
+ "ÑıÑĤ ÑģÑı",
+ "íĻ Ķë",
+ "Ġsynth etic",
+ "Ġseason ing",
+ "ĠL ost",
+ "on omy",
+ "ĠSp ark",
+ "Ġb ure",
+ "Ġass ured",
+ "Ġimag in",
+ "Ġcar ro",
+ "S ha",
+ "Äħ t",
+ "нÑĥ ÑĤÑĮ",
+ "át ica",
+ "T Y",
+ "Ġk ern",
+ "ĠBrazil ian",
+ "Ã °",
+ "Ġsusp ended",
+ "ĠCar ib",
+ "Ġbiz im",
+ "ĠOl iver",
+ "ãģ ¶",
+ "T om",
+ "Ġпл ан",
+ "Ġn ope",
+ "omet hing",
+ "Ġbe iden",
+ "ÑĨ ен",
+ "Ġflu ct",
+ "Ġμ οÏħ",
+ "Ġf athers",
+ "ĠBl ake",
+ "Ġup ward",
+ "ĠD ash",
+ "ĠL il",
+ "ĠìĪ ĺëıĦ",
+ "Ġrevel ation",
+ "Ġelev ated",
+ "ĠJi ang",
+ "LE D",
+ "ĠThom pson",
+ "Ġмог ÑĥÑĤ",
+ "ÑģÑĤ ÑĢÑĥ",
+ "if iers",
+ "Ġcome back",
+ "Ġbuy ers",
+ "ê² °",
+ "ĠS ales",
+ "иÑĩ е",
+ "c iones",
+ "Ġwh istle",
+ "Ġd ull",
+ "LE X",
+ "Ġíķĺ ê²łìĬµëĭĪëĭ¤",
+ "Ġcrimin als",
+ "Ġdes cent",
+ "ipp le",
+ "mas ı",
+ "Ġfool ish",
+ "ĠдÑĥм аÑİ",
+ "t ar",
+ "Ġman go",
+ "Ġchore ography",
+ "M att",
+ "Ġterr itor",
+ "Ġac aba",
+ "ĠEin stein",
+ "ĠI BM",
+ "ĠMet al",
+ "ĠCry stal",
+ "Ġr ah",
+ "Ġf oul",
+ "ĠIsland s",
+ "Ġint act",
+ "ĠR ail",
+ ". :",
+ "Ġac á",
+ "ĠпÑĢ оп",
+ "еÑĢ е",
+ "ĠWr ite",
+ "he he",
+ "ĠF O",
+ "ĠÏĥ ÏĦη",
+ "Ġdo in",
+ "h eld",
+ "Ġappropri ately",
+ "Ġdeliber ately",
+ "Ġarch ive",
+ "Ġgive away",
+ "ãģĵ ãģĵ",
+ "Ġfin ale",
+ "л аÑģ",
+ "ен о",
+ "Æ¡ n",
+ "æ£ Ĵ",
+ "og o",
+ "çī ©",
+ "ĠAud ience",
+ "ãħ ł",
+ "Ġsub ur",
+ "Ġhead ache",
+ "ан нÑı",
+ "ĠW itch",
+ "ĠSwed ish",
+ "ĠB I",
+ "Ġer ase",
+ "Ġk hi",
+ "Ġcomment ary",
+ "ĠS ultan",
+ "íĥ Ŀ",
+ "ĠLe ban",
+ "Ġë³´ì ĭ",
+ "ĠP am",
+ "pe kt",
+ "mon th",
+ "Ġground ed",
+ "ê ¾",
+ "ĠÅŁek ilde",
+ "2 50",
+ "ĠS CH",
+ "ios o",
+ "Ġin aug",
+ "he imer",
+ "Ġreflect ing",
+ "ĠR uth",
+ "ĠO il",
+ "Ġtrou ver",
+ "u ep",
+ ".. ]",
+ "Ġìŀ Īë",
+ "Ġol ha",
+ "Ġreason ably",
+ "Ġgl itch",
+ "U B",
+ "ĠGr an",
+ "Ġad alah",
+ "Ġl ent",
+ "ر ا",
+ "Ġtr action",
+ "Ġadjust ing",
+ "´ ¤",
+ "ниб ÑĥдÑĮ",
+ "Ġд оп",
+ "Ġstretch ed",
+ "Ġor t",
+ "Ġcos ine",
+ "vi ol",
+ "Ġì ħ",
+ "c ir",
+ "Ġbast ard",
+ "ä¸ ĩ",
+ "ĠÑħ од",
+ "Ġqu ier",
+ "Ġpress ures",
+ "ĠAn h",
+ "å¹ ¾",
+ "Ġell es",
+ "Ġд ÑĢÑĥз",
+ "ĠможеÑĤ е",
+ "Ġch á»",
+ "ĠM é",
+ "ö k",
+ "ầ u",
+ "ìł Ī",
+ "z in",
+ "Ġca ution",
+ "ib an",
+ "Ġjud ging",
+ "ÑĥÑİ ÑĤ",
+ "Ġb aj",
+ "ĠС ейÑĩаÑģ",
+ "ĠPo or",
+ "ĠNaz i",
+ "Ġup beat",
+ "y ang",
+ "Ġweek ends",
+ "ĠEss entially",
+ "Ġol uyor",
+ "Ġspat ial",
+ "ack er",
+ "Ġsell er",
+ "Ġ×IJ ×ķת",
+ "ij ׾",
+ "Ġv ivid",
+ "ĠB ond",
+ "ê ¶Į",
+ "is kt",
+ "ãĤ µ",
+ "Ġgo at",
+ "dri ver",
+ "Ġm ug",
+ "ict ional",
+ "Ġall t",
+ "ĠIn iti",
+ "ĠR and",
+ "Ġfinish es",
+ "Ġê° Ī",
+ "Ġvit am",
+ "Ġteen agers",
+ "ĠMor ris",
+ "ì¤ Ħ",
+ "ĠO ri",
+ "i ya",
+ "Ġmy ös",
+ "St ep",
+ "ĠK re",
+ "è¾ ¦",
+ "Ġdin osaur",
+ "Ġëª ĩ",
+ "aff e",
+ "ĠëIJ ©ëĭĪëĭ¤",
+ "Ġz eg",
+ "åĪ ĩ",
+ "ĠManh attan",
+ "Ġsu jet",
+ "ue lle",
+ "st off",
+ "Ġd ür",
+ "Ġsub mar",
+ "es es",
+ "Ġa quele",
+ "Ġn ou",
+ "ĠFa ith",
+ "t z",
+ "ĠÑĤ омÑĥ",
+ "ace ut",
+ "li ers",
+ "Ġband width",
+ "Æ°á» Ŀ",
+ "Ġrespect ive",
+ "ĠA ve",
+ "Ġspread she",
+ "ĠS ent",
+ "ic amente",
+ "Ġinf ra",
+ "Ġlearn ers",
+ "Ġà® ī",
+ "ai ah",
+ "ren al",
+ "Ġmust ard",
+ "Ġhab t",
+ "ç ĥ",
+ "ĠQu é",
+ "Ġanaly zing",
+ "æ¯ ı",
+ "Ġso lic",
+ "Ġ×Ķ ×ķ×IJ",
+ "Ġcaus a",
+ "Ġwel comed",
+ "ĠS uccess",
+ "Ġfac ile",
+ "ĠÐŁÐ¾ÑĤ омÑĥ",
+ "sche in",
+ "Ġf etch",
+ "Ġstr at",
+ "ĠÑģÑĤо иÑĤ",
+ "ìĹIJìĦľ ëĬĶ",
+ "ĠÑģп оÑģоб",
+ "m am",
+ "Ġser ÃŃa",
+ "nam ents",
+ "wr iter",
+ "Ġconsult ing",
+ "íĺ Ģ",
+ "ĠBer keley",
+ "e u",
+ "as ive",
+ "U U",
+ "ĠAnal yt",
+ "Ġsubm ission",
+ "Ġmagnific ent",
+ "en za",
+ "Ġe con",
+ "Ġprof iles",
+ "Ġinc ar",
+ "A b",
+ "ĠN un",
+ "Ġh ic",
+ "scream ing",
+ "Ġresil ient",
+ "åĪ ©",
+ "gr und",
+ "Ġconc ur",
+ "Ġbere its",
+ "L D",
+ "Ġnur t",
+ "ì ī",
+ "Ġfe ast",
+ "Ġenc uent",
+ "ĠMich el",
+ "Ġsup rem",
+ "\" ]",
+ "Ġfeed s",
+ "ĠKoll egen",
+ "iss er",
+ "ĠF eng",
+ "ĠW en",
+ "m un",
+ "Ġten ÃŃa",
+ "ĠW rest",
+ "Ġìĺ¤ëĬĺ ìĿĢ",
+ "Ġst ead",
+ "Ġrest oration",
+ "Ġdon ated",
+ "Ġdel s",
+ "Ġc ensus",
+ "Ġdesper ately",
+ "worth y",
+ "H E",
+ "ĠSp a",
+ "ĠBry an",
+ "Ġh j",
+ "ĠR aw",
+ "ìķĦ ë",
+ "ĠCam era",
+ "Ġz ien",
+ "Ġst yl",
+ "ĠT W",
+ "ĠChe ese",
+ "bor ne",
+ "Ġob l",
+ "ĠAl ready",
+ "Ġunst able",
+ "Ġfl ames",
+ "p ost",
+ "H a",
+ "rom agn",
+ "ĠìĹ Ħë§Ī",
+ "d est",
+ "Ġkole j",
+ "Ġtempor arily",
+ "Ġdeterm ining",
+ "ĠGl ass",
+ "ÑĢ он",
+ "ol an",
+ "Ġdom inated",
+ "åĮ ĸ",
+ "__ __",
+ "ĠÙĩ ذا",
+ "ĠD ana",
+ "Ġdin heiro",
+ "a qu",
+ "ë ¯¼",
+ "ĠÃł s",
+ "ĠJo ey",
+ "ĠGr iff",
+ "Ġatt ain",
+ "Ġtrans itions",
+ "ĠLiter ally",
+ "ен д",
+ "ĠHa ven",
+ "Ġgrab bing",
+ "Ġcryst als",
+ "ĠFour th",
+ "Ġcand les",
+ "ĠÑģлÑĥÑĩ а",
+ "ric o",
+ "Ġ5 000",
+ "et to",
+ "Ġund o",
+ "Ġk to",
+ "Ġdi vert",
+ "Ġch ir",
+ "Ġper sec",
+ "Ġh iking",
+ "Ġannounce ments",
+ "çĶ ±",
+ "з Ñĭ",
+ "Ġa uc",
+ "Ġsystem ic",
+ "ĠR M",
+ "Ïĥ α",
+ "ĠÐĶ ж",
+ "Ġy ar",
+ "ĠW ard",
+ "Ġpiss ed",
+ "Ġcar n",
+ "Ġautonom ous",
+ "ãħİ ãħİ",
+ "so ver",
+ "æ²Ĵ éĮ¯",
+ "å¾Ī 好",
+ "Ġref lex",
+ "Ġgard ens",
+ "Ġd ated",
+ "ì ±",
+ "ami ÄĻ",
+ "Ġcontinu ity",
+ "Ġcitizens hip",
+ "Ġsch wer",
+ "Ġz ak",
+ "t able",
+ "ĠÑģ Ñĩ",
+ "è§ ģ",
+ "ĠÏĥ ε",
+ "Ġgener ates",
+ "구ë Ĥĺ",
+ "ö h",
+ "ó m",
+ "al am",
+ "ĠJUD Y",
+ "ĠB ug",
+ "Ġãģ ¦",
+ "Ġdr ones",
+ "Ġá gua",
+ "ac aks",
+ "æ ļ",
+ "ĠÐļ он",
+ "× ĸ×Ķ",
+ "Ġstri ve",
+ "ĠAl tern",
+ "Ġne arest",
+ "Ġpro yect",
+ "ter a",
+ "ĠASH LEY",
+ "Ġwor m",
+ "Ġre play",
+ "Ġt ara",
+ "ĠInd ians",
+ "ãĤ °",
+ "ica id",
+ "ĠìĪ ľ",
+ "Ġappe aling",
+ "ĠW es",
+ "Ġment ions",
+ "Ġдел е",
+ "Ġk w",
+ "Ġfrag ile",
+ "is z",
+ "k ów",
+ "h ang",
+ "col or",
+ "Ġpresident e",
+ "8 7",
+ "е ÑĦ",
+ "çĪ ¸",
+ "Ġдоб ав",
+ "ĠN elson",
+ "á fic",
+ "ĠMIC HAEL",
+ "Ġmechan ic",
+ "Ġmet res",
+ "Ġo czywiÅĽcie",
+ "ĠC ind",
+ "Ġog sÃ¥",
+ "Ġlands ca",
+ "AC E",
+ "Ġhead lines",
+ "Ġcat alyst",
+ "ĠC atch",
+ "ink les",
+ "Ġp ills",
+ "ord o",
+ "Ġimmig rant",
+ "Ġexam ination",
+ "Ġacc idents",
+ "zÄħ d",
+ "Ġqui ere",
+ "Ġne lla",
+ "Ġ6 7",
+ "Ġpass a",
+ "Ġsuper fic",
+ "ist or",
+ "Ġno v",
+ "ëĭ µ",
+ "Ġmand ate",
+ "is ons",
+ "ĠVirt ual",
+ "Ġsel ber",
+ "Ġcounsel ing",
+ "ĠN BA",
+ "Ġse pt",
+ "Ġbelie ver",
+ "Ġmar vel",
+ "ĠInte gr",
+ "Ġм Ñĸ",
+ "Ġor ph",
+ "Ġback ward",
+ "ĠGen eration",
+ "ĠP ict",
+ "ĠÑĤо ÑĤ",
+ "Ġtap i",
+ "pro chen",
+ "Ġhall way",
+ "ht e",
+ "ĠÛģ ÛĴ",
+ "ĠZ um",
+ "èĢģ 師",
+ "ach ment",
+ "iqu er",
+ "fol g",
+ "ĠEd die",
+ "ĠK il",
+ "Ġwell ness",
+ "st ock",
+ "è¼ ĥ",
+ "Ġka ç",
+ "Ġterror ism",
+ "Ġpo inter",
+ "O f",
+ "her ic",
+ "ĠUlt imately",
+ "Ġmes es",
+ "ĠTr ade",
+ "Ġp int",
+ "Ġtu ition",
+ "Ġdisag re",
+ "Ġê²Į ìŀĦ",
+ "Ġmanus cript",
+ "Ġro omm",
+ "Ġoutput s",
+ "е ÑĨи",
+ "Ġr ies",
+ "Ġsal ud",
+ "otz dem",
+ "Ġmass es",
+ "Ġby ÅĤa",
+ "Ġclear ing",
+ "Ġdisc ourse",
+ "ats on",
+ "Ġfold ed",
+ "ĠJ ar",
+ "ÙĦ Ùī",
+ "9 00",
+ "ĠÑĥ Ñģп",
+ "Ġprophe cy",
+ "Ġinterf ere",
+ "иÑħ од",
+ "๠Į",
+ "Ġth ri",
+ "Ġ×ŀ× ©",
+ "Ġlaz ım",
+ "Ġ199 2",
+ "Ġfut uro",
+ "Ġlock ing",
+ "Ġembar go",
+ "ĠNe ither",
+ "iv amente",
+ "ĠmÃ¥ ste",
+ "Ġm ik",
+ "Ġcollect or",
+ "еко ÑĤоÑĢ",
+ "ĠG and",
+ "Ġsent ir",
+ "ĠM ight",
+ "å¡ Ķ",
+ "Ġgan zen",
+ "U C",
+ "Ġrel ating",
+ "S D",
+ "Ġmos quito",
+ "G R",
+ "Ġho llow",
+ "âĺ ħ",
+ "ĠWalk er",
+ "Ġaffili ate",
+ "Ġduplic ate",
+ "н ем",
+ "Ġgra pe",
+ "ĠOrgan ization",
+ "Ġsy nt",
+ "J oe",
+ "Ġg eg",
+ "Ġreve aling",
+ "ĠEth an",
+ "out er",
+ "Ġy ay",
+ "é« Ķ",
+ "л аÑĢ",
+ "Ġreported ly",
+ "Ġihr er",
+ "Ġrecogn ise",
+ "Ġbum per",
+ "ĠR andy",
+ "ĠVen us",
+ "t les",
+ "Ġappet ite",
+ "Ġgluc ose",
+ "Ġch odzi",
+ "ĠFurther more",
+ "t ir",
+ "Ġcont a",
+ "Ġint uition",
+ "Ġalt itude",
+ "Ġch unks",
+ "ĠJosh ua",
+ "ıģ ım",
+ "ry lic",
+ "le ans",
+ "ĠíĶ ¼ë",
+ "L L",
+ "Q ue",
+ "Ġg or",
+ "Ġзна ÑĩиÑĤ",
+ "Ġpo ems",
+ "Ġexc el",
+ "Ġexpl ored",
+ "Ġpop ul",
+ "Ġinclus o",
+ "st ä",
+ "ĠG avin",
+ "all ing",
+ "ĠÏĦο ν",
+ "é ©",
+ "ar beit",
+ "ĠG as",
+ "Ġgl orious",
+ "rie ben",
+ "Ġsp am",
+ "Ġindo or",
+ "Ġthr ust",
+ "ĠA ld",
+ "ĠPri or",
+ "Ġon board",
+ "ãģł ãģķãģĦ",
+ "o ca",
+ "AS H",
+ "£ ł",
+ "ĠChrist ine",
+ "Ġdra wer",
+ "Ġno on",
+ "Ġìŀ ĺë",
+ "Ġperman ently",
+ "æ· ±",
+ "ĠнапÑĢ имеÑĢ",
+ "Ġpodcast s",
+ "era peut",
+ "pr it",
+ "Ġstain less",
+ "ĠÚ© ÛĴ",
+ "Ġfamil ia",
+ "ĠÑĢаз ÑĢ",
+ "un to",
+ "ĠÑģÑĤ ол",
+ "Ġh ä",
+ "ĠH ai",
+ "ĠP B",
+ "iz on",
+ "Ġkon nte",
+ "Ġbüy ük",
+ "Ġutil izar",
+ "Ú Ĩ",
+ "Ġaqu esta",
+ "Ġmix er",
+ "ud ent",
+ "лек Ñģ",
+ "ÅĤ u",
+ "ĠÑģиÑģÑĤ ем",
+ "Ġн оÑĢм",
+ "Ġfat al",
+ "Ġconsider ations",
+ "Ġvalid ation",
+ "Ġo li",
+ "Ġk ardeÅŁ",
+ "ĠGL ORIA",
+ "Ġp all",
+ "еÑģÑĤ е",
+ "Ġrect ang",
+ "Ġmed ieval",
+ "allah i",
+ "ast i",
+ "ĠSy rian",
+ "Ġshe ar",
+ "Ġdeb ug",
+ "ĠM ai",
+ "Ġknock ing",
+ "ĠLe x",
+ "ard an",
+ "ro v",
+ "Ġmem orial",
+ "æ° £",
+ "ook y",
+ "Ġstuff ed",
+ "Ġpass é",
+ "Ġw ig",
+ "Ĥ ł",
+ "Ġpróxim a",
+ "Ġ199 1",
+ "Ġм еждÑĥ",
+ "Ġnuest ros",
+ "ĠBe ast",
+ "Ġsm o",
+ "atch ed",
+ "olog ia",
+ "Ġм од",
+ "Ġge e",
+ "Ġconcept ual",
+ "ĠÃ ´",
+ "Ġdecre ases",
+ "Ġquer ies",
+ "олÑĮ ÑĪ",
+ "ĠA part",
+ "Ġex empl",
+ "å± ±",
+ "Ġfl ed",
+ "ĠO FF",
+ "gg ak",
+ "Ġbe ad",
+ "h ir",
+ "l ies",
+ "ĠClear ly",
+ "ı lar",
+ "Ġch ess",
+ "Ġwhich ever",
+ "Ġ9 6",
+ "Ạ±",
+ "Ġrespect s",
+ "Ġм оÑĢ",
+ "Ġorgan ism",
+ "Ġgrand pa",
+ "ĠV ie",
+ "è·Ł ä½ł",
+ "Ġflo oding",
+ "Ġupgrad ed",
+ "Ñij ÑĢ",
+ "Ġcheek s",
+ "Ġcon quer",
+ "Ġstub born",
+ "Ġpuzz les",
+ "Ġau ction",
+ "Ġre lying",
+ "ĠPRO F",
+ "ĠEs per",
+ "ĠÐľ У",
+ "Ġhy pe",
+ "Ġposs ibil",
+ "Ġimp rison",
+ "ĠEr n",
+ "ìĹĪ ìĬµëĭĪëĭ¤",
+ "Ġenv ie",
+ "Ġresur rection",
+ "ä¸į è¡Į",
+ "Ġs per",
+ "ĠVenez uela",
+ "s om",
+ "Ġìŀł ê¹",
+ "Ġnouve lle",
+ "Ġclos es",
+ "Ġ19 40",
+ "Ġqu a",
+ "ĠJ ared",
+ "ĠP ir",
+ "Ġind e",
+ "Ġscr ub",
+ "uk u",
+ "Ġrequ iring",
+ "Ġв ами",
+ "Ġconsider able",
+ "åIJ Ľ",
+ "il ia",
+ "Ġin ne",
+ "Ġmein em",
+ "Ġhard ship",
+ "Ġtra ps",
+ "ro c",
+ "ĠìĦ ¤ë",
+ "Ġresearch ing",
+ "ĠMarg aret",
+ "Ġpen ny",
+ "Ġbı rak",
+ "Ñij л",
+ "Ġw ool",
+ "Ġr het",
+ "Ġflat ten",
+ "ç ĩ",
+ "à¹Ģภ£",
+ "Ġp ied",
+ "ĠCh ap",
+ "Ġunder m",
+ "Ġf ret",
+ "Ġcrash ed",
+ "ĠFra uen",
+ "Ø° Ùĩ",
+ "iv an",
+ "Ġliter ary",
+ "late go",
+ "Ġsp äter",
+ "Ġsimilar ities",
+ "â Ĩ",
+ "ĠCor on",
+ "ĠC reek",
+ "Ġboss es",
+ "Ġaccompan ied",
+ "Ġdeb ates",
+ "Ġassemb led",
+ "ĠÃ ģ",
+ "ĠV ai",
+ "Ġtr act",
+ "Ġsimple ment",
+ "ĠAr in",
+ "Ġvulner ability",
+ "Ġhorm one",
+ "I EL",
+ "OO K",
+ "Ġrel ay",
+ "ĠAnd rea",
+ "r il",
+ "Ġnecess ity",
+ "aceut ical",
+ "Ñİ Ñī",
+ "ous ing",
+ "nah men",
+ "Ġfoot print",
+ "m ap",
+ "ĠT ier",
+ "ann ya",
+ "int end",
+ "åĸ ®",
+ "å ¢",
+ "Ġdecor ate",
+ "Ġzomb ies",
+ "ĠHy d",
+ "ĠSu z",
+ "Ġcampus es",
+ "ĠE mb",
+ "Ġthr ottle",
+ "Ġad min",
+ "Ġop ortun",
+ "Ġmir rors",
+ "Ġident ities",
+ "ĠCl in",
+ "Ġë¹ Ħë",
+ "á¹ £",
+ "ĠO tt",
+ "Ġbl ues",
+ "Ġimpress ions",
+ "- ,",
+ "Ġv ague",
+ "a fe",
+ "Ġinfer ior",
+ "eral d",
+ "Ġmedic ines",
+ "Ġpre gunta",
+ "os ely",
+ "Ġt élé",
+ "ĠMon th",
+ "ĠLe aders",
+ "ĠEgypt ian",
+ "Ġr ation",
+ "k ers",
+ "he its",
+ "Ġre cht",
+ "P lay",
+ "Ġe g",
+ "Ġpoll s",
+ "ĠWOO DR",
+ "Ġsl ots",
+ "j am",
+ "B oth",
+ "ĠR at",
+ "ÑĢ аж",
+ "ĠBr ight",
+ "ä¸Ģ å®ļ",
+ "á»ij i",
+ "ur ious",
+ "Ġsing ers",
+ "Ġlo gin",
+ "Ġt êm",
+ "l ation",
+ "ĠM um",
+ "Æ°á»Ŀ ng",
+ "ĠEd itor",
+ "åIJ ij",
+ "Ġinnov ations",
+ "h ave",
+ "ĠS ek",
+ "Ġwe aker",
+ "ĠG ob",
+ "A fter",
+ "´ì §Ģ",
+ "Ġ문 ìłľ",
+ "ãĥ¼ ãĥ¼",
+ "Ġdisad vantage",
+ "ç¢ º",
+ "Ġg aze",
+ "ĠM ack",
+ "Ïģ ί",
+ "ĠK iss",
+ "ĠH olo",
+ "ĠBir th",
+ "iz i",
+ "b ab",
+ "ä¿ Ŀ",
+ "ìĭľ ê³ł",
+ "д еÑĢж",
+ "Ġsqu at",
+ "кÑĥ Ñģ",
+ "un i",
+ "ĠComm e",
+ "ĠWOODR UFF",
+ "ĠChampions hip",
+ "Ġwel che",
+ "ĠY outh",
+ "z em",
+ "Ġod pow",
+ "Ġpersist ent",
+ "r ut",
+ "ìĶ ©",
+ "íĸ ¥",
+ "la ir",
+ "ik u",
+ "Ġvend or",
+ "Ġch úng",
+ "Ġfinan ci",
+ "Ġover ly",
+ "â u",
+ "Ġgl uten",
+ "Ġ18 00",
+ "Ġdiv isions",
+ "Ġciud ad",
+ "Ġob ed",
+ "Ġwar um",
+ "Ġe her",
+ "Ġel im",
+ "ĠÐĴ о",
+ "Ġpeu vent",
+ "ĠW anna",
+ "Ġattend ance",
+ "Ġassess ments",
+ "ĠB og",
+ "Ġimag ery",
+ "Ġcollect ively",
+ "Ġinform al",
+ "ĠSch we",
+ "Ġde utlich",
+ "ĠCh el",
+ "ĠP E",
+ "ow ed",
+ "Ġb anner",
+ "Ġshel ves",
+ "ĠRet urn",
+ "æĭ ¿",
+ "LAUGH S",
+ "Ġcongrat ulate",
+ "ĠNor way",
+ "Ġd well",
+ "ĠCarib bean",
+ "Ġnorm s",
+ "ĠAn imal",
+ "ĠValent ine",
+ "Ġext ending",
+ "ĠV ou",
+ "or r",
+ "ĠCh eng",
+ "Â ¡",
+ "ĠдоÑĢ ог",
+ "Ġve g",
+ "Ġh Ã¥",
+ "ĠX in",
+ "Ġì¹ ´ë",
+ "em et",
+ "Ġhyp oth",
+ "Ġinteress ante",
+ "ric es",
+ "I Z",
+ "ĠUS D",
+ "Ġrun ner",
+ "ĠB ag",
+ "Ġê ½",
+ "Ġcomeç ar",
+ "Ġpig s",
+ "Ġweakness es",
+ "P h",
+ "ĠVi ol",
+ "ä¸į çĶ¨",
+ "Ġdra gging",
+ "ĠAqu ÃŃ",
+ "ĠCS S",
+ "Ġmill imeters",
+ "Ġest ás",
+ "Ġac ute",
+ "Ġde jar",
+ "i ÄŁ",
+ "ob ra",
+ "L ove",
+ "Ġsil k",
+ "** **",
+ "Ġjo ins",
+ "Ġpro l",
+ "Ġê°IJìĤ¬ íķ©ëĭĪëĭ¤",
+ "æĶ ¯",
+ "ØŃ Ø¯",
+ "agh etti",
+ "än ner",
+ "Ġstr ang",
+ "Ġdoub led",
+ "Ġdescri ptions",
+ "Ġst ellen",
+ "Ġpart i",
+ "ç« ĭ",
+ "² Ħë",
+ "Ġö ÄŁ",
+ "ig hing",
+ "Ġang ular",
+ "Ġnat uur",
+ "ĠSh el",
+ "Æ° Æ¡",
+ "Ġr ays",
+ "Ġse per",
+ "st art",
+ "v ised",
+ "Ġrush ed",
+ "Ġinternation ally",
+ "Ġnive l",
+ "Ġbox ing",
+ "fall en",
+ "á»ij c",
+ "Ġse inen",
+ "plic ity",
+ "Ġcarb oh",
+ "ĠTra vis",
+ "us o",
+ "ĠPh ase",
+ "Ġactiv ation",
+ "Ġop io",
+ "· ¨",
+ "Ġdecre ased",
+ "C ar",
+ "Ġbund le",
+ "Ġexp end",
+ "orm al",
+ "Ġadjac ent",
+ "Ġme e",
+ "ĠоÑĢ г",
+ "Ġtrans cript",
+ "ĠLang uage",
+ "G S",
+ "è§ ī",
+ "Ġse ul",
+ "Ãł nh",
+ "Ġn ya",
+ "ning s",
+ "Ġìĭ ľë",
+ "ĠëĶ°ë Ŀ¼",
+ "ĠA gr",
+ "ÃŃ d",
+ "çķ Ļ",
+ "Ġab y",
+ "ĠNe o",
+ "ıyor uz",
+ "ĠThink ing",
+ "a ime",
+ "Ġv ite",
+ "Ġtrav és",
+ "Ġ×ij× ¢",
+ "Ġм ед",
+ "O ur",
+ "ho ot",
+ "Ġl iner",
+ "ĠP izza",
+ "Ġhy g",
+ "fl ies",
+ "ĠContin ue",
+ "Ġdent al",
+ "ĠT ib",
+ "Ġreg ulate",
+ "lie ÃŁ",
+ "AL K",
+ "ĠTa e",
+ "ê¸ ¸",
+ "ĠBre xit",
+ "ĠG ut",
+ "Ġoccup ation",
+ "Ġz robi",
+ "â m",
+ "Ġwh isk",
+ "ä¸ĸ çķĮ",
+ "Ġkans ke",
+ "om on",
+ "ro be",
+ "Ġwar fare",
+ "Ġth á»ĥ",
+ "Ġjak i",
+ "Ġstro kes",
+ "Ġpe as",
+ "ĠDam it",
+ "H AN",
+ "Ġinter ference",
+ "Ġмин ÑĥÑĤ",
+ "N ER",
+ "out ing",
+ "Ġtext ures",
+ "Ł ī",
+ "ow i",
+ "Ġíķ Ļ",
+ "Ġd ens",
+ "Ġprotagon ist",
+ "än n",
+ "Ġgod dess",
+ "Ġwoll te",
+ "ij o",
+ "ĠWo che",
+ "ĠV PN",
+ "st ory",
+ "Ġkind erg",
+ "Ġfun nel",
+ "Ġdist ress",
+ "ноÑģÑĤÑĮ Ñİ",
+ "Ġno isy",
+ "ĠпÑĢод олж",
+ "Ġdar an",
+ "Ġenzy me",
+ "л ож",
+ "Ġm ute",
+ "Ġd war",
+ "Ġا س",
+ "Ġkom pl",
+ "Ġmer it",
+ "Ġf osse",
+ "ĠDr ink",
+ "Ġfor a",
+ "Ġw ohl",
+ "Ġbree ze",
+ "Ġsan it",
+ "Ġdr in",
+ "ĠìĿ´ê±° ëĬĶ",
+ "Ġ6 2",
+ "Ġì° ¨ë",
+ "aby tes",
+ "Ġde eds",
+ "ĠÐ ¹",
+ "i ème",
+ "igg ling",
+ "Ġ\" '",
+ "ĠÑĩа ÑģÑĤÑĮ",
+ "ĠAns wer",
+ "Ġev angel",
+ "Ġ10 80",
+ "ĠVis it",
+ "ic ient",
+ "Ġreli ability",
+ "Ñİ ÑģÑĮ",
+ "ĠEar lier",
+ "Ġf id",
+ "çŃī ä¸Ģä¸ĭ",
+ "Ġslee ves",
+ "iy orsun",
+ "Ġb ib",
+ "ĠAcc ount",
+ "Ñı ли",
+ "cipl inary",
+ "z as",
+ "Ġб еÑĢ",
+ "Ġneck lace",
+ "Ġbl ender",
+ "ĠPhill ips",
+ "et i",
+ "ĠJup iter",
+ "Ġprov oc",
+ "ĠYe ars",
+ "ent re",
+ "ac io",
+ "Ġk ü",
+ "Ġanten na",
+ "Ġnovel s",
+ "Ġf art",
+ "ĠS ugar",
+ "ĠJud y",
+ "Ġcollaps ed",
+ "ç °",
+ "rit is",
+ "Ġìĥģ íĻ©",
+ "ÐĹ Ð«",
+ "ĠVer f",
+ "rane an",
+ "ere um",
+ "ĠTar get",
+ "Ġ8 8",
+ "ĠÐĺ з",
+ "ide o",
+ "Ġreg ression",
+ "ì¶ ľ",
+ "Ġmów i",
+ "Ġstud ios",
+ "i ens",
+ "ip h",
+ "Ġfr ying",
+ "Ġfasc inated",
+ "ĠW ah",
+ "b ucks",
+ "m aya",
+ "ĠSat urn",
+ "ĠM ommy",
+ "Ġrating s",
+ "Ġaut umn",
+ "Æ°Æ¡ ng",
+ "Ġlos er",
+ "Ġcent ro",
+ "érie ur",
+ "ĠF old",
+ "Ġsuper visor",
+ "ĠNo bel",
+ "Ġunder est",
+ "ob ia",
+ "Ġв ÑģÑı",
+ "Ġver w",
+ "Ġfu els",
+ "Ġartif acts",
+ "Ġë¶ Ļ",
+ "ĠAut om",
+ "çļĦ æĺ¯",
+ "Û Ķ",
+ "×ķ× ¡",
+ "Ġih nen",
+ "Ġ5 9",
+ "ound ing",
+ "еÑĢ Ñĭ",
+ "in ars",
+ "ch ant",
+ "Ġadd icted",
+ "Ġexplos ive",
+ "Ġdisp ers",
+ "â ĸĪ",
+ "ax is",
+ "AR Y",
+ "Ġl um",
+ "ĠÑĥ Ñģл",
+ "ĠØ Į",
+ "Ġru pees",
+ "ĠPe arl",
+ "c amp",
+ "t v",
+ "oy a",
+ "Ġconclud es",
+ "Ġcoll ision",
+ "Ġbuy er",
+ "Ġplay ground",
+ "Ġspr ings",
+ "Ġfemin ine",
+ "ĠR as",
+ "Ġincar cer",
+ "íĹ ĺ",
+ "Ġdial ect",
+ "Ġclos ure",
+ "Ġchat ting",
+ "Ġb abe",
+ "Ġspot light",
+ "Ġnot ation",
+ "è· ¯",
+ "St ar",
+ "i ão",
+ "Ġt ête",
+ "Ġt ide",
+ "Ġjun to",
+ "Ġsen ator",
+ "Ð ¥",
+ "Ġexcus es",
+ "Ġbl ink",
+ "Ġadm ission",
+ "ĠL ily",
+ "Ñĭ ми",
+ "Ġam igo",
+ "Ġl ust",
+ "ëĭ ¬",
+ "Ġam ino",
+ "äºĭ æĥħ",
+ "Ġconsult ant",
+ "ĠElect ric",
+ "Ġëħ¸ë ŀĺ",
+ "uj ah",
+ "Ġshoot er",
+ "icht en",
+ "ĠUkrain ian",
+ "Ġaim s",
+ "ĠEnter tain",
+ "Ġmir acles",
+ "èŃ °",
+ "Ġze igen",
+ "Ġl am",
+ "Ġres s",
+ "ĠJ ill",
+ "yl an",
+ "Ġro ok",
+ "Ġh aya",
+ "Ġpass port",
+ "ad ata",
+ "Ġju icy",
+ "con f",
+ "л ей",
+ "ĠS z",
+ "Ġinter cept",
+ "ãģĤãĤĬãģĮãģ¨ãģĨ ãģĶãģĸ",
+ "ĠTe ams",
+ "Ġmak en",
+ "ir rel",
+ "ĠLI KE",
+ "áºŃ y",
+ "êµ °",
+ "Ġshort age",
+ "Ġparad igm",
+ "Ġpap el",
+ "Ġast ero",
+ "ãģ¾ ãģŁ",
+ "Ġsoll en",
+ "ĠMic key",
+ "ĠOr leans",
+ "Ġchol esterol",
+ "Ġgo ose",
+ "ÑĨи Ñİ",
+ "ãģĤ ãĤĭ",
+ "ĠF L",
+ "Ġгол ов",
+ "Ġtrib ute",
+ "ĠG am",
+ "Ġé videmment",
+ "Ñı Ñħ",
+ "å® ŀ",
+ "çĶ °",
+ "Ġin appropri",
+ "uh an",
+ "Ġorganiz ational",
+ "ail ed",
+ "Ġend ure",
+ "Ġ7 6",
+ "Ġshot gun",
+ "Ġliv re",
+ "Ġsu ited",
+ "Ġwarm th",
+ "ĠS IM",
+ "Ġenv ision",
+ "Ġde grad",
+ "î ne",
+ "La ughing",
+ "ĠWho ever",
+ "ĠBuddh ism",
+ "Ġspr inkle",
+ "ceÄŁ iz",
+ "Ġru ins",
+ "Ġst arch",
+ "ĠHer z",
+ "Ġinjust ice",
+ "Ġhum idity",
+ "ожал Ñĥй",
+ "ĠOb ject",
+ "ĠI gn",
+ "ĠEx am",
+ "ig ers",
+ "Ġth ou",
+ "ĠSo y",
+ "iv as",
+ "Ġpol es",
+ "m ath",
+ "Ġв ним",
+ "ING ING",
+ "ed ral",
+ "Ġexpl or",
+ "Ġroast ed",
+ "Ġcraw l",
+ "Ġco ff",
+ "Ġan om",
+ "Ġw ij",
+ "Ġimpro ves",
+ "Ġtreat y",
+ "Ġdiscover ing",
+ "Ġstat ute",
+ "Ġmerc ado",
+ "ĠÑģ ил",
+ "Ġint el",
+ "ĠChance llor",
+ "ĠMed icaid",
+ "ug i",
+ "Ġver bal",
+ "Ġd ön",
+ "Ġscript ure",
+ "Ġit eration",
+ "ek s",
+ "ĠOx ford",
+ "Ġw äh",
+ "ĠV ad",
+ "ĠA K",
+ "ĠìķĦ ìĿ´ë",
+ "Ġi ets",
+ "Ġneed les",
+ "Ùĥ Ùħ",
+ "Ġpas ado",
+ "Ġalbum s",
+ "Ġye a",
+ "et zen",
+ "Ħë ıĦ",
+ "Ġdeterm ines",
+ "Ġthe e",
+ "ĠPlay ing",
+ "är t",
+ "Ġ× ¦",
+ "c led",
+ "Ġdown ward",
+ "al one",
+ "Ġsol u",
+ "Ġpart ition",
+ "Ġw z",
+ "d d",
+ "Ġpesso al",
+ "å ª½",
+ "Ġfact ories",
+ "Ġble ibt",
+ "ม า",
+ "als a",
+ "ĠNF L",
+ "Ġfu era",
+ "Ġres erved",
+ "ĠE arn",
+ "Ġhel t",
+ "Ġshort cut",
+ "Ġconvin cing",
+ "sp ace",
+ "Ġen force",
+ "Ġc ores",
+ "Ġe fter",
+ "Ġrecess ion",
+ "x ico",
+ "Ġprop osition",
+ "ar ians",
+ "rop ol",
+ "Ġëª °ë",
+ "ĠÎ ľ",
+ "ĠìļĶ ì¦ĺ",
+ "Ġactiv ist",
+ "Ġconv iction",
+ "Ġz ab",
+ "Ġcancel ed",
+ "ÑĤо Ñĩно",
+ "ĠÎ ®",
+ "éĢĻ樣 åŃIJ",
+ "n ite",
+ "Ġfund ra",
+ "buz zer",
+ "ел о",
+ "ic ations",
+ "Ġz ona",
+ "Ġte ens",
+ "Ġmethod ology",
+ "Ġì¤ij ìļĶ",
+ "th an",
+ "ĠU l",
+ "ĠG rey",
+ "Ġh og",
+ "IN K",
+ "ĠS ung",
+ "ĠC laud",
+ "ĠCN N",
+ "Ġdel ivers",
+ "al in",
+ "ĠAd obe",
+ "ot he",
+ "ĠDes wegen",
+ "ภ³",
+ "Ġwer de",
+ "Ġgre ase",
+ "Ġup grades",
+ "ĠFin land",
+ "ac cept",
+ "Ġinter rog",
+ "be e",
+ "Ġãģ «",
+ "Ġpre de",
+ "ĠN ep",
+ "ĠCam bridge",
+ "Ġgraph s",
+ "Ġha unted",
+ "Ñģ ем",
+ "æ §",
+ "åħ ĭ",
+ "S ome",
+ "ĠM all",
+ "Ġrehears al",
+ "ĠUr ban",
+ "ĠL ag",
+ "Ġn im",
+ "ê° ķ",
+ "Ġposition ed",
+ "Ġavo ided",
+ "EM A",
+ "Ġlleg ar",
+ "Ġráp ido",
+ "Ġgou vern",
+ "Ġh ing",
+ "Ġdeal er",
+ "Ġreform s",
+ "Ġfat ty",
+ "к ол",
+ "ĠA ce",
+ "Ġne p",
+ "Ġì² Ń",
+ "Ġcomput ation",
+ "ĠSt ream",
+ "bour ne",
+ "t ur",
+ "P or",
+ "Ġsleep y",
+ "Ġbang et",
+ "ãģĤ ãģ®",
+ "Ġwe ighs",
+ "Ġble iben",
+ "ĠG ren",
+ "Ġun ions",
+ "Ġêµ IJ",
+ "Ġap render",
+ "uit ar",
+ "ĠJ est",
+ "um ing",
+ "ĠPlay er",
+ "ĠExt rem",
+ "Ġinteg er",
+ "аÑĩ е",
+ "Ġconcert s",
+ "×ķ× Ľ",
+ "Ġtro chÄĻ",
+ "ĠRe pe",
+ "éĩį è¦ģ",
+ "๠Ĥ",
+ "ż en",
+ "Ġsound ing",
+ "Ġan onymous",
+ "Ġex ca",
+ "ĠIran ian",
+ "Ġener getic",
+ "Ġw ives",
+ "ĠÑĨ веÑĤ",
+ "Ġa is",
+ "ãģĭ ãģª",
+ "Ġsud ah",
+ "Ġunder wear",
+ "Ġcrunch y",
+ "ĠP ain",
+ "Ġger çek",
+ "red ict",
+ "Ġm isma",
+ "Ñĸ ÑĤ",
+ "Ġsurv iving",
+ "ÎŃ ÏĤ",
+ "Ġparticip ant",
+ "ĠH essen",
+ "ári as",
+ "Ġsub way",
+ "ist ä",
+ "Ġcor al",
+ "Ġmar ijuana",
+ "ĠMem orial",
+ "ÑĪ ий",
+ "ri z",
+ "Ġsatell ites",
+ "Ġle ase",
+ "ĠCam eron",
+ "um ph",
+ "Ġclass mates",
+ "äh än",
+ "ÑģÑĤв е",
+ "Ġh ue",
+ "ĵ¤ ìĿĦ",
+ "Ġproport ional",
+ "Ġn oss",
+ "Ġl aps",
+ "r å",
+ "Ġbit coin",
+ "ÐĹЫ ÐļÐIJ",
+ "Ġì¶ ©",
+ "ĠÙĦ ÙĦ",
+ "ĠM ort",
+ "ĠEs p",
+ "arn os",
+ "ĠÑģказ ал",
+ "Ġä nd",
+ "åħ Ħ",
+ "×Ļ ×Ļ×Ŀ",
+ "ĠGe b",
+ "ge hen",
+ "I naudible",
+ "bor ough",
+ "ÑĦ ÑĦ",
+ "Ġfellow ship",
+ "ĠP aper",
+ "Ġcur ved",
+ "ĠGE OR",
+ "Ġcalcul ator",
+ "ĠCat al",
+ "ĠvÃł o",
+ "Ġby pass",
+ "л еÑĤ",
+ "à ³",
+ "tr ans",
+ "ren cies",
+ "ì ¡Į",
+ "ig ent",
+ "Ġtast ed",
+ "Ġo ceans",
+ "u ft",
+ "erv ice",
+ "ĠÐľÐ£ ÐĹЫÐļÐIJ",
+ "ĠClass ic",
+ "Ġrespect ively",
+ "~ )",
+ "î tre",
+ "ĠN ash",
+ "Ġz it",
+ "ĠìĽ ĥ",
+ "ĠëĨ Ĵ",
+ "qu ote",
+ "ĠUn s",
+ "Ġt ac",
+ "Ġpro ves",
+ "ĠPort land",
+ "b ly",
+ "Ġ ere",
+ "ì¶ Ķ",
+ "Ġépo ca",
+ "ĠÑĤÑĭ ÑģÑıÑĩ",
+ "7 6",
+ "Ġhad e",
+ "ĠF ro",
+ "ĠpolÃŃt ica",
+ "t ag",
+ "Ġíķ Ń",
+ "Ġsch ö",
+ "are tt",
+ "Ġprov isions",
+ "Ġmot ors",
+ "Ġimag ing",
+ "Ġdo k",
+ "ul ously",
+ "Ġme ille",
+ "çİ° åľ¨",
+ "ë IJ",
+ "ĠIS O",
+ "ĠST EM",
+ "ĠBow l",
+ "Ġto wers",
+ "ĠE e",
+ "ĠPerform ance",
+ "Ġlo in",
+ "cuss ion",
+ "Ġcoast al",
+ "ial e",
+ "com pass",
+ "Ġspell s",
+ "Ġdisappoint ing",
+ "Ġë²Ī 째",
+ "E ER",
+ "Ġvers atile",
+ "as ury",
+ "Ġen fin",
+ "Ġdown side",
+ "Ġgu iding",
+ "ĠاÙĦ ÙĤ",
+ "Ġnin ety",
+ "char ged",
+ "ĠF ans",
+ "Ġphilosoph ical",
+ "Ġg arn",
+ "ĠmÃ¥ nga",
+ "Ġwilling ness",
+ "Ġport ions",
+ "ab en",
+ "Ġ ï",
+ "Â ¿",
+ "ra ul",
+ "Ġspr int",
+ "if en",
+ "ıy la",
+ "Ġк Ñĥп",
+ "ãģı ãģłãģķãģĦ",
+ "Ġens uite",
+ "ĠCap itol",
+ "Ġ6 3",
+ "ĠговоÑĢ иÑĤ",
+ "Ġappoint ments",
+ "æī ¾",
+ "omi ast",
+ "Ġcare g",
+ "Ġpubl isher",
+ "Ġher aus",
+ "Ġε ί",
+ "ĠV S",
+ "ãģĿ ãģĹãģ¦",
+ "ä¸Ń åħ±",
+ "Ġsacrific es",
+ "th ird",
+ "Ġhuman itarian",
+ "ĠëĤ ´ì",
+ "im on",
+ "Ġine qu",
+ "Ġz ob",
+ "Ġcomfort ably",
+ "ĠD inge",
+ "Ġcancell ed",
+ "ĠPS AKI",
+ "ĠRob inson",
+ "Ġfin s",
+ ") ?",
+ "ĠHist or",
+ "ĠÑĩеловек а",
+ "Ġt bsp",
+ "te xt",
+ "k im",
+ "Ġupd ating",
+ "Ġgel d",
+ "f eld",
+ "ı ¼",
+ "Ġm ä",
+ "Ġcaf é",
+ "Ö Ģ",
+ "ĠS ri",
+ "ĠReg ion",
+ "ĠH ahaha",
+ "Ġfin ances",
+ "ĠاÙĦØ ´",
+ "Ġb unk",
+ "ru k",
+ "ha ft",
+ "Ġlater al",
+ "Ġext ensions",
+ "ĠìķĦ ìĿ´",
+ "Ġdefin ite",
+ "ĠZ hao",
+ "ĠLu is",
+ "st y",
+ "Ġcas os",
+ "ĠK lim",
+ "Ġ199 3",
+ "Ġreal ization",
+ "Ġhistor ian",
+ "Ġcrack ed",
+ "ëĤ ´",
+ "Ġsyst ème",
+ "ĠC IA",
+ "ĠÑĤ во",
+ "osp heric",
+ "Ġfle e",
+ "Ġr ất",
+ "ĠRegard less",
+ "Ġrel uct",
+ "Ġtim ely",
+ "ĠJul ian",
+ "G M",
+ "é Ĵ",
+ "ad ura",
+ "é£ Ł",
+ "Ġdress es",
+ "çģ £",
+ "ĠëĶ Ķ",
+ "Ġnom inated",
+ "Ġadvoc ates",
+ "ym ph",
+ "Ġrecord ings",
+ "Ġdev iation",
+ "Ġpriorit ize",
+ "Ġspir al",
+ "ĠYOU R",
+ "Ġtransp ose",
+ "amp oo",
+ "ĠìĽIJë ŀĺ",
+ "ĠV ision",
+ "Ġpol ite",
+ "Ġha mb",
+ "ĠPat ient",
+ "æ¯Ķ è¼ĥ",
+ "íģ ¬ë",
+ "Ġs ia",
+ "Ġê³ ³",
+ "Ġž e",
+ "è§ Ģ",
+ "Ġsuper market",
+ "ë ¹",
+ "ĠS ierra",
+ "Ġgr illed",
+ "ĠUp on",
+ "Ġabs ent",
+ "Ġme c",
+ "ĠAp ollo",
+ "Ġp unk",
+ "ĠPa ÅĦst",
+ "ĠÑģв ой",
+ "Ġê±° 기",
+ "G irl",
+ "Ġskin ny",
+ "ĠPrem ier",
+ "Ġterrit ories",
+ "Ġli ability",
+ "Ġj erk",
+ "r atic",
+ "Ġdan cers",
+ "ĠÑĥ ÑĢов",
+ "Ġê´ Ģë",
+ "on ly",
+ "ĠSt u",
+ "Ġske leton",
+ "ĠëŃ IJë",
+ "Ġзак он",
+ "ı kt",
+ "ĠMI KE",
+ "Ġl ö",
+ "m ie",
+ "Ġre iter",
+ "ãģĵãĤĮ ãģ¯",
+ "ĠKoll eg",
+ "ĠAd ams",
+ "lich er",
+ "Ġçoc uk",
+ "Ñı г",
+ "Ġbl ush",
+ "Ġsun shine",
+ "Ġe z",
+ "ĠDev il",
+ "Ġê¸ ¸",
+ "Ġãģ Ĭ",
+ "ad d",
+ "Ġlic ensed",
+ "Ġv inyl",
+ "ĠC zech",
+ "im ag",
+ "Ġcrack ing",
+ "Ġì º",
+ "Ġud ah",
+ "Ġs ommes",
+ "Ġìĸ¼ êµ",
+ "wa Äĩ",
+ "Ġf res",
+ "åij ½",
+ "ĠWal mart",
+ "ĠТ епеÑĢÑĮ",
+ "at isf",
+ "C I",
+ "l ang",
+ "Ġdiff usion",
+ "çĶ ·",
+ "Ġsom os",
+ "ĠM akes",
+ "æĪij æĥ³",
+ "ĠRick y",
+ "Ġmuch a",
+ "íķ ¨",
+ "Ġhorse power",
+ "as ia",
+ "Ġfib ers",
+ "Ġ erm",
+ "Ñģ кие",
+ "Ġjest e",
+ "Ġfire fight",
+ "Ġcu isine",
+ "Ġbesond ers",
+ "d ig",
+ "Ġì¢ ħ",
+ "ĠÑĥ ж",
+ "Ġtr acing",
+ "Ġcertain s",
+ "ĠApp ly",
+ "Ñĭв аÑĤÑĮ",
+ "ç Į",
+ "Ġbr u",
+ "ĠY ES",
+ "ĠB ai",
+ "ĠD it",
+ "ĠB is",
+ "Ġun le",
+ "ÑģÑĤа ÑĤоÑĩно",
+ "ĠAw ak",
+ ".. \"",
+ "Ġ12 5",
+ "Ġroot ed",
+ "Ġcaut ious",
+ "con st",
+ "Ġorchest ra",
+ "çľ ¼",
+ "Ġвн ÑĥÑĤ",
+ "Ġquel qu",
+ "ĠоÑĤ веÑĤ",
+ "ĠMet hod",
+ "ì¹ ľ",
+ "Ġμ αÏĤ",
+ "l ü",
+ "ĠìķĦ ê¹Į",
+ "Ġn aming",
+ "C har",
+ "ĠS icher",
+ "Ġprivile ged",
+ "ĠF ly",
+ "Ġãģ ĭ",
+ "áºŃ t",
+ "Ġadv ances",
+ "ĠZel da",
+ "Ġand ra",
+ "Ġgr inding",
+ "ĠEd ition",
+ "p f",
+ "Ġwarri ors",
+ "Ġh edge",
+ "Ġuns eren",
+ "ĠÑģÑİ Ð´Ð°",
+ "el iness",
+ "Ġpersonal ities",
+ "Ġf ö",
+ "' M",
+ "ĠÑĤо Ñĩно",
+ "Ġsh ipped",
+ "Ġmete or",
+ "Ġsurround ings",
+ "ĠF ill",
+ "u esta",
+ "ĠPerson al",
+ "ĠAll e",
+ "OR T",
+ "ä¹ ħ",
+ "ĠS che",
+ "V I",
+ "Ġcompar able",
+ "dam n",
+ "Ġd itch",
+ "Y AN",
+ "ism us",
+ "Ġpick up",
+ "Ġd ak",
+ "ĠE P",
+ "b est",
+ "ĠS ue",
+ "äll t",
+ "Ġpop corn",
+ "Ġfold ing",
+ "h ome",
+ "ив аеÑĤ",
+ "å·² ç¶ĵ",
+ "Ġan not",
+ "ch uck",
+ "Ġfier ce",
+ "Ġdam aging",
+ "Ġfl op",
+ "Ġpas ar",
+ "Ġre ef",
+ "ĠÑģво ей",
+ "Ġz oo",
+ "o vers",
+ "j ets",
+ "Ġpr ès",
+ "ĠSil icon",
+ "te ok",
+ "ĠS eth",
+ "at amente",
+ "Ġtransm itted",
+ "Ġrepl icate",
+ "Ġsl im",
+ "ĠC ream",
+ "æĦŁ ãģĺ",
+ "Ġside walk",
+ "ìĪ ĺë",
+ "Ġжиз нÑĮ",
+ "ĠMon ica",
+ "ä¾Ĩ äºĨ",
+ "Ġcop ied",
+ "ĠTer ra",
+ "ist ent",
+ "ç³ »",
+ "Ġо но",
+ "Ġwh ale",
+ "ĠW ITH",
+ "л ÑĥÑĪ",
+ "å½± çīĩ",
+ "ĠE en",
+ "ĠÑģво и",
+ "Ġord in",
+ "Ġpl ural",
+ "Ġsp okes",
+ "Ġdisp ute",
+ "Ġsens ible",
+ "Ġpre aching",
+ "Ġktó rzy",
+ "pt ed",
+ "av ier",
+ "Ġpist ol",
+ "ĠTap i",
+ "Ġ ÅĤ",
+ "ff ff",
+ "Ġac rylic",
+ "Ġignor ance",
+ "ĠZ iel",
+ "r ans",
+ "Ġweld ing",
+ "m id",
+ "æĪij ä¸į",
+ "Ġзан им",
+ "Ġlan es",
+ "Ġmin es",
+ "Ġmom s",
+ "×ķ× Ĺ",
+ "ĠCham ber",
+ "t ier",
+ "Ġmod est",
+ "ĠìĹ¬ê¸° ìĦľ",
+ "Ġun as",
+ "Ġw rench",
+ "hand ed",
+ "Ġsatur ated",
+ "ĠF ang",
+ "ĠCommission er",
+ "ठ°",
+ "Ġ× ĸ",
+ "ĠLouis iana",
+ "ĠM ask",
+ "Ġcub es",
+ "ìĶ ¨",
+ "Ġvidé os",
+ "ĠnÃ¥ gon",
+ "Ġr ider",
+ "Ġì¶ ľ",
+ "Ġs ón",
+ "ĠLat ino",
+ "b ank",
+ "íķ´ì £¼",
+ "ĠB rend",
+ "Ġsexual ity",
+ "... ,",
+ "Ġforget ting",
+ "Ġ ÛĮ",
+ "ĠAven gers",
+ "ĠBon jour",
+ "cess or",
+ "кÑĢа ÑĹ",
+ "c ence",
+ "Ġge ograph",
+ "cul o",
+ "о ÑģÑĤÑĮ",
+ "Ġswe ating",
+ "íĥ Ģ",
+ "Ġsymm etry",
+ "ts å",
+ "Ġj an",
+ "ĠFer r",
+ "é¦ ĸ",
+ "Ġamb assador",
+ "ziÄĻ k",
+ "Ġmus un",
+ "ĠÑĥ ÑĤ",
+ "ĠL G",
+ "iss ent",
+ "comm un",
+ "Ġcour s",
+ "Ġdevelop s",
+ "Ġbron ze",
+ "Ġsubst ances",
+ "dri ven",
+ "주 ìĦ¸ìļĶ",
+ "Ġa os",
+ "åĦ Ħ",
+ "ĠPROF ESS",
+ "h alf",
+ "Ġsort ed",
+ "ĠB omb",
+ "л аг",
+ "ĠMalays ia",
+ "ĠChrist ina",
+ "Ġteam mate",
+ "èģ ŀ",
+ "F T",
+ "Ġk ı",
+ "heart ed",
+ "+ +",
+ "ogen ic",
+ "Ġbell s",
+ "ĠOu ais",
+ "Ġspecial ists",
+ "б Ñĭ",
+ "dep th",
+ "lass es",
+ "g ies",
+ "ĠCo ffee",
+ "Ġmark ing",
+ "Ġfo ll",
+ "ul i",
+ "Ġad hesive",
+ "ĠB ot",
+ "ĠP unkt",
+ "e ye",
+ "ĠB ub",
+ "el ong",
+ "åĪ ¶",
+ "ĠпÑĢ ик",
+ "Ġdon or",
+ "8 4",
+ "Ġen for",
+ "Ġcatch es",
+ "Ġbr icks",
+ "Ġkn itting",
+ "ĠKnow ing",
+ "ok s",
+ "H Y",
+ "r ide",
+ "ĠFant asy",
+ "im an",
+ "Ġp se",
+ "Ġìĺ ¨",
+ "Ġв д",
+ "Ġrest ra",
+ "Ġevalu ated",
+ "ÑĢ ев",
+ "Ġfortun ately",
+ "Ġche gar",
+ "ر ب",
+ "Ġdom ains",
+ "ib i",
+ "ar ry",
+ "Ġshut ter",
+ "Ġfic ou",
+ "M ike",
+ "Ġinc lu",
+ "Ġdon ors",
+ "Ġa pl",
+ "ĠL ower",
+ "Ġimport ed",
+ "Ġacad emy",
+ "Ġfin als",
+ "Ġdisappe ars",
+ "ÙĬ ا",
+ "Ġadministr ator",
+ "j s",
+ "Ġcut ter",
+ "Ġr anging",
+ "ör per",
+ "Ġconstra int",
+ "ĠT able",
+ "ĠSh an",
+ "v ic",
+ "ĠF ix",
+ "ĠSw ift",
+ "oun ces",
+ "ĠWar um",
+ "Ġlett uce",
+ "app elle",
+ "Ġsh ave",
+ "Ġb ás",
+ "Ġ7 7",
+ "ĠO oo",
+ "a o",
+ "ĠMc M",
+ "ĠD rew",
+ "Ġl ump",
+ "Ġl ashes",
+ "schein lich",
+ "R ep",
+ "in is",
+ "ĠC ette",
+ "Ġcompos ite",
+ "emet ery",
+ "Ġsort e",
+ "ĠFin ancial",
+ "он е",
+ "ron es",
+ "ĠV oy",
+ "Ġt éc",
+ "ł ¹",
+ "ĠNin ja",
+ "ĠCor in",
+ "ен нÑı",
+ "ìĿ´ìĹ Ī",
+ "Ġn ich",
+ "Ġdetect ive",
+ "âĢ¦ \"",
+ "Ïĥ ε",
+ "Ŀ¼ë ıĦ",
+ "Ġë³ Ģ",
+ "Ġë¸ Ķë",
+ "Ġpro pe",
+ "ĠW right",
+ "Ġ×Ķ× ª",
+ "ĠSh i",
+ "Ġãģ Ł",
+ "Ġinvestig ations",
+ "éĤĦ æĺ¯",
+ "ĠPower Point",
+ "ĠCh u",
+ "Ġìĺ ¤í",
+ "ĠìĻĦ ìłĦ",
+ "ĠFra gen",
+ "un ning",
+ "Ġpour rait",
+ "Ġtext book",
+ "м Ñĭ",
+ "Ġf ahren",
+ "Ġ ÑĤоÑĢ",
+ "Ġl akes",
+ "ünd e",
+ "I nt",
+ "ĠMet ro",
+ "Ġmans ion",
+ "Ġа б",
+ "ĠZh ou",
+ "Ġcorrid or",
+ "Ġesc ol",
+ "Ġindic ating",
+ "ia ÅĤa",
+ "Ġm ommy",
+ "Ġarch ives",
+ "Ġfound ers",
+ "eng ine",
+ "ĠDie u",
+ "Ġsick ness",
+ "Ġë³´ ëĭĪê¹Į",
+ "Ġar b",
+ "Ġn ed",
+ "ĠCh op",
+ "Ġco vid",
+ "Ġsl am",
+ "Ġpublic ations",
+ "D C",
+ "Ġsp ends",
+ "æ ¾",
+ "Ġrefuge e",
+ "Ġd ile",
+ "Ġ×IJ× ĸ",
+ "ific ar",
+ "ĠS ach",
+ "G u",
+ "Ġre load",
+ "?? ??",
+ "Ġje ÅĽli",
+ "ĠÑģ оÑģÑĤо",
+ "Ġsim plicity",
+ "Ġbull ying",
+ "Ġм ол",
+ "Ġreal idad",
+ "Ġuncle ar",
+ "app a",
+ "le vant",
+ "ĠIS IS",
+ "ĠW atson",
+ "Ġde in",
+ "ĠMic ro",
+ "íķ ľë",
+ "ü g",
+ "Ġdev am",
+ "Ġtwe eted",
+ "å° İ",
+ "Ġunderstand able",
+ "at an",
+ "Ġvers a",
+ "Ġpre ca",
+ "Ġv á»ģ",
+ "ĠCop y",
+ "ĠOr acle",
+ "Ġmindful ness",
+ "Ġdisc ret",
+ "ern en",
+ "ĠP le",
+ "H ave",
+ "Ġisol ate",
+ "Ġde u",
+ "Ġsevent y",
+ "ĠH ills",
+ "Ġarc ade",
+ "ĠÑģп еÑĨи",
+ "Ġsigu iente",
+ "ĠB ÃľNDNIS",
+ "lig a",
+ "ĠвÑģÑĤÑĢ еÑĩ",
+ "ô m",
+ "Ġtwe ets",
+ "Ġsch auen",
+ "Ġcrit ique",
+ "ĠðŁİ µ",
+ "Ġst att",
+ "ĠÑģам ое",
+ "ân cia",
+ "Ġsuper natural",
+ "Ġplug ged",
+ "F l",
+ "yn ı",
+ "ĠTamb ién",
+ "Ġencourage ment",
+ "ĠSer ver",
+ "ëĤ ľ",
+ "up a",
+ "Ġast on",
+ "Ġhe ars",
+ "ÑĢа Ñħ",
+ "Ġsch e",
+ "Ġr ats",
+ "Ġrec uper",
+ "Ġun ten",
+ "ĠFight ing",
+ "Ġacadem ics",
+ "ç¤ º",
+ "ĠS ü",
+ "Ñģ киÑħ",
+ "Ġpa ired",
+ "Ģ ìĿĦ",
+ "Ġá rea",
+ "Ġsweet ness",
+ "åı Ĭ",
+ "Ġde fer",
+ "Ġmuit as",
+ "ĠAud io",
+ "Ġlock er",
+ "ÙĬ د",
+ "ĠÑģÑĤ ав",
+ "Ġbu ena",
+ "AN S",
+ "Ġdetect or",
+ "av o",
+ "be k",
+ "Ġα ν",
+ "íİ ¸",
+ "Ġdra gged",
+ "Ġдолж ен",
+ "Ã ĸ",
+ "ر ة",
+ "ìĿ´ì §Ģ",
+ "Ġcell e",
+ "ck ing",
+ "ĠاÙĦØ ¬",
+ "ĠCan vas",
+ "Ġespa ñ",
+ "Ġgl imp",
+ "Ġspread s",
+ "ong o",
+ "ĠM ason",
+ "ĠIn g",
+ "Ġê°Ģ ëĬ¥",
+ "ÏĦ ικ",
+ "Ġsec ular",
+ "Ġb ater",
+ "Ġinqu iry",
+ "Ġenerg ies",
+ "Ġmanufact ured",
+ "Ġveget arian",
+ "Ġpine apple",
+ "ÑıÑĤ а",
+ "Ġpractition ers",
+ "2 000",
+ "Ġíķ´ì ļĶ",
+ "ĠìĹ¬ëŁ¬ë ¶Ħëĵ¤",
+ "Ġë¶ Īë",
+ "ĠJeff erson",
+ "ĠJo an",
+ "Ġtr am",
+ "å® ¹",
+ "ch mal",
+ "ĠH ait",
+ "á¹ ĩ",
+ "Ġun real",
+ "Ġsymbol ic",
+ "Ġste alth",
+ "Ġspl ash",
+ "ĠEntertain ment",
+ "Ġmetall ic",
+ "?\" .",
+ "è¶ Ĭ",
+ "ar ound",
+ "Ġdesp air",
+ "ĠNev ada",
+ "ĠFin ance",
+ "Ġk rie",
+ "ĠL ux",
+ "ĠSm ash",
+ "ke eping",
+ "Ġз аг",
+ "Ġnarc iss",
+ "Ġdz isiaj",
+ "Ġtoler ate",
+ "o ard",
+ "Ġlink ing",
+ "ĠEconom ic",
+ "Ġì ¼",
+ "Ġmor ph",
+ "ĠN ak",
+ "ĠB aker",
+ "at on",
+ "r ings",
+ "ĠP eng",
+ "ĠAir port",
+ "ãģĭ ãģ£ãģŁ",
+ "íķĺ ëĭ¤",
+ "§ ģ",
+ "pr ints",
+ "Ġhad i",
+ "Ġemp ir",
+ "ĠL ives",
+ "ann ers",
+ "Ġн им",
+ "ĠPROFESS OR",
+ "Ġpositive ly",
+ "ant om",
+ "Ġbad ge",
+ "ke lt",
+ "Ġinter fer",
+ "Ġfulf illing",
+ "Ġvisual ization",
+ "éĹľ ä¿Ĥ",
+ "ĠPr ice",
+ "� �",
+ "Ġscen ery",
+ "Ġpr one",
+ "Ġw izard",
+ "Ġb anyak",
+ "ver b",
+ "s ky",
+ "Ġwish ed",
+ "Ġrail way",
+ "Ġü zer",
+ "Ġalgu ien",
+ "ĠA W",
+ "Ġкол иÑĩе",
+ "Ġreact ing",
+ "ĠB uch",
+ "ภ¶",
+ "Ġan th",
+ "Ġsi h",
+ "Ġh ust",
+ "ĠSc reen",
+ "il ant",
+ "ah o",
+ "Ġfragr ance",
+ "Ġelev ation",
+ "ĠMed iter",
+ "Ġë ¿",
+ "Ġé qu",
+ "Ġwra ps",
+ "Ġin ert",
+ "Ġrecre ate",
+ "л аÑĤ",
+ "Ġbo leh",
+ "Ġharass ment",
+ "unk y",
+ "Ġglimp se",
+ "reg ierung",
+ "Ġfut ur",
+ "Ġreposit ory",
+ "Ġeng ra",
+ "Ġtraff icking",
+ "ass is",
+ "ĠTre k",
+ "Ġë² Į",
+ "Ġë§ Īë",
+ "ĠK ab",
+ "ani u",
+ "g ive",
+ "Ġdin osaurs",
+ "Ġfe ather",
+ "Ġatt itudes",
+ "Ġpl um",
+ "ĠR S",
+ "ĠAn fang",
+ "ill ery",
+ "ĠìĬ ¤",
+ "M Y",
+ "Ġtrze ba",
+ "Ġsk ies",
+ "ĠA j",
+ "ur able",
+ "C U",
+ "ĠSh ane",
+ "Ġdepart ure",
+ "ĠT ON",
+ "iet en",
+ "r ats",
+ "æ° Ĺ",
+ "is u",
+ "Ġb ord",
+ "Ġinteresting ly",
+ "çĻ »",
+ "oug hing",
+ "Ġr ushing",
+ "Ġvol atility",
+ "Ġp yt",
+ "Ġform ats",
+ "Ġз аÑĤ",
+ "Ġê¼ Ń",
+ "Ġwhat not",
+ "Ġcomp ort",
+ "s w",
+ "ore an",
+ "ĠRel ax",
+ "Ġcl an",
+ "ĠA H",
+ "Ġpe w",
+ "Ġdiction ary",
+ "T ake",
+ "sh irts",
+ "ĠH ugh",
+ "ĠعÙĦ ÙĬ",
+ "ĠP ic",
+ "Ġenroll ed",
+ "Ġjed nak",
+ "Ġoffer ings",
+ "Ġcor az",
+ "L ife",
+ "Ġ !!!",
+ "Ġcl er",
+ "ĠVide os",
+ "ĠRod rig",
+ "ĠId ent",
+ "ĠP os",
+ "ĠSt age",
+ "ĠR ace",
+ "Ġen act",
+ "ãģĦ ãģ¾ãģĹãģŁ",
+ "ĠG y",
+ "ĠHis pan",
+ "Ġdef ence",
+ "ĠCamp bell",
+ "m atic",
+ "Ġrele v",
+ "Ġpe ach",
+ "Ħ¸ ìļĶ",
+ "Ġparad ise",
+ "Ġcere mon",
+ "Ġannoy ed",
+ "æĮ ĩ",
+ "la x",
+ "Ġexplo it",
+ "Ġcla use",
+ "ek er",
+ "ĠBlo om",
+ "n ant",
+ "ate urs",
+ "Ġhe ights",
+ "E ven",
+ "Ñģ он",
+ "Ġoutra ge",
+ "ĠVietnam ese",
+ "ãģ¯ ãģ¯",
+ "T R",
+ "Ġe er",
+ "Ġcann on",
+ "ĠCom b",
+ "IJë §Į",
+ "è» Ĭ",
+ "Ġê²ĥ ëıĦ",
+ "Ġaccomplish ments",
+ "ĠAnalyt ics",
+ "Ġshap ing",
+ "re iben",
+ "Ġb achelor",
+ "Ġfing ert",
+ "ack ed",
+ "Ġpyram id",
+ "ĠStew art",
+ "á st",
+ "Ġsurviv or",
+ "Ġdu ct",
+ "Ġdeal ers",
+ "æ´ »",
+ "ع Ùħ",
+ "ли н",
+ "Ġed e",
+ "×ķ× ¢",
+ "ĠÙĥ اÙĨ",
+ "ĠÏĦ ι",
+ "Ġcho oses",
+ "ĠO wn",
+ "го ÑĤов",
+ "h ire",
+ "алÑĮ нÑĭе",
+ "ĠÐĽ Ñİ",
+ "Ġо ÑģÑĤав",
+ "te ch",
+ "Ġdro it",
+ "Ġsubject ive",
+ "en es",
+ "Ġdiv is",
+ "ave z",
+ "Ġmaneu ver",
+ "à¹Ħ à¸Ķ",
+ "ade ce",
+ "ĠEn s",
+ "ac ial",
+ "ĠProt ection",
+ "ĸ ´",
+ "Ġform ally",
+ "Ġwy d",
+ "ingu ém",
+ "Ġz iem",
+ "Ġrecru iting",
+ "×Ļ× ļ",
+ "n em",
+ "Ġforb idden",
+ "ĠB apt",
+ "×IJ× ł×Ļ",
+ "Ġsubs et",
+ "ĠMag az",
+ "n ement",
+ "Ġaqu ela",
+ "rag on",
+ "Ġcomm ittees",
+ "Ġéta ient",
+ "ud i",
+ "ĠDa wn",
+ "Ġb ore",
+ "Ġcompos er",
+ "ĠwiÄĻ cej",
+ "ang a",
+ "Ġdis like",
+ "ĠD ays",
+ "åŁ º",
+ "Ġpar al",
+ "Ġm ientras",
+ "Ġheaven s",
+ "ãģ Ĵ",
+ "he id",
+ "Ġtrad ers",
+ "on ce",
+ "Ġmasc ara",
+ "ĠÏĢ Ïģο",
+ "Ġwhis per",
+ "ĠMus k",
+ "éĽ Ĩ",
+ "ĠFamil ie",
+ "All ah",
+ "ĠOl ivia",
+ "ĠPr os",
+ "Ġol ika",
+ "il im",
+ "Ġrép ond",
+ "ĠP eters",
+ "Ġ å¾Ī",
+ "Ġbit es",
+ "Ġv ic",
+ "ĠN Y",
+ "em ption",
+ "Ġ4 50",
+ "Ġvisual s",
+ "Ġlie u",
+ "ück en",
+ "ĠSte el",
+ "ĠG P",
+ "w ait",
+ "Ġnotice able",
+ "uch a",
+ "Ġreh abil",
+ "Ġreject ion",
+ "ĠÑģлед ÑĥÑİÑī",
+ "Ġsl ider",
+ "Ġregard ed",
+ "Ġgrav it",
+ "ĠRes erve",
+ "c ount",
+ "Ġbre eding",
+ "Ġlon ge",
+ "ale b",
+ "Ġkn ight",
+ "Ġв ой",
+ "Ġprés ent",
+ "Ĥĺ ìļĶ",
+ "ĠSpec ifically",
+ "Ġpos es",
+ "Ġve ure",
+ "ok ay",
+ "em as",
+ "Ġ ãģ§ãģĻ",
+ "Ġma jÄħ",
+ "Ġweb inars",
+ "Ġcann abis",
+ "Ġdam als",
+ "ĠNorth west",
+ "Ġp ada",
+ "Ġcrowd s",
+ "Ġfut ures",
+ "Ġä n",
+ "Ġciv ilians",
+ "ĠS achen",
+ "æ į",
+ "Ġtr aces",
+ "Ġ먹 ê³ł",
+ "Q U",
+ "é¡ĺ ãģĦ",
+ "ĠI F",
+ "an ın",
+ "ìĤ ´",
+ "Ġb iblical",
+ "ĠV ed",
+ "Ġst oring",
+ "ÑĢав лÑı",
+ "æĩī 該",
+ "Ġn ast",
+ "Ġd ö",
+ "ÑĢ оп",
+ "el ia",
+ "Ġside ways",
+ "ĠUnder stand",
+ "ĠQ ur",
+ "Ġper pend",
+ "ĠMill ionen",
+ "Ġwater melon",
+ "ĠDiv ine",
+ "ult ur",
+ "ab ord",
+ "Ġsuccess es",
+ "Ġhom bre",
+ "Ġcar p",
+ "Ġsus cept",
+ "ung kin",
+ "Ġk ij",
+ "ul us",
+ "Ø§Ø ¬",
+ "Ġnot ch",
+ "Ġpolynom ial",
+ "å¹ ²",
+ "å ©",
+ "Ġún ico",
+ "Ġteles cope",
+ "Ġpolit ique",
+ "k iem",
+ "ĠÎŃ Î½Î±",
+ "Ġaggreg ate",
+ "ĠGe off",
+ "Ġtr il",
+ "ĠG RA",
+ "Ġsubscri ber",
+ "im et",
+ "Ġдол лаÑĢ",
+ "op ing",
+ "Ġth erapeut",
+ "ĠCan cer",
+ "Ġpar ade",
+ "Ġir rig",
+ "âĻª âĻª",
+ "Ġclear er",
+ "Ġb og",
+ "ĠM aur",
+ "า à¸ĩ",
+ "ĠShang hai",
+ "acht e",
+ "ĠK ol",
+ "el ujah",
+ "Ġha v",
+ "ĠCr ime",
+ "se k",
+ "Ġë ¡ľ",
+ "ien na",
+ "ĠG or",
+ "è Ľ",
+ "ĠпоÑĤ ÑĢ",
+ "Ġкаж еÑĤÑģÑı",
+ "ĠL ift",
+ "ĠS ort",
+ "ĠP sal",
+ "Ġp ing",
+ "ĵ Ŀ",
+ "ph is",
+ "ĠF UCK",
+ "ĠS yn",
+ "Ġbam boo",
+ "¬ ìĺģ",
+ "c uts",
+ "Ġm mm",
+ "Ġfunktion iert",
+ "Ġ _",
+ "ÃŃ cio",
+ "St op",
+ "Ġimag inary",
+ "Ġnot amment",
+ "ĠIniti ative",
+ "ãĥ ¥",
+ "ĠK urt",
+ "Ġlo osen",
+ "Ġbus car",
+ "çģ «",
+ "Ġz elf",
+ "Ġpro ps",
+ "åĽ ī",
+ "Ġmoet en",
+ "Ġmill i",
+ "Ġhall s",
+ "ĠM atch",
+ "Ġbrack ets",
+ "ĠC ou",
+ "æ¦ Ĥ",
+ "ĠÐľ аÑĢ",
+ "IS A",
+ "Ġcig arette",
+ "Ġcompet itions",
+ "ĠM IN",
+ "Ġbeh ö",
+ "vo or",
+ "Ġ ust",
+ "ĠZ i",
+ "ĠO cc",
+ "ul ates",
+ "Ġball oons",
+ "Ġpr onto",
+ "ĠM iy",
+ "ĠF ile",
+ "Ġкл аÑģÑģ",
+ "нÑĥ л",
+ "Ġcere al",
+ "Ġincre ment",
+ "Ġref ined",
+ "åı¦ å¤ĸ",
+ "pr ising",
+ "ĠR F",
+ "Ġrespect ful",
+ "Ġlo ot",
+ "ask et",
+ "Ġdeix a",
+ "ing le",
+ "Ġfuncion a",
+ "ĠRe vel",
+ "Ġso ber",
+ "Ġperform s",
+ "ĠG entle",
+ "ãĤ ¨",
+ "Ġrecip ient",
+ "ĠHa use",
+ "Ġë ĥ",
+ "F rom",
+ "Ġmin isters",
+ "Ġpar adox",
+ "å°±æĺ¯ èªª",
+ "Ġtast ing",
+ "Ġ×Ķ× Ĺ",
+ "Ġre use",
+ "ĠL ane",
+ "ĠÑģов еÑĢÑĪ",
+ "Ġremem bers",
+ "Ġfemin ist",
+ "Ġcommit ments",
+ "Ġproject ed",
+ "Ġg az",
+ "iyor uz",
+ "Ġoblig ations",
+ "R o",
+ "z ar",
+ "Ġch w",
+ "ĠJ AM",
+ "ĠbÄĻd Äħ",
+ "asp berry",
+ "Ġм еÑģÑĤо",
+ "ë² ķ",
+ "Ġreg ulated",
+ "Ġw icht",
+ "ĠTre vor",
+ "Ġsecond ly",
+ "ĠIh re",
+ "els h",
+ "Ġrep orters",
+ "ÑĤоÑĢ а",
+ "oy o",
+ "G I",
+ "Ġinter connect",
+ "é IJĺ",
+ "OS H",
+ "æŃ ²",
+ "Ġbr ass",
+ "Ġign oring",
+ "ä»Ĭ æĹ¥",
+ "in fect",
+ "Ġpro jekt",
+ "ore t",
+ "ÏĦα ν",
+ "ĠÑĤ ип",
+ "Ġmut ta",
+ "Ġunbox ing",
+ "Ħ °",
+ "å¡ Ĭ",
+ "Ġadv ised",
+ "ĠDen ver",
+ "Ġsevere ly",
+ "ĠM hm",
+ "Ġfl ipped",
+ "Ġp ien",
+ "Ġkomm un",
+ "ĠF RE",
+ "Ġà®ĩ à®°",
+ "aint ed",
+ "Ġkn ives",
+ "Ġhab l",
+ "Ġgew orden",
+ "arett es",
+ "C S",
+ "Ġмал енÑĮ",
+ "Ġgal ax",
+ "Ġnin ete",
+ "ê±°ë Ĥĺ",
+ "Ġs is",
+ "Ġadvis ory",
+ "Ġdr illing",
+ "ĠWould n",
+ "ün f",
+ "gest ellt",
+ "ĠHel en",
+ "Ġ×ŀ× IJ",
+ "ap olis",
+ "Ġrze czy",
+ "Ġter ra",
+ "Ġhe p",
+ "Ġalg ún",
+ "ik k",
+ "Ġastron om",
+ "ĠStar bucks",
+ "k Äħ",
+ "Ġpat rol",
+ "Ġì½ Ķ",
+ "Ġg on",
+ "Ġ ãĢIJ",
+ "Ġson st",
+ "Ġencoun ters",
+ "Ġret rou",
+ "Ġshark s",
+ "Ġd or",
+ "ĠR ever",
+ "Ġev apor",
+ "Ġreserv oir",
+ "Ġalleg ed",
+ "ul er",
+ "Ġver m",
+ "Ġcommer ce",
+ "Ġf itted",
+ "ge m",
+ "Ġtact ical",
+ "Ġl ith",
+ "éīĦ å¡Ķ",
+ "h ad",
+ "è® Ĭ",
+ "Ġcarboh yd",
+ "Ġlength s",
+ "ι ο",
+ "Ġdem ographic",
+ "R ob",
+ "ĠS kin",
+ "cc oli",
+ "Ġsimpl ified",
+ "Ġread ily",
+ "ĠC um",
+ "ades h",
+ "ĠD Ã¥",
+ "us st",
+ "ig ne",
+ "et on",
+ "Ġmen or",
+ "q i",
+ "OO M",
+ "à¸Ń à¸Ļ",
+ "Ġpsych iat",
+ "Ġeight y",
+ "Ġм илли",
+ "ĠT ob",
+ "ed o",
+ "ç¶ ²",
+ "ĠÄij ến",
+ "Ġcirc uits",
+ "ĠLAU GH",
+ "ic ism",
+ "em or",
+ "Ġreg ener",
+ "eg ree",
+ "Ġbure auc",
+ "ĠAl ber",
+ "ä¹ĭ å¾Į",
+ "ĠW or",
+ "å¤ «",
+ "Ġres in",
+ "Ġby ÅĤy",
+ "ĠI G",
+ "à¯į ,",
+ "Ġ7 8",
+ "Ġwe eds",
+ "ĠMy th",
+ "9 3",
+ "æ ¿",
+ "ĠëĤĺ ìĻĶ",
+ "é v",
+ "á ½",
+ "ö ren",
+ "ç ar",
+ "ĠP AUL",
+ "Ġdisad vant",
+ "Ġposition ing",
+ "Ġcock tail",
+ "Ġagre es",
+ "n n",
+ "ĠS ally",
+ "M s",
+ "Ġinher ent",
+ "Ġmonet ary",
+ "Ġnat ur",
+ "ĠN h",
+ "ĠImp ort",
+ "Ġle ben",
+ "Ġw i",
+ "uss y",
+ "Ġob es",
+ "Ġwand ering",
+ "Ġìĭ łë",
+ "Äħ da",
+ "etch up",
+ "Ġdispos al",
+ "ĠJ A",
+ "ĠC er",
+ "z illa",
+ "Ġvir gin",
+ "ĠSl ide",
+ "and el",
+ "Ġrighteous ness",
+ "ĠÎ £",
+ "Ġide ia",
+ "ä½ł 好",
+ "иÑĢов аÑĤÑĮ",
+ "ר ×IJ",
+ "Com ment",
+ "Ġpre lim",
+ "ĠV ale",
+ "Ġì§Ģë Ĥľ",
+ "ĠV anc",
+ "OM AN",
+ "Ġп Ñĸд",
+ "Ġy um",
+ "st re",
+ "ce m",
+ "Ġpo cz",
+ "Ġfrag ment",
+ "ĠÑģлÑĥÑĩа е",
+ "Ġunder go",
+ "ĠH ank",
+ "ce ks",
+ "ĠF PS",
+ "Ġoc ur",
+ "Ġdeter ior",
+ "æ³ ¨",
+ "Ġempres as",
+ "Pa ul",
+ "Ġ) ))",
+ "ĠвÑĢем ени",
+ "Ġsc old",
+ "×Ļ× ¢",
+ "Ġsuspect ed",
+ "Ġaccess ing",
+ "Ġsubst it",
+ "Ġhistor ians",
+ "ä» »",
+ "Ġдел о",
+ "Ġsoci ed",
+ "r one",
+ "Ġre den",
+ "Ġext ends",
+ "epher d",
+ "Ġbal con",
+ "ä¸į èµ·",
+ "ĠSol o",
+ "Ġpolit ician",
+ "олÑĮ но",
+ "Ġirgend w",
+ "Ġtraum atic",
+ "Ġrapp er",
+ "ĠRO BERT",
+ "Re ally",
+ "æģ ¯",
+ "Ġline up",
+ "AS E",
+ "Ġcontract or",
+ "ĠCorpor ation",
+ "g or",
+ "ĠTod o",
+ "ÑģÑĤÑĢ ой",
+ "F BE",
+ "Ġnews letter",
+ "Ġko ÅĦ",
+ "alt ies",
+ "ĠпÑĢ иÑĩ",
+ "ĠHe avy",
+ "Ġsw ords",
+ "Ġmanip ulation",
+ "Ġfun k",
+ "Ġv Ã¥r",
+ "ĠTal iban",
+ "Ġë° ¥",
+ "Ġac ne",
+ "ür ü",
+ "Ġdes wegen",
+ "ĠD ust",
+ "Ġsil ic",
+ "Ġhook s",
+ "Ġbl ij",
+ "Ġpet its",
+ "Ġfil me",
+ "ĠBere ich",
+ "ĠSa id",
+ "Ġimp osed",
+ "Ġdi ary",
+ "Ġго ÑĢ",
+ "ĠG ates",
+ "Ġal ta",
+ "å¸ Į",
+ "Ġch cia",
+ "ple asant",
+ "Ġë° Ŀ",
+ "Ġmoż emy",
+ "ĠAust ria",
+ "Ġbro ker",
+ "Ġsuck ed",
+ "èĢ ĥ",
+ "Ġcomp artment",
+ "Ġcl one",
+ "Ġ×Ķ× ¢",
+ "ĠDan ke",
+ "Ġnoch mal",
+ "ез д",
+ "Ġad renal",
+ "Ġkle inen",
+ "ãģ¾ ãģĹãĤĩãģĨ",
+ "Ġsubsequ ently",
+ "Ġdecent ral",
+ "Ġgen etics",
+ "Ġê´ ij",
+ "Ġmon itors",
+ "ĠApp lic",
+ "ĠRep orter",
+ "w ert",
+ "Ġwie m",
+ "ĠMove ment",
+ "Ġinterview ing",
+ "Ġhair s",
+ "Ġpu ò",
+ "ĠChel sea",
+ "Ġco her",
+ "Ġc ot",
+ "Ġz as",
+ "Ġpatch es",
+ "Ġl ah",
+ "Ñĥн к",
+ "ĠRe agan",
+ "ĠMar co",
+ "c ity",
+ "Ġdef ender",
+ "Ġdecor ation",
+ "ij i",
+ "Ġl itter",
+ "Ð ¨",
+ "Ġj ego",
+ "RE W",
+ "ĠP ik",
+ "ĠHe e",
+ "ĠI v",
+ "Ġи де",
+ "ĠThe ater",
+ "ĠÑĩаÑģ ÑĤо",
+ "Ġswe ater",
+ "Ġhighlight ing",
+ "Ġa insi",
+ "Ġdipl omatic",
+ "ĠNever theless",
+ "å ³",
+ "AS ON",
+ "Ġpúblic o",
+ "Ġf erm",
+ "reat ed",
+ "c od",
+ "Ġë¬ ¼ë",
+ "Ġm ister",
+ "ĠVanc ouver",
+ "Ġrecogn izes",
+ "ec d",
+ "Ġcomplic ations",
+ "en cial",
+ "ãģĹ ãģı",
+ "Ġê°Ģ ì§Ģ",
+ "ĠUlt imate",
+ "Ġva ig",
+ "ĠM erry",
+ "×ķ× Ĵ",
+ "ĠMar cus",
+ "ç¸ ½",
+ "ow ego",
+ "Ġm ente",
+ "S m",
+ "Ġa ja",
+ "ĠTa o",
+ "Ġjud icial",
+ "Ġentrepreneurs hip",
+ "Ġнем ного",
+ "Ġp is",
+ "Ġer g",
+ "Ġch rist",
+ "ĠC urt",
+ "ĠÑĢаÑģ п",
+ "λ ε",
+ "ens ch",
+ "ÃŃ re",
+ "Ġfo cal",
+ "ĠDiam ond",
+ "av ÃŃa",
+ "Ġh anno",
+ "ĠSqu ad",
+ "Ġassoci ations",
+ "ĠCreat ive",
+ "Ġmess enger",
+ "Ġbe gging",
+ "Ġdec imal",
+ "Ġd Ä±ÅŁ",
+ "Ġmet adata",
+ "sel s",
+ "ĠÄ° ÅŁ",
+ "ữ a",
+ "Ġdiffic ile",
+ "d ı",
+ "Ġs laughter",
+ "ĠVer g",
+ "Ġ×Ĵ ×Ŀ",
+ "ç° ¡",
+ "æĮ ī",
+ "ĠTe a",
+ "ass es",
+ "O k",
+ "Ġsynth es",
+ "ot iation",
+ "Ġpain ter",
+ "Ġel bows",
+ "Ġarchitect ural",
+ "ĠÑĢ ад",
+ "Ġgl or",
+ "im age",
+ "amp a",
+ "cul iar",
+ "ł ¨",
+ "Ġte ve",
+ "ĠSt elle",
+ "ĠB am",
+ "Ġì´ Ī",
+ "as is",
+ "ip edia",
+ "ĠG I",
+ "ĠAct ive",
+ "çĦ¶ åIJİ",
+ "az i",
+ "ãĤĮ ãģ¦",
+ "ĠL ucky",
+ "íķ ©",
+ "ĠпÑĢ иÑħод",
+ "Ġrun way",
+ "Ġauthent ication",
+ "Ġpos ible",
+ "Ġsupp lements",
+ "Ġsurg ical",
+ "G en",
+ "Ġfeas ible",
+ "D O",
+ "Ġout look",
+ "Ġinter vals",
+ "Ġan ecd",
+ "Ãł ng",
+ "Ġstra ps",
+ "ĠSh u",
+ "ud d",
+ "iss enschaft",
+ "Ġport e",
+ "Ġcomm itting",
+ "Ġall ey",
+ "Ġco venant",
+ "ĠPed ro",
+ "less ness",
+ "ĠSol id",
+ "ĠM olly",
+ "Ġн екоÑĤоÑĢ",
+ "Ġcooper ate",
+ "åĮ Ĺ",
+ "oll en",
+ "Ġtun a",
+ "Ġkinderg arten",
+ "ĠS iz",
+ "Ġduż o",
+ "ĠM BA",
+ "ĠGEOR GE",
+ "ĠF isher",
+ "å¿ ĺ",
+ "ĠCa esar",
+ "ĠкÑĢаÑģ ив",
+ "ĠDel hi",
+ "zy m",
+ "Ġexpl icar",
+ "ê°Ģ ì§Ģ",
+ "un s",
+ "gr ow",
+ "ĠпÑĢ иÑģ",
+ "Ġ8 6",
+ "Ġst ating",
+ "Ġmass a",
+ "ch ter",
+ "Ġì»¬ë Ł¬",
+ "Ġdep uty",
+ "S M",
+ "n oc",
+ "Ġge ography",
+ "ĠEnter prise",
+ "ĠC ant",
+ "ö z",
+ "Ġun pack",
+ "ĠíĻ Ķë",
+ "Ġsearch es",
+ "Ġpres idency",
+ "Ġtri vial",
+ "Ġp ige",
+ "ou bt",
+ "ãĤ ļ",
+ "ì¼ ĢìĿ´",
+ "Ġbudget s",
+ "Ġu b",
+ "Ġp ne",
+ "ĠY ale",
+ "ĠÅŁ öyle",
+ "reg ular",
+ "Ġimper fect",
+ "AR A",
+ "Ġfam ÃŃlia",
+ "ur m",
+ "ĠAdvent ure",
+ "ãĥ Ĭ",
+ "c is",
+ "em ark",
+ "Ġne go",
+ "Ġinappropri ate",
+ "ĠпÑĢи з",
+ "ĠÑĢ ол",
+ "Ġdream ed",
+ "B ry",
+ "Ġshut tle",
+ "Ġpill ars",
+ "Ġb ik",
+ "in um",
+ "ĠÑĥ Ñģ",
+ "ĠNe br",
+ "Ġperpend icular",
+ "Ġbook ed",
+ "ber y",
+ "Ġv ikt",
+ "be ar",
+ "es us",
+ "Ġвозм ожно",
+ "¨ ¹",
+ "Ġpresum ably",
+ "ĠMem phis",
+ "Ġambul ance",
+ "×ķ× ŀר",
+ "Ġthumbna il",
+ "Ġmod ification",
+ "éĩ ı",
+ "Ġinterpret ed",
+ "Ġprom o",
+ "Ġκ ά",
+ "Ġε ÏĢ",
+ "Ġacoust ic",
+ "ĠD B",
+ "åĵ İ",
+ "Ġnon etheless",
+ "ou le",
+ "Ġpe qu",
+ "Ġkn ob",
+ "ãĤ £",
+ "ĠëıĮ ìķĦ",
+ "Ġpurch ases",
+ "ĠÃĩ ünkü",
+ "Ġdivid ing",
+ "per form",
+ "ract ion",
+ "health y",
+ "ĠTit le",
+ "Ġu k",
+ "Ġcer ca",
+ "Ġargu ably",
+ "Ġf ale",
+ "ë³ µ",
+ "Ġgam ers",
+ "Ġutil izing",
+ "Ġoff ended",
+ "Ġt ava",
+ "al ı",
+ "Ġmed ian",
+ "Ġinfect ious",
+ "ĠAn nie",
+ "Ġsmart phones",
+ "Ġpar ole",
+ "åĸ Ŀ",
+ "ĠEp ic",
+ "z za",
+ "Ġun ified",
+ "Ġê·¸ë ķĮ",
+ "Ġcur tain",
+ "ĠÄ ĥ",
+ "Ġsex ually",
+ "Ġuns erem",
+ "ĠCon vention",
+ "Ġalleg edly",
+ "Y a",
+ "ĠH oo",
+ "en ment",
+ "æĢ ª",
+ "íĽ Ħ",
+ "Ġgig antic",
+ "Ġnot ing",
+ "Ġre bo",
+ "ĠJ ama",
+ "ĠAl z",
+ "Ġborrow ed",
+ "ì¹ ¨",
+ "Ġper ipher",
+ "оÑĤ а",
+ "ĠG B",
+ "ĠGe ar",
+ "Ġeconom ically",
+ "Ġtele fon",
+ "Ġqu eremos",
+ "ĠдалÑĮ ÑĪе",
+ "Ġr as",
+ "ĠTe ach",
+ "ic ios",
+ "at os",
+ "Ġpl edge",
+ "b au",
+ "ĠHim self",
+ "L ink",
+ "Ġesper o",
+ "Ġchrom os",
+ "ĠP ER",
+ "Ġer le",
+ "Ġpod ium",
+ "ç os",
+ "Ġnie u",
+ "Ġf en",
+ "ĠGO D",
+ "ĠCh ocolate",
+ "wer k",
+ "Ġt ừ",
+ "Ġsupp ress",
+ "λ η",
+ "Ġ24 0",
+ "Ġsit ä",
+ "Ġhonest y",
+ "ĠB io",
+ "ĠB ard",
+ "ĠобÑī ем",
+ "Ġм Ñĥз",
+ "Ġmar ble",
+ "ĠÑĨ енÑĤ",
+ "Ġproc ure",
+ "Ġrot or",
+ "ber n",
+ "Ġtu h",
+ "Ġhead set",
+ "at em",
+ "Ġwarrant y",
+ "à® ´",
+ "Ġfil ing",
+ "ι ά",
+ "Ġcomp rendre",
+ "Ġimp ulse",
+ "Ġsal v",
+ "wr itten",
+ "Ġinstit ute",
+ "K im",
+ "ĠLGBT Q",
+ "fic iente",
+ "H is",
+ "ĠαÏħÏĦ ÏĮ",
+ "Ġteen age",
+ "or us",
+ "ĠÑĢаз б",
+ "S ee",
+ "ĠCons erv",
+ "á»ģ n",
+ "ful ness",
+ "Ġstraw berries",
+ "ĠAb u",
+ "и он",
+ "Ġo lla",
+ "NO ISE",
+ "ĠEm ploy",
+ "Ġwip ed",
+ "ur ger",
+ "Ġmod ifications",
+ "Ġíķĺ ì§Ģ",
+ "Ġfoot steps",
+ "Ġhon ors",
+ "Ġad ul",
+ "Ġfl ipping",
+ "ĠH U",
+ "Z Y",
+ "Ġintegr ating",
+ "ب ر",
+ "ull a",
+ "Ġnatuur lijk",
+ "ĠíĹ Ī",
+ "ĠEth ereum",
+ "ÙĬ ÙĦ",
+ "w ed",
+ "Ġpe aks",
+ "ĠK es",
+ "Ġblo om",
+ "Ġcr ashing",
+ "Ġ9 11",
+ "ĠоÑĤ лиÑĩ",
+ "Ġcontro llers",
+ "ĠD od",
+ "Ġвм еÑģÑĤе",
+ "Ġsort ir",
+ "å¥ ĩ",
+ "ĠStra ight",
+ "ĠGrac ias",
+ "Ġgro ove",
+ "Ġto gg",
+ "Ġìĭ¶ ìĿĢ",
+ "é ro",
+ "Ġout ward",
+ "ĠW A",
+ "ĠRock y",
+ "Ġsc am",
+ "Ġhay at",
+ "ig nty",
+ "â Ħ",
+ "pl ings",
+ "Ġantibiot ics",
+ "Ġ ä¸Ģ",
+ "Ġnever theless",
+ "j ang",
+ "com merce",
+ "Ġspo iler",
+ "Ġglo ve",
+ "Ġch atter",
+ "ĠB Y",
+ "~ ?",
+ "Ġíĺ ¸",
+ "Ġdem ol",
+ "we chsel",
+ "im ir",
+ "Ġra id",
+ "еÑĢ Ñħ",
+ "ìŀIJ 기",
+ "en f",
+ "Ġcomment ed",
+ "Ġoptim ized",
+ "Ġconv icted",
+ "Ġb ats",
+ "ĠS B",
+ "ĠA ur",
+ "ĠT ong",
+ "Ġimplic it",
+ "ĠJan et",
+ "Ġre ag",
+ "ãģ ²",
+ "ĠAdv anced",
+ "Ġimp ose",
+ "ש ×Ķ",
+ "Ġschem es",
+ "oug her",
+ "ab olic",
+ "Ġê±° ì£ł",
+ "Ġslow ing",
+ "Ġwt edy",
+ "Ġdest ructive",
+ "Ġоп ÑĢед",
+ "Ġland mark",
+ "Ġëı Ī",
+ "ĠWalk ing",
+ "Ạ¹",
+ "Ġt ijd",
+ "ĠK N",
+ "ĠQu ant",
+ "ìĺ ¤ë",
+ "Ġк ÑĢÑĥ",
+ "Ġper der",
+ "Ġno ve",
+ "änd e",
+ "Ġãģ Ĺ",
+ "b ia",
+ "Ġcust ody",
+ "Ġb iod",
+ "æĿ± 西",
+ "Ġdirect ing",
+ "... âĢĭ",
+ "Ġre loc",
+ "Ġdemand e",
+ "ãĤĵ ãģł",
+ "Ġo ÄŁlum",
+ "Ġод на",
+ "ĠMil k",
+ "åı ·",
+ "ĠK ra",
+ "ĠH onda",
+ "Ġp ue",
+ "Ġele kt",
+ "Ġbegin ners",
+ "Ġspe ar",
+ "ÃŃ nh",
+ "ĠLu ft",
+ "Ġn ig",
+ "ĠSchool s",
+ "Ġfor ums",
+ "ĠQ in",
+ "pp o",
+ "Ġz ag",
+ "ĠÐ ®",
+ "Ġtooth p",
+ "ĠSt yle",
+ "ì´ Ī",
+ "Ġpun ct",
+ "Ġrep s",
+ "ĠA ly",
+ "Ġamend ments",
+ "Ġö z",
+ "Ġdig its",
+ "ur ai",
+ "Ġcha otic",
+ "ĠMas ters",
+ "e on",
+ "ĠC ash",
+ "ĠC uz",
+ "Ġbede utet",
+ "Ġscan ning",
+ "Ġж д",
+ "н еÑĤ",
+ "Ġcertain ty",
+ "j ek",
+ "Ġdi jo",
+ "ĠCl imate",
+ "Ġr inse",
+ "Ġk rij",
+ "vel and",
+ "Ġsound track",
+ "ĠSa fe",
+ "ĠNo va",
+ "9 4",
+ "Ġa the",
+ "ĠVer b",
+ "ol er",
+ "ìĿ´ì £ł",
+ "Ġv in",
+ "Ġrespir atory",
+ "ĠStud y",
+ "ĠC AM",
+ "Ġav ocado",
+ "ĠZ hen",
+ "Ġlat ency",
+ "Ġfe athers",
+ "Ġcont ar",
+ "Ġв еÑī",
+ "Ġf ark",
+ "Ġbl ended",
+ "Ġexpl oded",
+ "ĠX X",
+ "ĠBen im",
+ "Ġalgu ém",
+ "isto ire",
+ "Ġconfident ial",
+ "Ġm ast",
+ "Ġì ¿",
+ "ge h",
+ "Ġdis respect",
+ "ĠSystem s",
+ "Æ° a",
+ "E d",
+ "Ġw ys",
+ "Ġex otic",
+ "Ġgl owing",
+ "ù ng",
+ "oun ge",
+ "è Ħ",
+ "ани з",
+ "Ġpal av",
+ "ĠSw ord",
+ "Ġg im",
+ "ĠC row",
+ "Ġpot ent",
+ "b ish",
+ "Ġab used",
+ "ĠJ ed",
+ "Ġg ambling",
+ "ĠS pect",
+ "Ġinvestig ators",
+ "æĻ ļ",
+ "Ġr att",
+ "Ġdo b",
+ "ĠD ES",
+ "h og",
+ "ĠоÑĤк ÑĢÑĭ",
+ "íĮ ħ",
+ "ĠденÑĮ ги",
+ "Ġíĺ ¹",
+ "Ġë¨ ¸ë¦¬",
+ "Ġsat uration",
+ "Ġinher ited",
+ "ĠInnov ation",
+ "ìĹ Īëįĺ",
+ "Ġtang ible",
+ "Ġdep ri",
+ "h ed",
+ "Ġпом ог",
+ "Ġslic ed",
+ "ॠį",
+ "Ġth ế",
+ "Å ¥",
+ "6 8",
+ "Ġcor ona",
+ "Ġgift ed",
+ "Ġso ir",
+ "Ġhum ility",
+ "ĠìĿ´ 걸",
+ "Ġflaw s",
+ "ĠпÑĢ акÑĤи",
+ "Ġk ald",
+ "wa ż",
+ "y w",
+ "ãĤĵ ãģ§ãģĻ",
+ "ir teen",
+ "Ġcroch ets",
+ "¦¬ ê°Ģ",
+ "ĠìłĦ ìĹIJ",
+ "Ġdes e",
+ "æ¥ Ń",
+ "Ġм аг",
+ "Ġdz iaÅĤ",
+ "Ġl ég",
+ "ch anging",
+ "Ġlle v",
+ "ÅĦ sk",
+ "çĶ »",
+ "Ġ198 4",
+ "orn s",
+ "ĠW elsh",
+ "Ġpharm aceutical",
+ "Ġpump ing",
+ "ĠSh aw",
+ "p unk",
+ "Ġva ult",
+ "Ġkin etic",
+ "Ġhur ricane",
+ "ĠInc luding",
+ "ứ c",
+ "ĠGrand pa",
+ "ans hip",
+ "é¦Ļ 港",
+ "ĠвÑĭ Ñħод",
+ "н ож",
+ "ľ ł",
+ "ut ta",
+ "Ġê²ģ ëĭĪëĭ¤",
+ "Ġb az",
+ "Ġпо ÑĪ",
+ "Ġpe culiar",
+ "zy Äĩ",
+ "ĠEll ie",
+ "Ġlearn s",
+ "ĠKr ishna",
+ "Ġconse cut",
+ "Ġemp ath",
+ "ĠD in",
+ "Ġtrad ed",
+ "ĠBor is",
+ "ugg age",
+ "oll a",
+ "Ġназ в",
+ "Ġetern ity",
+ "Ġв п",
+ "è mes",
+ "Ġgra pp",
+ "b é",
+ "ĠпÑĢед ÑģÑĤав",
+ "ĠF C",
+ "į ëĭĪëĭ¤",
+ "e ven",
+ "ĠNebr aska",
+ "ortun e",
+ "Ġk arena",
+ "ĠAg ent",
+ "Ġst ing",
+ "ĠP I",
+ "Ġmunicip al",
+ "power ed",
+ "Ġconse gue",
+ "ĠMan chester",
+ "Ġrain y",
+ "Ġbl i",
+ "Ġk ost",
+ "Ġhal ten",
+ "ĠAh hh",
+ "ins ula",
+ "er ting",
+ "ĠاÙĦ Ùģ",
+ "Ġrel acion",
+ "Ġk omen",
+ "Ġd ome",
+ "Ġpri ests",
+ "ĠInt rodu",
+ "rop he",
+ "sh ore",
+ "vel t",
+ "clip se",
+ "ĠÑĢ ÑĥÑģ",
+ "×Ļ× ¡",
+ "Ġsab emos",
+ "ĠHoll and",
+ "og i",
+ "ank i",
+ "ĠM ats",
+ "Ġsm oked",
+ "ull ie",
+ "Ġeuro pe",
+ "ĠдейÑģÑĤв иÑĤелÑĮно",
+ "Ġbard ziej",
+ "Ġtransform ing",
+ "ĠE z",
+ "op ath",
+ "Ġìĸ¸ ëĭĪ",
+ "ĠÑģÑĤ ан",
+ "ằ ng",
+ "ั à¹ī",
+ "ĠO uch",
+ "Ġclear ance",
+ "ust ain",
+ "Ġsolid arity",
+ "Ġpro ving",
+ "ĠÐĺ н",
+ "ĠÑģ ÑĬ",
+ "Ġpro long",
+ "ад но",
+ "Ġs os",
+ "ĠDe al",
+ "Ġ17 0",
+ "m ons",
+ "Ġз ем",
+ "Ġlo gged",
+ "Ġlif elong",
+ "Ġsens ory",
+ "Ġbe hold",
+ "ĠF AR",
+ "èt ement",
+ "ĠFed eration",
+ "Ġdod ge",
+ "ĠSh ir",
+ "Ġdrag ons",
+ "ĠAr ctic",
+ "Äħ ż",
+ "Å į",
+ "Â º",
+ "Ġden ke",
+ "Ġpodr ÃŃa",
+ "co le",
+ "ÑĥлÑĮÑĤ аÑĤ",
+ "Ġsystem atic",
+ "ам а",
+ "ch os",
+ "Ġclin ics",
+ "ĠB S",
+ "Ġtal es",
+ "us ions",
+ "Ġí Ī¬",
+ "Ġpres ervation",
+ "Ġl ore",
+ "ĠProt est",
+ "á» Ľ",
+ "å¸ Ĥ",
+ "Ġacknowled ged",
+ "ĠIs aiah",
+ "ĠëķĮ ëĬĶ",
+ "Ġ× ĺ",
+ "Ġcompet itor",
+ "Ġadv ancing",
+ "z ip",
+ "Ġtent h",
+ "ĠLa ure",
+ "Ġh ints",
+ "Ġexerc ising",
+ "ŀ ľë",
+ "ĠIntell igence",
+ "u ated",
+ "OU T",
+ "op ed",
+ "Ġaut onomy",
+ "Ġbrand ing",
+ "ĠMediter ranean",
+ "Ñĸ к",
+ "Ġscrew driver",
+ "Ġsu pre",
+ "Ġst ap",
+ "Ġjurisd iction",
+ "ĠSetting s",
+ "Ġfore front",
+ "ĠF emale",
+ "com fort",
+ "Ġmultiplic ation",
+ "ĠMur ray",
+ "Ġbo b",
+ "ĠT as",
+ "Ġt ahu",
+ "Ġon un",
+ "et ter",
+ "Ġproph ets",
+ "l ag",
+ "Ġreven ues",
+ "Ġpr á",
+ "Ġupload ing",
+ "Ġmach inery",
+ "asc al",
+ "ĠEst á",
+ "ĠG oth",
+ "ĠB ald",
+ "ĠS aw",
+ "Ġstri pes",
+ "ìł ij",
+ "Ġpow in",
+ "æĹ¥ æľ¬",
+ "Ġhost ile",
+ "Ġdar um",
+ "Ġprevent ed",
+ "ожалÑĥй ÑģÑĤа",
+ "Ġalgun as",
+ "Ġhop eless",
+ "Ġz naj",
+ "Ġread ings",
+ "Ġcra ving",
+ "t at",
+ "ĠP ig",
+ "Ġli ar",
+ "çĪ ±",
+ "Ġmulti player",
+ "Ġd ale",
+ "ĠCour se",
+ "íģ ¼",
+ "ĠK ita",
+ "Ġcustom s",
+ "Ġrespond s",
+ "end ra",
+ "è¦ ĸ",
+ "Ġmet ro",
+ "Ñģ ол",
+ "Ġmitig ate",
+ "Ġopp ression",
+ "Ġ æĪijåĢij",
+ "qu inho",
+ "Ġam mo",
+ "Ġen fer",
+ "Ġp ony",
+ "Ġ ounces",
+ "° Ķ",
+ "ĠìĪĺ ê°Ģ",
+ "Ġdich o",
+ "ĠDe b",
+ "Ġwond ers",
+ "ĠRo ose",
+ "Ġpri zes",
+ "ĠA LEX",
+ "Ġthank fully",
+ "Ġtiss ues",
+ "ĠÑĢав но",
+ "ĠL una",
+ "intell igible",
+ "ĠìĻ ¸",
+ "ê° ij",
+ "ĠHe at",
+ "ĠÑģ ид",
+ "ĠQu i",
+ "Ġ ions",
+ "Ġaccommod ation",
+ "ä¾ ¿",
+ "ĠK art",
+ "ien st",
+ "Ġt arde",
+ "Ġso aked",
+ "ĠCase y",
+ "Ġì´ Ŀ",
+ "ĠÑĢ Ñĥб",
+ "Ġdifferent i",
+ "Ġleft over",
+ "Ġexch anges",
+ "sec ond",
+ "Ġfirst ly",
+ "Ġbuild er",
+ "ri en",
+ "Ġd w",
+ "Ġboun cing",
+ "? <",
+ "olog ÃŃa",
+ "we alth",
+ "Ġmed itate",
+ "ĵ¤ ìĿĺ",
+ "ĠC raft",
+ "è§ī å¾Ĺ",
+ "æĻ ®",
+ "ri v",
+ "ĠAgain st",
+ "Ġcer amic",
+ "esp ère",
+ "Ġcompet ent",
+ "ĠHop kins",
+ "Ġkil os",
+ "Ġgra vel",
+ "Ġpist on",
+ "Ġfriends hips",
+ "Ġesc re",
+ "Ġvo z",
+ "ĠGes ellschaft",
+ "Ġunter stüt",
+ "Ġmu j",
+ "Ġwarning s",
+ "p os",
+ "ĠProfess ional",
+ "w szy",
+ "od le",
+ "b ands",
+ "Ġteam work",
+ "stell ung",
+ "Ġd x",
+ "åį Ĭ",
+ "Ġatt orneys",
+ "Ġweit ere",
+ "ãħĭãħĭ ãħĭ",
+ "ĠOrig inal",
+ "×Ļ× Ĺ",
+ "Ġbroadcast ing",
+ "ĠпеÑĢв Ñĭй",
+ "uch i",
+ "Ġhe ure",
+ "Ġgra bs",
+ "ĠW OR",
+ "ĠPla id",
+ "M in",
+ "Ġp az",
+ "ĠP uis",
+ "um u",
+ "it ates",
+ "Ġco ats",
+ "Ġbu en",
+ "Ġhe ir",
+ "Ġpne um",
+ "ש ר",
+ "ens er",
+ "ĠJUD GE",
+ "Ġbl onde",
+ "á¹ Ľ",
+ "Ġg ak",
+ "Ġs ık",
+ "Ġquot ed",
+ "Ġequip o",
+ "Ġw ishing",
+ "ÃŃ cia",
+ "Ġver bs",
+ "çµ Ħ",
+ "ĠCanad ians",
+ "Ġgover ning",
+ "ĠEv ans",
+ "E uro",
+ "Ġgen res",
+ "Ġunters chied",
+ "ĠBeck y",
+ "³¼ ê²ĮìļĶ",
+ "Ġe inge",
+ "ĠRa ise",
+ "ol and",
+ "ĠStr ateg",
+ "Ġer es",
+ "ĠVeter ans",
+ "Ġbreak out",
+ "Ġsant é",
+ "Ġad el",
+ "Ġinvestig ated",
+ "Ġpe ur",
+ "Ġag ile",
+ "Ġrail road",
+ "ans ka",
+ "Ġе й",
+ "Ġexp os",
+ "ator ies",
+ "ĠCont ent",
+ "Ġtruth s",
+ "ĠTra il",
+ "Ġgu a",
+ "Ġp ores",
+ "Ġwrit ings",
+ "ĠU hr",
+ "ĠThat s",
+ "Ġic ing",
+ "O C",
+ "ĠProdu ction",
+ "Ġcar ne",
+ "IS S",
+ "Ġn inguém",
+ "n on",
+ "Ġv icious",
+ "×ķ× Ķ",
+ "Ġrecon nect",
+ "Ġcent res",
+ "ĠK em",
+ "Ġcre ase",
+ "ĠìĿ´ë ¯¸",
+ "айÑĤ еÑģÑĮ",
+ "Ġб оÑĢ",
+ "ĠHay ır",
+ "ĠÑģ Ñĥд",
+ "Ġún ica",
+ "owa ÅĤ",
+ "Ġad her",
+ "h ua",
+ "Z Z",
+ "Ġprecis o",
+ "Ġcurrent s",
+ "Ġseason ed",
+ "ĠIo T",
+ "ĠB ishop",
+ "è¨ Ī",
+ "st ed",
+ "ĠBern ard",
+ "ì¤ ĺ",
+ "æ² »",
+ "ĠGl enn",
+ "Ġktóry m",
+ "ื à¹Ī",
+ "Ġast rolog",
+ "ĠK ot",
+ "å¤ ľ",
+ "Ġparf ois",
+ "Ġfor wards",
+ "ĠW iÄĻ",
+ "ĠÎ ĺ",
+ "Ġn ano",
+ "è» į",
+ "s ub",
+ "ĠBr ill",
+ "Ġgr it",
+ "Ġc ited",
+ "g ado",
+ "Ġmel ts",
+ "Ġfor cé",
+ "âĸĪ âĸĪ",
+ "Ġb ajo",
+ "Ġdiscret ion",
+ "° °",
+ "at ivity",
+ "Ġsitu ated",
+ "ãĥ« ãĤ¯",
+ "Ñīе е",
+ "åľ° æĸ¹",
+ "ĠпÑĢин ÑĨип",
+ "am az",
+ "Ġaqu arium",
+ "Ġdissol ve",
+ "ĠGod s",
+ "S uper",
+ "Ġam id",
+ "z k",
+ "Ġ ãģĦ",
+ "éł IJ",
+ "amp f",
+ "Ġhel a",
+ "' !",
+ "Ġdevelopment al",
+ "ĠD ise",
+ "ĠÑĢабоÑĤ аеÑĤ",
+ "Ġsnaps hot",
+ "好 好",
+ "Õ ¸",
+ "ĠY ue",
+ "ĠH ulk",
+ "ĠDo om",
+ "ĠFel ix",
+ "Ġré f",
+ "M ale",
+ "ç· Ĭ",
+ "ph ants",
+ "EN S",
+ "ĠMe chan",
+ "ĠG olf",
+ "åĨį è¦ĭ",
+ "Ġgener osity",
+ "ät ze",
+ "Ġunlock ed",
+ "Ġ ãĤĴ",
+ "íĥ ģ",
+ "ocaly pse",
+ "Al right",
+ "Ġê° ľë",
+ "Ġ×IJ× ij׾",
+ "ĠKeep ing",
+ "Ġcollabor ating",
+ "ch ief",
+ "ĠFern ando",
+ "Ġchef s",
+ "ĠíĶ¼ë ¶Ģ",
+ "Ġsk ipped",
+ "Ġperson n",
+ "Ġax e",
+ "che z",
+ "Ġextract ion",
+ "ĠA V",
+ "ĠGib bs",
+ "Ġí ľ",
+ "Ġs ı",
+ "I AM",
+ "V iew",
+ "ĠGR ANT",
+ "Ġëª ¸",
+ "Ġver ification",
+ "Ġdep icted",
+ "ĠMo z",
+ "ou x",
+ "Ġt ul",
+ "Ġsc anner",
+ "Ġcomed ian",
+ "ĠVol ks",
+ "ĠJE FF",
+ "è¨Ĥ éĸ±",
+ "§ Ħ",
+ "Ġdistract ion",
+ "r á",
+ "ĠIN TER",
+ "Ġsin cer",
+ "Ġ×ŀ× ª",
+ "Ġש ׳",
+ "Ġconstruct ive",
+ "ar f",
+ "ĠëĪ Ħë",
+ "Ġe co",
+ "r amos",
+ "Ġrenew ed",
+ "in ement",
+ "ĠU b",
+ "ĠPe pper",
+ "ì§Ģ ê°Ģ",
+ "ĠDar win",
+ "Ġmerch and",
+ "Ġv árias",
+ "è ce",
+ "N G",
+ "ĠìľĦ íķ´ìĦľ",
+ "Ġак ÑĤив",
+ "ĠUn ters",
+ "ع ÙĦ",
+ "Ġint ric",
+ "omm a",
+ "ie ving",
+ "ĠCarol ine",
+ "åĵ ģ",
+ "ĠPR ES",
+ "Ġperform er",
+ "Ġaut our",
+ "ãģ¾ãģĽ ãĤĵ",
+ "Ġutter ly",
+ "Ġsynth esis",
+ "Ġles bian",
+ "Ġretrie ve",
+ "Ġmane ira",
+ "Ġimp air",
+ "Ġment oring",
+ "ĠSoul s",
+ "ĠGo Pro",
+ "ÑĢ аÑĤÑĮ",
+ "Ġc ose",
+ "ĠSS D",
+ "I RE",
+ "Ġup front",
+ "ĠA un",
+ "Ġgam er",
+ "Ġl itt",
+ "Ġag gression",
+ "ĠLike wise",
+ "ĠBet ty",
+ "ĠD art",
+ "ĠD LC",
+ "ish ment",
+ "ìŀ¥ ìĿĦ",
+ "Ġ 对",
+ "ç» ı",
+ "c ream",
+ "ĠBaby lon",
+ "Ġn ug",
+ "br ar",
+ "Ġa ynı",
+ "am ily",
+ "b ike",
+ "ahah aha",
+ "lo yd",
+ "Ġmir a",
+ "Ġper me",
+ "ĠG aming",
+ "Ġfirm ware",
+ "M a",
+ "Ġassist ed",
+ "at ics",
+ "Ġìķŀ ìľ¼ë¡ľ",
+ "ĠM ental",
+ "niej s",
+ "ĠI z",
+ "ow Äħ",
+ "Ġt ougher",
+ "Ġde ed",
+ "èĭ ¦",
+ "Ġsty lish",
+ "ĠTool s",
+ "ĠH amp",
+ "Ġsun screen",
+ "Ġartic ulate",
+ "i ye",
+ "и ÑĦ",
+ "ĠSp read",
+ "ĠHA VE",
+ "Ġsw irl",
+ "Ġspons oring",
+ "ä» ĭ",
+ "iov ascular",
+ "mes i",
+ "Ġrelax ation",
+ "ĠÑģво иÑħ",
+ "Ġmar gins",
+ "Ġsa ÄŁ",
+ "ĠPr ide",
+ "ĠÏĦοÏħ ÏĤ",
+ "и ÑĨи",
+ "en ci",
+ "Do es",
+ "Ġcor pse",
+ "Ġend urance",
+ "Ġí ŀĺ",
+ "ì¹ ´",
+ "Ġhair cut",
+ "Ġinterrupt ed",
+ "Ġwind y",
+ "ĠC aleb",
+ "Ïģ Ïĩ",
+ "ĠPour quoi",
+ "Ġhol istic",
+ "uc lear",
+ "ĠWho le",
+ "å£ «",
+ "A ct",
+ "Ġgall on",
+ "c ade",
+ "ĠReg ional",
+ "ro ads",
+ "ĠSch ne",
+ "á ng",
+ "Ġиз мен",
+ "ãĤĪ ãģŃ",
+ "Ġmen us",
+ "Ġspl itting",
+ "Ġpr iced",
+ "ĠÎ ĵ",
+ "Ġus ername",
+ "ĠÐŀ Ñĩ",
+ "Ġcomp ressed",
+ "y in",
+ "Ġguard ian",
+ "Ġgo of",
+ "Ġcheck list",
+ "Ġinter change",
+ "Ġexped ition",
+ "Ġex tern",
+ "Ġinfra red",
+ "eng o",
+ "Ġden ying",
+ "Ġpack ets",
+ "on ent",
+ "B B",
+ "ĠInc re",
+ "Ġsin i",
+ "ÃŁ er",
+ "è g",
+ "ma al",
+ "gen eration",
+ "Ġminor ities",
+ "Ġlle var",
+ "Ġnom ination",
+ "Ġcons id",
+ "Ġ×ľ× ¢",
+ "m uÅŁ",
+ "ĠEs c",
+ "Ġnumer ator",
+ "Ġka ik",
+ "Ġktóry ch",
+ "ies en",
+ "Ġv ê",
+ "ĠUS S",
+ "ĠPri vate",
+ "Ġод но",
+ "Ġal ém",
+ "ÃŃt ulo",
+ "Ġlim b",
+ "Ġforg iven",
+ "Ġdiscl osure",
+ "ÏĦ ί",
+ "Ġning ún",
+ "Ġtherapeut ic",
+ "Ġnegoti ating",
+ "ĠN ike",
+ "ense ful",
+ "Ġin cap",
+ "Ġflag ship",
+ "t own",
+ "â Ī",
+ "ĠÏĢ ολ",
+ "Ġwol ves",
+ "Ġviol ations",
+ "ĠAr nold",
+ "Ġinterven e",
+ "Ġhe ater",
+ "Ġrecurs os",
+ "Ġma id",
+ "ê² ¼",
+ "Ġдав айÑĤе",
+ "ĠCe lebr",
+ "Ġca pe",
+ "ĠSt y",
+ "ain en",
+ "s ite",
+ "b ij",
+ "Ġп олÑĮз",
+ "Ġfr amed",
+ "Ġpublish ers",
+ "ĠÑĩ ÑĥÑĤÑĮ",
+ "Ġtempt ation",
+ "Ġcert eza",
+ "Ġex empt",
+ "ìĬ ¹",
+ "se lling",
+ "ĠT ask",
+ "ho on",
+ "ĠC oc",
+ "ĠPark s",
+ "Ġrepet ition",
+ "ĠÑĤ Ñĥда",
+ "Ġens l",
+ "ĠdeÄŁ iÅŁ",
+ "ĠOr lando",
+ "ĠMain ten",
+ "æŃ ¢",
+ "oc ument",
+ "ĠH C",
+ "Ġscoot er",
+ "Ġнап иÑģ",
+ "Ġtight er",
+ "Ġte ase",
+ "Ġremo ves",
+ "Ġkij ken",
+ "ĠÑģÑĥ ÑīеÑģÑĤв",
+ "Ġth é",
+ "ĠвÑĭ глÑıд",
+ "Ġrel ieve",
+ "Ġmit ä",
+ "Ġstation ary",
+ "ö ff",
+ "p able",
+ "Ġar ter",
+ "Ġdé f",
+ "r ative",
+ "Ġcon ect",
+ "Ġsad dle",
+ "ĠD iane",
+ "Ġcomm emor",
+ "fend im",
+ "S ÃŃ",
+ "Ġíģ ´ë",
+ "Ġman ge",
+ "at te",
+ "Ġarrog ant",
+ "Ġrobot ic",
+ "Ġgi Ãł",
+ "æĺ¯ çļĦ",
+ "Ġneighbour hood",
+ "iss on",
+ "Ġдв иж",
+ "ĠR I",
+ "ĠNorm an",
+ "b rand",
+ "am ation",
+ "Ġraz or",
+ "Ġmur ders",
+ "ĠÑĤ Ñĥ",
+ "Ġwszystk im",
+ "Ġut ilities",
+ "Ġmicros cop",
+ "ê ¿",
+ "Ġda qui",
+ "oll ar",
+ "ĠÐĶав айÑĤе",
+ "Ġann ée",
+ "Ġkilomet res",
+ "Ġhom osexual",
+ "Ġarchitect s",
+ "ãģ¡ ãģ¯",
+ "Ġni ye",
+ "L ER",
+ "Ġmicro phones",
+ "ĠSt unden",
+ "Ġconsecut ive",
+ "iend a",
+ "v änd",
+ "D ER",
+ "Ġlif ts",
+ "ĠMe at",
+ "Ġsave z",
+ "íĸ Īëįĺ",
+ "M en",
+ "Ġdism ant",
+ "ê±°ë ¥¼",
+ "Ġins ulation",
+ "Ġsc all",
+ "Ġsp ooky",
+ "Ġpar c",
+ "Ġball et",
+ "ĠWhats App",
+ "Ġfr anc",
+ "Ġdeliber ate",
+ "Ġíħ Į",
+ "Ġm ars",
+ "ĠZ ur",
+ "P r",
+ "dis ciplinary",
+ "Ġobs ession",
+ "м е",
+ "Ġmarch ing",
+ "ĠEmer gency",
+ "ig uous",
+ "Ġs zy",
+ "ĠL ands",
+ "Ġboard ing",
+ "ĠпоÑĩ ÑĤи",
+ "Ġenv y",
+ "Ġcompassion ate",
+ "Ġmer ci",
+ "Ġdes irable",
+ "d ale",
+ "Ġcan ım",
+ "ĠAnt ar",
+ "tem ps",
+ "Ġconfig ured",
+ "ĠComp ared",
+ "ne h",
+ "ic ating",
+ "Ġnic kel",
+ "ÙĪ ÙĤ",
+ "Ùĥ ÙĪÙĨ",
+ "op es",
+ "Ġform ulas",
+ "ĠÐķ ÑģÑĤÑĮ",
+ "Ġpo bl",
+ "ĠP J",
+ "ĠL ud",
+ "ä»Ĭ åĽŀ",
+ "ĠBr id",
+ "ĠH og",
+ "ĠBr is",
+ "J en",
+ "Ġshad ing",
+ "ĠY as",
+ "Ġdistur bed",
+ "Ġrecomm ending",
+ "Ġc é",
+ "ĠH OW",
+ "ìĹĪ ìĸ´",
+ "Ġrevers ed",
+ "ĠInteresting ly",
+ "iox id",
+ "åħ Ń",
+ "Ġìĺ¤ ì¼ĢìĿ´",
+ "ế u",
+ "x x",
+ "Ġou ais",
+ "ĠYouT ubers",
+ "ĠR osa",
+ "ĠH aupt",
+ "j adi",
+ "Ġvlog s",
+ "Ġcult ura",
+ "ĠLeaders hip",
+ "ĠH ep",
+ "Ġill um",
+ "´ë ıĻ",
+ "Ġcustom ized",
+ "Ġmar ca",
+ "Ġqu atro",
+ "Ġн аг",
+ "ĠSpace X",
+ "ĠE igen",
+ "ast ing",
+ "ĠolduÄŁ u",
+ "Ġfor ts",
+ "ãģ ī",
+ "r iment",
+ "ien cia",
+ "Ġten ir",
+ "ro ffen",
+ "Ġ197 9",
+ "Ġc ie",
+ "ĠëIJĺ ê³ł",
+ "Ġes cri",
+ "ÏĮ ÏĤ",
+ "íı ¬",
+ "uz zy",
+ "C ong",
+ "ìĿ¸ ìĿ´",
+ "G reat",
+ "s il",
+ "é ch",
+ "ãģ¨ ãģĭ",
+ "Ġmult ic",
+ "ĠDis k",
+ "² ķ",
+ "Ġfaz la",
+ "Ġle vant",
+ "Ġab ajo",
+ "ur ry",
+ "st ru",
+ "Ġ먹 ëĬĶ",
+ "Ġaccess ory",
+ "Ġдв иг",
+ "ĠR id",
+ "20 19",
+ "Ġdown stream",
+ "æķ ¸",
+ "Ġk az",
+ "ut an",
+ "Ġchar coal",
+ "Ġa fect",
+ "w u",
+ "Ġcontext s",
+ "Ġfe ared",
+ "ĠìĦ ¤",
+ "Ġhist ories",
+ "Ġf as",
+ "ens ible",
+ "Ġcoco a",
+ "ill ar",
+ "ge ons",
+ "Ġspiritual ity",
+ "ĠP ew",
+ "Ġpharm acy",
+ "Ġpass ions",
+ "Ġb os",
+ "Ġall á",
+ "Ġthri ving",
+ "ĠRe act",
+ "Ġoccup y",
+ "Ġwithdraw al",
+ "Ġallow ance",
+ "ĠFra ktion",
+ "Ġbud dies",
+ "Ġid le",
+ "Ġdissol ved",
+ "Ġpreval ent",
+ "Ġmil itar",
+ "Ġsens ing",
+ "Ġpo jaw",
+ "Ġanc ora",
+ "Ġabund ant",
+ "Ġha irst",
+ "ãģĤ ãĤĮ",
+ "Ġtw ee",
+ "Ġnäch ste",
+ "ĠMöglich keit",
+ "Ġho o",
+ "uff icient",
+ "Ġfant ast",
+ "Ġed ible",
+ "Ġëĸ¨ ìĸ´ì",
+ "ìĽ ĥ",
+ "Ġve in",
+ "uc ci",
+ "Ġdevot ion",
+ "Ġconce aler",
+ "in come",
+ "Ġrecy cled",
+ "ĠìĬ¤í ĥĢ",
+ "Ġpont os",
+ "Ġdess us",
+ "Ġvé rit",
+ "Ġreflect ions",
+ "ĠA A",
+ "Ġtake away",
+ "b are",
+ "ĠCont act",
+ "e il",
+ "ĠHe ar",
+ "Ġmir ac",
+ "ĠGer ilim",
+ "ĠÑģам Ñĭй",
+ "Ġv ivo",
+ "Ġkilogram s",
+ "ĠCr im",
+ "û t",
+ "7 8",
+ "Ġsincere ly",
+ "ra z",
+ "Ġë³ µ",
+ "Ġarri v",
+ "Ġconcept ion",
+ "ĠPers ian",
+ "Ġsj äl",
+ "Ġst arring",
+ "ĠìķĦë ¬´",
+ "ĠFore ver",
+ "е ÑģÑĤÑĮ",
+ "Ġve il",
+ "Ġsubt it",
+ "od ka",
+ "ĠоÑĤно ÑĪ",
+ "Ġcook s",
+ "ен Ñı",
+ "K ay",
+ "Ġni ños",
+ "ĠPh one",
+ "Ġstitch ing",
+ "Ġfinger print",
+ "é¢ ĺ",
+ "λ ά",
+ "Ġded icate",
+ "ĠL ob",
+ "Ġblack s",
+ "ĠB le",
+ "b out",
+ "ĠÄij ang",
+ "Ġe ks",
+ "Ġsqu ash",
+ "ĠK ü",
+ "od i",
+ "Ġn Æ°á»Ľc",
+ "Ġvoy age",
+ "Ġplay ful",
+ "ĠØ¥ ÙĦÙī",
+ "an ic",
+ "Ġcondem n",
+ "ĠB öyle",
+ "ĠPol ize",
+ "ãĤ¿ ãĥ¼",
+ "Ġay uda",
+ "Ġp am",
+ "à¹Ħ à¸Ľ",
+ "ĠK athy",
+ "ед ин",
+ "нов а",
+ "Ġbr ig",
+ "eg er",
+ "Ġe agle",
+ "Ġvis ions",
+ "ĠíķŃ ìĥģ",
+ "Ġsh itty",
+ "Ġh ott",
+ "ĠBr itt",
+ "ut ors",
+ "ENT E",
+ "æĽ ²",
+ "Ġph on",
+ "ĠB ing",
+ "Ġпод деÑĢж",
+ "spr ing",
+ "æĸ ¯",
+ "et ten",
+ "Ġpil gr",
+ "Ġed iyor",
+ "енÑĤ Ñĭ",
+ "ag gio",
+ "Ġj ul",
+ "Ġcomp rend",
+ "te il",
+ "ĠØ ²",
+ "Ġperform ers",
+ "Ġinf amous",
+ "ĠM K",
+ "ç ª",
+ "æ³ ģ",
+ "ot le",
+ "e ff",
+ "ĠH ash",
+ "Ġcow ard",
+ "ĠB RA",
+ "ĠD D",
+ "Ġcom ida",
+ "Ġpl ata",
+ "Ġfl ap",
+ "ĠMe hr",
+ "rib ution",
+ "ĠY emen",
+ "Ġmyster ies",
+ "ĠÄ° yi",
+ "Ġst ell",
+ "Ġeyel iner",
+ "Ġdel es",
+ "Ġnail ed",
+ "Ġillness es",
+ "Ġst acks",
+ "Ġtrabaj ar",
+ "fl ower",
+ "ci u",
+ "Ġcr ude",
+ "Ġsubstant ially",
+ "Ġhome m",
+ "Ġnep hew",
+ "Ġstamp s",
+ "Ġcar bs",
+ "ÑĮ ÑĤе",
+ "mo oth",
+ "Ġtun nels",
+ "ac ie",
+ "æ³ ¢",
+ "ĠSe ñ",
+ "ĠH era",
+ "ĠìķĦëĭĪ ìĹIJìļĶ",
+ "ĠWy oming",
+ "ĠHD MI",
+ "ĠL is",
+ "u ción",
+ "Ġste er",
+ "о Ñİ",
+ "иÑĤ а",
+ "N T",
+ "Ġìĸ¼êµ ´",
+ "Ġpal ms",
+ "Ġne on",
+ "ов аниÑı",
+ "Ġfilter ing",
+ "Ġjou er",
+ "ĠH ö",
+ "Ġне Ñģ",
+ "ê²ł ìĸ´ìļĶ",
+ "Ġ8 1",
+ "Ġstory line",
+ "Ġprz ep",
+ "Ġthank ing",
+ "ĠBo eing",
+ "Ġsoft ly",
+ "j em",
+ "алÑĮ нÑĭÑħ",
+ "Ġflash light",
+ "Ġп Ñĥ",
+ "ĠW OMAN",
+ "ắ c",
+ "ÃŃ ch",
+ "Ġlux urious",
+ "Ġw ün",
+ "Ġimpact ful",
+ "Ġcons on",
+ "re u",
+ "ir ring",
+ "if ter",
+ "Ġconstitu ents",
+ "èIJ ½",
+ "Ġ9 4",
+ "ĠT ou",
+ "g om",
+ "ĠìĥĿê°ģ ìĿĦ",
+ "Ġstere otypes",
+ "Ġmoż li",
+ "åĪĨ 享",
+ "Ĥ ¨",
+ "Ġpencil s",
+ "ĠÑģл ож",
+ "Ġih rem",
+ "ĠBes ch",
+ "ĠK oh",
+ "ĠEnt scheid",
+ "Ġle k",
+ "Ġför s",
+ "Ġtotal mente",
+ "Ġlive ly",
+ "Ġent ropy",
+ "Ġdisc ern",
+ "ĠÐĹ Ð½Ð°",
+ "Ġdo v",
+ "Ġmyth ology",
+ "è¨ĺ å¾Ĺ",
+ "apan ese",
+ "Ġapprox imate",
+ "аÑĤ ив",
+ "if iable",
+ "ĠSe o",
+ "åĢ Ĵ",
+ "´ìĭ¬ íŀĪ",
+ "Ġìĺ ·",
+ "Ġtempor al",
+ "Ġi T",
+ "Ġest at",
+ "к им",
+ "Ġspr ink",
+ "Ġgr und",
+ "Ġinfant ry",
+ "Ġsch affen",
+ "ç´ Ħ",
+ "Ġan k",
+ "ri ages",
+ "ĠYe on",
+ "ĠMor oc",
+ "Ġinv asive",
+ "ģ Ķ",
+ "Ġparent ing",
+ "ĠR is",
+ "ib ile",
+ "Ġmod s",
+ "å½ ¢",
+ "ĠпÑĢов еÑĢ",
+ "ĠTh ing",
+ "ĠWhere ver",
+ "Ġacknowled ging",
+ "Ġpa wn",
+ "um mer",
+ "or b",
+ "6 9",
+ "Ġretr ouve",
+ "Ġrel ies",
+ "ĠHigh way",
+ "Ġa we",
+ "ãģ§ãģĻ ãģĭ",
+ "ita ire",
+ "Ġapplic ant",
+ "Ġais le",
+ "w orm",
+ "Ġpay load",
+ "Ġcar re",
+ "ĠB ach",
+ "æł ¼",
+ "Ġì¹ľ 구ë",
+ "ни е",
+ "Ġit ÃŃs",
+ "onna ise",
+ "s ol",
+ "èı ¯",
+ "alg ia",
+ "Ġrock ing",
+ "Ġbest en",
+ "rit es",
+ "^ ^",
+ "ин ой",
+ "Ġba ixo",
+ "Ġ기 ìĸµ",
+ "оÑĤ ÑĢи",
+ "s im",
+ "Ġinc arn",
+ "ëĭ¤ ìĿĮ",
+ "Ġl ick",
+ "s ided",
+ "Ġ7 1",
+ "f order",
+ "Ġreson ance",
+ "Ġte gen",
+ "Ġmet aph",
+ "ows er",
+ "Ġ×IJ× ł×Ĺ׳×ķ",
+ "? ãĢį",
+ "Ġsp ielen",
+ "Ġvoll ey",
+ "ĶìĿ´íģ¬ ìĹħ",
+ "lo oked",
+ "Ġsent enced",
+ "Ġmultip lying",
+ "Ġide als",
+ "Ġwahr scheinlich",
+ "Ġdepos its",
+ "bil ir",
+ "Ġeff et",
+ "ill on",
+ "Īë §Į",
+ "Ġtestim on",
+ "Ġz awsze",
+ "ĠпÑĢоÑĨ еÑģÑģ",
+ "ĠL av",
+ "ä¸į éĮ¯",
+ "Ġtrava iller",
+ "Ġla isse",
+ "ĠMount ains",
+ "ĠÑĢ об",
+ "Ġexam ined",
+ "it us",
+ "W as",
+ "л Ñĭ",
+ "Ġattrib uted",
+ "ĠìĬ ¹",
+ "ĠBar on",
+ "Ġg ep",
+ "Ġatt ent",
+ "ĠColl ection",
+ "Ġthe at",
+ "ĠC ai",
+ "Ġwell s",
+ "Ġhuman o",
+ "çĹ ħ",
+ "ĠH ast",
+ "ĠÑħоÑĤ Ñı",
+ "cz as",
+ "Ġperm its",
+ "Ġle gg",
+ "Ġe po",
+ "ĠF en",
+ "Ġth i",
+ "ĠF oi",
+ "Ġé lect",
+ "Ġ8 3",
+ "Ġover th",
+ "Ġ è¬Ŀè¬Ŀ",
+ "Ġten ant",
+ "è² ·",
+ "N ext",
+ "Ġpra ised",
+ "sec urity",
+ "ĠImp act",
+ "为 ä»Ģä¹Ī",
+ "Ġv ouch",
+ "Ġneg ó",
+ "Ġun ve",
+ "Ġcritic ize",
+ "ĠKen ya",
+ "Ġtact ic",
+ "Ġlo gr",
+ "Ġpo is",
+ "Ġpap a",
+ "spe aks",
+ "ðŁ ij",
+ "isp ers",
+ "Ġsur plus",
+ "Ġcold er",
+ "åį Ĺ",
+ "åIJ ¬",
+ "pl ets",
+ "ĠV ienna",
+ "ĠLe ad",
+ "Ġaer ial",
+ "ĠT ah",
+ "енÑĤ ов",
+ "ĠGree ks",
+ "C am",
+ "Ġmá xim",
+ "Ġk uin",
+ "ch io",
+ "Ġdemonst rates",
+ "an os",
+ "ĠC ert",
+ "ĠÑį н",
+ "Ġblog s",
+ "ĠìĦľ ìļ¸",
+ "Ġbe ams",
+ "ик ов",
+ "Ġprompt ed",
+ "Ġfright ening",
+ "ĠPors che",
+ "ãģĪ ãģ¦",
+ "lar ını",
+ "Ġch illing",
+ "is phere",
+ "Ġfl ashing",
+ "ĠK ard",
+ "b read",
+ "Ġex h",
+ "Ġty cker",
+ "Ġec ological",
+ "ĠMa e",
+ "Ġ×ŀ×IJ ×ķ×ĵ",
+ "ĠëĤ ĺëıĦ",
+ "л он",
+ "ys s",
+ "Ġper gunt",
+ "Ġpri x",
+ "izz ard",
+ "Ġcan cers",
+ "Ġ9 1",
+ "s usp",
+ "ĠIt em",
+ "ÅŁ a",
+ "Ġp est",
+ "Ġtak Äħ",
+ "Ġl ymph",
+ "ĠPat ri",
+ "f ill",
+ "Ġrec onna",
+ "Ġoptim ism",
+ "Ġmim ic",
+ "Ġì² ľ",
+ "ĠMad ame",
+ "oc y",
+ "l ining",
+ "åijĬ 訴",
+ "erm e",
+ "Ġfold ers",
+ "Ġcz ÅĤ",
+ "uch ar",
+ "Ġcur so",
+ "Ġbre ach",
+ "ни ÑĤÑĮ",
+ "Ġp amiÄĻ",
+ "Ġel ig",
+ "Ġaut op",
+ "F low",
+ "Ġprogram med",
+ "ĠPro cess",
+ "Ġfig ur",
+ "ĠS F",
+ "ĠE les",
+ "Ġprogram mes",
+ "Ġdiz zy",
+ "ìĭľ ê°Ħ",
+ "Ġли бо",
+ "Ġsn iff",
+ "ĠSeb astian",
+ "ĠH ye",
+ "Ġ4 000",
+ "Ġperm ite",
+ "æ¢ Ŀ",
+ "Ġза Ñī",
+ "Ġgu it",
+ "ĠD ais",
+ "Ġaccord ance",
+ "Ġmod ular",
+ "ogene ous",
+ "æĭ į",
+ "Ġpou quinho",
+ "Ġart illery",
+ "Ġlub ric",
+ "Ġvol can",
+ "ĠN H",
+ "ðŁ ¤",
+ "Ġde an",
+ "R h",
+ "Ġminist re",
+ "åĿ IJ",
+ "ĠIn v",
+ "ĠBul gar",
+ "ĠD aten",
+ "è İ",
+ "I m",
+ "Ġorigin ated",
+ "ĠN ixon",
+ "inte gr",
+ "Ġlack s",
+ "ĠN acht",
+ "ìĸ´ë Ĥĺ",
+ "cam era",
+ "Ġrad ish",
+ "ki ye",
+ "Ġang es",
+ "Ġpré f",
+ "j uk",
+ "ĠBe e",
+ "ĠB U",
+ "ĠвоÑģ п",
+ "ĠB T",
+ "ê mes",
+ "ĠSt ück",
+ "ĠIn k",
+ "æĪĸ èĢħ",
+ "ĠSerge ant",
+ "ĠMult ip",
+ "Ġhiç bir",
+ "ĠС ам",
+ "ĠD é",
+ "ol ph",
+ "ìĸ ¸",
+ "Ġimp at",
+ "ĠìķĬ ê³ł",
+ "ĠÑĤак ого",
+ "ĠнавеÑĢ ное",
+ "Ġunpredict able",
+ "Ġm end",
+ "ĠìĹĨ ìĸ´ìļĶ",
+ "Ġjakie ÅĽ",
+ "Ġann i",
+ "Ġdon né",
+ "ĠK irsty",
+ "Ġrectang ular",
+ "Ġempez ar",
+ "ĠEx change",
+ "ê° Ķ",
+ "Ġé conom",
+ "ãģĵ ãĤĵ",
+ "el in",
+ "re ibt",
+ "Ġ×Ķ× ¤",
+ "Ġc emetery",
+ "Ġespañ ol",
+ "ol in",
+ "лÑİ Ð´",
+ "Ġgr âce",
+ "all en",
+ "ĠPh ilos",
+ "ĠEr st",
+ "Ġìĥ Ī",
+ "ĠV id",
+ "G ive",
+ "O H",
+ "μ ο",
+ "ĠP are",
+ "Ġmetabol ism",
+ "Ġma ple",
+ "Ġax le",
+ "ĠD y",
+ "Ġkomm e",
+ "Ïİ Î½",
+ "Ġgreat ness",
+ "Ġver ified",
+ "Ġsp é",
+ "ĠFahren heit",
+ "ĠB ren",
+ "ĠConf eder",
+ "Ġhist oire",
+ "Ġelimin ating",
+ "ĠAd ding",
+ "ĠAb i",
+ "æĿ İ",
+ "Ġhospital ity",
+ "t im",
+ "Ġbon ito",
+ "Ġpart es",
+ "ĠдÑĢÑĥг иÑħ",
+ "ĠSh ay",
+ "ĠS ed",
+ "Ġreg rets",
+ "Ñı ми",
+ "Ġten ants",
+ "éĢ Ł",
+ "ĠP TS",
+ "Ġdev i",
+ "ĠL ate",
+ "ue z",
+ "Ġsö yl",
+ "ãĤ »",
+ "Ġìŀ¬ë °Į",
+ "Ġtogg le",
+ "Ġmas king",
+ "алÑĮ ного",
+ "Ġpers ön",
+ "Ġamer ican",
+ "f ik",
+ "ĠR GB",
+ "ens on",
+ "ĠK A",
+ "ww ww",
+ "ĠÑĢ ег",
+ "met ics",
+ "Ġeduc ator",
+ "ãĤ· ãĥ«ãĤ¯",
+ "p ark",
+ "елÑĮ зÑı",
+ "ar us",
+ "ÑĢ еÑĤ",
+ "Ġfe ito",
+ "Ġcho ir",
+ "Ġlar go",
+ "Ġe ens",
+ "Ġwat ts",
+ "ĠSing le",
+ "Ġsuscept ible",
+ "ic er",
+ "Ġв клÑİÑĩ",
+ "Ġp us",
+ "íĻ ĺ",
+ "E ng",
+ "Ġfant as",
+ "Ġspecific ation",
+ "Ġconfront ed",
+ "ĠColumb us",
+ "ив еÑĤ",
+ "ar ım",
+ "Ġcaffe ine",
+ "mun ition",
+ "Ġmig rants",
+ "l ide",
+ "it ations",
+ "ĠG eme",
+ "Ạ«",
+ "Ġpl anner",
+ "Ġstim ulate",
+ "Ġapro xim",
+ "ce u",
+ "ĠN om",
+ "Ġv og",
+ "ĠÑĢ аÑģÑĤ",
+ "Ġense ñ",
+ "Ġsell ers",
+ "Ġgut en",
+ "z d",
+ "C al",
+ "Ġdescri pt",
+ "Ġrecon ciliation",
+ "z inho",
+ "á¹ĩ a",
+ "ãģĺãĤĥ ãģĤ",
+ "acy j",
+ "ĠCO L",
+ "s aw",
+ "ĠíĻķ ìĿ¸",
+ "Ġvar it",
+ "Ġpartner ing",
+ "Ġdet ention",
+ "Ġbomb ing",
+ "c lapping",
+ "ien cies",
+ "ond u",
+ "AM E",
+ "Ġê°Ļ ìĬµëĭĪëĭ¤",
+ "c ÃŃa",
+ "ĠпоÑģ ÑĤо",
+ "ĠAS MR",
+ "Ġhome page",
+ "Ġsi è",
+ "an tha",
+ "ĠP oll",
+ "Ġ igen",
+ "cy ch",
+ "Ġê°ij ìŀIJ기",
+ "Ġconsider ably",
+ "ä»ĸ çļĦ",
+ "ĠAr ist",
+ "Ġwith stand",
+ "Ġqual itative",
+ "ĠK raft",
+ "ĠÑį лекÑĤ",
+ "ĠBe ad",
+ "екÑĤ ив",
+ "Ġcr ushing",
+ "ì³ IJ",
+ "Ġnav y",
+ "ÙĪ Úº",
+ "s ho",
+ "Ġo ak",
+ "ipp ers",
+ "Ġso ils",
+ "Ġpig ment",
+ "Ġev itar",
+ "ãĥ ĩ",
+ "Ġf use",
+ "ĠD ale",
+ ": \"",
+ "Ġcompl ètement",
+ "Ġke l",
+ "๠Ĩ",
+ "Ġqu atre",
+ "ĠU M",
+ "Ġë§ IJë",
+ "æł ¹",
+ "ÃŃ r",
+ "Ġle isure",
+ "ĠH ousing",
+ "Ġfold s",
+ "est ion",
+ "AR S",
+ "Ġm ash",
+ "urp ose",
+ "Ġaccum ulated",
+ "ĠSt uff",
+ "èª ŀ",
+ "Ġtap es",
+ "ĠÑģ илÑĮно",
+ "ĠLO VE",
+ "Ġ198 2",
+ "Ġsc ars",
+ "Ġcapital ist",
+ "ĠN ed",
+ "Ġsoft en",
+ "Ġnot ably",
+ "Ġforcé ment",
+ "ĠRa um",
+ "Ġнеоб Ñħод",
+ "Ġtrad emark",
+ "Ġfert ig",
+ "Ġ? !",
+ "æĹ ł",
+ "Ġreinfor ced",
+ "Ġre charge",
+ "ĠPut ting",
+ "Ġvill ains",
+ "Ġhand ic",
+ "Ġadvertis ement",
+ "ت ÙĬ",
+ "ĠÑģ Ñĥм",
+ "ĠR iley",
+ "×ķ× ij×",
+ "äº ¬",
+ "O s",
+ "Ø§Ø ²",
+ "B oy",
+ "Ġsqu ish",
+ "ock et",
+ "Ġtest ify",
+ "æ¼ Ķ",
+ "Ġ×ľ× ŀ×",
+ "Ġм аÑģÑģ",
+ "man uel",
+ "ĠArk ansas",
+ "if fe",
+ "Ġanalyst s",
+ "ĠDe af",
+ "Ġj ó",
+ "Ġgrocer ies",
+ "ĠWhe el",
+ "ĠÑĢ иÑģ",
+ "Ġc òn",
+ "ĠC ob",
+ "Ġpris ons",
+ "è ve",
+ "ĠCab inet",
+ "Ġpos ed",
+ "Ġguer re",
+ "ĠL loyd",
+ "Ġcl erk",
+ "Ġcr ises",
+ "ĠSh o",
+ "ĠO re",
+ "ĠFoot ball",
+ "ĠAd vis",
+ "ĠZh eng",
+ "è į",
+ "ĠAM Y",
+ "Ġun for",
+ "Ġmon aster",
+ "Ġcomp ile",
+ "Ġimm ortal",
+ "at able",
+ "Ġpar ano",
+ "Ġt iver",
+ "ĠStep h",
+ "ĠFu ÃŁ",
+ "Ġdisc ontin",
+ "Ġr ipe",
+ "Ġhack ing",
+ "Ġs iendo",
+ "Ġsegu ro",
+ "alt res",
+ "Ġand eres",
+ "Ġë ¦¬ë",
+ "Ġexp orts",
+ "æŃ ¥",
+ "Ġtab ii",
+ "Ġ기 ëĭ¤ë",
+ "Ġbother ing",
+ "Ġpick le",
+ "ĠBRI AN",
+ "Ġalt ar",
+ "ĠпÑĢи б",
+ "Ġtransfer ring",
+ "ĠV ors",
+ "ĠÙĩ ÙĪ",
+ "ĠZ a",
+ "ĠFr ances",
+ "Ġbrow se",
+ "em it",
+ "Ġche wing",
+ "ĠFred dy",
+ "Ġedit ors",
+ "ä lle",
+ "Ġí ĮĢ",
+ "ĠS que",
+ "ĠC ultural",
+ "aw k",
+ "ĠS ache",
+ "ĠCar bon",
+ "ắ t",
+ "F L",
+ "ĠN GO",
+ "pe ÅĤ",
+ "ĠS ou",
+ "Ġh vor",
+ "un intelligible",
+ "Ġë² ķ",
+ "ĠÂ °",
+ "i in",
+ "Ġ×¢ ×Ŀ",
+ "Ġder rière",
+ "Ġczy m",
+ "ĠAp ost",
+ "Ġregard er",
+ "Ġag rade",
+ "ĠC andy",
+ "Ġma re",
+ "Ġintrodu ces",
+ "bird s",
+ "Ġuniqu ely",
+ "Ġm uk",
+ "Ġcook er",
+ "Ġcrew s",
+ "Ġje ito",
+ "ER T",
+ "¶ Ħë",
+ "n isse",
+ "Ġe f",
+ "Ġcart e",
+ "ĠY ak",
+ "ĠP AT",
+ "и но",
+ "bok ki",
+ "Ġm ates",
+ "Ġdist int",
+ "Ġì½Ķë¡ľ ëĤĺ",
+ "Ġy ıl",
+ "Ġκ άν",
+ "Ġconfigur ations",
+ "eng a",
+ "re cht",
+ "H appy",
+ "ãĤĦ ãģ£ãģ¦",
+ "in vest",
+ "Ġreconst ruct",
+ "ĠÑįÑĤ омÑĥ",
+ "Ġmos que",
+ "ra um",
+ "Ġvoy ez",
+ "ĠN BC",
+ "ĠìŀIJ ìĭł",
+ "Ġstur dy",
+ "Ġк ап",
+ "Ġans ch",
+ "al id",
+ "Ġmas ih",
+ "ĠR EP",
+ "Ġì½ Ķë",
+ "Ġded uct",
+ "Ġsal ir",
+ "w urf",
+ "il ot",
+ "ĠM utter",
+ "old s",
+ "ĠF EMA",
+ "ĠB ib",
+ "Ġneighb oring",
+ "Ġbl iss",
+ "Ġíĺ ¼",
+ "ли ÑģÑĮ",
+ "ĠÑĤÑĢ еб",
+ "Ġ å°±æĺ¯",
+ "Ġgren ade",
+ "Ġe gal",
+ "Ġfin ely",
+ "Ġpet als",
+ "Ġke er",
+ "Ġch yba",
+ "Ġsk ipping",
+ "Ġth irteen",
+ "Ġgrav y",
+ "ĠS AT",
+ "6 1",
+ "Ġн ог",
+ "Ġmin s",
+ "IT E",
+ "Ġso zial",
+ "íķĺë ©´ìĦľ",
+ "rukt ur",
+ "Ġвозм ож",
+ "Ġоп ÑıÑĤÑĮ",
+ "Ġar th",
+ "ĠCub an",
+ "Ġtre asures",
+ "Ġfertil izer",
+ "Ġawak ening",
+ "Ġë°± ìĭł",
+ "Ġr all",
+ "Ġdep ict",
+ "ĠP ablo",
+ "Ġninete en",
+ "Ġw att",
+ "Ġentire ty",
+ "K S",
+ "ĠWood s",
+ "S ch",
+ "ĠÚ© ÙĪ",
+ "ĠD ry",
+ "ãģ ŀ",
+ "u ve",
+ "Ġreconst ruction",
+ "Ġanat omy",
+ "Īë ¥¼",
+ "Ġb aba",
+ "Ġlisten er",
+ "Ġshar pen",
+ "ĠPer u",
+ "ĠвÑĭ з",
+ "Ġrecre ation",
+ "Ġiniti ate",
+ "Ġcal or",
+ "ĠN aj",
+ "ge e",
+ "ĠFe els",
+ "ĠSnap chat",
+ "ĠT et",
+ "ĠN est",
+ "ĠD af",
+ "ĠFin ish",
+ "ĠÑĤак им",
+ "ú c",
+ "iz ens",
+ "Ġsp ins",
+ "Ġemb ry",
+ "Ġpass ages",
+ "Ġc ient",
+ "Ġjust ification",
+ "ä»ĸ 說",
+ "Ġolm az",
+ "Ġflood ed",
+ "Ġemo ji",
+ "Ġembr acing",
+ "Ġdisc ard",
+ "ĠBas ic",
+ "ag og",
+ "ĠìľĦ íķ´",
+ "Ġas ylum",
+ "er in",
+ "Ġf im",
+ "Ġnin ja",
+ "Ġautom ate",
+ "Ġaller gic",
+ "ÿÿ ÿÿ",
+ "am am",
+ "Ġм аÑĢ",
+ "ĠO i",
+ "ä us",
+ "Ġin duct",
+ "ĠB EN",
+ "Ġz ÅĤ",
+ "Ġkaż dy",
+ "ĠAM P",
+ "n ÄĽ",
+ "S ure",
+ "Ġqu il",
+ "Ġespe c",
+ "ro k",
+ "BS CRI",
+ "Ġlie be",
+ "p us",
+ "ach sen",
+ "Ġcr icket",
+ "ëĬ IJ",
+ "ĠFr ame",
+ "ekk ür",
+ "ar b",
+ "Ġp ÅĻ",
+ "иÑģ Ñģ",
+ "Ġzeg gen",
+ "Ġdou bles",
+ "ĠD re",
+ "t est",
+ "ins p",
+ "bo ys",
+ "Ġm ão",
+ "ĠVer se",
+ "Ġmus cular",
+ "ĠMA LE",
+ "Ġd ulu",
+ "Ġoccas ional",
+ "L o",
+ "conom ic",
+ "Ġv ak",
+ "Ġrem edy",
+ "å¤ ł",
+ "ĠâĻªâĻª âĻª",
+ "ve m",
+ "Ġön em",
+ "ĠkarÅŁ ı",
+ "ĠSh arp",
+ "h ur",
+ "Ġë°© ë²ķ",
+ "Ġgrand son",
+ "Ġakt iv",
+ "ĠTh rones",
+ "ĠìķĪ ìĹIJ",
+ "Ġto ts",
+ "Ġsub d",
+ "ĠPa ula",
+ "Ġgra ves",
+ "ĠB rent",
+ "Ġник ÑĤо",
+ "Ġsö z",
+ "Ġcre c",
+ "ĠVlad imir",
+ "çĸ «",
+ "Ġп ой",
+ "Ġ\" -",
+ "Ġp sy",
+ "at ri",
+ "id an",
+ "Ġa ún",
+ "Ġstandard ized",
+ "ì¹ ĺë",
+ "Ġк ÑĢов",
+ "ĠZh u",
+ "s omething",
+ "Ġ7 50",
+ "Ġmuj eres",
+ "Ġa it",
+ "éĹ ´",
+ "ag u",
+ "Ġcorrect ed",
+ "ik ka",
+ "el ed",
+ "ĠCare er",
+ "ow ym",
+ "Ġroomm ate",
+ "Ġdescend ants",
+ "ĠNapole on",
+ "ĠÐĶ о",
+ "íĸĪ ìĸ´ìļĶ",
+ "Ġbun un",
+ "ĠMich a",
+ "ç· ļ",
+ "Ġdesc ob",
+ "P I",
+ "Ġpalab ra",
+ "Ġtrack ed",
+ "Ġdepend ence",
+ "ĠBar ack",
+ "åģ ĩ",
+ "Ġfert ility",
+ "ĠSouth west",
+ "Ġincom plete",
+ "Ġcomun ic",
+ "Ġcomp ris",
+ "ĠRest aur",
+ "Ġac ron",
+ "κ α",
+ "Ġapprent ices",
+ "Ġmus st",
+ "ĠA br",
+ "Ġpent ru",
+ "ĠCons ort",
+ "ĠAve c",
+ "Ġdum plings",
+ "L R",
+ "Ġwszystk ie",
+ "Ġsw amp",
+ "н ев",
+ "ugg le",
+ "Ġwater color",
+ "Ġprot on",
+ "ĠEspa ña",
+ "ock ing",
+ "ов ал",
+ "Ġtak im",
+ "V ery",
+ "Ġdement ia",
+ "ĠÅŁey i",
+ "J ac",
+ "ĠMac Book",
+ "ĠL iv",
+ "ffic ients",
+ "ĠH unt",
+ "Ġover lay",
+ "æĦŁ 覺",
+ "ĠSky pe",
+ "p unkt",
+ "Ġconf ined",
+ "ĠAd rian",
+ "ر Ùĥ",
+ "ĠJe ep",
+ "Ġenqu anto",
+ "Ġan est",
+ "оÑĤ веÑĤ",
+ "Ġм енÑĮ",
+ "Ġirrig ation",
+ "á»ij n",
+ "Ġeight een",
+ "ĠP on",
+ "Ġresc ued",
+ "Ġ198 3",
+ "r ü",
+ "ja e",
+ "ĠJe ong",
+ "Ġamazing ly",
+ "ĠF DP",
+ "Ġback stage",
+ "c ue",
+ "ĠÏĥÏĦη ν",
+ "ĠاÙĦØ µ",
+ "Ġlivest ock",
+ "ĠW arner",
+ "Ġmaj ors",
+ "ãĥģ ãĥ£",
+ "Ġcooper ative",
+ "ĠBr ady",
+ "ra ined",
+ "rie b",
+ "Ġ×ij× ŀ×",
+ "Ġдов олÑĮно",
+ "ĠF E",
+ "Ġle aked",
+ "ĠMerc ury",
+ "Ġpersu ade",
+ "Ġtransform er",
+ "ĠNor weg",
+ "ĠìĹ¬ë Ł¬",
+ "Ġzrobi Äĩ",
+ "Ġcard iovascular",
+ "ĠCr ash",
+ "Ġg ossip",
+ "а ÑģÑĤÑĮ",
+ "Ġì ª½",
+ "Ġsw ept",
+ "ĠH orn",
+ "ĠAt é",
+ "Ġbu kan",
+ "ĠK aw",
+ "K Y",
+ "ĠSt ories",
+ "G ary",
+ "Ġgard ening",
+ "ĠQuick ly",
+ "ĠFal con",
+ "Ġov at",
+ "c ı",
+ "ĠCom plet",
+ "ĠD ate",
+ "ĠпÑĢ им",
+ "Ġlä uft",
+ "ĠAud rey",
+ "ĠW ent",
+ "Ġpel ÃŃcul",
+ "Ġcar riage",
+ "Ġun acceptable",
+ "ny mi",
+ "ĠÑģл ÑĭÑĪ",
+ "Ġter re",
+ "uell ement",
+ "EE EE",
+ "Ġpharm ac",
+ "h ões",
+ "Ġz ich",
+ "Ġmig rate",
+ "ĠF ry",
+ "ñ ana",
+ "ĠM uito",
+ "EO VER",
+ "Ġfort ress",
+ "ĠCom pan",
+ "ĠJ SON",
+ "ord nung",
+ "Ġw arto",
+ "Ġun gef",
+ "ìħĶ ìĦľ",
+ "ĠÑĢ ок",
+ "Ġpad dle",
+ "J ared",
+ "Ġsubm itting",
+ "Ġl atch",
+ "Ġf ug",
+ "Ġк оÑģ",
+ "ĠE f",
+ "Ġlaunch es",
+ "Ġf t",
+ "ote chn",
+ "Ġtrave lled",
+ "ا Ùģ",
+ "éģ ķ",
+ "Ġpro ch",
+ "Ġded im",
+ "8 3",
+ "Ġreb ound",
+ "ĠL U",
+ "p ath",
+ "ĠÑģп ÑĢав",
+ "Ġö l",
+ "ĠíĤ ¤",
+ "Ġpriv at",
+ "Ġtr actor",
+ "ĠAtt ention",
+ "S er",
+ "Ġcos es",
+ "á ria",
+ "p al",
+ "ĠìĿ Ģ",
+ "Ġsuccess or",
+ "Ġconnect ors",
+ "ĠÑĥÑģÑĤ анов",
+ "Ġgen ocide",
+ "Ġsufficient ly",
+ "ĠA ixò",
+ "Ġstabil ize",
+ "Ġcon gest",
+ "Ġcar ving",
+ "Ġz ost",
+ "ĠбÑĭ ÑģÑĤÑĢо",
+ "Ġshort est",
+ "Ġli vel",
+ "Ġ8 9",
+ "éģ Ĭ",
+ "Ġer k",
+ "Ġport raits",
+ "ॠĢ",
+ "è ĺ",
+ "bo at",
+ "ll ah",
+ "AN C",
+ "Ġempir ical",
+ "ĠE cho",
+ "ĠNeder land",
+ "è¿Ļ ä¹Ī",
+ "N et",
+ "Ġcuid ado",
+ "ĠR oma",
+ "Ġc alf",
+ "Ġgi ants",
+ "ĠExpl orer",
+ "ĠColl ect",
+ "al ition",
+ "ĠDest iny",
+ "Ġaus ge",
+ "ĠE du",
+ "ĠC lo",
+ "Ġear rings",
+ "ĠTr ack",
+ "ĠR OS",
+ "ĠBe lle",
+ "çĻ ¾",
+ "Ġpu eda",
+ "Ġday time",
+ "Ġsupp lier",
+ "ĠS V",
+ "ĠEx hale",
+ "Ġgal era",
+ "c ourse",
+ "Ġcent imeter",
+ "ĠB ast",
+ "m ud",
+ "Ġsang at",
+ "ĠPhys ical",
+ "Ġpriv ately",
+ "Ġtr ata",
+ "lyn n",
+ "ill i",
+ "Ġë© ĶìĿ´íģ¬ìĹħ",
+ "Ġcryst all",
+ "Ġpod s",
+ "ả n",
+ "in ator",
+ "ĠRec ords",
+ "å® ĺ",
+ "ÄŁim iz",
+ "isse ment",
+ "h are",
+ "h adow",
+ "ĠD K",
+ "ĠìķĮ ê³ł",
+ "Ġw yn",
+ "Ġrequest ing",
+ "ĠD onna",
+ "ĠìĹ ´ìĭ¬íŀĪ",
+ "ine a",
+ "Ġex ert",
+ "ĠDun can",
+ "Ġв еÑĩ",
+ "ĠH ah",
+ "ठĤ",
+ "ĠL if",
+ "ĠF inding",
+ "ĠNo v",
+ "Ġзн ак",
+ "Ġо ÑĦ",
+ "ĠQu è",
+ "Ġquarter back",
+ "ĠÑĦ ак",
+ "Ġbipart isan",
+ "ÄŁ in",
+ "Ġné cess",
+ "Ġrefer endum",
+ "Ġcomp iler",
+ "Ġprob abil",
+ "ед и",
+ "Ġtrad er",
+ "æĺ ĵ",
+ "ĠR um",
+ "ge me",
+ "Ġd io",
+ "ĠbÄĻdzie my",
+ "ĠÏĢ ά",
+ "ê¾ ¸",
+ "×ķ× ĺ",
+ "Ġठķ",
+ "Ġбл аг",
+ "Ġscal p",
+ "ĠPa use",
+ "Ġcapt ion",
+ "Ġend anger",
+ "Ġen lar",
+ "Ġrot ten",
+ "ãĥĥ ãĥĪ",
+ "Ġw ah",
+ "èĤ ī",
+ "Ġd zi",
+ "ĠInst all",
+ "A y",
+ "Ġcre ar",
+ "енÑĤ а",
+ "Ġwe ighing",
+ "Ġbutter flies",
+ "ĠG ast",
+ "äº ķ",
+ "h orn",
+ "war z",
+ "IC EOVER",
+ "Ġнай ÑĤи",
+ "Ġcoe fficients",
+ "ç°¡ åĸ®",
+ "ĠSp encer",
+ "ĠH igher",
+ "Ġcow ork",
+ "å¨ ĺ",
+ "ĠкоÑĤоÑĢ ое",
+ "Ġmon it",
+ "Ġdys function",
+ "ĠÑģÑĤ анов",
+ "Ġtour naments",
+ "Ġoy ster",
+ "B N",
+ "Ġtr ud",
+ "sl ow",
+ "ĠPen ny",
+ "ĠOd ys",
+ "æ r",
+ "Ġf ou",
+ "Ġenjoy ment",
+ "аÑĤ Ñĭ",
+ "Ġwygl Äħda",
+ "алÑĮ наÑı",
+ "ĠProt ect",
+ "Ġmo y",
+ "Ġcl aw",
+ "Ġsusp icion",
+ "Ġsacrific ed",
+ "Ġgost o",
+ "B ig",
+ "Ġaggress ively",
+ "Ġvor ne",
+ "ãĥ ł",
+ "Ġbl amed",
+ "ĠSe hr",
+ "פ ר",
+ "c ito",
+ "Ġse als",
+ "Ġmu jer",
+ "ĠWe ird",
+ "Ġfore ns",
+ "Ġcontrib utes",
+ "est ra",
+ "Ġp og",
+ "L OL",
+ "Ġhacer lo",
+ "о ÑĤÑĮ",
+ "f iction",
+ "7 9",
+ "λ ο",
+ "大 æ¦Ĥ",
+ "å£ °",
+ "ĠÑĤ об",
+ "ĠG S",
+ "ĠCl ara",
+ "ite z",
+ "Ġadvoc ating",
+ "ĠíĶ Ħë",
+ "s ung",
+ "Ġvert ices",
+ "Ġnavig ating",
+ "Ġeurop é",
+ "çļ Ĩ",
+ "Ġslow ed",
+ "Ġfore ground",
+ "ĠIndust rial",
+ "Ġad ore",
+ "ìĭ Ń",
+ "Ġcré er",
+ "æŀ Ĺ",
+ "chn itt",
+ "Ġun aware",
+ "Ġcur ly",
+ "ent ar",
+ "Ġl er",
+ "Ġprohib ited",
+ "ĠHero es",
+ "ĠRe ed",
+ "u ca",
+ "Ġsm ok",
+ "Ġkun na",
+ "zeit ig",
+ "im men",
+ "ĠL un",
+ "Ġаб ÑģолÑİÑĤ",
+ "Ġdeg li",
+ "Ġvill agers",
+ "Ġpres et",
+ "z ept",
+ "ud s",
+ "Ġem it",
+ "ä½ł è¦ģ",
+ "Ġë ī",
+ "ëĬĶ ì§Ģ",
+ "нак о",
+ "Ġos ób",
+ "Ġ196 9",
+ "ĠÐIJ ÑĢ",
+ "Ġman chmal",
+ "ĠBro ck",
+ "Ġmant ra",
+ "ĠW IL",
+ "b ach",
+ "in ä",
+ "el as",
+ "kel n",
+ "Ġdisci ple",
+ "Ġqual c",
+ "Ġde hyd",
+ "ìĿ´ë Ŀ¼ëĬĶ",
+ "A f",
+ "ìĦ± ìĿ´",
+ "R yan",
+ "Ġpupp et",
+ "ĠдÑĢÑĥг ие",
+ "Ġr ud",
+ "Ġp ending",
+ "P lus",
+ "ĠìķĬ ìĿĦ",
+ "Ġb á»ĭ",
+ "ĠSe ga",
+ "ç e",
+ "Ġprogram mer",
+ "b li",
+ "Ġun l",
+ "Ġensl aved",
+ "Ġsoci été",
+ "Äģ h",
+ "Ġinherit ance",
+ "ĠBang l",
+ "erm aid",
+ "Ġpractition er",
+ "ĠSt alin",
+ "ĠUs er",
+ "ci ble",
+ "Ġcard iac",
+ "ĠKore ans",
+ "Ġdump ed",
+ "Ġ×Ķ ×Ļ×Ķ",
+ "á is",
+ "Ġhydraul ic",
+ "oubt edly",
+ "ĠP it",
+ "Ġpic nic",
+ "Ġbehö ver",
+ "ĠÑģм ог",
+ "Ġbra king",
+ "é» ij",
+ "ut ar",
+ "ĠìĦ ¸ë",
+ "ub l",
+ "Ġü z",
+ "Ġmaj esty",
+ "Ġb ers",
+ "ut able",
+ "Ġhot ter",
+ "çħ §",
+ "ÛĮ ÙĨ",
+ "Ġbi ases",
+ "Ġsubject ed",
+ "Ġnaught y",
+ "Ġcir cus",
+ "ãģĹ ãģĭ",
+ "ĠIm medi",
+ "ĠSte fan",
+ "ĠTri ple",
+ "en k",
+ "Ġw it",
+ "Ġrecy cle",
+ "em ie",
+ "d ated",
+ "Ġun load",
+ "Ġpop ula",
+ "ch in",
+ "Ġyield s",
+ "Ġeng lish",
+ "ĠBon nie",
+ "Ġsp iders",
+ "Ã ģ",
+ "Ġer osion",
+ "éĥ¨ åĪĨ",
+ "ĠN ICK",
+ "иÑı Ñħ",
+ "Ġimp art",
+ "Ġк ни",
+ "Ġres olutions",
+ "Ġlith ium",
+ "Ġconver gence",
+ "ĠT ara",
+ "Ġдв е",
+ "th s",
+ "ĠCind y",
+ "æĪij è¦ģ",
+ "å¹ «",
+ "ĠD IE",
+ "Ġass urance",
+ "Ġоп иÑģ",
+ "Ġbu ckets",
+ "Ġc ues",
+ "ĠQu iet",
+ "Ġsimilar ity",
+ "Ġfound ational",
+ "ĠMin ist",
+ "æ» ¿",
+ "Ġp ian",
+ "Ġcent r",
+ "Ġnum b",
+ "Ġmon ks",
+ "uj ourd",
+ "en zie",
+ "Ġskate board",
+ "Ġd latego",
+ "ĠÑģ оÑĤ",
+ "ĠA E",
+ "Ġmaster piece",
+ "ĠSol omon",
+ "ĠRed dit",
+ "Ġr iot",
+ "ab l",
+ "ĠJ azz",
+ "Ġelectromagn etic",
+ "Ġinsec ure",
+ "ĠComp et",
+ "ger ies",
+ "об од",
+ "ł ×ķ",
+ "ðŁ Ĵ",
+ "Ġsen ators",
+ "ĠBris bane",
+ "ĠAl b",
+ "utter ing",
+ "ĠAll ow",
+ "z ero",
+ "Ġp ai",
+ "ĠÐIJ лекÑģ",
+ "ĠDis play",
+ "ĠBl ade",
+ "ĠApp s",
+ "Ġp ä",
+ "Ġд еÑģÑı",
+ "Ġque lla",
+ "ĠGa o",
+ "ен нÑĭÑħ",
+ "Ġspoil ers",
+ "Ġgall ons",
+ "ĠÙĦ ÙĬ",
+ "ĠZ ion",
+ "æľī ä¸Ģ",
+ "on ie",
+ "rag t",
+ "ĠCh and",
+ "Ġë³ ij",
+ "Ġbl unt",
+ "Ġus u",
+ "ĠK ad",
+ "ra kt",
+ "Ġcin ematic",
+ "Ġam munition",
+ "re ne",
+ "Ġfour teen",
+ "ĠC arn",
+ "c rit",
+ "Ġten ure",
+ "v u",
+ "Ġprincipal mente",
+ "Ġalle en",
+ "éĢĻ ä¸Ģ",
+ "Ġkompl ett",
+ "Ġdü ny",
+ "J ames",
+ "Ġrecept or",
+ "Ġones elf",
+ "g uru",
+ "Ġmerch ant",
+ "l iness",
+ "Ġover looked",
+ "Ġharmon ic",
+ "éķ ¿",
+ "ies o",
+ "×ķ× ŀ",
+ "col m",
+ "ĠпÑĢо екÑĤ",
+ "ĠAd a",
+ "ا س",
+ "T im",
+ "Ġrecur ring",
+ "Ġproceed s",
+ "ĠPart icularly",
+ "ĠDown load",
+ "et rical",
+ "Ġmat rices",
+ "Ġproyect o",
+ "anc ies",
+ "ĠUh m",
+ "Ġc aves",
+ "Ġìĸ´ë ł¤",
+ "ĠLe af",
+ "Ġоб ÑĭÑĩ",
+ "ĠìĿ´ì ľł",
+ "Euro pe",
+ "Ġt Äħ",
+ "Ġpul s",
+ "Ġtak iego",
+ "ÐĿ е",
+ "G U",
+ "Ġfor s",
+ "Ïģ γ",
+ "Ġfot os",
+ "Ġ) )",
+ "Ġë© ¤ë",
+ "Ġaqu ilo",
+ "ĠK urd",
+ "ï¸ ı",
+ "pt ic",
+ "ĠD ort",
+ "Ġmis ery",
+ "aus o",
+ "åĬ Ł",
+ "chuck ling",
+ "ĠR idge",
+ "ĠíĸĪ ìĬµëĭĪëĭ¤",
+ "Ġ* **",
+ "å® ¢",
+ "ĠHmm m",
+ "Ġge ographic",
+ "Ġany s",
+ "Ġtal vez",
+ "Ġske let",
+ "Ġsign atures",
+ "Ġlit ers",
+ "IJë ©´",
+ "ĠÑģво его",
+ "Ġski ing",
+ "ĠÐľ оÑģ",
+ "Ġadop ting",
+ "Ġha ft",
+ "Ġsymm etric",
+ "ĠL iqu",
+ "Ġthy roid",
+ "Ġmis in",
+ "lud e",
+ "Ġh ull",
+ "ĠX D",
+ "ĠG ust",
+ "ze ich",
+ "Ġvibr ations",
+ "Ġes emp",
+ "ĠвÑģ Ñİ",
+ "ĠQu em",
+ "Ġü brig",
+ "ĠS ke",
+ "ĠLyn ch",
+ "room s",
+ "art et",
+ "f est",
+ "Ġfr üher",
+ "Ġl ure",
+ "ä¸į好 æĦıæĢĿ",
+ "ĠìķĮ ìķĦ",
+ "ĠW IN",
+ "ĠR YAN",
+ "ĠкоÑĤоÑĢ ÑĥÑİ",
+ "ĠK ash",
+ "Ġ×Ķ× ŀ",
+ "Ġsaf eg",
+ "ĠHall elujah",
+ "Ġдв ÑĥÑħ",
+ "Ġstap le",
+ "Ġsed iment",
+ "ĠAct s",
+ "Ġbl aming",
+ "Ġmain land",
+ "Ġsport ing",
+ "Ġdecor ations",
+ "Ġexecut ing",
+ "Ġpar an",
+ "ĠDoll ar",
+ "Ġproject ions",
+ "Ġcommission ed",
+ "Ġb our",
+ "ö m",
+ "Ġste amed",
+ "ĠëŃ ĺ",
+ "Ġpet rol",
+ "Ġcel ular",
+ "å¸ ¶",
+ "ĠHung ary",
+ "Ġrent ed",
+ "Ġв аÑĢи",
+ "bb ie",
+ "Ġsé cur",
+ "ü ll",
+ "Ġsw ings",
+ "bet ween",
+ "Ġи ÑĤ",
+ "est ro",
+ "Ġnie mand",
+ "ĠìĤ ¼",
+ "ĠP ardon",
+ "ess es",
+ "ĠM ID",
+ "Ġcentral ized",
+ "ĠAl ien",
+ "cul os",
+ "Ġcr ise",
+ "裡 éĿ¢",
+ "Ġcl asse",
+ "beit et",
+ "i ÄŁi",
+ "Ġwh ales",
+ "Ġper imeter",
+ "Ġty ing",
+ "Ġstr ony",
+ "Ġlike wise",
+ "ĠP unch",
+ "D a",
+ "ĠBapt ist",
+ "Ġsort ing",
+ "Ġ iv",
+ "Ġíķ ©",
+ "Ġre hab",
+ "Ġet a",
+ "ri ver",
+ "Ġsa i",
+ "ãģĦãģŁ ãģł",
+ "od us",
+ "ãģĬé¡ĺãģĦ ãģĹãģ¾ãģĻ",
+ "Ġess ayer",
+ "Ġtur tles",
+ "ĠHaz rat",
+ "Ġfab rics",
+ "Ġcav ity",
+ "Ġpon ieważ",
+ "Ġschle cht",
+ "Ġs alsa",
+ "ÅŁ ekkür",
+ "Ġse ating",
+ "Ġeconom ists",
+ "Ġman g",
+ "Ġsegu inte",
+ "Ġr ang",
+ "Ġrat ios",
+ "Ġconst ell",
+ "Ġlong temps",
+ "u ating",
+ "Ġspo iled",
+ "Ġrecip ients",
+ "Ġsn iper",
+ "ä¹ĭ åīį",
+ "ìĬµ ëĭĪê¹Į",
+ "Ġw p",
+ "ĠLIN KE",
+ "Ġfl are",
+ "ĠAd ri",
+ "ñ as",
+ "Ġback l",
+ "mä ÃŁ",
+ "ĠB end",
+ "Ġworkload s",
+ "ĠÑģ Ñĥп",
+ "Ġ197 5",
+ "им ÑģÑı",
+ "ан е",
+ "Ġм он",
+ "Ġaspir ations",
+ "ĠA er",
+ "ĠговоÑĢ иÑĤÑĮ",
+ "ĠQ ian",
+ "å¦ Ī",
+ "Ġcomprom ised",
+ "Ġyol k",
+ "ла ÑģÑĤ",
+ "Ġhe men",
+ "ro ve",
+ "d ens",
+ "Ġком менÑĤ",
+ "Ġ- --",
+ "Ġflu ores",
+ "но Ñģ",
+ "ĠLiver pool",
+ "ĠÑģоб ой",
+ "ĠZ we",
+ "Ġl umin",
+ "ĠO G",
+ "á ¸",
+ "hol m",
+ "pro fits",
+ "S N",
+ "Ġproport ions",
+ "Ġm ica",
+ "ĠB oh",
+ "ĠAt las",
+ "Ġuns ure",
+ "Ġtour ing",
+ "Ġn ied",
+ "Ġt ÄĻ",
+ "Ġimper ative",
+ "Ġdem ek",
+ "ĠSher iff",
+ "r ance",
+ "Ġhom eland",
+ "ĠH ail",
+ "ĠG anz",
+ "y mm",
+ "M on",
+ "åĨ ·",
+ "v ida",
+ "Ġdesar roll",
+ "æĬ Ģ",
+ "Ġintrig uing",
+ "ĠH ugo",
+ "Ġ ãĤĤ",
+ "é ¬",
+ "а ÑĨ",
+ "ĠWiÄĻ c",
+ "att ed",
+ "ĠìķĦëĭĪ ê³ł",
+ "ĠV ari",
+ "á d",
+ "Ġsur real",
+ "Ġdispar ities",
+ "Ġm ó",
+ "ull en",
+ "ĠìŀĪ ëĭ¤ê³ł",
+ "Ġп ожалÑĥйÑģÑĤа",
+ "Ġma ins",
+ "Ġe ject",
+ "Ġmeth ane",
+ "Ġmarginal ized",
+ "Ġchill i",
+ "r ès",
+ "Ġy em",
+ "ä½ł æĺ¯",
+ "ĠCh un",
+ "Ġdeb ts",
+ "Ġdownload ing",
+ "ĠAth ens",
+ "is ierung",
+ "ry n",
+ "Ġte kn",
+ "ĠQu indi",
+ "éľ Ģ",
+ "Ġtara f",
+ "Ġh é",
+ "Ġconscious ly",
+ "Ġfix es",
+ "uck le",
+ "may ın",
+ "Ġfre i",
+ "Ġsp a",
+ "Ġì§Ħ íĸī",
+ "ĠاÙĦØ °",
+ "ĠÑĥ к",
+ "let t",
+ "Ġolm uÅŁ",
+ "Ġche esy",
+ "า à¸ģ",
+ "na ire",
+ "Ġw iden",
+ "Ġli en",
+ "Ġesca ping",
+ "igg s",
+ "ĠBl ick",
+ "c Äħ",
+ "ĠìĦ ľë",
+ "Ġ×Ķ× ¡",
+ "Ġв пеÑĢ",
+ "oph one",
+ "ie ll",
+ "ĠSU BSCRI",
+ "Ġl ions",
+ "Ġê·¸ ê²ĥ",
+ "Ġinsp ires",
+ "Ġguarante es",
+ "Ġcome ça",
+ "ĠGrow ing",
+ "Ġneg lig",
+ "ĠFrank f",
+ "Ġge geben",
+ "ĠÄij ầu",
+ "Ġend lich",
+ "Ġì į¨",
+ "ĠT T",
+ "ĠL ith",
+ "ÏĢ α",
+ "aster n",
+ "ĠA zer",
+ "Ġlun ar",
+ "h ic",
+ "Ġна ÑĢод",
+ "Ġnen hum",
+ "è· ij",
+ "ĠSalv ador",
+ "ĠPro gress",
+ "Ġprivile ges",
+ "ĠëıĻ ìķĪ",
+ "Ġant agon",
+ "ĠImp f",
+ "Ġdesc ub",
+ "ĠLe i",
+ "ĠìĥĪë ¡ľ",
+ "Ñĩ е",
+ "Ġdó lares",
+ "ĠMeg han",
+ "ĠW ire",
+ "to o",
+ "ay ing",
+ "us c",
+ "Ġt ud",
+ "Ġappe als",
+ "ed uc",
+ "Ġp ane",
+ "Ġj i",
+ "Ġde cks",
+ "ĠAl ter",
+ "Ġ å°±",
+ "ìĦ ¤",
+ "åĪĨ éIJĺ",
+ "Ġproduct ions",
+ "ĠWILL IAM",
+ "Ġimpl ied",
+ "Ġfulfill ment",
+ "ĠA ah",
+ "Ġsa ja",
+ "x us",
+ "ĠÎļ αι",
+ "Ãł s",
+ "uc ch",
+ "ок о",
+ "ĠDisc ord",
+ "ĠS Y",
+ "j sk",
+ "ĠWall ace",
+ "un ction",
+ "Dan iel",
+ "Ġk öt",
+ "ij ah",
+ "Ġmarch e",
+ "Ġdis gr",
+ "Ġm ungkin",
+ "Ġal ma",
+ "³ µ",
+ "Ġextensive ly",
+ "ĠFl oren",
+ "ĠAll ison",
+ "ãĤ ±",
+ "ÙĬ Ùħ",
+ "Ġju ven",
+ "ĠRena issance",
+ "Ġfundra ising",
+ "ĠCha os",
+ "Ġpar aly",
+ "Ġnarr ator",
+ "Ġecosystem s",
+ "A sh",
+ "Ġmitig ation",
+ "ĠA ujourd",
+ "ĠIde e",
+ "! ,",
+ "ĠÂ ½",
+ "Ġland lord",
+ "Ġdefect s",
+ "Ġac re",
+ "uls ive",
+ "Ġalg ae",
+ "pe k",
+ "Ġem ba",
+ "ĠR oc",
+ "éĽ ¢",
+ "ks om",
+ "ä che",
+ "Ġle uk",
+ "Ġlever aging",
+ "Ġê·¸ëłĩ ì§Ģ",
+ "ĠPal m",
+ "Ġä ven",
+ "Ġl is",
+ "ĠIn sp",
+ "ĠR ita",
+ "ĠAb b",
+ "ith m",
+ "Ġsuper vision",
+ "Ġrevis it",
+ "Ġpi ÄĻ",
+ "Ġeu h",
+ "Ġf ades",
+ "Ġmot to",
+ "åį ¡",
+ "ез ж",
+ "ĠSh im",
+ "Ġrelev ance",
+ "Ġo o",
+ "Ġo stat",
+ "n ica",
+ "Ġcho ix",
+ "ĠFac ulty",
+ "Ġì¤ij ìĹIJ",
+ "ĠAb ove",
+ "Ġнеб олÑĮÑĪ",
+ "Ġsequ encing",
+ "Ġnutri ent",
+ "Ġconqu ered",
+ "Ġdigest ive",
+ "Ġback drop",
+ "ĠL ori",
+ "ail able",
+ "G ame",
+ "Ġneglect ed",
+ "om orph",
+ "ill ah",
+ "Ġkn e",
+ "Ġsi itä",
+ "Ġworks pace",
+ "ĠVen ice",
+ "ĠK ne",
+ "Ñī о",
+ "ħ Ģ",
+ "ĠH ass",
+ "Ġv ita",
+ "Ŀ¼ë ©´",
+ "Ġlay s",
+ "ên cias",
+ "é rica",
+ "ĠL l",
+ "æ± Ĥ",
+ "ĠCo ca",
+ "ĠWH Y",
+ "èĪ ŀ",
+ "Ġrout ing",
+ "Ġperm issions",
+ "Ġd ings",
+ "pre nd",
+ "pro gram",
+ "Ġcro cod",
+ "br al",
+ "AAAA AAAA",
+ "ag it",
+ "ĠN ä",
+ "Ġgek ommen",
+ "at ten",
+ "Ġrefer enced",
+ "Ġpair ing",
+ "ĠPart ner",
+ "ĠCoron avirus",
+ "Ñĸ Ñģ",
+ "è½ ī",
+ "Ġ×Ķ× ĵ",
+ "Ġespec ÃŃfic",
+ "ars i",
+ "qu elle",
+ "Ġspont aneous",
+ "çĨ ±",
+ "Ġê²ĥ ìĿĦ",
+ "ĠÐŁÐ¾Ñģ ле",
+ "ĠاÙĦ د",
+ "ĠSh out",
+ "Ġн ал",
+ "Ġdisgu ise",
+ "ĠJ ord",
+ "Ġwe e",
+ "Ġmiej sc",
+ "Ġser um",
+ "Ġplais ir",
+ "Ġcred ible",
+ "Ġb Ã¥",
+ "ĠA J",
+ "ma res",
+ "Ġrod s",
+ "Ġer an",
+ "ãģ¾ ãģĤ",
+ "Ġp ää",
+ "ĠU A",
+ "ĠUn known",
+ "ĠÙĦ Ùħ",
+ "ĠRab bi",
+ "Ġla at",
+ "Ġhairst yle",
+ "ĠØ º",
+ "éģ ĭ",
+ "Ġc ach",
+ "ĠWr iting",
+ "оÑĩ ки",
+ "ab ad",
+ "Ġstraight en",
+ "-- \"",
+ "w ife",
+ "Ġhott est",
+ "Ġpun ya",
+ "ĠF ashion",
+ "gr iff",
+ "ĠQ R",
+ "ot ch",
+ "ĠÐľ ожеÑĤ",
+ "Cl oud",
+ "ĠStri ke",
+ "ĠHe in",
+ "Ġ 羣çļĦ",
+ "Ġle i",
+ "ĠFl ow",
+ "weg s",
+ "Ġha br",
+ "åīĽ åīĽ",
+ "nah me",
+ "Ì ģ",
+ "Ġple asing",
+ "op ping",
+ "Ġ구ë ıħ",
+ "Ġdr an",
+ "Ġbang s",
+ "Ġ7 9",
+ "Ġsk et",
+ "Ġcav al",
+ "ĠMac ron",
+ "Ġweight ed",
+ "Ġm uted",
+ "Ġnuest ras",
+ "EE P",
+ "Ġmath ematic",
+ "ĠM RI",
+ "ag us",
+ "Ġtherap ies",
+ "θ ε",
+ "Ġun pl",
+ "Ġcomm encer",
+ "f ull",
+ "Ġtow els",
+ "Ġpr ue",
+ "Ġlic enses",
+ "׼ ×ķ׾",
+ "ĠÐŁ оÑĩемÑĥ",
+ "Ġpoint less",
+ "B ye",
+ "Ġelig ibility",
+ "Ġscra pe",
+ "Ġab usive",
+ "ĠM ant",
+ "Ġje unes",
+ "t al",
+ "ĠPrin cip",
+ "ĠOrth odox",
+ "Ġmel od",
+ "ĠмаÑĤ еÑĢи",
+ "Ġprosecut or",
+ "Ġopio id",
+ "ĠÑĥ веÑĢ",
+ "ĠBe en",
+ "Ġìłij ì¢ħ",
+ "Ġd ynasty",
+ "Ġajud a",
+ "Ġent reg",
+ "Ġweigh ed",
+ "Ġe ure",
+ "ĠB em",
+ "Ġab normal",
+ "8 2",
+ "ĠJ R",
+ "ĠA kt",
+ "ĠB ri",
+ "ú t",
+ "Ġst agn",
+ "! *",
+ "Ġwe gen",
+ "Ġle aking",
+ "ĠW ords",
+ "ĠM au",
+ "Ġv ue",
+ "ĠL iam",
+ "ани ем",
+ "Ġclin icians",
+ "ĠP ump",
+ "Ġför st",
+ "? ...",
+ "Ġautom otive",
+ "ĠOw en",
+ "zus agen",
+ "ĠH undred",
+ "Ġdecentral ized",
+ "Ġbul bs",
+ "Ġ×ľ× Ľ",
+ "Ġprovin ces",
+ "ĠMil an",
+ "8 1",
+ "k as",
+ "Ġëĵ £",
+ "Ġfor ça",
+ "Ġright ly",
+ "å³ ¶",
+ "r Äħ",
+ "Ġven ues",
+ "Ġw ai",
+ "Ġpred icting",
+ "ĠWi Fi",
+ "Ġê¶ģ ê¸Ī",
+ "ر ÙĪ",
+ "Ġ×Ķ× ĸ",
+ "cent ury",
+ "Ġgrad ual",
+ "ĠProblem e",
+ "ĠìĹ ħ",
+ "Ġcop ing",
+ "ĠBr us",
+ "Ġpean uts",
+ "irts chaft",
+ "Ġз ал",
+ "ĠT roy",
+ "Ġsper m",
+ "ĠM itar",
+ "ĠTür kiye",
+ "g rand",
+ "¦ Ń",
+ "Ġ×ŀ× ¡",
+ "Ġp ans",
+ "ĠKnow ledge",
+ "ber ly",
+ "ĠÐķ го",
+ "Ġdan ced",
+ "ĠFr ost",
+ "ĠB urg",
+ "Ġbit ing",
+ "ìłķ ìĿĦ",
+ "me al",
+ "Ġhero ic",
+ "Ġmother board",
+ "ĠL icht",
+ "ãģ£ ãģ",
+ "ll an",
+ "ай н",
+ "ĠÑĢ Ñıд",
+ "Ġ à¹Ģà¸",
+ "on en",
+ "ir ie",
+ "Ar t",
+ "r ang",
+ "ν η",
+ "Ġnew born",
+ "Ġam is",
+ "Ġا ÙĪر",
+ "Ġsoph om",
+ "ĠCare ful",
+ "Ġprospect s",
+ "ens en",
+ "Ġthr ill",
+ "ĠVi á»ĩt",
+ "A dam",
+ "r ition",
+ "ent ric",
+ "ud en",
+ "Ġcertific ates",
+ "Ġas hes",
+ "èª ¿",
+ "play ing",
+ "Ġs adece",
+ "Ġo st",
+ "Ġairpl anes",
+ "ÑĢ ок",
+ "on er",
+ "Ġmagnes ium",
+ "Ġgod damn",
+ "Ġ197 2",
+ "ĠSch ule",
+ "Ġtem at",
+ "Ġpart out",
+ "௠Ĥ",
+ "Ġin ve",
+ "ĠScient ists",
+ "ĠHud son",
+ "win ning",
+ "ceks in",
+ "Ġcongress ional",
+ "or u",
+ "Ġro pes",
+ "в ед",
+ "Ġmad re",
+ "Ġf erry",
+ "ĠCoh en",
+ "ĠP red",
+ "Ġvag y",
+ "Ġб еÑģп",
+ "Ġmult im",
+ "Ġdrain age",
+ "Ġsim ulator",
+ "g iggles",
+ "ĠSt adium",
+ "об Ñī",
+ "Ġnot ices",
+ "Ġcraw ling",
+ "Ġgr oupe",
+ "åı ¸",
+ "Ġkto ÅĽ",
+ "ĠY oga",
+ "Ġmed ida",
+ "ĠÑħ ваÑĤ",
+ "ĠL ite",
+ "Ġr av",
+ "or ama",
+ "Ġdisc ord",
+ "ĠDI RE",
+ "Ġte h",
+ "ĠN urs",
+ "ç² ī",
+ "Ġpitch ed",
+ "Ġbark ing",
+ "ĠC oke",
+ "wi ad",
+ "Ġpop ulated",
+ "éĻ ¤",
+ "pe lled",
+ "Ġб ог",
+ "Ġpe wno",
+ "ĠC ube",
+ "Ġrecru ited",
+ "éĢĻ 種",
+ "ĠC ara",
+ "ıģ ını",
+ "im ated",
+ "ĠÑĪ кол",
+ "ic ional",
+ "ĠпÑĢо ÑĦ",
+ "Ġcontam ination",
+ "Ġúlt imos",
+ "Ġfear ful",
+ "Ġele phants",
+ "us i",
+ "ĠiT unes",
+ "ĠSw ami",
+ "ê ¼",
+ "ĠìĦ¤ë ªħ",
+ "ĠRich ards",
+ "Ġmagn ets",
+ "ĠRicht ung",
+ "ĠLeg ion",
+ "èı ľ",
+ "Ġk itty",
+ "Ġkiss ed",
+ "Ġwater ing",
+ "Ġcon o",
+ "ĠPalest ine",
+ "id ir",
+ "Ġma ze",
+ "Ġflu ids",
+ "ĠProdu cer",
+ "ĠKr sna",
+ "好 åķ¦",
+ "la f",
+ "Ġ×IJ ×ķ",
+ "Ġm iesz",
+ "ĠX ing",
+ "oint ed",
+ "se in",
+ "ĠF uk",
+ "ĠDep ression",
+ "ĠD uty",
+ "ĠPan ther",
+ "Ġsu nd",
+ "Ġref ere",
+ "Ġexc lusion",
+ "Ġnav al",
+ "ĠWin ston",
+ "Ġsl ogan",
+ "Ġhypoth etical",
+ "Ġelev ate",
+ "ë ł¹",
+ "Ġcabe ça",
+ "ĠGes und",
+ "m eter",
+ "ĠìķĦëĭĪë ©´",
+ "Ġcloud y",
+ "âĢ¦ ?",
+ "ĠSch ritt",
+ "ĠJ S",
+ "ì į",
+ "ĠSpr ings",
+ "ĠB atter",
+ "· °",
+ "Ġtail or",
+ "ĠPTS D",
+ "ĠG ent",
+ "Ġba ÄŁ",
+ "Ġspat ula",
+ "Ġcr ay",
+ "ĠLeg isl",
+ "Ġs ú",
+ "Ġle ve",
+ "า ม",
+ "Ġer ad",
+ "Ġdon g",
+ "Ġd erm",
+ "ĠBank s",
+ "ich o",
+ "åħĪ çĶŁ",
+ "ĠFr anz",
+ "ra vel",
+ "éģ Ķ",
+ "ол о",
+ "Ġfl ute",
+ "ĠE k",
+ "Ġjoy ful",
+ "Ġch ased",
+ "ĠLar ge",
+ "O ver",
+ "Ġentrepreneur ial",
+ "Ġcons iders",
+ "Ñĥ ем",
+ "op a",
+ "Ġdorm ir",
+ "ĠElement ary",
+ "Ġprzy pad",
+ "ÑĥÑģ ка",
+ "ĠоÑĩ еÑĢ",
+ "ug ene",
+ "Ġten ido",
+ "Ġlug ares",
+ "ë ¥",
+ "ĠÑĩ аÑģÑĤ",
+ "Ġsa o",
+ "Ġbra id",
+ "ĠV ere",
+ "ĠRe ich",
+ "ĠP oss",
+ "Ġin an",
+ "w and",
+ "re f",
+ "Ġmont rer",
+ "Ġ198 1",
+ "çķ ª",
+ "as ında",
+ "Ġch rome",
+ "ĠTr inity",
+ "Ġexplo itation",
+ "ĠS ense",
+ "ĠC MS",
+ "ĠNo ble",
+ "ĠìĦł íĥĿ",
+ "Ġswe lling",
+ "elect ronic",
+ "] ?",
+ "Ġbr ushing",
+ "Ġliquid ity",
+ "ĠH ook",
+ "ĠCon nor",
+ "ĠAl um",
+ "Ġgu cken",
+ "su ite",
+ "Ġwie le",
+ "Ġbarrel s",
+ "ĠReg el",
+ "ĠM ent",
+ "ĠT rip",
+ "ĠBr ush",
+ "ĠE rik",
+ "ur ate",
+ "ÉĻ r",
+ "ĠC yr",
+ "ou ble",
+ "ĠBe cca",
+ "Ġpass words",
+ "Å ±",
+ "bor g",
+ "Ġv endo",
+ "ĠCla us",
+ "ĠF az",
+ "ind est",
+ "Ġdece ased",
+ "Ġcompar isons",
+ "ĠL CD",
+ "ĠP ork",
+ "Ġevent ual",
+ "Ġpat reon",
+ "Ġin ability",
+ "Ġext inction",
+ "Ġì¢ĭìķĦ íķĺëĬĶ",
+ "ĠÑģ оÑģ",
+ "aj u",
+ "Ġ×ij× IJ×",
+ "Ġso fort",
+ "Ġdest ined",
+ "ĠR in",
+ "Ġmouth s",
+ "ĠNat ürlich",
+ "Ġpres erving",
+ "Ġlim p",
+ "é» ¨",
+ "oc used",
+ "ин г",
+ "Ġexp osing",
+ "ĠÎ ¾",
+ "ë į",
+ "la ugh",
+ "Ġhis s",
+ "ãģł ãģĭãĤī",
+ "Ġind ie",
+ "Ġdet al",
+ "ÑĢав ÑģÑĤв",
+ "Ġtr ên",
+ "æķ °",
+ "Ġog ni",
+ "Ġsimple mente",
+ "Ġ197 8",
+ "Ġgo o",
+ "Ġ196 7",
+ "Ġgen ug",
+ "h ö",
+ "Ġhist ó",
+ "å® Ł",
+ "Ġlob ster",
+ "c endo",
+ "Ġte il",
+ "Ġalle vi",
+ "00 00",
+ "OL D",
+ "Ġpes os",
+ "Ġbon uses",
+ "Ġam i",
+ "Ġrev ival",
+ "ĠHor se",
+ "Ġs ack",
+ "T alk",
+ "Ġmul her",
+ "ĠпоÑģÑĤо Ñıн",
+ "ĠH ood",
+ "H uh",
+ "Ġë¶ ģ",
+ "Ġhy ung",
+ "ĠMe eting",
+ "Ġimport a",
+ "Ġì°¾ ìķĦ",
+ "ĠV ern",
+ "Ġstri pped",
+ "Ġref uses",
+ "Ġqual ifications",
+ "op l",
+ "Ģë ıĦ",
+ "ix ÃŃ",
+ "Ġdi ab",
+ "it ime",
+ "fl ows",
+ "Ġin ac",
+ "ĠG ong",
+ "Ġmeaning less",
+ "Ġcourage ous",
+ "Ġmicro bi",
+ "az y",
+ "h ist",
+ "Ġvolunte ering",
+ "V IE",
+ "Ġviol ated",
+ "Ġsymp athy",
+ "ĠEd it",
+ "好 åĥı",
+ "elect ric",
+ "produ ct",
+ "Ġpand emia",
+ "Ġgeomet ric",
+ "ĠCon vers",
+ "g re",
+ "Ġgl ut",
+ "ist ed",
+ "ĠاÙĦ Ùĥ",
+ "ĠCh ain",
+ "ĠPres ent",
+ "ĠY in",
+ "ĠÑģ ог",
+ "ĠV log",
+ "Ġìĸ´ë ¨¸",
+ "Ġdon n",
+ "Ġh itch",
+ "uck ing",
+ "ãģĬ ãģĦ",
+ "w ald",
+ "ris k",
+ "Ġhar i",
+ "ĠK ens",
+ "ĠId ol",
+ "Ġвним ание",
+ "Ġtod d",
+ "Ġsm ashed",
+ "Ġinv ari",
+ "Ġкон ÑĤÑĢ",
+ "Ġaut istic",
+ "ìŀ¥ ëĭĺ",
+ "R es",
+ "д Ñĭ",
+ "ch au",
+ "Ġsel v",
+ "Ġhät ten",
+ "ठ¿",
+ "Ġexpect s",
+ "Ïģ η",
+ "Ġaç ık",
+ "ĠHT TP",
+ "le ÅŁ",
+ "Ġswe eping",
+ "ĠBet a",
+ "Ġcounterpart s",
+ "ab ile",
+ "ĠSim s",
+ "C s",
+ "Ġrep ar",
+ "s qu",
+ "Ġprovin cial",
+ "Ġshare holders",
+ "Ġrun ter",
+ "Ġged acht",
+ "ĠTe en",
+ "Ġgrand s",
+ "çĶ ¢",
+ "ag les",
+ "Ġrock y",
+ "ven s",
+ "Ġr ivals",
+ "un al",
+ "Ġreact s",
+ "ë ©",
+ "Ġmerc ury",
+ "ĠLu igi",
+ "Ġо г",
+ "ĠJ UST",
+ "Ġl od",
+ "Ġcort ex",
+ "w ig",
+ "Ġl akh",
+ "ì¤ij ìĹIJ",
+ "ĠV ic",
+ "ĠM und",
+ "Ġma pped",
+ "ĠD ell",
+ "ĠD ruck",
+ "Ġlif es",
+ "алÑĮ ное",
+ "ivid ual",
+ "ad ım",
+ "Ġat rav",
+ "ĠFl ug",
+ "ĠKle in",
+ "ê±° ìķ¼",
+ "ห à¸Ļ",
+ "Ġapp li",
+ "ா ?",
+ "ü yorum",
+ "ĠинÑĤеÑĢеÑģ но",
+ "Ġdis infect",
+ "> -",
+ "Ġchamp agne",
+ "Ġk la",
+ "op ers",
+ "Tr ans",
+ "ĠDes ert",
+ "Ġcultiv ate",
+ "ĠFuck ing",
+ "idel ity",
+ "ĠÑĤ ан",
+ "Ġinc ub",
+ "Ġtem u",
+ "Ġlearn er",
+ "found er",
+ "ĠSy l",
+ "ãĤ Ģ",
+ "Ġf ato",
+ "z ier",
+ "ĠìĹĨ ìĿ´",
+ "ĠìĪ ¨",
+ "Ġpsych o",
+ "ĠÑĤел еÑĦ",
+ "Ġregard e",
+ "Ġrepresent ations",
+ "Ġlit igation",
+ "Ġsp ann",
+ "ult s",
+ "b ior",
+ "è¦ĭ ãģ¦",
+ "ä¸į å¤ļ",
+ "ĠSur vey",
+ "ĠLED s",
+ "Ġtr ä",
+ "Ġl ên",
+ "Ġant ioxid",
+ "еÑĢ ом",
+ "Ġindu ction",
+ "Ġfool ed",
+ "ät zlich",
+ "ĠговоÑĢ ÑıÑĤ",
+ "ĠF act",
+ "umb ai",
+ "Ġw iggle",
+ "NO UN",
+ "Ġdévelop p",
+ "ĠCl aro",
+ "Ġì ¸",
+ "ë ¬",
+ "ãģªãĤĵ ãģł",
+ "Ġaccum ulate",
+ "Ġmaint ains",
+ "ë Ħ",
+ "ĠFight er",
+ "íĨ ł",
+ "Ġmat in",
+ "Ġcoup on",
+ "Ġst unt",
+ "Ġdeb uted",
+ "å¾ħ ãģ£ãģ¦",
+ "Ġpra g",
+ "ив аем",
+ "7 3",
+ "Ġexp res",
+ "Ġìĺ¤ë ¹ł",
+ "ĠпеÑĢ Ñģон",
+ "Ġcalcul us",
+ "Ġab rupt",
+ "ĠInspect or",
+ "our t",
+ "æĸ Ļ",
+ "ź niej",
+ "int ense",
+ "B a",
+ "Ġl ounge",
+ "Ġast hma",
+ "ĠHi ç",
+ "ª »",
+ "Ġeditor ial",
+ "Ġse ize",
+ "Ġk ır",
+ "Ġm ouve",
+ "Ġtier ra",
+ "Ġtestoster one",
+ "Ġr h",
+ "ĠKing ston",
+ "EL LE",
+ "ĠRepresent ative",
+ "Ġ197 4",
+ "Ġi ba",
+ "T s",
+ "Ġsort a",
+ "Ġ( ?)",
+ "Ġت ÙĪ",
+ "ĠëĤ´ë ł¤",
+ "Ġbek ommt",
+ "Ġspirit ually",
+ "Ġdist orted",
+ "M ad",
+ "Ġre im",
+ "á nh",
+ "ĠOtt oman",
+ "ĠRel ig",
+ "ĠEl s",
+ "Ġret ained",
+ "ĠLa ughs",
+ "æĢ »",
+ "ĠS AS",
+ "ĠколиÑĩе ÑģÑĤво",
+ "×ķת ר",
+ "Ġinnov ate",
+ "Ġk ork",
+ "ĠÑĢаÑģÑģк азÑĭв",
+ "ond ere",
+ "iv i",
+ "ay e",
+ "ount y",
+ "ĠполÑĥÑĩ аеÑĤÑģÑı",
+ "Ġbun s",
+ "åħ «",
+ "Ġyüz den",
+ "Ġsur geries",
+ "Ø£ ÙĨ",
+ "Ġbankrupt cy",
+ "w elt",
+ "Ġsi amo",
+ "Ġdark est",
+ "ĠH ann",
+ "gg a",
+ "Ġform as",
+ "ĠD j",
+ "n amed",
+ "Ġshield s",
+ "ue ller",
+ "ĠF ew",
+ "Ġl ace",
+ "Ġfur ious",
+ "ĠY U",
+ "Ġsociet al",
+ "Ġjudge ment",
+ "ĠD os",
+ "Ġj ab",
+ "law s",
+ "Ġrein vent",
+ "ĠK atherine",
+ "ĠCh oi",
+ "ad ows",
+ "Ġr ans",
+ "od en",
+ "ĠMid west",
+ "n ın",
+ "Ġdep ort",
+ "ĠD ip",
+ "ç´ ħ",
+ "Ġaten ción",
+ "ĠCourt ney",
+ "ivid ad",
+ "ĠÚ© Ûģ",
+ "Ġeffic acy",
+ "ĠBrook s",
+ "Ġrefer ral",
+ "Ġкон ÑĨ",
+ "Ġmal icious",
+ "Ġk ir",
+ "ĠGod dess",
+ "Ġfun ky",
+ "Ġinter im",
+ "ĠK örper",
+ "Ġìĸ¼ë §",
+ "k ur",
+ "Ġк ли",
+ "Ġtruc s",
+ "ges etz",
+ "Ġz ug",
+ "ĠGl ück",
+ "ĠMin ute",
+ "Ġprest igious",
+ "Ġnie z",
+ "Ġconcent rations",
+ "ла ÑģÑĤи",
+ "ĠS is",
+ "ĠVit amin",
+ "ko v",
+ "ĠP BS",
+ "Ġне е",
+ "Ġretail ers",
+ "Ġcon ventions",
+ "ĠSam antha",
+ "Ġproud ly",
+ "J ordan",
+ "ĠJ ASON",
+ "at k",
+ "Ġtr iste",
+ "Ġst är",
+ "Ġreiter ate",
+ "Ġpos terior",
+ "Ġ197 3",
+ "ĠP ine",
+ "ĠJul iet",
+ "Ġped ir",
+ "k il",
+ "Ġover lapping",
+ "Ġexclud e",
+ "Ġecon óm",
+ "Ġaccept s",
+ "ĠS ter",
+ "æ± º",
+ "Ġìļ ´ëıĻ",
+ "est ab",
+ "Ġt ug",
+ "ar g",
+ "Ġliv ro",
+ "Ø§Ø µ",
+ "Ġse ams",
+ "Ġbur aya",
+ "Ġe llo",
+ "ĠT M",
+ "ĠP aw",
+ "ĠInd ex",
+ "Ex c",
+ "Ġinspir ational",
+ "Ġd unk",
+ "è° ģ",
+ "ak ter",
+ "Ġcondition er",
+ "ĠSal ut",
+ "ÅĤ ec",
+ "Ġìī ½",
+ "ĠÑĥз на",
+ "ĠRome o",
+ "f ruit",
+ "ĠY O",
+ "Ġchá» ī",
+ "б Ñĥ",
+ "b ons",
+ "Ġreprodu ctive",
+ "Ġor ada",
+ "Ġíļ ¨",
+ "Ġtent ar",
+ "Ġma ñana",
+ "ãĤ ¬",
+ "Ġsol vent",
+ "Jess ica",
+ "ĠLeg al",
+ "Ġtu a",
+ "Ġs ic",
+ "ĠE Q",
+ "au kee",
+ "ìĭľ ëĭ¤",
+ "ĠÅŀ u",
+ "Ġad here",
+ "ĠT ul",
+ "Ġà® Ĩ",
+ "Ġtext books",
+ "ĠFif th",
+ "Ġexper i",
+ "Ġch ic",
+ "Ġhe ap",
+ "in ely",
+ "at ra",
+ "T wo",
+ "Ġhele maal",
+ "Ġf ren",
+ "æİ ¨",
+ "Ġbis her",
+ "Ø§Ø ´",
+ "ĠìĦł ìĥĿ",
+ "ĠT ages",
+ "Ġs á»±",
+ "Ġbull ied",
+ "Ø ¤",
+ "Ġbenef ited",
+ "ĠPre viously",
+ "ĠÑį ÑĦÑĦ",
+ "Ù į",
+ "Ġsen ate",
+ "ĠM orm",
+ "ij ke",
+ "ĠF lu",
+ "Ġincorpor ating",
+ "j ack",
+ "Ġп иÑĤ",
+ "Ġimp ly",
+ "Ġha cks",
+ "ĠR ICH",
+ "Ġк ваÑĢ",
+ "ĠпÑĢек ÑĢаÑģ",
+ "Ġdepend ency",
+ "Ġìļ ©",
+ "Ġì± ħ",
+ "Ġwäh rend",
+ "Ġsu lla",
+ "ĠPitts burgh",
+ "Ġesemp io",
+ "¼ë ¡ľ",
+ "pr ot",
+ "ĠR osen",
+ "ĠIndepend ence",
+ "Ġpars ley",
+ "ie gen",
+ "Ġha w",
+ "Ġaqu ell",
+ "ĠC AP",
+ "ĠÑĢабоÑĤ аÑĤÑĮ",
+ "ĠCl iff",
+ "ion ar",
+ "Ġsec uring",
+ "æĪijåĢij çļĦ",
+ "ν ε",
+ "Ġutil is",
+ "Ġcou le",
+ "ĠP ing",
+ "Ġtre k",
+ "Ġf ak",
+ "Ġenorm e",
+ "Ġìĭ «",
+ "è® ©",
+ "Ġdoub ling",
+ "ĠнÑĢав иÑĤÑģÑı",
+ "Ġh ed",
+ "ho ven",
+ "ĠStand ing",
+ "Ġm ÃŃn",
+ "ĠJ imin",
+ "Ġmon arch",
+ "Ġco ke",
+ "Ġm r",
+ "Ġcl ic",
+ "Ã į",
+ "Ġimpe achment",
+ "Ġdur ability",
+ "Ġvar ios",
+ "Ġcommercial s",
+ "Ġgreet ings",
+ "ĠR i",
+ "ĠApp reci",
+ "ìŀĪ ëĬĶ",
+ "Ġrés ult",
+ "ér t",
+ "Ġsal ute",
+ "Ġpoder ia",
+ "Ġsun rise",
+ "ve ck",
+ "Ġreluct ant",
+ "Ġcommission er",
+ "å¿ µ",
+ "â te",
+ "ĠKen ny",
+ "ĠSir i",
+ "ãĥĥ ãĥĹ",
+ "ĠëĬ ĺ",
+ "ĠE E",
+ "Ġun ch",
+ "к он",
+ "ĠاÙĦØ ¥",
+ "Ġbel ts",
+ "Ġhas s",
+ "Ġмо Ñı",
+ "Ġdispl aced",
+ "Ġab ra",
+ "ÎŃ Î»",
+ "Ġscratch es",
+ "Ġcom et",
+ "Ġauthor ization",
+ "ĠL LC",
+ "Ġprodu k",
+ "Ġrehabil itation",
+ "å ŀ",
+ "Ñĸ Ñĩ",
+ "ud ing",
+ "ol it",
+ "Ġ10 5",
+ "Ġexp ands",
+ "Ġalt ri",
+ "ĠKom ment",
+ "Ġan f",
+ "P l",
+ "ĠM ana",
+ "f ed",
+ "Ġb ri",
+ "Ġor a",
+ "G s",
+ "ĠG ur",
+ "uck land",
+ "Ġjun ction",
+ "Ġiron ic",
+ "ĠFe ed",
+ "Ġpra kt",
+ "ĠHam mer",
+ "Įë ıĦ",
+ "ĠTr acy",
+ "çµ ±",
+ "ĠAs ide",
+ "н его",
+ "ĠиÑģполÑĮз оваÑĤÑĮ",
+ "Ġz aj",
+ "Ġequ itable",
+ "Ġcur b",
+ "Ġãģĵ ãĤĮ",
+ "Ġderiv atives",
+ "Ġpupp ies",
+ "ĠKenn eth",
+ "ĠCom pl",
+ "ig ram",
+ "ĠGar cia",
+ ") \"",
+ "ĠHar bor",
+ "est ial",
+ "Ġ ä¾Ĩ",
+ "Ġ ers",
+ "æ ¹",
+ "Ġunw anted",
+ "Ġbel ang",
+ "аР³Ð¾",
+ "em b",
+ "d os",
+ "ĠìĻ ľë",
+ "ĠBud get",
+ "Ġbatt ling",
+ "ØŃ Øª",
+ "k ok",
+ "наÑĩ ала",
+ "Ġpl ag",
+ "Ġcant idad",
+ "Ġgrup os",
+ "Ġplug ins",
+ "ler ini",
+ "Ġиме еÑĤ",
+ "Ġso zusagen",
+ "ol ics",
+ "Ġpue blo",
+ "Ġrem inis",
+ "r än",
+ "ĠMor rison",
+ "Ġl inha",
+ "Ġbreath s",
+ "ĠT aste",
+ "Ġenf rent",
+ "ĠDo cker",
+ "Ġд ен",
+ "Ġethnic ity",
+ "Ġw ob",
+ "Ġsuff ers",
+ "Ġtransition ing",
+ "ĠR ange",
+ "ÄĻd zy",
+ "Ġк аÑĤ",
+ "Ġsy ner",
+ "Ġdon ut",
+ "Ġprob abilities",
+ "ĠO mar",
+ "Wh ich",
+ "u ish",
+ "is in",
+ "Ġdem os",
+ "ĠìłĢ 기",
+ "Ġëĺij ê°Ļ",
+ "Ġед ин",
+ "Ġc erve",
+ "Ġj oka",
+ "I AN",
+ "Ġkilomet er",
+ "Ġhorizont ally",
+ "ĠBh ag",
+ "Ġ- >",
+ "ĠMon itor",
+ "Ġknowledge able",
+ "Ġf av",
+ "Ġpin ned",
+ "Ġe Bay",
+ "ick er",
+ "Ġìŀłê¹ IJë§Į",
+ "ĠXia omi",
+ "Ġcap it",
+ "Ġn p",
+ "Ġ196 5",
+ "ho e",
+ "Ġn ok",
+ "ĠS age",
+ "Ġн елÑĮзÑı",
+ "ĠT ow",
+ "g am",
+ "Ġdic en",
+ "ĠSUBSCRI BE",
+ "Ġrebo ot",
+ "Ġp aj",
+ "Ġë³´ìĹ ¬ë",
+ "Ġth icken",
+ "ĠRe ality",
+ "id än",
+ "N a",
+ "Ġê²ĥ ìĿĢ",
+ "!! )",
+ "Ġrout ines",
+ "Ġод ного",
+ "Ġex ting",
+ "Ġì¦ Ŀ",
+ "Ġsulf ur",
+ "Ġcar ve",
+ "Ġastero id",
+ "ĠWarri or",
+ "Ġphotograph ers",
+ "Ġpe ll",
+ "Ġcros sover",
+ "æĪij çŁ¥éģĵ",
+ "Ġhace mos",
+ "ĠNe j",
+ "Ġsett ling",
+ "Ġir m",
+ "ĠBook s",
+ "ient ôt",
+ "Ġesp acio",
+ "ĠSchol ars",
+ "Ġdo omed",
+ "ĠIR S",
+ "w ohl",
+ "Ġseg ue",
+ "ĠëĪĦ ê°Ģ",
+ "Ġpr atic",
+ "B T",
+ "ĠConsider ing",
+ "ĠBuff alo",
+ "Ġtrain ings",
+ "Ġge bru",
+ "ĠG leich",
+ "Ġpir ates",
+ "Ġen velop",
+ "Ġre open",
+ "im at",
+ "Ġte e",
+ "Ġsu ed",
+ "fe h",
+ "Ġ×Ķ× §",
+ "Ġdi ets",
+ "Ġjunt os",
+ "ast o",
+ "Ġmisunder stood",
+ "Ġru im",
+ "Ġclass ify",
+ "ĠпÑĢод Ñĥк",
+ "Ġin se",
+ "Ġillust rated",
+ "Ġcorros ion",
+ "Ġacc red",
+ "ĠAunt ie",
+ "ĠпÑĢив еÑĤ",
+ "ĠLI VE",
+ "Ġre k",
+ "Ġrece ipt",
+ "åĪ° åºķ",
+ "ĠBar bie",
+ "ĠSn ake",
+ "t urn",
+ "Je ff",
+ "ãģĬ ãģĬ",
+ "ķ Ħ",
+ "VO ICEOVER",
+ "co ll",
+ "Ġrun ners",
+ "ìł ľë",
+ "os os",
+ "mo on",
+ "Ġkey note",
+ "ĠInst it",
+ "S PEAK",
+ "Ġplug s",
+ "Ġcur v",
+ "ĠY uri",
+ "ĠTh eres",
+ "ĠP s",
+ "Ġμ ÏĢο",
+ "Ġconver ter",
+ "Ġref ine",
+ "Ġbad ass",
+ "Ġο ι",
+ "Ġreg en",
+ "az zi",
+ "ÙĬ Ùģ",
+ "Ġse ized",
+ "Ġiç er",
+ "ile e",
+ "Ġup stream",
+ "Ġbud s",
+ "Ġp im",
+ "Ġíķĺë £¨",
+ "Ġall uded",
+ "Ġthem ed",
+ "Ġconsist ing",
+ "Ġb ons",
+ "un uz",
+ "ĠпÑĢов од",
+ "ĠLove ly",
+ "ॠĭ",
+ "Ġpar ach",
+ "ĠSta ats",
+ "éļ Ĭ",
+ "Ġselect ive",
+ "Ġf ase",
+ "ĠGeor get",
+ "Ġcoc aine",
+ "Ġreprodu ction",
+ "ĠL ara",
+ "ĠL D",
+ "Ġg h",
+ "J on",
+ "Ġl Ã¥",
+ "Ġëij IJë",
+ "Ġtyp ed",
+ "ĠB ana",
+ "ë ĵľë",
+ "Ġsav ory",
+ "ĠZ omb",
+ "stand en",
+ "Ġpedest rian",
+ "Ġdifférent s",
+ "Ġìĭ ¸",
+ "èī ¯",
+ "Ġcompl ained",
+ "ç¦ ı",
+ "ĠÐļ ÑĤо",
+ "Ġ×ľ× ¤",
+ "ali ÅĽmy",
+ "Ġmort ar",
+ "Ġverd ict",
+ "Ġsu ficiente",
+ "ĠMill ion",
+ "mitt el",
+ "in als",
+ "ĠاÙĦØ ®",
+ "аÑİ ÑģÑĮ",
+ "Ġmi ÄĻdzy",
+ "ĠO le",
+ "Ġin vert",
+ "czy Äĩ",
+ "озм ожно",
+ "star ter",
+ "Ġaud itor",
+ "ĠSc out",
+ "ch ien",
+ "ĠSver ige",
+ "uff led",
+ "Ġze hn",
+ "ĠA uckland",
+ "Ġarg ent",
+ "Ġ197 6",
+ "ĠHo e",
+ "Ġboth ers",
+ "Ġsocial ist",
+ "Ġpl iers",
+ "Ġemer gen",
+ "ĠX P",
+ "еÑĢ ов",
+ "M ore",
+ "ĠLe vi",
+ "ĠAnd ers",
+ "ibil idad",
+ "ĠP arents",
+ "Ġindu ced",
+ "ìĸ´ì ¤",
+ "Ġbal ances",
+ "ĠвÑĭ ÑĪ",
+ "Ġsubmar ine",
+ "St art",
+ "Ġdri es",
+ "Ġvol ver",
+ "Ġtick ing",
+ "c ott",
+ "Ġf aj",
+ "pr és",
+ "ĠS abb",
+ "Ġза Ñĩ",
+ "Ġпок Ñĥп",
+ "Ġbapt ized",
+ "ĠBrill iant",
+ "ĠÐij ог",
+ "Ġm ots",
+ "b its",
+ "Ġlatt ice",
+ "æĪij è·Łä½ł",
+ "Ġcor iander",
+ "Ġresid ency",
+ "yn c",
+ "Ġpier wszy",
+ "ĠKn ock",
+ "ĠZ ap",
+ "ĠÐķ в",
+ "ê² ¬",
+ "å°ı å¿ĥ",
+ "Ġune ven",
+ "ĠJ as",
+ "od or",
+ "ç¿ Ĵ",
+ "7 4",
+ "ĠS ite",
+ "Ġacontece u",
+ "ym pt",
+ "Ġtril ogy",
+ "Ġlan tern",
+ "ĠZ ucker",
+ "v ari",
+ "we lling",
+ "ĠPot ato",
+ "gom ery",
+ "Ġreact ed",
+ "ĠChr on",
+ "Ġj ede",
+ "be eld",
+ "Ġtw ent",
+ "Ġl act",
+ "æ¨ Ĥ",
+ "Ġré se",
+ "Ġrel ent",
+ "Ġfurn ace",
+ "Ġwid get",
+ "Ġearthqu akes",
+ "ĠAd just",
+ "il it",
+ "ĠØ£ ÙĪ",
+ "Ġhear ings",
+ "Ġdefend ant",
+ "irs iniz",
+ "Ġbas k",
+ "c ja",
+ "ľ ¨",
+ "Ġrif les",
+ "Ġinst al",
+ "ĠFor give",
+ "p ical",
+ "ĠÐŀÑĩ енÑĮ",
+ "Ġpet ites",
+ "Ġh p",
+ "Ġren owned",
+ "ĠIn n",
+ "Ġ주 ìĦ¸ìļĶ",
+ "Ġemphas ized",
+ "éĹ® é¢ĺ",
+ "ĠìŀĪ ì£ł",
+ "Ġê²ĥ ìľ¼ë¡ľ",
+ "ãĤ Ĩ",
+ "Å ĵ",
+ "g ili",
+ "D ave",
+ "Ġexha usting",
+ "ÅĤ ug",
+ "Ġsch ema",
+ "μ ά",
+ "cy cl",
+ "Ġaut ant",
+ "Ġpar cel",
+ "Ġmater ia",
+ "ĠB erry",
+ "ĠÑģ ами",
+ "Ġextract ed",
+ "ĠSay ing",
+ "ism atic",
+ "Ġпоп ÑĢоб",
+ "Ġneur on",
+ "g raph",
+ "ľë ©´",
+ "Ġencl osure",
+ "ĠJoh ann",
+ "Ġafter math",
+ "ÑĤ об",
+ "Ġu ży",
+ "Ġs amp",
+ "3 60",
+ "ĠMe i",
+ "Ġt aco",
+ "Ġrecept ors",
+ "Ġpunch es",
+ "ĠHo je",
+ "ĠÙĩ ÙĨا",
+ "=\" #",
+ "ĠAng ular",
+ "Ġmus ique",
+ "Ġro l",
+ "ĠÃ ±",
+ "ster reich",
+ "Ġcl am",
+ "ĠTre asury",
+ "chem ical",
+ "Ġap ar",
+ "Ġapp end",
+ "Ġforb id",
+ "ĠHamb urg",
+ "ак ов",
+ "Ġê¸ Ī",
+ "ild a",
+ "Ġprepar ations",
+ "Ġmog Äħ",
+ "Ġcam ino",
+ "E ric",
+ "ĠBl ind",
+ "èĪ ĩ",
+ "å¹´ çļĦ",
+ "ĠDis covery",
+ "ì¸ ł",
+ "çĪ ¶",
+ "Ġinterpre ter",
+ "Ġb red",
+ "ĠPsal m",
+ "Ġdef ended",
+ "ìī ¬",
+ "ĠEr fahr",
+ "ĠPe ach",
+ "Ġmo ons",
+ "ĠO st",
+ "Ġspé cial",
+ "Ġarri ver",
+ "ĠW is",
+ "u ci",
+ "Ġrobot ics",
+ "I VE",
+ "Ġsie ge",
+ "ar la",
+ "Ġsepar ates",
+ "ĠT C",
+ "íı °",
+ "quis ite",
+ "Ġparenth eses",
+ "ик е",
+ "ç« Ļ",
+ "Ġtr ous",
+ "å» º",
+ "ĠÑģ илÑĮ",
+ "Ġbe ers",
+ "Ġпл аÑĤ",
+ "ãģĻãģĶ ãģĦ",
+ "Ġso la",
+ "Ġd ès",
+ "ming ham",
+ "ik te",
+ "Ġo ops",
+ "Ġtw itch",
+ "å° ĩ",
+ "Ï Ī",
+ "ĠShould n",
+ "uv re",
+ "Ġle er",
+ "cript ions",
+ "Ġeyes hadow",
+ "ĠGu o",
+ "ĠPow ell",
+ "Ġsup uesto",
+ "Ġan a",
+ "r als",
+ "ĠMont real",
+ "Ġsurf ing",
+ "ĠÐŁÐµÑĢ в",
+ "×ŀ ×ķ",
+ "Ġmillise conds",
+ "Ġsubur bs",
+ "Ġplanet a",
+ "ÑĥÑĪ ка",
+ "hr lich",
+ "ĠH Y",
+ "Ġس ÛĴ",
+ "ĠM M",
+ "ĠE ff",
+ "åı¯ æĦĽ",
+ "ĠH S",
+ "ans on",
+ "Ġì§ģ ìłij",
+ "Ġsu o",
+ "Ġdeploy ing",
+ "Ġk unt",
+ "ter ing",
+ "Ġere ct",
+ "ìŀ¥ ìĿ´",
+ "ĠìĿĮ ìĭĿ",
+ "Ġspec imen",
+ "! ...",
+ "æĪij 說",
+ "Ġlig ne",
+ "Ġk onst",
+ "ade qu",
+ "Ġìĥģ íĥľ",
+ "Ġaccess ed",
+ "ĠP ole",
+ "k ill",
+ "Ġë² Ħë",
+ "Ġauthentic ity",
+ "Ġapp elle",
+ "ull e",
+ "Ġrev ision",
+ "Ġgo ats",
+ "г ли",
+ "Ġp au",
+ "ĠR anger",
+ "ĠIm ag",
+ "aut hor",
+ "Ġe ve",
+ "ĠMess enger",
+ "Ġn ay",
+ "Ġwh oles",
+ "ät te",
+ "Ġon wards",
+ "ĠDep ois",
+ "Ġíijľ íĺĦ",
+ "ĠSAR S",
+ "Ġwszystk ich",
+ "Ġdest ru",
+ "umb ing",
+ "Ġcompat ibility",
+ "Ġmis information",
+ "od ore",
+ "ĠF avor",
+ "ek o",
+ "ı Į",
+ "w aukee",
+ "ĠTe aching",
+ "ĠK O",
+ "Ġbet ting",
+ "Ġquest s",
+ "Ġviv re",
+ "ĠмÑĥз Ñĭ",
+ "Ġs aga",
+ "Ġswe ll",
+ "Ġge he",
+ "æĢİ麼 樣",
+ "ĠоÑĢг аниз",
+ "Ġg ide",
+ "ĠG ross",
+ "Ġdale j",
+ "Ġcl aws",
+ "á»Ļ c",
+ "Ġprejud ice",
+ "Ġins ign",
+ "i hood",
+ "Ġpl ed",
+ "Ġdó nde",
+ "ĠPolit ical",
+ "Ġprem ises",
+ "und ert",
+ "ع ت",
+ "on nen",
+ "Ġespa ço",
+ "Ġf é",
+ "ĠHarr ison",
+ "ĠC ensus",
+ "Ġcard io",
+ "Ġdi y",
+ "Ġmil ieu",
+ "Ġjourn ée",
+ "ĠRe lease",
+ "N IE",
+ "ĠM uk",
+ "id ée",
+ "á»į i",
+ "Ġiç inde",
+ "ŀ Ļ",
+ "Ġreson ate",
+ "Ġm oles",
+ "ĠF lying",
+ "ĠGl oria",
+ "ĠPast or",
+ "ĠAre na",
+ "好 ä¸į好",
+ "N ON",
+ "ол ов",
+ "Ġall ÃŃ",
+ "om at",
+ "ìĸ´ë ıĦ",
+ "Ġcaracter ÃŃst",
+ "Ġdecl ining",
+ "Ñĸ Ñı",
+ "an co",
+ "ĠIn form",
+ "Ġbarg ain",
+ "Ġbus hes",
+ "ĠNat urally",
+ "Ġre chts",
+ "ĠT ensor",
+ "ĠPat ricia",
+ "Ġprincip io",
+ "ĠM umbai",
+ "Ġwom b",
+ "Ġnost ra",
+ "Ġdile mma",
+ "Ġirgendw ann",
+ "Ġ196 4",
+ "Ġenerg ÃŃa",
+ "Ġна ÑĢ",
+ "Ġseg regation",
+ "ĠA thlet",
+ "Ġ» ,",
+ "Ġy eni",
+ "ĠSe it",
+ "Ġven om",
+ "Ġdak ika",
+ "Ġëı Įë",
+ "ĠÃī l",
+ "Ġf us",
+ "ĠM og",
+ "¦½ ëĭĪëĭ¤",
+ "Ġrem ar",
+ "ĠTed dy",
+ "Ġbreast s",
+ "ic ans",
+ "æĶ¶ çľĭ",
+ "k ap",
+ "Ġh Æ¡n",
+ "ĠJ P",
+ "ãĥ³ ãĤ¿",
+ "Ġresur rect",
+ "ĠìĿ ¸ë",
+ "her ical",
+ "Ġfot ograf",
+ "ĠJos é",
+ "Ġlivel ihood",
+ "Ġbib li",
+ "ter i",
+ "Ġvor stellen",
+ "ĠA AA",
+ "Ġassess ing",
+ "Y A",
+ "Ġspl end",
+ "Ġexca v",
+ "Ġbapt ism",
+ "y ll",
+ "w ow",
+ "M ac",
+ "Ġpl astics",
+ "teok bokki",
+ "Ġintéress ant",
+ "Ġcommand ed",
+ "Ġfamous ly",
+ "ĠÐĺ ли",
+ "ĠMan uel",
+ "Ġsouth west",
+ "Ġde formation",
+ "ÃŃcul o",
+ "ĠнаÑħод иÑĤÑģÑı",
+ "ĠP atter",
+ "d egree",
+ "ĠczÄĻ sto",
+ "\" -",
+ "Ġìħ ĭ",
+ "Ġman ger",
+ "ĠTrust ee",
+ "Ģë ¦¬",
+ "Ġpunt os",
+ "iv able",
+ "Ġvol atile",
+ "ĠëĬ IJ",
+ "Ġinst ability",
+ "Ġc iel",
+ "ci Äħ",
+ "Ġpur ity",
+ "но ÑģÑĤ",
+ "S il",
+ "ed ar",
+ "åĻ ¨",
+ "NOUN CER",
+ "Ġspe lled",
+ "G ER",
+ "Ġsanct uary",
+ "Ġacceler ating",
+ "Ġsc out",
+ "ĠпÑĢ ев",
+ "f ahren",
+ "ãģĵ ãģ¡ãĤī",
+ "ĠëĤĺìĺ ¨",
+ "Ġpocz Äħt",
+ "ĠMe u",
+ "ka ar",
+ "³´ ê³ł",
+ "ak ra",
+ "D own",
+ "ĠÃĦ r",
+ "ĠEl ite",
+ "Ġall ons",
+ "Ġmay onnaise",
+ "ĠS ustain",
+ "prising ly",
+ "Ġsuper vis",
+ "Ġê·¸ëłĩ ì£ł",
+ "Ġunemploy ed",
+ "Ġfresh ly",
+ "Ġ×ŀ× ¢",
+ "ĠD h",
+ "Ġtack ling",
+ "Ġo gr",
+ "Ġì´ Īë",
+ "ãĤĪ ãĤį",
+ "Ġlo ft",
+ "ar ah",
+ "ĠA irl",
+ "ĠD ir",
+ "ĠÐľ ожно",
+ "Ġbook ing",
+ "ĠC RA",
+ "Ġhtt ps",
+ "Ġcho ke",
+ "Ġg own",
+ "Ġno ite",
+ "Ġz ac",
+ "ist ol",
+ "Ġsec re",
+ "Ġresemb les",
+ "Ġcu ad",
+ "ìĤ¬ ê°Ģ",
+ "sh ow",
+ "Ġbl anc",
+ "Ġag u",
+ "ĠPr int",
+ "ast ed",
+ "ĠWe ather",
+ "i pl",
+ "Ġobsc ure",
+ "Ġcont e",
+ "ough s",
+ ") ;",
+ "ĠD ame",
+ "ä¸Ģ 缴",
+ "Ġclar ification",
+ "Ġintim acy",
+ "Ġup hold",
+ "ĠMir ror",
+ "Ġw agon",
+ "x ide",
+ "Ġcl og",
+ "app er",
+ "ĠImmedi ately",
+ "ú de",
+ "Ġtouch down",
+ "Ġro oft",
+ "аÑĪ а",
+ "Ġç ıkt",
+ "Ġla isser",
+ "ĠUn real",
+ "ens itive",
+ "Ġ12 3",
+ "Ġpl aster",
+ "Ġduck s",
+ "Ġet me",
+ "Ġb ishop",
+ "bre vi",
+ "Ġb ic",
+ "ä¸ĭ åİ»",
+ "Ġrun time",
+ "Ġamb itions",
+ "м аÑĤ",
+ "ĠWe in",
+ "ĠMar i",
+ "ĠíĬ ¸ë",
+ "Ġresol ver",
+ "Ġng Ãły",
+ "ĠR ise",
+ "ãĤĪãģĨ ãģ«",
+ "ĠCr us",
+ "Ġmerchand ise",
+ "Ġel i",
+ "Ġstate wide",
+ "Ġow l",
+ "éģ ł",
+ "æĶ ¹",
+ "Ġtwist ing",
+ "Ġcontam inated",
+ "ĠCom merce",
+ "hy thm",
+ "ĠÃ Ī",
+ "Ġìĭ ¤ë",
+ "Ġmus ste",
+ "u ir",
+ "Ġsum s",
+ "ĠSome where",
+ "ãĥ İ",
+ "Ġk ami",
+ "Ġa ired",
+ "ĠAND REW",
+ "Ġê º",
+ "Ġv iendo",
+ "Ġantib ody",
+ "Ġabsol ument",
+ "Ġprotest ers",
+ "ĠQué bec",
+ "st adt",
+ "Sha un",
+ "Ġcham bers",
+ "ĠWe ar",
+ "ĠEffect s",
+ "Ġhaz ards",
+ "Ġne i",
+ "Ġcoraz ón",
+ "Ġá ¼",
+ "ĠS G",
+ "Ķ ©",
+ "ĠìĹŃ ìĭľ",
+ "Ġcom fy",
+ "ĠC ody",
+ "Ġpens ando",
+ "Ġg anska",
+ "ĠAc ross",
+ "öll ig",
+ "aby te",
+ "Ġwed ge",
+ "Ġkal ian",
+ "Ġsig ue",
+ "end es",
+ "ĠGro ÃŁ",
+ "Ġutil iser",
+ "Ġfl own",
+ "ани Ñİ",
+ "Ġle var",
+ "rest rial",
+ "Ġillust rations",
+ "Ġas lında",
+ "BLE EP",
+ "Ġдо ÑģÑĤ",
+ "Ġtur ret",
+ "Ġsuit case",
+ "ziÄĻ ki",
+ "Ġsket ches",
+ "Ġac red",
+ "ĠRe i",
+ "Ġt sun",
+ "ĠS ag",
+ "Ġthird s",
+ "ĠKIR BY",
+ "ra i",
+ "Ġhuman os",
+ "Ġrecomm ends",
+ "Ġextraordin arily",
+ "Ġcommence ment",
+ "K N",
+ "ope z",
+ "Ġ×ij× ©",
+ "Ġlet hal",
+ "ĠEst amos",
+ "Ġinspect or",
+ "ĠSe ok",
+ "e un",
+ "Ġoff shore",
+ "Ġget tin",
+ "ye ars",
+ "ĠSil ence",
+ "ĠNat ur",
+ "up un",
+ "Ġtr zy",
+ "Ġno get",
+ "Ġhamb urger",
+ "ĠPra ise",
+ "é nd",
+ "Ġ197 1",
+ "yl ie",
+ "k rit",
+ "ĠìĥĿê°ģ ìĿ´",
+ "çļ ®",
+ "Ġmoment os",
+ "Ġest é",
+ "Ġdisse min",
+ "Ġgig s",
+ "Ġdes af",
+ "Ġav is",
+ "ĠZ oo",
+ "ĠìķĬ ìĿĢ",
+ "h äng",
+ "åı ¥",
+ "h ake",
+ "ĠB ism",
+ "Ġre think",
+ "ĠMal colm",
+ "Ġident ifies",
+ "l ower",
+ "ix el",
+ "Ġtv Ã¥",
+ "k ed",
+ "ier z",
+ "Ġö ffentlich",
+ "Ġproc laim",
+ "so on",
+ "l ol",
+ "Ġlo i",
+ "Ġb itten",
+ "ro llo",
+ "Ġser mon",
+ "Ġes qu",
+ "Ġjack ets",
+ "Ġgr áfic",
+ "Ġпок азÑĭв",
+ "Ġcabe za",
+ "ch odzi",
+ "Ġpel vis",
+ "Ġnost algia",
+ "Ġbre w",
+ "Ġshort cuts",
+ "ĠAd emás",
+ "Ġsuperfic ial",
+ "åħ© åĢĭ",
+ "Ġbo ca",
+ "ĠæĪij æĺ¯",
+ "iment os",
+ "åĽł 为",
+ "Ġspr outs",
+ "é£ Ľ",
+ "ĠJon as",
+ "ĠFloren ce",
+ "st atic",
+ "da ughter",
+ "* )",
+ "ÅĤ by",
+ "f ashion",
+ "ĠG inger",
+ "Ġë§ ¤ë",
+ "Ġhust le",
+ "ut os",
+ "ĠÑĤ Ñıж",
+ "ĠL ös",
+ "ש ×Ļ×Ŀ",
+ "any ch",
+ "tu ber",
+ "Ġtid y",
+ "Ġfront al",
+ "Ġwhis key",
+ "Ġhum id",
+ "ĠÎ Ł",
+ "Ġr idge",
+ "Ġmar in",
+ "Ġb ientôt",
+ "ĠCarr ie",
+ "ch w",
+ "Ġtah un",
+ "ĠEr geb",
+ "F R",
+ "Ġìłķ ë¶Ģ",
+ "ĠSold ier",
+ "Ġenlight enment",
+ "Ġexam ining",
+ "ĠNot re",
+ "Ġer am",
+ "ĠSun ny",
+ "Ġlay ered",
+ "ĠD azu",
+ "r ades",
+ "好 åIJĥ",
+ "ĠнаÑĪ ей",
+ "Ġtim ber",
+ "Ġman ners",
+ "ĠBir mingham",
+ "Ġmini ature",
+ "omet ers",
+ "Ġfill er",
+ "ĠR ip",
+ "ĠK omb",
+ "own er",
+ "ì ¿",
+ "id ian",
+ "Ġdem ás",
+ "ĠÙĪ ت",
+ "Ġpreca utions",
+ "Ġgovern o",
+ "z elf",
+ "ĠCom plete",
+ "å¸ ĥ",
+ "ĠPh antom",
+ "ãģ¾ ãģļ",
+ "Ġн ез",
+ "ĠкаÑĢ ÑĤ",
+ "ĠAnt wort",
+ "ĠPf izer",
+ "ĠFran co",
+ "Ġw ÅĤ",
+ "Ġfr ig",
+ "es per",
+ "Ġk ale",
+ "Ġfilm maker",
+ "Ġk urt",
+ "Ġinv alid",
+ "å± Ģ",
+ "are lla",
+ "Äĥ ng",
+ "ram ento",
+ "Ġnutr itional",
+ "Ġdict ators",
+ "Ġaf in",
+ "Ġf uzzy",
+ "ĠG ina",
+ "ó t",
+ "ĠExtrem adura",
+ "Ġdemonst rations",
+ "ĠMont gomery",
+ "íķ´ì Ħ¤",
+ "ĠGand hi",
+ "ãĥ Ŀ",
+ "ç½ ®",
+ "Ġreun ion",
+ "Ġjaki ÅĽ",
+ "ĠZ ug",
+ "OU GH",
+ "l ifting",
+ "Ġ à²",
+ "á¹Ľ á¹£",
+ "e b",
+ "ĠW OW",
+ "ĠSh iva",
+ "omet ry",
+ "Ġwild ly",
+ "Ġt ended",
+ "Ġmeg ap",
+ "ì² ĺ",
+ "Ġna use",
+ "Ġg erek",
+ "ãĥ ĭ",
+ "ĠMar cel",
+ "Ġn este",
+ "خ ر",
+ "Ġfe h",
+ "åĨ ħ",
+ "susp enseful",
+ "ĠWrest le",
+ "ĠPalestin ians",
+ "ĠG ORD",
+ "iy et",
+ "ĠÑĢ ади",
+ "Ġvers uchen",
+ "Ġtrans istor",
+ "ĠÐŁÑĢ оÑģÑĤо",
+ "Ġпон ÑĢав",
+ "Ġrhy me",
+ "ĠVerm ont",
+ "pl atz",
+ "è® °",
+ "ĠÄ°ÅŁ te",
+ "ĠH ag",
+ "ĠÐĺ м",
+ "ĠÑĢаÑģÑģк аз",
+ "Ġmet ros",
+ "ĠInfin ity",
+ "w olf",
+ "ib al",
+ "ft ig",
+ "Ġ ÚĨ",
+ "Ġíĺ¹ ìĭľ",
+ "Ġo ggi",
+ "Ġdisp osit",
+ "ĠпÑĢ ил",
+ "ĠвÑĭ пол",
+ "Ġth ôi",
+ "ĠK ENN",
+ "Ġhand ing",
+ "act us",
+ "Ġtac os",
+ "Ġformer ly",
+ "ĠCorinth ians",
+ "ãģ« ãģ¯",
+ "ÑĨÑĸ ÑĹ",
+ "Ġpad re",
+ "Ġcongreg ation",
+ "æ ij",
+ "fer t",
+ "Ġsub ir",
+ "ais er",
+ "qu a",
+ "ara oh",
+ "ĠCur ry",
+ "ĠìķĬ ëĬĶ",
+ "ел Ñİ",
+ "Ġf uss",
+ "Ġbo oty",
+ "Ġl ows",
+ "Ġh ommes",
+ "ĠM H",
+ "ĠDisney land",
+ "w ent",
+ "Ġresid ue",
+ "Ġbe eping",
+ "è¼ ķ",
+ "ät ta",
+ "Ġm ould",
+ "ĠPro jekt",
+ "st alk",
+ "Ġartif act",
+ "ĠAnt rag",
+ "ĠAM D",
+ "ĠCry pt",
+ "Ġë© Ķ",
+ "ĠFel ipe",
+ "ĠCO B",
+ "el u",
+ "Ġself ies",
+ "ĠS anti",
+ "ch utz",
+ "ĠУ кÑĢаÑĹ",
+ "ges amt",
+ "Ġflo ck",
+ "j az",
+ "pl ain",
+ "Ġwr inkles",
+ "Ġre ais",
+ "Ġpal jon",
+ "Ġempower ment",
+ "Ġattend ees",
+ "pp a",
+ "Ġn eden",
+ "он Ñĭ",
+ "Ġtime frame",
+ "ĠCher ry",
+ "Ġid ée",
+ "Ġg ag",
+ "Ġdon key",
+ "Ġô ng",
+ "ĠH are",
+ "éļ Ľ",
+ "ĠK ara",
+ "Ġacom pan",
+ "pl aces",
+ "im ientos",
+ "ĠH amm",
+ "б и",
+ "ub en",
+ "ili yor",
+ "Ġth irst",
+ "Ġk ry",
+ "ĠGeorget own",
+ "׳ ×Ķ",
+ "Ġor ch",
+ "Ġheart beat",
+ "Ġtransform ations",
+ "est ones",
+ "ĠK H",
+ "Ġcart oons",
+ "Ġan ci",
+ "Ġworth less",
+ "Ġtail ored",
+ "p u",
+ "Americ ans",
+ "Ġp iles",
+ "ĠMon key",
+ "Ġbas in",
+ "ĠTem per",
+ "ĠP aint",
+ "Ġpunch ing",
+ "Ġba ik",
+ "ĠOak land",
+ "v re",
+ "ÅŁ allah",
+ "yd d",
+ "Ġcas ually",
+ "od u",
+ "Ġc oded",
+ "ĠNorweg ian",
+ "ĠV ince",
+ "Ġprem ature",
+ "ĠProm ise",
+ "ек ÑģÑĤ",
+ "Ġdevast ated",
+ "ĠPrem ium",
+ "ĠPar am",
+ "ĠÃĸ yle",
+ "um uz",
+ "P O",
+ "r ators",
+ "Ġlamp s",
+ "Ġterritor ial",
+ "Ġback bone",
+ "list ed",
+ "D Y",
+ "ĠاÙĦ ر",
+ "Ġpurs ued",
+ "ĠComm ons",
+ "Ġê³ ¡",
+ "lo cks",
+ "ed or",
+ "Ġconce ived",
+ "g ere",
+ "Ġdisappe aring",
+ "ĠS ull",
+ "ĠìĹ °ë",
+ "Ġho ffe",
+ "Ġdet ox",
+ "íĶ Į",
+ "Ġret ir",
+ "ĠëģĿ ëĤ",
+ "Ġper gunta",
+ "ĠB OY",
+ "ç² ¾",
+ "Ġp enn",
+ "æĿ¥ äºĨ",
+ "h és",
+ "h on",
+ "Ġcatastroph ic",
+ "Ġa ust",
+ "Ġtor so",
+ "Ġìĸ´ ëĬIJ",
+ "ĠìĤ¬ëŀĮë ĵ¤ìĿ´",
+ "Ġmarvel ous",
+ "ĠHar ley",
+ "ach ine",
+ "Ġti ế",
+ "itt o",
+ "ĠI ÃŃm",
+ "yl on",
+ "Ġshut down",
+ ".' '",
+ "Ġap ologies",
+ "ĠCommun ication",
+ "ĠговоÑĢ Ñİ",
+ "ãģĤ ãĥ¼",
+ "âĦ ¢",
+ "ÃŃ veis",
+ "ac un",
+ "Ġret aining",
+ "Ġcontrad iction",
+ "ĠAD AM",
+ "C OM",
+ "Bry an",
+ "ĠM onsieur",
+ "Ġadap ting",
+ "Ш ÐIJ",
+ "ĠSc r",
+ "änd ert",
+ "Ġpl aus",
+ "ä»Ĭ天 çļĦ",
+ "Ġon set",
+ "Ġassist ants",
+ "Ġval ves",
+ "Ġsc atter",
+ "ĠR ust",
+ "aw ia",
+ "Ġread iness",
+ "Ġp ais",
+ "Ġb ible",
+ "Ġamb iente",
+ "Ġа меÑĢик",
+ "Ġunc ond",
+ "Ġk alk",
+ "åĬ ¨",
+ "Ġmo c",
+ "un n",
+ "Ġact u",
+ "Ġhum ming",
+ "iss imo",
+ "ĠPat rol",
+ "g ow",
+ "ãĥ ¤",
+ "ĠTHE Y",
+ "ĠBod en",
+ "ĠB ie",
+ "Ġre el",
+ "ĠÑĥÑģл ов",
+ "Ġende avor",
+ "ĠPer iod",
+ "ustom ed",
+ "m als",
+ "al on",
+ "B ox",
+ "ĠÏĥ αÏĤ",
+ "Ġom dat",
+ "Ġal tre",
+ "ĠHe h",
+ "k ad",
+ "Ġprotect or",
+ "Ġdomin ance",
+ "odynam ic",
+ "Ġcommunic ated",
+ "k ö",
+ "Ġprede cessor",
+ "ĠL uk",
+ "ĠFl ower",
+ "Ġãģ ©",
+ "po que",
+ "ÑĤи ÑĢов",
+ "Ġret rospect",
+ "Ġdecis ive",
+ "Ġexem pel",
+ "{ \\",
+ "ĠR ück",
+ "r ite",
+ "ĠZe us",
+ "Ġcal orie",
+ "Ġattract ions",
+ "ĠH inter",
+ "Ġuh m",
+ "ĠíĮ IJ",
+ "Ġrul ers",
+ "Ġdiscour aged",
+ "Ġaconte cer",
+ "Ġacc ents",
+ "ĠOpt im",
+ "ĠAl g",
+ "k ids",
+ "20 21",
+ "ĠLind say",
+ "Ġfilm makers",
+ "pr owad",
+ "Ġter ug",
+ "ëĭ ´",
+ "ĠSom mer",
+ "20 18",
+ "Ġborrow ing",
+ "ĠTrans fer",
+ "н оп",
+ "ari as",
+ "Ġhead phone",
+ "ì¼ ľ",
+ "Ġtransl ating",
+ "Ġauf ge",
+ "ப à®Ł",
+ "we is",
+ "av ant",
+ "pa id",
+ "b aby",
+ "Ġtough est",
+ "Ġrepe ats",
+ "ĠTer esa",
+ "L ord",
+ "Ġacab ar",
+ "ĠR ide",
+ "d ir",
+ "Ġl eng",
+ "Ġd wa",
+ "Ġhead aches",
+ "Ġn ữa",
+ "ĠнаÑģ ÑĤоÑıÑī",
+ "Ġbo ils",
+ "Ġlong ing",
+ "ri as",
+ "ó rio",
+ "ĠParad ise",
+ "ĠSeñ or",
+ "erd em",
+ "Ġrein st",
+ "Ġsal aries",
+ "Ġinsec urity",
+ "ÅĤo ÅĽci",
+ "ĠабÑģолÑİÑĤ но",
+ "ink en",
+ "ĠEd dy",
+ "ud os",
+ "Ġd ummy",
+ "Ðļ ак",
+ "s ix",
+ "Ġin box",
+ "Ạ©",
+ "Pe ople",
+ "á»ĵ ng",
+ "Ġorganiz ers",
+ "f ind",
+ "Ġü l",
+ "ĠCO M",
+ "ż a",
+ "we ile",
+ "Comment ary",
+ "íĬ¸ë ¥¼",
+ "ĠMitt el",
+ "k us",
+ "èĽ ĭ",
+ "ठ¨",
+ "ir al",
+ "Ġgar ment",
+ "ικ ά",
+ "Ġst ool",
+ "pay ers",
+ "Ġsh immer",
+ "ĠO llie",
+ "ĠJe żeli",
+ "è¿ĺ æľī",
+ "Ġ197 7",
+ "Ġje ux",
+ "Ġext inct",
+ "ĠTransport ation",
+ "ĠM aker",
+ "Ġj ohn",
+ "Ġrich est",
+ "Ġtraum at",
+ "Ġli egen",
+ "´ë ¥¼",
+ "è¿Ļ éĩĮ",
+ "Ġun rest",
+ "ĠSt raw",
+ "æĭľ æĭľ",
+ "Ġcom a",
+ "ĠKr isten",
+ "ĠÐļон еÑĩно",
+ "ĠBry ce",
+ "ĠÑıк Ñĸ",
+ "Ġpearl s",
+ "Ġпоним аÑİ",
+ "Ġadd itions",
+ "Ġas ympt",
+ "ĠменÑĮ ÑĪе",
+ "Ġsc ans",
+ "Ch ild",
+ "ĠH ide",
+ "к ÑĥÑİ",
+ "et as",
+ "Ġd ank",
+ "Ġple as",
+ "Ġess ays",
+ "Ġj ets",
+ "åħ Ĵ",
+ "Ġв ед",
+ "Ġposit ives",
+ "ho f",
+ "- )",
+ "zz o",
+ "Ġstar ters",
+ "Ġsm iled",
+ "Ġ194 4",
+ "qu iera",
+ "Ġro k",
+ "Ġpu esto",
+ "N ico",
+ "Ġsim ulations",
+ "Ġ à¶",
+ "Ġintrig ued",
+ "ĠOver watch",
+ "åĸ Ĥ",
+ "s igh",
+ "b ai",
+ "Ġë§IJ ê³ł",
+ "id é",
+ "Ġcra bs",
+ "áºŃ p",
+ "ĠIraq i",
+ "ìĿ´ë ¥¼",
+ "ÑĤ Ñı",
+ "ĠSoph ia",
+ "ĠDN S",
+ "Ġönem li",
+ "ĠLu o",
+ "Ŀ ¤",
+ "ĠCoun sel",
+ "l igen",
+ "анÑĮ ÑĪе",
+ "Ġtrump et",
+ "Ġd apat",
+ "ĠJ M",
+ "ĠEVER Y",
+ "Ġå°į ä¸įå°į",
+ "å¤ ¢",
+ "ĠL ayer",
+ "Ġc ô",
+ "н ал",
+ "ĠJ oo",
+ "ĠH ack",
+ "Ġs unt",
+ "ĠLeon ard",
+ "ĠFire base",
+ "äng er",
+ "Ġexpl oding",
+ "v oy",
+ "Ġì¦ IJ",
+ "ĠÑģ еÑĢÑĮ",
+ "Ġsever ity",
+ "Ġbest imm",
+ "çµIJ æŀľ",
+ "Ġt iring",
+ "Ġprocure ment",
+ "Ġdiplom acy",
+ "Ġdecor ative",
+ "ĠÙĬ ا",
+ "Ġpenet ration",
+ "Õ «",
+ "Ġout right",
+ "EN E",
+ "ĠUn i",
+ "od les",
+ "Ġz eros",
+ "Ġdelight ful",
+ "j m",
+ "Ġdo po",
+ "没 äºĭ",
+ "Ġposit ivity",
+ "ĠVIS TA",
+ "ĠRes ource",
+ "íĥ Ģë",
+ "ÑĪ ие",
+ "C arl",
+ "Ġpip ing",
+ "Ġchop ping",
+ "ĠGan ze",
+ "ü ss",
+ "ĠA o",
+ "Ġsh attered",
+ "ĠDet ective",
+ "Ġund oubtedly",
+ "Ġhall uc",
+ "Ġen ch",
+ "Ñĭ Ñĩно",
+ "ÑĥлÑı ÑĢ",
+ "is esti",
+ "Ġped als",
+ "Ġdur um",
+ "¤í Ķ",
+ "la imer",
+ "Ġprop re",
+ "C u",
+ "Ġtransl ator",
+ "Ġca ÅĤ",
+ "Ġê·¸ 걸",
+ "Ġca ÅĤy",
+ "U A",
+ "Ġrev ised",
+ "Ġпод об",
+ "ĠArt icle",
+ "ĠHait i",
+ "ĠÃ ĵ",
+ "ĠC trl",
+ "Ġroz m",
+ "la it",
+ "Ġletz te",
+ "is pering",
+ "dis play",
+ "Ġalumin ium",
+ "Ġpalab ras",
+ "Ġconoc er",
+ "Ġz itten",
+ "Ġdir ig",
+ "åıª æľī",
+ "Ġbrain storm",
+ "Ġw ifi",
+ "ĠPart icip",
+ "Ġview point",
+ "ĠQu an",
+ "Ġhier arch",
+ "W elcome",
+ "å¯ ¾",
+ "Ġoff en",
+ "ĠRe covery",
+ "gan o",
+ "W ould",
+ "Ġrep ro",
+ "Ġper ceptions",
+ "Ġdem asi",
+ "ĠBangl adesh",
+ "ĠIncred ible",
+ "Ġlet zt",
+ "Ġbehav ing",
+ "Ġaston ishing",
+ "Ġâ Ĩ",
+ "ĠëĤ¨ ìŀIJ",
+ "èµ° äºĨ",
+ "ãĥ Ķ",
+ "ĠGORD ON",
+ "C AR",
+ "? !\"",
+ "ĠP rest",
+ "Ġë§ŀ ìķĦìļĶ",
+ "Ġt and",
+ "Ġl ash",
+ "ç Ĭ",
+ "ific ant",
+ "Ġint oler",
+ "Ġг еÑĢо",
+ "Ġte u",
+ "as o",
+ "ĠÑģов еÑĤ",
+ "Ġtravel ers",
+ "ĠSy nd",
+ "ĠвеÑĢ Ñģ",
+ "F onda",
+ "ad ı",
+ "Ġtrans cription",
+ "Ġtit anium",
+ "Ġtw ists",
+ "Ġgear box",
+ "ens ation",
+ "f at",
+ "C oll",
+ "ĠCommon wealth",
+ "z on",
+ "ĠPolize i",
+ "ĠAPP LAUSE",
+ "f ry",
+ "ĠJud a",
+ "este em",
+ "Ġso ck",
+ "ĠJug end",
+ "Ġк ÑģÑĤаÑĤи",
+ "ĠD ro",
+ "Ġproch aine",
+ "ãĥ¼ ãĥ«",
+ "Ġli ksom",
+ "ĠEner gie",
+ "ĠMar ina",
+ "Ġ2 30",
+ "Ġê°Ģ ìĦľ",
+ "ump ing",
+ "Ġl one",
+ "ç´ ļ",
+ "Ġfont s",
+ "Ġbusiness man",
+ "Ġp ly",
+ "Ġdo e",
+ "gr id",
+ "ĠMil waukee",
+ "ĠE den",
+ "! \".",
+ "ĠÛĮ Ûģ",
+ "og ens",
+ "Ġteas er",
+ "Ġqui én",
+ "Ġincent iv",
+ "go vern",
+ "Ġchild care",
+ "Ġsneak ers",
+ "Ġimprison ed",
+ "Â ®",
+ "иÑĤ еÑģÑĮ",
+ "an bul",
+ "Ġreg ain",
+ "Ġtranqu il",
+ "Red ner",
+ "éĽ ¨",
+ "IF A",
+ "Ġide ological",
+ "Ġmayor ÃŃa",
+ "Ġb ureau",
+ "et erm",
+ "ĠD ID",
+ "ìĬ ·",
+ "Ġw aving",
+ "Ġbe b",
+ "Ġá r",
+ "Ġк в",
+ "Ġenv oy",
+ "an ut",
+ "ик Ñĥ",
+ "ĠEnviron ment",
+ "ĠAss ass",
+ "ãĤĵ ãģ§",
+ "ĠB read",
+ "ĠТ ÑĥÑĤ",
+ "Ġstair case",
+ "ĠDise ase",
+ "Ġauc un",
+ "Ġëĭ Ī",
+ "Ġconfront ation",
+ "Ġ194 1",
+ "Ġiron y",
+ "Ġwor sh",
+ "ãĤĮ ãĤĭ",
+ "Ġf ick",
+ "ĠNa omi",
+ "Ġback side",
+ "ie ux",
+ "K ap",
+ "Ġved ere",
+ "Ġlength y",
+ "Ġbreak er",
+ "ĠRoll e",
+ "Ġpred ator",
+ "Ġnoss os",
+ "Ġadvert ise",
+ "è³ ĩ",
+ "ÑĢод е",
+ "Redner wechsel",
+ "re ten",
+ "Ġcollect ors",
+ "ıģ ımız",
+ "Ġtr ig",
+ "Ġax es",
+ "in ters",
+ "Ġpen alties",
+ "ĠOs man",
+ "ĠJen na",
+ "Ġfl akes",
+ "Ġtrain ers",
+ "Ġstun ned",
+ "ĠSc roll",
+ "ĠP ip",
+ "Ġна ÑģÑĤ",
+ "Ġnh Ãł",
+ "ĠSm ack",
+ "ẫ n",
+ "rat os",
+ "ĠÑĢабоÑĤ Ñĭ",
+ "Ġu cz",
+ "ĠLem on",
+ "ĠS ind",
+ "Ġpsych ic",
+ "ĠAb g",
+ "Ġmamm als",
+ "Ġimmers ive",
+ "Ġb ots",
+ "Ġverschied ene",
+ "Ġg eral",
+ "Ġfoll ower",
+ "Ġ ä»ĸ",
+ "Ġsegur idad",
+ "Ġimmers ed",
+ "fe ito",
+ "c ross",
+ "Ġö ld",
+ "íĥ Ħ",
+ "Ġãģĵ ãģ®",
+ "Ġ×Ķ ×Ļ×IJ",
+ "ĠJ ian",
+ "Ġbili yor",
+ "are a",
+ "Ġk af",
+ "Ġgod t",
+ "缸 ä¿¡",
+ "Ġë°© ìĨ¡",
+ "Ġdet riment",
+ "æ¥ ļ",
+ "Ñĸ л",
+ "ĠÄij âu",
+ "Ġchlor ide",
+ "ø re",
+ "le i",
+ "Ġmont e",
+ "Ġdifférent es",
+ "à¯ģ .",
+ "Ġcareg ivers",
+ "Ġin adequ",
+ "Ġfare well",
+ "ĠÑĤип а",
+ "ont ec",
+ "ĠE ph",
+ "HH H",
+ "ĠTod os",
+ "ĠС ШÐIJ",
+ "Ġtro v",
+ "Ġl ige",
+ "Ġc ông",
+ "ĠC iv",
+ "Ġcap az",
+ "ĠV allahi",
+ "Ġquest e",
+ "Ġrepl ica",
+ "س ب",
+ "z na",
+ "ĠÑģл Ñĥж",
+ "ĠP T",
+ "w ave",
+ "ien i",
+ "Ġrel ied",
+ "de velop",
+ "Ġdem e",
+ "ĠA man",
+ "Ġ[ ...]",
+ "Ġcompl iments",
+ "u ais",
+ "ĠíĮ ¨",
+ "Ġsmell ing",
+ "Ġdad urch",
+ "ÙĪ ت",
+ "Ġor anges",
+ "Ġл ай",
+ "Ġstabil ization",
+ "åĢ į",
+ "ãĤĮ ãģŁ",
+ "æ¥ ½",
+ "Ġappl iances",
+ "Ġh m",
+ "ĥ IJë©´",
+ "odynam ics",
+ "Ġc iÄĻ",
+ "ĠC ott",
+ "M ON",
+ "ĠM ang",
+ "æĶ¯ æĮģ",
+ "Ġall erdings",
+ "ικ ή",
+ "sh ots",
+ "Ġt s",
+ "ĠG ör",
+ "ĠCH AR",
+ "Ġ: (",
+ "Ġwr ath",
+ "Ġf ique",
+ "Ġfüh ren",
+ "Ġtest ament",
+ "Ġ^ ^",
+ "á¹Ľá¹£ á¹ĩa",
+ "AL D",
+ "Ġtext o",
+ "ĠDog s",
+ "Ġs ib",
+ "Ġpath etic",
+ "ock s",
+ "Ġrad ically",
+ "ĠM ORE",
+ "ĠJAM ES",
+ "Ġing l",
+ "ĠTechn ical",
+ "Ġpor ch",
+ "ĠU T",
+ "ĠобÑıз аÑĤелÑĮно",
+ "Ġrenew al",
+ "Ġaesthet ics",
+ "ik um",
+ "Ġbe verage",
+ "der n",
+ "Ġpredict ive",
+ "Ġch uy",
+ "ĠRegard ing",
+ "ĠFor ward",
+ "ĠÙĪ ÙĦ",
+ "Ġcontext ual",
+ "Ġdwar f",
+ "Ġpre he",
+ "Ġgovern ed",
+ "ħ Ħ",
+ "Ġtrabal har",
+ "Ġnegó cio",
+ "ĠболÑĮÑĪ ой",
+ "еÑĩ аÑĤ",
+ "Ġд ÑĥÑħ",
+ "Ġflood s",
+ "Ġbow ling",
+ "ĠO B",
+ "ĠH är",
+ "Ġgrad ing",
+ "주 ëĬĶ",
+ "Ġg ars",
+ "d ling",
+ "Ġr ak",
+ "ë Ī",
+ "c reat",
+ "ĠÑī е",
+ "Ġneighb ours",
+ "f ood",
+ "Qu ery",
+ "Ġhero in",
+ "ice ps",
+ "ĠK inda",
+ "N ET",
+ "Ġmar i",
+ "Ġim itate",
+ "Ġach ter",
+ "Ġsettle ments",
+ "ra re",
+ "cc iones",
+ "Ġë ĵľ",
+ "Ġf ik",
+ "it ung",
+ "Ġм акÑģим",
+ "Ġel f",
+ "Ġd alla",
+ "ĠPol sce",
+ "ĠP ul",
+ "Ч ÑĤо",
+ "ĠMor gen",
+ "ØŃ Ùħ",
+ "Ġsuprem acy",
+ "Ġk ys",
+ "ĠHur ricane",
+ "ĠG TA",
+ "ĠFe h",
+ "Ġfinal mente",
+ "m und",
+ "ĠK rie",
+ "é poque",
+ "ĠT ucker",
+ "IT T",
+ "Ġl ur",
+ "Ġdi pping",
+ "ä v",
+ "Ġeer ste",
+ "ĠFl int",
+ "bild ung",
+ "ู à¹ī",
+ "Ġto im",
+ "Ġpr acy",
+ "Ġtransform s",
+ "Ġspeed ing",
+ "Ġpresent er",
+ "Ġfellow s",
+ "f illed",
+ "ie za",
+ "Ġadv ising",
+ "ĠInter view",
+ "и гÑĢ",
+ "we hr",
+ "ĠD ante",
+ "pt ure",
+ "Īë¬ ¸",
+ "¯ ¸ë",
+ "IJ IJ",
+ "ĠCoun ter",
+ "Ġcr ist",
+ "Ġì§ ľ",
+ "Ġje une",
+ "ĠÑģÑĤ ÑĢаÑĪ",
+ "Ġmie Äĩ",
+ "Ġtut or",
+ "Ġmas ala",
+ "Ġpowder ed",
+ "Ġn au",
+ "ĠFreder ick",
+ "Ġbill ing",
+ "ĠE isen",
+ "Ġд обÑĢ",
+ "Ġm est",
+ "æ ½",
+ "Ġsn ipp",
+ "Ġmon o",
+ "ĠA lo",
+ "ĠMer cy",
+ "éri ence",
+ "Ġcasual ties",
+ "ĠAN NOUNCER",
+ "ä» İ",
+ "Ġto car",
+ "Ġbacter ial",
+ "H o",
+ "Ġstre ak",
+ "ĠJ ENN",
+ "Ġpl ast",
+ "Ñģ лед",
+ "Ġre app",
+ "Ġpay check",
+ "Ġmin ers",
+ "hab t",
+ "ĠJ ap",
+ "н ÑĥÑĤ",
+ "Ġred emption",
+ "Ġqu ir",
+ "hn lich",
+ "Ġaccum ulation",
+ "Ġsh ove",
+ "Ġadrenal ine",
+ "M ake",
+ "ĠH ern",
+ "oss ing",
+ "ĠV il",
+ "ub by",
+ "her tz",
+ "bre aks",
+ "Ġsp ur",
+ "ĠD aha",
+ "US TIN",
+ "Ġcontinu er",
+ "ĠSa ul",
+ "ãģ® ãģ¯",
+ "Ġíı Ń",
+ "ĠëIJĺë ©´",
+ "Ġë§IJìĶ Ģ",
+ "Ġо ж",
+ "Ġsuspect s",
+ "Ġla quelle",
+ "ĠMuch as",
+ "Ġv öllig",
+ "ul en",
+ "Ġimp res",
+ "Ġlo bb",
+ "ene e",
+ "Ġн аж",
+ "T a",
+ "Ġréal ité",
+ "ĠRe x",
+ "Ġharvest ing",
+ "Ġest r",
+ "æ ¶",
+ "osp ace",
+ "OS S",
+ "Ġdisturb ance",
+ "ass ic",
+ "ĠIs ab",
+ "Ġdéc ouv",
+ "ĠHamp shire",
+ "Ġor nament",
+ "Ġlu ôn",
+ "ĠU W",
+ "Ġj Äħ",
+ "éĤ£ ä¹Ī",
+ "Ġrespect o",
+ "Ġcomun idad",
+ "Ġcom igo",
+ "ag na",
+ "Ġintrins ic",
+ "ĠAlum ni",
+ "Ġses leri",
+ "Ġestim ation",
+ "âĢĶ âĢĶ",
+ "Ġprodu it",
+ "ãĢĤ ãĢį",
+ "Ġв ÑĢ",
+ "Ġwh irl",
+ "Ġac ces",
+ "ç u",
+ "Ġvari ability",
+ "Ġv odka",
+ "its u",
+ "Ġinternship s",
+ "Ġalloc ate",
+ "R R",
+ "íĽ Ī",
+ "Ġinstruction al",
+ "t ant",
+ "Ġà®ħ த",
+ "Ġinv ites",
+ "Ġha k",
+ "Ġsca res",
+ "Ġe clipse",
+ "п ов",
+ "к олÑĮ",
+ "ativ as",
+ "Ġstab bed",
+ "ĠD OM",
+ "ä¸į åĪ°",
+ "ro ots",
+ "ĠPict ure",
+ "íĺ ¼",
+ "ĠC HA",
+ "ie c",
+ "ı ı",
+ "han ol",
+ "Ġmisunder stand",
+ "R ay",
+ "Ġroad map",
+ "ocument ed",
+ "iz ione",
+ "ĠOl ive",
+ "r ift",
+ "Ġ×Ķ× ł",
+ "æ¯ į",
+ "l est",
+ "; ;",
+ "ĠE A",
+ "éľĢ è¦ģ",
+ "од Ñĥ",
+ "Ġhob bies",
+ "Ġbur ial",
+ "ãģ« ãģ¡ãģ¯",
+ "Ð ¤",
+ "le ge",
+ "ĠH J",
+ "Ġobject ion",
+ "Ġãģ Ń",
+ "ct ory",
+ "Ġincre mental",
+ "Ġgym n",
+ "Ġepid emi",
+ "Ñģ Ñĭл",
+ "Ã ij",
+ "Ġadvance ment",
+ "Ġpar ch",
+ "New s",
+ "Ġa yr",
+ "л ам",
+ "Ġ×ľ× ©",
+ "Ġdipl oma",
+ "ãģ¡ãĤĥ ãĤĵ",
+ "Ġrob bed",
+ "On ly",
+ "Ġinc ur",
+ "Ġch anting",
+ "Ġíķ´ë ıĦ",
+ "Ġrich es",
+ "ĠCar men",
+ "Ġnost ro",
+ "λ ÎŃ",
+ "ĠPow der",
+ "à¹Ģภ«",
+ "ĠìŀĪ ìľ¼ë©´",
+ "Ġgerçek ten",
+ "ĠPik achu",
+ "ем он",
+ "OL L",
+ "Ġplanet ary",
+ "Ġsl ows",
+ "Ġclock wise",
+ "al ion",
+ "Ġì Į",
+ "Ġver n",
+ "Ġh omme",
+ "Ġend point",
+ "Ġinnoc ence",
+ "Ġelement os",
+ "Ġsophom ore",
+ "Ġnot ions",
+ "ĠCould n",
+ "p ur",
+ "Ġz at",
+ "Ġobs ess",
+ "Ġmotiv o",
+ "ĠK ub",
+ "ĠDr ug",
+ "A nt",
+ "ĠPlay ers",
+ "ĠHum ans",
+ "Ġme lee",
+ "ĠWild life",
+ "ĠV P",
+ "Ġvolcan ic",
+ "Ġcom in",
+ "ĠGu ang",
+ "ĠÏĦι ÏĤ",
+ "ĠоÑģоб енно",
+ "ĠS ize",
+ "L isten",
+ "ĠA aa",
+ "app ro",
+ "Ġbar bar",
+ "ĠPark inson",
+ "нÑı ÑĤÑĮ",
+ "å į°",
+ "Ġunderest imate",
+ "Ġsubst itution",
+ "Ġcosm etic",
+ "ä¸ĭ 次",
+ "Ġwill en",
+ "Ġbe ide",
+ "ann i",
+ "Ġcondition ed",
+ "ĠDe bbie",
+ "Ġis to",
+ "ĠEd wards",
+ "ìĽĮ ìļĶ",
+ "ĠÑĤ ов",
+ "Ġab brevi",
+ "ĠM ün",
+ "ĠPr inc",
+ "ĠLi ang",
+ "Ġst ink",
+ "Ġradio active",
+ "ãģĨ ãĤı",
+ "Ġac ontec",
+ "Ġun con",
+ "ĠTur bo",
+ "ãģ IJ",
+ "Ġkiss es",
+ "æĺ¯ ä»Ģ麼",
+ "еÑĤ ÑĢов",
+ "Ġfront ier",
+ "ĠSp y",
+ "ĠBel arus",
+ "ĠC BS",
+ "á» Ĺ",
+ "am oto",
+ "íķľë į°",
+ "ĠÑģÑĤ ÑĢо",
+ "ĠEn fin",
+ "Ġbread th",
+ "éĺ ²",
+ "ĠCa fe",
+ "ĠDaf ür",
+ "ĠB our",
+ "ar as",
+ "Ġbl ueprint",
+ "an ı",
+ "Ġconst ants",
+ "Ġattack er",
+ "ĠForm ula",
+ "za Äĩ",
+ "Ġs owie",
+ "Ġeyebr ow",
+ "ob ook",
+ "Ġset zen",
+ "第 ä¸ī",
+ "ons ider",
+ "aw ning",
+ "Ġsöyle ye",
+ "Ġinv aded",
+ "Ġpronoun s",
+ "Ġdob ry",
+ "S i",
+ "ĠÐ¥ оÑĤ",
+ "Ġvolley ball",
+ "Ġl ament",
+ "is ches",
+ "ar me",
+ "ap i",
+ "ĠW iki",
+ "ли ÑĪ",
+ "Ġkas ih",
+ "Ġp ess",
+ "ĠÑĦ оÑĤ",
+ "ĠS ul",
+ "å¾ ·",
+ "Ġpse udo",
+ "Ġmem o",
+ "ĠìĹ° ìĬµ",
+ "ĠдоллаÑĢ ов",
+ "ĠпеÑĢ ем",
+ "ĠRe ach",
+ "mir al",
+ "alt ed",
+ "Ġstat ut",
+ "read ing",
+ "Ġsöy led",
+ "ĠLind sey",
+ "ĠAh mad",
+ "ë ¶Ģë",
+ "ĠС егоднÑı",
+ "Ġprzy got",
+ "Ġhy ster",
+ "U RE",
+ "ĠNe igh",
+ "Rep orter",
+ "ĠB unu",
+ "ĠTreat y",
+ "ĠR ank",
+ "ĠF ame",
+ "in ished",
+ "Ġge ared",
+ "Ġcomp ose",
+ "od ia",
+ "ĠL on",
+ "Ġjeste ÅĽmy",
+ "ĠDIRE CTOR",
+ "Ġel kaar",
+ "ĠV iel",
+ "×IJ× ©",
+ "ynth ia",
+ "ä¸ ¦",
+ "Ġm ère",
+ "ĠTom ato",
+ "Ġex atamente",
+ "ni ÄĻ",
+ "ĠFre i",
+ "ĠD if",
+ "Ġopen ings",
+ "Ġgraph ical",
+ "ĠÑĥд об",
+ "ĠвÑģ п",
+ "ĠWeek ly",
+ "ев а",
+ "Ġhang s",
+ "Ġuns afe",
+ "Ġem blem",
+ "ĠKolleg innen",
+ "al ay",
+ "Ġk si",
+ "Ġh ides",
+ "Ġol may",
+ "Ġent ste",
+ "Ġarth ritis",
+ "ÃŁ erdem",
+ "Ġbin nen",
+ "Ġlist ens",
+ "ĠH ess",
+ "åĨį ä¾Ĩ",
+ "ĠLou ise",
+ "ld en",
+ "ен Ñģ",
+ "ĠVers ion",
+ "ĠAgric ulture",
+ "ìĬ¤ë ¥¼",
+ "м ан",
+ "ë Ħ¤ìļĶ",
+ "Ġw ines",
+ "ĠIN F",
+ "r ul",
+ "ĠJ K",
+ "ıyor lar",
+ "sh ield",
+ "reat h",
+ "Ġter us",
+ "ĠL um",
+ "Ġanticip ation",
+ "Ġacc ustomed",
+ "ĠM ina",
+ "Ġw ield",
+ "io è",
+ "mer a",
+ "Ġcount down",
+ "Ġcl ing",
+ "Ġcomm end",
+ "Ġfakt iskt",
+ "Ġdef enses",
+ "Ġcock pit",
+ "Ġком анд",
+ "Ġdish was",
+ "ĠThan os",
+ "Ġkid neys",
+ "Ġse he",
+ "Ġmicro bes",
+ "Ġc uff",
+ "ĠвÑĭÑģ ок",
+ "ĠSp icy",
+ "çŃī çŃī",
+ "வ ர",
+ "cul us",
+ "or c",
+ "ç¾ ħ",
+ "ix es",
+ "ĠC redit",
+ "Ġr aj",
+ "Ġbring t",
+ "ĠN iss",
+ "Ġgr im",
+ "ĠS OL",
+ "Ġten im",
+ "ĠSud an",
+ "ĠSp art",
+ "Ġpromot es",
+ "ĠN ossa",
+ "ĠÑģоÑģÑĤо Ñıни",
+ "Ġì° ©",
+ "Ġunc ont",
+ "ĠLiber al",
+ "ĠТ олÑĮко",
+ "ĠV iele",
+ "Ġktóre j",
+ "Ġ* ***",
+ "M ax",
+ "ĠЧ ÑĤобÑĭ",
+ "3 50",
+ "Ġíĺ¼ ìŀIJ",
+ "Ġë¶Ħë ĵ¤ìĿ´",
+ "Ġwar p",
+ "Ġteng a",
+ "Ġsympath etic",
+ "Ġbiz i",
+ "ĠZ ack",
+ "ied o",
+ "Ġëī ´ì",
+ "p iel",
+ "ĠÑĤ ол",
+ "Ġsc aled",
+ "ĠPET ER",
+ "ĠCO MM",
+ "ĠC ame",
+ "Ġcatast rophe",
+ "Ġsweat y",
+ "ig ration",
+ "Ġstuff ing",
+ "ĠÏĢολ Ïį",
+ "ĠDri ver",
+ "zy st",
+ "T ech",
+ "Ġassess ed",
+ "ĠSur face",
+ "ır ım",
+ "s ur",
+ "ler weile",
+ "Ġд ог",
+ "Ġshut ting",
+ "Ġfr actions",
+ "ĠÑģ ол",
+ "every one",
+ "Ġer n",
+ "ĠÐĿ ов",
+ "Ġdefend ers",
+ "Ġvers ucht",
+ "ãĥ³ãĥ Ģ",
+ "Ġpol ity",
+ "ĠÐŁ он",
+ "ver ständ",
+ "Ġbrows ers",
+ "Ġtransform ative",
+ "Ġdict ate",
+ "ĠLE GO",
+ "Ġning una",
+ "ê´ ij",
+ "Ġp izz",
+ "ĠHar old",
+ "ĠL opez",
+ "Ú¾ ÛĮ",
+ "an ız",
+ "atch et",
+ "ÙĬ ت",
+ "Ġl ernen",
+ "Ġê·Ģ ìŬ",
+ "Ġhous ed",
+ "Ġclean se",
+ "ĠW AT",
+ "lar ation",
+ "Ġby tes",
+ "Ġtuck ed",
+ "Ġfault s",
+ "д о",
+ "F X",
+ "Ġìĸ¼ë§ ĪëĤĺ",
+ "Ġde form",
+ "Ġcontract ing",
+ "ĠTIM E",
+ "ir se",
+ "Ġne ben",
+ "Ġc erc",
+ "ĠArm strong",
+ "Ġtest er",
+ "Ġparf ait",
+ "Ġjealous y",
+ "Ġtox ins",
+ "Ġdis bel",
+ "ÑĥÑĢ Ñĭ",
+ "imp ression",
+ "Ġprost ate",
+ "Ġfire wall",
+ "Ġclass ics",
+ "еÑĩ ÑĮ",
+ "Ġsocial ism",
+ "Ġgrac ious",
+ "ĠÑģ нова",
+ "Ġд нÑı",
+ "Ġburn er",
+ "ĠMin or",
+ "Ġìļ°ë ¦¬ë",
+ "Ġjed es",
+ "Ġcontinu um",
+ "Ġh ots",
+ "Ġoccur rence",
+ "Ġadminister ed",
+ "Ġзам еÑĤ",
+ "Ġhes itation",
+ "Ġdr ills",
+ "er ca",
+ "ĠвÑĤоÑĢ ой",
+ "Ġstead ily",
+ "Ġinsan lar",
+ "Ġi han",
+ "í ij",
+ "Ġhel per",
+ "ĠSen in",
+ "åģ ľ",
+ "ов ание",
+ "ĠER IC",
+ "b la",
+ "ĠAcad emic",
+ "Ġhuman ities",
+ "bl ack",
+ "ump y",
+ "ort ex",
+ "Ġìł Īë",
+ "ĠØ¥ ÙĨ",
+ "Ġdiscl ose",
+ "ĠEl ijah",
+ "Ġλ ÎŃ",
+ "ĠQu er",
+ "ب ÙĦ",
+ "ãĤ ¡",
+ "T ell",
+ "ar le",
+ "Ñĸ ÑĢ",
+ "Ġaug mented",
+ "Ġë¹Ħ ìĬ·",
+ "Ġand roid",
+ "ठ¤",
+ "ar ma",
+ "Ġs zer",
+ "ge ord",
+ "Ġge ek",
+ "Ġye ux",
+ "Ġp ong",
+ "ĠãģĿ ãģĨ",
+ "Ġtort ured",
+ "ĠB ath",
+ "z ig",
+ "ason able",
+ "Ġn ets",
+ "Ġbar u",
+ "ĠFl at",
+ "ĠV ater",
+ "ĠTer ror",
+ "ĠA vo",
+ "Ġceremon ies",
+ "ro e",
+ "Ùģ س",
+ "O ps",
+ "Ġhy vin",
+ "Ġap resent",
+ "ol or",
+ "ĠигÑĢ Ñĭ",
+ "ort on",
+ "Ġê·¸ëŀ ¬",
+ "Ġlook in",
+ "ĠT Y",
+ "ĠM int",
+ "Ad d",
+ "Ġm ite",
+ "ĠSm oke",
+ "Ġnot a",
+ "Ġm oss",
+ "ĠAb end",
+ "Ġì» ¨",
+ "Ġexagger ated",
+ "f ires",
+ "Ġred ist",
+ "ff iti",
+ "Ġopen ness",
+ "ê°IJ ìĿ´",
+ "ende u",
+ "ен ной",
+ "W atch",
+ "Ġav atar",
+ "ĠP ey",
+ "ur un",
+ "Ġsen za",
+ "Ġì§Ģ ìĹŃ",
+ "ĠNat omiast",
+ "Ġemer gence",
+ "ray s",
+ "Ġcraft ed",
+ "g ary",
+ "ãģł ãģij",
+ "ü ng",
+ "- \"",
+ "Ġhack ed",
+ "Ġstr ay",
+ "en cie",
+ "em o",
+ "Ġcom en",
+ "ĠK ız",
+ "ĠJ asmine",
+ "ĠH indi",
+ "man as",
+ "Ġinfin itely",
+ "em on",
+ "ìĿ¸ëį° ìļĶ",
+ "j ak",
+ "Ġro aring",
+ "éri que",
+ "s weise",
+ "ĠRo lex",
+ "åł± å°İ",
+ "ĠStu art",
+ "bn b",
+ "Ġdiagn ose",
+ "Ġcoher ent",
+ "ĠM J",
+ "æºĸ åĤĻ",
+ "Ġp ike",
+ "l av",
+ "Ġorchest ral",
+ "а ÑģÑĤи",
+ "Ġterm inar",
+ "Ġgather ings",
+ "Ġcompl iant",
+ "Ġupgrad ing",
+ "Ġregul ator",
+ "Ġlan ç",
+ "éĢ £",
+ "Ġmerch ants",
+ "ta wa",
+ "Ġmonit ored",
+ "Ġrend re",
+ "ä¸ ¤",
+ "Ġunter wegs",
+ "ang uard",
+ "g ard",
+ "ĠBel ow",
+ "du ino",
+ "ĠЦ е",
+ "Ġimped ance",
+ "ìľ ¡",
+ "ä» ½",
+ "Ġakt uell",
+ "ĠV atic",
+ "åŃ ©",
+ "Ġste wards",
+ "Ġbright est",
+ "Ġk enn",
+ "Ġk au",
+ "ĠMat rix",
+ "ĠB ark",
+ "ĠðŁ ij",
+ "Ġt aper",
+ "Ġcas ino",
+ "ר ×Ķ",
+ "ys ical",
+ "Ġbuild ers",
+ "ĠczÅĤ owie",
+ "ĠNep al",
+ "Ġ! \"",
+ "Ġterm e",
+ "Ġin nych",
+ "Ġmath s",
+ "Ġdraft ed",
+ "ĠB alk",
+ "Ġhesit ant",
+ "Ġvolt ar",
+ "Ġrev ive",
+ "ĠÑĦилÑĮ ма",
+ "Ġassass in",
+ "ĠS olutions",
+ "Ġdu el",
+ "Ġbear ings",
+ "à¸Ħ ะ",
+ "Ġrook ie",
+ "ik at",
+ "Ġbisc uits",
+ "Ġc ords",
+ "Ñĥв аÑĤи",
+ "AR IN",
+ "Ġprogress ing",
+ "ĠG ir",
+ "Ġpenet rate",
+ "ĠSt orage",
+ "e ight",
+ "ĠÑĤ ÑĢÑĥ",
+ "Ġdon ÃŃt",
+ "Ġsiz in",
+ "Ġout dated",
+ "ĠнаÑĪ и",
+ "Ġaff ir",
+ "Ġspo ons",
+ "Ġon i",
+ "Ġfl ank",
+ "ĠG ol",
+ "h ã",
+ "Ġp éri",
+ "Ġhonor able",
+ "ĠBreat he",
+ "sc enes",
+ "Ġob viamente",
+ "ик Ñģ",
+ "Ġש ×ŀ×",
+ "Ġsmooth ie",
+ "ŀ Īë",
+ "Ġd ime",
+ "ĠíĸĪ ìĸ´ìļĶ",
+ "Ġapp el",
+ "ĠCath olics",
+ "Ġsing les",
+ "Ġlat en",
+ "Ġç ünkü",
+ "ĠV ader",
+ "æı Ľ",
+ "Ġvard ı",
+ "ĠIst anbul",
+ "gr é",
+ "ĠEl sa",
+ "ë l",
+ "Ġinve ce",
+ "Ġcr ane",
+ "Ġo be",
+ "ĠSh ark",
+ "Ġsm ack",
+ "Ġrest oring",
+ ". \\",
+ "Ġë¹ łë",
+ "Ġf aded",
+ "um bers",
+ "S inging",
+ "Ġdep ressing",
+ "th est",
+ "ĠW ahr",
+ "Ġmult itude",
+ "ÑĢавÑģÑĤв ÑĥйÑĤе",
+ "rij k",
+ "ek a",
+ "Ġcomplet es",
+ "ĠWell s",
+ "Ġro y",
+ "ĠPr ay",
+ "ĠKal au",
+ "iz in",
+ "iaÅĤ em",
+ "Ġlo com",
+ "ĠNash ville",
+ "ĠPent agon",
+ "ë ¯¸",
+ "ĠNE W",
+ "Äħ Äĩ",
+ "ÃŃ ss",
+ "Ġmarry ing",
+ "Ġfe ud",
+ "íĻ ķ",
+ "æĢ ¥",
+ ") !",
+ "ĠOper ations",
+ "Ñĥ ÑĶ",
+ "Ġmo je",
+ "Ġinstruct ed",
+ "ĠëĪĦ 구",
+ "Ġ×Ķ× Ĵ",
+ "ĠпомоÑī ÑĮÑİ",
+ "Ġsab ia",
+ "ìķĺ ìĸ´ìļĶ",
+ "pl ane",
+ "p ri",
+ "Ġпол ноÑģÑĤÑĮÑİ",
+ "ĠK itty",
+ "Ġpróp rio",
+ "ed ere",
+ "Ġinteres ante",
+ "Ġд е",
+ "Ġcond ensed",
+ "Ġav ent",
+ "T OR",
+ "Ġgre asy",
+ "AR K",
+ "ort a",
+ "A J",
+ "Ġdis reg",
+ "Ġcorrect ions",
+ "Ġst ero",
+ "Ġinfluen za",
+ "Ġdess es",
+ "Ġball ots",
+ "Ġme get",
+ "Ġma fia",
+ "Ġb öl",
+ "n ost",
+ "ĠÑģÑĤ аÑĤÑĮ",
+ "Ġrespond er",
+ "Ġhint en",
+ "g rav",
+ "à¸Ń ะ",
+ "yn chron",
+ "Ġvi ens",
+ "Ġsam o",
+ "Ġd t",
+ "pan nt",
+ "ĠÅĽwi at",
+ "Ġзап иÑģ",
+ "Ġmer ged",
+ "Ġke p",
+ "Ġmis leading",
+ "Ġdig amos",
+ "Ġam mon",
+ "è¾ Ľ",
+ "ch et",
+ "Ġê°Ģ ìł¸",
+ "Ġun i",
+ "ĠëIJĺ ëĬĶëį°",
+ "Ġнап ÑĢав",
+ "ĠкоÑĤоÑĢ ого",
+ "Ġanim ate",
+ "×ķ× IJ×",
+ "еÑĢ в",
+ "Ġmin ced",
+ "Ġka um",
+ "ãģĤ ãģģ",
+ "ÏĢ ε",
+ "л ег",
+ "exist ing",
+ "Ġplata form",
+ "ĠK RIS",
+ "ìĽ ł",
+ "ĠFamil ien",
+ "ĠLib ya",
+ "Ġbiod iversity",
+ "Ġidi ots",
+ "ird i",
+ "Ġszy b",
+ "ĠRoll ing",
+ "ü cht",
+ "ĠÑĥд ив",
+ "Ñģ Ñĥд",
+ "Ġreal izar",
+ "Ġcan ned",
+ "ĠÑĢ ан",
+ "Ġmet abolic",
+ "ĠBe ef",
+ "Ġkil ka",
+ "лÑİ Ñģ",
+ "Ġreg istry",
+ "моÑĤÑĢ иÑĤе",
+ "Ġviel ä",
+ "Ġod c",
+ "Ġcondem ned",
+ "æ© ĭ",
+ "f al",
+ "ĠD il",
+ "wo ÅĽci",
+ "A w",
+ "Ġstatist ically",
+ "Ġso gen",
+ "ĠB ETH",
+ "Ġsh aving",
+ "å¹ ¸",
+ "oc al",
+ "ĠFun ny",
+ "Ġpeace fully",
+ "Ġaddict ive",
+ "ĠIns ert",
+ "la uf",
+ "Ġexperien cia",
+ "é¦ĸ åħĪ",
+ "иÑĤ елÑı",
+ "ÃŃ gen",
+ "ág ina",
+ "Ġabdom en",
+ "íķľ ëĭ¤",
+ "ic us",
+ "im ana",
+ "ì į¨",
+ "arch ing",
+ "Ġkonk ret",
+ "ìķ ĺë",
+ "ек а",
+ "ou fl",
+ "ive l",
+ "Ġn ude",
+ "èt res",
+ "Ġm onsieur",
+ "Ġcl ash",
+ "Ġtherap ists",
+ "Ġcub ed",
+ "Ġretrou ver",
+ "Ġwave form",
+ "Ġpot em",
+ "ĠForm er",
+ "is ión",
+ "åº ľ",
+ "Ġ×IJ× Ŀ",
+ "und os",
+ "ĠMein ung",
+ "ص ÙĦ",
+ "ĠJ ude",
+ "Ġn Ã¥r",
+ "ĠLeon ardo",
+ "ĠCr isto",
+ "ĠG OT",
+ "ÑģÑĤÑĢÑĥ к",
+ "L AN",
+ "Ġg Ã¥ng",
+ "Ġdé b",
+ "ĠFrankf urt",
+ "Ġcra ppy",
+ "Ġli l",
+ "ann ée",
+ "ĠмеÑģÑĤ е",
+ "RE T",
+ "ĠN er",
+ "ĠCO STA",
+ "Ġjed em",
+ "Ġcurt ains",
+ "Ġiter ations",
+ "Ġun av",
+ "Ġpla que",
+ "or um",
+ "ĠÎ ¶",
+ "Ġnúmer os",
+ "Ġdes ap",
+ "² ½",
+ "Ġcomp iled",
+ "Ġref le",
+ "Ġrank ings",
+ "Ġrep aired",
+ "ĠÐĿап ÑĢ",
+ "Ġdownload s",
+ "Ġarm our",
+ "Ġ×Ļ ×ķתר",
+ "Ġlonge vity",
+ "ĠTON ER",
+ "ĠкомменÑĤ аÑĢ",
+ "Ġcz ego",
+ "Ġnot ify",
+ "Ġairport s",
+ "Ġend uring",
+ "let te",
+ "Ġapp arat",
+ "Ġhab il",
+ "á»ĩ c",
+ "n ad",
+ "IC O",
+ "ĠBra h",
+ "Ġseg ún",
+ "Ġgovern ors",
+ "k aha",
+ "ĠSchl uss",
+ "Ġodpow ied",
+ "ir ting",
+ "Ġrem pl",
+ "ĠAb original",
+ "ident ally",
+ "Ġenhan cing",
+ "lic ting",
+ "ĠHawai ian",
+ "Ġstri ving",
+ "ĠN iet",
+ "Ġzn aczy",
+ "Ġobed ience",
+ "ĠnÃ¥ got",
+ "Ġexp ired",
+ "Ġ19 18",
+ "pres ented",
+ "Ġpr owad",
+ "ĠTer r",
+ "ĠPrinc eton",
+ "Ġmor gen",
+ "Ġattract ing",
+ "ĠS igma",
+ "ign er",
+ "ĠRe chts",
+ "ĠP eki",
+ "Ġmet hy",
+ "Ġha mm",
+ "Ġdire ito",
+ "Ġdeleg ation",
+ "ив аÑİÑĤ",
+ "Ġg in",
+ "You ng",
+ "Ġdepend encies",
+ "ĠBrad ley",
+ "bud s",
+ "Ġf is",
+ "Ġpyt anie",
+ "Ġinterconnect ed",
+ "Ġemba ixo",
+ "ĠS as",
+ "Ġr uh",
+ "ĠS icht",
+ "S ur",
+ "Ġsuper b",
+ "ĠSabb ath",
+ "ĠD anger",
+ "k ol",
+ "Ġh ou",
+ "s upp",
+ "ĠN acional",
+ "Ġsuccess ion",
+ "Ġv á",
+ "ĠMaÃŁ nahmen",
+ "ĠJess ie",
+ "ĠId aho",
+ "fore st",
+ "ħ ĺ",
+ "Ġ×ŀ× ĵ",
+ "ĠØ£ ÙĬ",
+ "Ġsweet heart",
+ "Ġneat ly",
+ "ĠEv angel",
+ "ê³ ¡",
+ "ĠSu ite",
+ "úblic a",
+ "ĠÑĥ ли",
+ "ĠAnn ouncer",
+ "l igh",
+ "Ġsens ations",
+ "Ġshel ters",
+ "Ġh art",
+ "Ġsqueez ing",
+ "ĠR ivers",
+ "ĠCook ing",
+ "ì± ħ",
+ "person al",
+ "Ġman os",
+ "ÑijÑĤ ÑģÑı",
+ "w ij",
+ "Ġgo gg",
+ "ĠMill i",
+ "ĠF P",
+ "ün st",
+ "ĠL S",
+ "Ġspray ing",
+ "Ġf aux",
+ "Ġaut ograph",
+ "olog ic",
+ "Ġtor ment",
+ "Ġencry pted",
+ "á» ħ",
+ "Ġest re",
+ "ç¹ ¼",
+ "à ±",
+ "Ġst umbled",
+ "Ġa ider",
+ "Ġsab en",
+ "x ter",
+ "ĠC ities",
+ "ĠTür k",
+ "ëĭ ¥",
+ "ch ine",
+ "Ġto pping",
+ "Ġpoison ed",
+ "ĠRoman ia",
+ "×ĵ ×Ļ",
+ "Ģë ¡ľ",
+ "ĠпоÑĢ Ñıд",
+ "Ġchir ping",
+ "ĠìĻ Ħë",
+ "×ij× ¢",
+ "Ġcu anto",
+ "Ġdon ating",
+ "ĠReg ent",
+ "ĠBer uf",
+ "Ġdistract ing",
+ "Ġstam ina",
+ "ĠDar ren",
+ "Ġì¶ ķ",
+ "l ists",
+ "d al",
+ "ch uss",
+ "Ġeconom ist",
+ "ãģĪ ãĥ¼",
+ "org t",
+ "Ġist iyorum",
+ "è¿ Ľ",
+ "ĠSur prise",
+ "ĠHa o",
+ "Ġìµľ ê³ł",
+ "ĠG W",
+ "ĠIn ner",
+ "Ġqu ieren",
+ "Ġmind ed",
+ "Ġsupercom puter",
+ "Ġdiagram s",
+ "íĬ ľë",
+ "ê²ł ìĸ´",
+ "ĠобÑĬ ÑıÑģ",
+ "Ġestab an",
+ "Ġdestro ys",
+ "ĠBre aking",
+ "Ġkar Ä±ÅŁ",
+ "Ġrebuild ing",
+ "ľë ĮĢ",
+ "ли во",
+ "ĠSau ce",
+ "ĠF usion",
+ "×ķ× ŀ×",
+ "ĠQu inn",
+ "Ġga uche",
+ "ĠÙĪ Ø£",
+ "Ġ È",
+ "ç ĵľ",
+ "Ġtechn o",
+ "Ġdisp atch",
+ "ĠaÅŁ k",
+ "Ġein zel",
+ "ĠG mail",
+ "ç ŀ",
+ "Ġê°ľ ìĿ¸",
+ "ĠÑģем ÑĮ",
+ "Ġjour neys",
+ "Ġi ht",
+ "Ġfib re",
+ "Ġdram as",
+ "ouch ed",
+ "Ġren ame",
+ "Ġоп еÑĢ",
+ "Ġpo o",
+ "ĠD ru",
+ "ĠиÑĤ ог",
+ "Ġz ast",
+ "Ġco z",
+ "Ġz ucch",
+ "Ġobt aining",
+ "Ġcomm ute",
+ "Ġsub mer",
+ "ĠV ish",
+ "ĠR abb",
+ "og g",
+ "Ġh ut",
+ "íĸĪ ìĸ´",
+ "æ¯Ķ å¦Ĥ",
+ "ere mi",
+ "Ġμ α",
+ "Ġdisk ut",
+ "Ġб Ñĥк",
+ "Ġimp aired",
+ "d epend",
+ "ĠÙĪ ا",
+ "ĠÑĢ Ñĥк",
+ "Ġб аÑĢ",
+ "Ġoxid ation",
+ "Ġsitu ação",
+ "ÉĻ n",
+ "u ção",
+ "Ġsag te",
+ "ĠS ER",
+ "ĠC ake",
+ "Ġtur meric",
+ "ĠK ak",
+ "b ung",
+ "ĠK á¹Ľá¹£á¹ĩa",
+ "Ġpoison ing",
+ "Ġsl ipping",
+ "ĠS ays",
+ "å°± åı¯ä»¥",
+ "ò ng",
+ "çŁ ³",
+ "Â «",
+ "ĠClaud ia",
+ "ĠChar acter",
+ "ни ÑĨ",
+ "co at",
+ "Ġprogress ed",
+ "ĠFer gus",
+ "Ġìĺ¤ ëĬ",
+ "Ġo at",
+ "ord able",
+ "ĠLe y",
+ "ĠHera us",
+ "Ġresult ados",
+ "ĠKay la",
+ "Ġr iff",
+ "Ġcheg ou",
+ "Ġx i",
+ "Ġsp acious",
+ "Ġrecogn ised",
+ "Ġe ch",
+ "ĠT ie",
+ "Ġlaunch er",
+ "J im",
+ "Ġsupp ression",
+ "ĠImp ossible",
+ "Ġguit ars",
+ "ĠFour ier",
+ "иÑĩеÑģ кий",
+ "ĠTh erap",
+ "ĠK af",
+ "cent ered",
+ "ĠÑģо оÑĤвеÑĤ",
+ "Ġk lim",
+ "Ġcarbohyd rates",
+ "ign ant",
+ "ĠAst ron",
+ "Ġem ple",
+ "Ġdr astic",
+ "ĠмиÑĢ е",
+ "в ин",
+ "u w",
+ "Ġpret tier",
+ "Ġdon uts",
+ "ĠAth ena",
+ "Ġdiss ert",
+ "Ġpl ante",
+ "Ġur anium",
+ "ìĿ Įë",
+ "ar é",
+ "Ġrze cz",
+ "Ġdisplay ing",
+ "æĪ ²",
+ "Ġsar c",
+ "r ão",
+ "Ġtamp oco",
+ "Ġphilosoph ers",
+ "ĠRe cht",
+ "æĵ ļ",
+ "Ġcoment arios",
+ "y se",
+ "Ġìľ ¤",
+ "Ġm ise",
+ "ĠG in",
+ "Ġн ом",
+ "ĠFR OM",
+ "l iner",
+ "at if",
+ "Ġspo ÅĤec",
+ "x a",
+ "ĠÑĤ ÑĢÑĥд",
+ "Ġw ag",
+ "기 ìĹIJ",
+ "ĠM G",
+ "Ġoff spring",
+ "ĠUnder standing",
+ "åıª æĺ¯",
+ "OR A",
+ "Ġwh irring",
+ "Ġsur rend",
+ "Ġpok er",
+ "Ġmon uments",
+ "ĠâĻ ©",
+ "Ġorgan ised",
+ "ĠSo zial",
+ "ĠF actory",
+ "Ñħ а",
+ "Ġrese mble",
+ "з д",
+ "Ġexplos ions",
+ "Ġpay roll",
+ "Ġom n",
+ "ĠJ orge",
+ "ι Ïĥ",
+ "Ġfract ure",
+ "Ġpersec ution",
+ "Ġdem ais",
+ "E CH",
+ ", )",
+ "Ġcri ar",
+ "ĠJ OSH",
+ "Ġdem ographics",
+ "Ġ16 00",
+ "Ġcur rencies",
+ "ĠT ips",
+ "Ġ éĢĻåĢĭ",
+ "ĠRe fer",
+ "ĠDan cing",
+ "Ġincons istent",
+ "Ġde h",
+ "Ġimm ens",
+ "Ġme ist",
+ "Ġimpat ient",
+ "Ġbehav es",
+ "æĿ ¾",
+ "ĠëĤ´ì ļ©",
+ "Ġback story",
+ "Ġagree ing",
+ "ĠÅ ģ",
+ "ih in",
+ "Ġtemper atura",
+ "ĠBack ground",
+ "Ġnut zen",
+ "Ġëħ ¹",
+ "ĠM änner",
+ "Ġcollabor ations",
+ "ĠK os",
+ "éģİ åİ»",
+ "Ġnight mares",
+ "ë ĵ±",
+ "ĠQueens land",
+ "Ġassoci ates",
+ "ĠK ok",
+ "Ġfact orial",
+ "ĠHy ung",
+ "Ġê·¸ ëĭ¤ìĿĮ",
+ "Ġfil ho",
+ "Ġel ét",
+ "Ġíĸī ë³µ",
+ "° ±",
+ "Ġgef unden",
+ "Ġsemic ondu",
+ "Ġcounsel ors",
+ "ĠU pper",
+ "ĠA ub",
+ "ick ers",
+ "V er",
+ "Ġnorth west",
+ "ĠMainten ant",
+ "ĠL akes",
+ "аÑı в",
+ "int é",
+ "ì° ½",
+ "Ġг аз",
+ "Ġgi orn",
+ "Ġdigit ally",
+ "ĠCirc uit",
+ "ì¼ Ģ",
+ "ãĤĬ ãģ¾ãģĹãģŁ",
+ "Ġcheer ful",
+ "ĠPet erson",
+ "ĠDan ish",
+ "ativ os",
+ "Ġli ken",
+ "Ġhar bor",
+ "али ÑģÑĤ",
+ "x e",
+ "Ġcur ls",
+ "ĠR hod",
+ "E nd",
+ "ĠE T",
+ "Ġacqu aint",
+ "ĠKel vin",
+ "Ġtr if",
+ "ĠA way",
+ "ìŀIJ ëĬĶ",
+ "v s",
+ "Ġp ágina",
+ "Ġin let",
+ "ĠSant os",
+ "Ġìļ° ìĻĢ",
+ "Ġyap ıyorsun",
+ "th eme",
+ "Ġsou ff",
+ "Ġinject ed",
+ "Ġpó źniej",
+ "iver so",
+ "amp ed",
+ "Ġda her",
+ "Ġd agger",
+ "ĠлÑİб им",
+ "Ġt ummy",
+ "Ġenlight ened",
+ "c ents",
+ "ĠD ah",
+ "Ġcu est",
+ "ä¾Ĩ 說",
+ "IL Y",
+ "Ġ×ij ר",
+ "Ġbang ing",
+ "ĠEm il",
+ "ĠC ler",
+ "ĠB order",
+ "иж Ñĥ",
+ "Ġpresent ers",
+ "ĠST UD",
+ "co ins",
+ "ĠíĻ į",
+ "Ġper ks",
+ "Ġpar ap",
+ "Ġcertain es",
+ "ĠL ore",
+ "ö st",
+ "ĠMAR TIN",
+ "Ġb ios",
+ "Ġwhere by",
+ "ver ts",
+ "ĠMir anda",
+ "Ġst ip",
+ "æ¾ ¤",
+ "and ez",
+ "׼ ׾",
+ "uj in",
+ "Ġê ¾",
+ "Ġaller gies",
+ "pl ate",
+ "Ġyap ıl",
+ "Ġundert ake",
+ "ĠëĤĺ ê°Ģ",
+ "P art",
+ "Ġkız ım",
+ "h guru",
+ "ãģĤ ãģ¨",
+ "ĠJohn s",
+ "Ġeyel ashes",
+ "Ġdra ined",
+ "Ġst Ã¥r",
+ "ãģĤãĤĬ ãģ¾ãģĻ",
+ "ĠJ ade",
+ "Ġcal end",
+ "fil m",
+ "Ġmes a",
+ "Ġlud zie",
+ "Ġattract s",
+ "Ġju ices",
+ "Ġк ил",
+ "Ġnieu we",
+ "Ġmen cion",
+ "Ġign ition",
+ "Ġbl adder",
+ "anda ag",
+ "ĠExt ension",
+ "íĤ ¨",
+ "fe ed",
+ "ĠÙĪ Ùĩ",
+ "Ġsp un",
+ "Ġt ät",
+ "оÑĢ оÑĤ",
+ "ty ard",
+ "ron ics",
+ "ĠH uge",
+ "Ñĥж д",
+ "st ring",
+ "Ġun just",
+ "Ġpra wn",
+ "Ġfrost ing",
+ "Ġdisappear ance",
+ "ios a",
+ "Ġcard i",
+ "ĠPri est",
+ "Ġcient ÃŃfic",
+ "åĵª 裡",
+ "ĠÐĴ аÑģ",
+ "Ġë¶Ģ íĥģ",
+ "Ġth ieves",
+ "Ġphys ique",
+ "ĠE ugene",
+ "Ġбли з",
+ "Ġmon opoly",
+ "Ġbi ography",
+ "Ġho ÅŁ",
+ "Ġt ö",
+ "m ac",
+ "Ġshock s",
+ "ìĦ ¸ë",
+ "h it",
+ "Ġsn ug",
+ "Ġinc l",
+ "Ġded ic",
+ "Ġult ras",
+ "Ġизв еÑģÑĤ",
+ "Ġutil ization",
+ "ĠÑģовеÑĢÑĪ енно",
+ "Ġserv i",
+ "st ag",
+ "1 80",
+ "Ġse wer",
+ "ĠCh oice",
+ "Ġdis charged",
+ "ĠJ D",
+ "ол еÑĤ",
+ "ĠкваÑĢ ÑĤи",
+ "Ġteles cop",
+ "ĠJe ÅĽli",
+ "ĠN ana",
+ "c ale",
+ "ĠÑĤ он",
+ "mm m",
+ "äºĨ åIJ§",
+ "Ġge habt",
+ "ëĤ ł",
+ "æĬ ķ",
+ "à¸Ļ à¸Ļ",
+ "Ġet her",
+ "Ġz en",
+ "Ġresearch ed",
+ "ĠCzy li",
+ "å®Į åħ¨",
+ "work ers",
+ "Ġê²½ ì°°",
+ "Ġsher iff",
+ "all o",
+ "Ġtip os",
+ "Ġprosec ution",
+ "Ġfrog s",
+ "Ġf alt",
+ "j d",
+ "ĠíĮ Ķ",
+ "Ġfilter ed",
+ "ĠO ft",
+ "Ġì į",
+ "Ġdis fr",
+ "ĠMust ang",
+ "Ġwo ah",
+ "ĠRE ALLY",
+ "Ġмог ли",
+ "Ġentr ada",
+ "Ġиг ÑĢа",
+ "Ġmix es",
+ "ĠавÑĤом об",
+ "Ð Ļ",
+ "Ġsh in",
+ "Ġparan ormal",
+ "Ġsome place",
+ "Ġdish on",
+ "eta an",
+ "Ġfu erte",
+ "Ù ¹",
+ "Ġdo om",
+ "ìĪ ľ",
+ "Ġexist ential",
+ "Ġbu ld",
+ "ĠSD K",
+ "ĠпÑĢав да",
+ "Ġturn over",
+ "ĠìĹ¬ê¸° ìĹIJ",
+ "Ġठ¹",
+ "Ġmodel ed",
+ "Ġbug ün",
+ "Ġexperiment ation",
+ "Ġmorning s",
+ "Ġmed o",
+ "Ste vie",
+ "Ġplay able",
+ "Ġairl ines",
+ "g ments",
+ "Ġê¸°ë ¶Ħ",
+ "ĠT omb",
+ "ĠMV P",
+ "AUDI ENCE",
+ "Ġcheck out",
+ "Ġpas st",
+ "Ġbe ispiel",
+ "ĠLink s",
+ "he avy",
+ "Ġquestion able",
+ "Ġìĵ °ë",
+ "Ġs ill",
+ "Ġmanip ulated",
+ "ĠL oren",
+ "Ġìľ ¼",
+ "Ġver ge",
+ "á k",
+ "I ES",
+ "Ġsab ot",
+ "ĠCustom er",
+ "ale ży",
+ "Ġnom inee",
+ "ĠG ad",
+ "Ġnouve lles",
+ "ĠS PE",
+ "ist ling",
+ "Ġo val",
+ "обÑĢ аж",
+ "if ty",
+ "éĩ İ",
+ "Ġbez el",
+ "y et",
+ "Ġfre ight",
+ "ĠHan ım",
+ "r ÃŃa",
+ "Ġz oning",
+ "Ġind em",
+ "ĠB ü",
+ "Ġfemin ism",
+ "Ġvo ix",
+ "Ġof icial",
+ "Ġdi yorum",
+ "» IJ",
+ "Ġar ose",
+ "Ġpar ar",
+ "ìĿ¸ ì§Ģ",
+ "ĠMart ine",
+ "ĠL ect",
+ "Ġrest er",
+ "Ġdrown ing",
+ "u ya",
+ "c ida",
+ "ĠAri el",
+ "Ġ0 2",
+ "Ġ×Ķ ×Ķ",
+ "ç´ ł",
+ "ĠW ert",
+ "Т Ñĭ",
+ "Ġwid ow",
+ "Ġparch ment",
+ "Ġcott age",
+ "ĠX L",
+ "ĠSl ack",
+ "ĠN ES",
+ "Ġro be",
+ "Ġg imm",
+ "Ġcam inho",
+ "ĠHar per",
+ "Ġcit rus",
+ "Ġfirefight ers",
+ "Ġdop amine",
+ "el ets",
+ "Ġdemocr at",
+ "ìł ľë¡ľ",
+ "Ġplay back",
+ "o j",
+ "ĠпÑĢ ок",
+ "ĠSull ivan",
+ "se mble",
+ "ĠW orth",
+ "ĠMust afa",
+ "า ร",
+ "Ġmet s",
+ "éĸ Ģ",
+ "л оÑģÑĮ",
+ "Ġinert ia",
+ "Ġuniform s",
+ "è¶ ³",
+ "é rio",
+ "×ķר ×Ķ",
+ "é nt",
+ "Ġà® Ĵ",
+ "ĠÑģам ÑĭÑħ",
+ "Ġvou lais",
+ "ĠZ immer",
+ "ê² łë",
+ "Ġн оÑģ",
+ "en cias",
+ "Ġrel ación",
+ "Ġê± ¸ë",
+ "Ġfact ion",
+ "Ġg osp",
+ "пол ож",
+ "n ap",
+ "h ak",
+ "Ġproceed ings",
+ "ĠìĨ Ķ",
+ "ìķĦ ëĭĪ",
+ "ĠìŀIJ 기",
+ "Ġwer d",
+ "Ġso f",
+ "Ġsch lim",
+ "Ġfl avored",
+ "Ġquad ratic",
+ "ĠBo ot",
+ "Ġpublic ity",
+ "ĠCar o",
+ "Ġ ?\"",
+ "ни ÑĨа",
+ "man ia",
+ "ĠS UR",
+ "ĠB UR",
+ "l ance",
+ "ét ica",
+ "Ġzob aczy",
+ "Ġtri o",
+ "s ama",
+ "Ġta ÅŁ",
+ "Ġas ymm",
+ "ress er",
+ "Ġت ع",
+ "Ġп еÑģ",
+ "Ġbeginning s",
+ "lad ım",
+ "ĠбÑĭ ÑģÑĤÑĢ",
+ "Ġmo o",
+ "ĠGene va",
+ "Ġ åľ¨",
+ "er us",
+ "bor ah",
+ "Ġref using",
+ "b ull",
+ "ĠWait ing",
+ "ĠInd ividual",
+ "Ġan onym",
+ "im ens",
+ "Ġmed idas",
+ "Ġfragr ant",
+ "Ġdirect ement",
+ "ĠìķĦ ë§Ī",
+ "ur ia",
+ "Ġsp herical",
+ "Ġab ge",
+ "ĠVictor ian",
+ "Ġspect acle",
+ "ĠRodrig uez",
+ "Ġoc up",
+ "ĠN är",
+ "mark s",
+ "ng ulo",
+ "ĠLu ci",
+ "Ġshout ed",
+ "Ġregul ators",
+ "ÄŁ ini",
+ "Ġdis ent",
+ "ĠÑĢÑĭ н",
+ "ëĤ ¨",
+ "ĠìĤ ´ë",
+ "Ġprobl èmes",
+ "ĠF inger",
+ "asse mble",
+ "Ġpe ar",
+ "Ġdro ite",
+ "ĠEvery where",
+ "t am",
+ "оÑĤ ив",
+ "в ой",
+ "ordin ate",
+ "ĠL ak",
+ "Ġm Ỽi",
+ "ĠTele vision",
+ "Ġexpon entially",
+ "av as",
+ "Ġble v",
+ "ĠM T",
+ "ä¿ º",
+ "Con nell",
+ "ĠêµŃ 민",
+ "ĠÑģво им",
+ "Ġach a",
+ "ĠD ynasty",
+ "J in",
+ "Ġto re",
+ "Ġfl or",
+ "Ġмног ие",
+ "æ²Ĵ äºĭ",
+ "ow an",
+ "b ah",
+ "Ġì£ Ħ",
+ "ĠC ela",
+ "Ġìµľ ê·¼",
+ "Ġpermett re",
+ "Ġab ras",
+ "Ġverste hen",
+ "Ġesc ort",
+ "ĠThe m",
+ "är ke",
+ "por ter",
+ "Ġkah kaha",
+ "Ġhe ct",
+ "Ġda u",
+ "w ah",
+ "ol ve",
+ "ĠAg es",
+ "s chaft",
+ "ĠSt ell",
+ "ne lle",
+ "ĠEn suite",
+ "ĠÐĴÑģ ем",
+ "Ġcr éd",
+ "ĠP P",
+ "l ords",
+ "gr unting",
+ "Ġcontract ion",
+ "G ot",
+ "Ġacqu iring",
+ "Ġso pr",
+ "Ġpoison ous",
+ "R NA",
+ "Ġan ar",
+ "ĠH of",
+ "' )",
+ "Ġremark ably",
+ "Ġintern acional",
+ "ü cke",
+ "in qu",
+ "Ġdu y",
+ "Ġbeast s",
+ "ĠL AN",
+ "Ġpreced ent",
+ "ĠRP M",
+ "åij ¨",
+ "Ġsel on",
+ "Ġmort e",
+ "Ġcomeç ou",
+ "Ñı ла",
+ "Ġinterpre ting",
+ "ĠBur ke",
+ "ÑĤ ÑĢа",
+ "ĠìĿ´ë Ł¬",
+ "Ġpess im",
+ "ĠN ok",
+ "íĮ Ŀ",
+ "F emale",
+ "Ġìĭ ¤í",
+ "Ļ Ģ",
+ "Ġstim ulation",
+ "Ġsl ick",
+ "Ġê°Ģ ëĬĶ",
+ "Ġк аз",
+ "ĠH BO",
+ "Ġpap ier",
+ "Ġkön nten",
+ "Ñĥб ли",
+ "ĠConst ant",
+ "SPEAK ING",
+ "Ġktó rÄħ",
+ "Ġcos metics",
+ "ĠT rend",
+ "Ġrob bery",
+ "Ġt itt",
+ "Ġgj ort",
+ "Ġdiet ary",
+ "ł Į",
+ "ĠKir by",
+ "ĠпÑĢимеÑĢ но",
+ "Ġqual ification",
+ "Ġìķ ī",
+ "Ġcabin ets",
+ "Ġhtt p",
+ "ĠEric a",
+ "ç¾ ©",
+ "Ġdisadvant ages",
+ "Ġch attering",
+ "y z",
+ "fe it",
+ "Ġgu ild",
+ "ĠE TF",
+ "ĠDrag ons",
+ "ĠH ERE",
+ "vent h",
+ "ÙĦ اÙħ",
+ "Ġmarch é",
+ "D am",
+ "Ġphot on",
+ "Ġest able",
+ "M ag",
+ "Ġol har",
+ "Ġcou pling",
+ "ĠHil fe",
+ "ĠW izard",
+ "Ġм ало",
+ "hel p",
+ "ĠlÃŃ nea",
+ "Ġì «",
+ "Ġstand alone",
+ "Ġmor ale",
+ "Ġzwe ite",
+ "ãĤĪãĤį ãģĹãģı",
+ "ähr t",
+ "Ġd otted",
+ "Ġdri pping",
+ "ĠFl ag",
+ "éĿ Ĵ",
+ "ro cket",
+ "rate gy",
+ "ir im",
+ "Ġíķĺë ©´ìĦľ",
+ "Ġsogen an",
+ "ĠUn o",
+ "ĠSch utz",
+ "Ġest ilo",
+ "ĠS ubs",
+ "ĠDais y",
+ "ÐĿ еÑĤ",
+ "' ...",
+ "Ġplat inum",
+ "Ġb irl",
+ "ĠSo vi",
+ "Ġviol ate",
+ "Ñĥ еÑĤÑģÑı",
+ "r ill",
+ "Ġtra z",
+ "Ġsn ip",
+ "Ġcum pl",
+ "à¸Ń à¸ģ",
+ "Ġc uk",
+ "éħ Ĵ",
+ "ĠParl ament",
+ "Ġhyper t",
+ "Ġpul p",
+ "Ġtong ues",
+ "at to",
+ "Ġbus ca",
+ "ih n",
+ "ER O",
+ "ĠÙĬ ع",
+ "Ġvari as",
+ "ĠMar ian",
+ "Ġbound ed",
+ "Ġpitch ing",
+ "Ġdefic iency",
+ "ĠBless ed",
+ "ĠEx erc",
+ "uch s",
+ "ĠnhÆ° ng",
+ "æľ¬ å½ĵ",
+ "Ġrap ed",
+ "h ales",
+ "Ġmal a",
+ "p ic",
+ "Ġ40 1",
+ "ÅĽ niej",
+ "ar ina",
+ "ëĵ¤ ìĿĦ",
+ "ott i",
+ "Ġдол го",
+ "Ġtrack er",
+ "ĠShel by",
+ "Ġvan ished",
+ "Ġbak ery",
+ "Kap ı",
+ "J esus",
+ "ĠK R",
+ "J O",
+ "ħ ¸",
+ "Ġdisc s",
+ "ìĦ ¯",
+ "ì§Ģ ë",
+ "×Ļ× ¦",
+ "em ary",
+ "K endra",
+ "Ġy ük",
+ "ück t",
+ "Ġv az",
+ "Ġk up",
+ "akt u",
+ "ĠÑģп аÑģибо",
+ "Ġa ik",
+ "Ġnurs ery",
+ "Ġendanger ed",
+ "êm ement",
+ "emat ics",
+ "Ġrespond ers",
+ "ĠRepresent atives",
+ "Ġsculpt ures",
+ "ig keiten",
+ "Ġde pl",
+ "Ġinterpret ations",
+ "Ġdead lines",
+ "Ġ194 2",
+ "Ã Ĺ",
+ "Ġsug ars",
+ "em u",
+ "l ively",
+ "Ġrecre ational",
+ "Ġdist ort",
+ "Ġunders core",
+ "Ġun quote",
+ "Ġsaf est",
+ "Ġsw ollen",
+ "Ġanalys es",
+ "Ġcommen cé",
+ "å¦ ¹",
+ "and in",
+ "ĠÐ¥ оÑĢоÑĪо",
+ "Ġdi arr",
+ "ãģ¾ ãģģ",
+ "zi est",
+ "Ġtooth brush",
+ "éł» éģĵ",
+ "u ations",
+ "Ġc ade",
+ "Ġbackl ash",
+ "h ind",
+ "Ġris que",
+ "z ess",
+ "ĠìĿ´ìķ¼ 기",
+ "Ġesper ar",
+ "Ġtransl ations",
+ "ion ed",
+ "gro ans",
+ "Ġп ÑĥÑĤ",
+ "Ġgen etically",
+ "éĢ ł",
+ "Ġhapp iest",
+ "Ġwer k",
+ "ato on",
+ "Ġmus i",
+ "Ġfun ção",
+ "Ġìŀħ ëĭĪëĭ¤",
+ "ĠÑĢ ай",
+ "Ġbe vor",
+ "BL ANK",
+ "Ġrepent ance",
+ "P ut",
+ "Ġpotrze b",
+ "Ġsal a",
+ "Ġcamp a",
+ "W ER",
+ "Ġdec ÃŃa",
+ "Ġsécur ité",
+ "ĠAppreci ate",
+ "Ñĩ и",
+ "ĠR andom",
+ "ë³ Ħ",
+ "k ah",
+ "Ġmö j",
+ "Ġsä ger",
+ "Ġ×Ļ ׼×ķ׾",
+ "Ġ19 0",
+ "xt ures",
+ "E u",
+ "Ġg ä",
+ "Ġ×ij× ª",
+ "ĠC roat",
+ "ap o",
+ "P LE",
+ "Ġpersist ence",
+ "åĬ ©",
+ "Ġbl ends",
+ "Ġtre ffen",
+ "ĠSanti ago",
+ "yd ia",
+ "al do",
+ "ĠTensor Flow",
+ "ĠD ual",
+ "ãĥ ľ",
+ "Ġch iff",
+ "ìĹ ´",
+ "Ġcontract ed",
+ "Ġseg reg",
+ "ĠFair y",
+ "Ġwis ely",
+ "Ġvulner abilities",
+ "Ġhand held",
+ "Ġgad gets",
+ "Ġbo ÅŁ",
+ "ĠPop ular",
+ "Ġcurv ature",
+ "ë ¬¸",
+ "ĠMAR Y",
+ "ìĿ´ì Ĭ",
+ "Ġform ulation",
+ "Ġcel ery",
+ "Ġblur ry",
+ "ĠT S",
+ "ale z",
+ "Ġw s",
+ "Ġprogram m",
+ "ĠSt ack",
+ "ĠJ IM",
+ "ов али",
+ "ı ll",
+ "Ġp ère",
+ "ĠKan ye",
+ "ĠDel aware",
+ "Ġãģ ł",
+ "Ġda unting",
+ "Ġб еÑģ",
+ "ĠSt upid",
+ "b ig",
+ "ffic ial",
+ "Ġprecip itation",
+ "Ġpl ung",
+ "ụ c",
+ "bur se",
+ "Ġdar le",
+ "Ġcri pp",
+ "Ġpione er",
+ "Ġdis put",
+ "Ġse an",
+ "ãģĵ ãĤĵãģª",
+ "Ġresist or",
+ "Ġalle in",
+ "ipp les",
+ "are l",
+ "Ġend ors",
+ "z ust",
+ "ĠÑĢеб ÑıÑĤа",
+ "ed ed",
+ "Ġì¹´ë ©Ķë",
+ "Ġlle va",
+ "Ġken nt",
+ "Ġб ал",
+ "ĠDoc ument",
+ "ĠKn ights",
+ "Ġbuck le",
+ "Ġìī ¬",
+ "Ġal k",
+ "ĠEvery day",
+ "atter s",
+ "Ġtoil ets",
+ "Ġj ugar",
+ "ĠìŀĪ ì§Ģ",
+ "Ġgen auso",
+ "ĠLandes regierung",
+ "ãģ£ãģ ±",
+ "ij e",
+ "Ġtrail ers",
+ "ĠT igers",
+ "Ġg itti",
+ "Ġforg iving",
+ "Ġconcur rent",
+ "ĠV u",
+ "ĠíĬ¹ íŀĪ",
+ "ĠBR OWN",
+ "ound ed",
+ "\" ;",
+ "Ġtre mb",
+ "Ġt iet",
+ "ĠÑĢеж им",
+ "Ġnuts hell",
+ "ел иÑĩ",
+ "Ġlos ers",
+ "ric ting",
+ "Ġrede em",
+ "def ined",
+ "N ice",
+ "Ġbroad band",
+ "K O",
+ "Ġte asing",
+ "Ġpart isan",
+ "ı ma",
+ "Ġìŀ¬ë ¯¸",
+ "ĠJour ney",
+ "Ġslop es",
+ "un ing",
+ "gr unts",
+ "Ġt äll",
+ "Ġuncover ed",
+ "Ġmy ÅĽlÄĻ",
+ "ĠEst her",
+ "äº İ",
+ "ĠHealth y",
+ "Ġë° ij",
+ "r ée",
+ "Ġpolar ization",
+ "Ġfl av",
+ "Ġcambi ar",
+ "Ġy r",
+ "ĠR anch",
+ "Ġspl its",
+ "Ġtrou vé",
+ "åľĭ 家",
+ "Ġrecord er",
+ "Ġdé part",
+ "ÙĪ ب",
+ "ĠK ry",
+ "Ġinteress ant",
+ "Ġeder im",
+ "ÅĽ wiad",
+ "il ateral",
+ "w right",
+ "Ġpour ra",
+ "ê ter",
+ "Ġcam el",
+ "á ŀ",
+ "Ġrapid ement",
+ "Ġme j",
+ "Ġstiff ness",
+ "AD AS",
+ "Ġdiff ers",
+ "Ġal ot",
+ "ĠS ig",
+ "ÑıÑĤ елÑĮ",
+ "Ġabstract ion",
+ "åľ ĺ",
+ "Ġke iner",
+ "gr upp",
+ "ĠSher lock",
+ "íĺ Ķ",
+ "Ġc ite",
+ "Ġover flow",
+ "Ġt ại",
+ "ú car",
+ "b ula",
+ "Ġconjun to",
+ "ĠC I",
+ "Ġmoder ator",
+ "Ġindirect ly",
+ "Ġalle ine",
+ "â Ĥ",
+ "ÑĪ иб",
+ "Ġб аб",
+ "Ġdan ach",
+ "Ġ19 39",
+ "Ġpr omet",
+ "Ġdest inations",
+ "ĠIll ust",
+ "ικ ÏĮ",
+ "Ġsab es",
+ "Ġhe h",
+ "ĠGesetz ent",
+ "ĠM iz",
+ "ен ко",
+ "ĠM ys",
+ "Ð ¬",
+ "ĠJuda ism",
+ "Ġmust ache",
+ "Ġst immt",
+ "ĠG aza",
+ "Ġvol te",
+ "Ġnu o",
+ "Ġm ón",
+ "ĠCom put",
+ "ู à¹Ī",
+ "ĠR adi",
+ "Ġexception ally",
+ "Ġassum es",
+ "éĸĭ å¿ĥ",
+ "ãģĪ ãģ°",
+ "in form",
+ "Ġshr ine",
+ "æĵ Ĭ",
+ "Ġimplic ation",
+ "ĠF itz",
+ "æ²Ĵ éĹľä¿Ĥ",
+ "! .",
+ "Ġl t",
+ "Ġall oy",
+ "Ġeth ic",
+ "Ġmonaster y",
+ "ìĭľ ì£ł",
+ "ica ção",
+ "Ġcoordin ating",
+ "ĠM oto",
+ "Ġover look",
+ "Ġcho is",
+ "Ġantibiot ic",
+ "ĠMin ne",
+ "ĠB J",
+ "ĠA pa",
+ "or ian",
+ "Ġsp illed",
+ "J am",
+ "Ġhus bands",
+ "Ġcre ations",
+ "Ġa ñ",
+ "üs sel",
+ "ĠìĿ´ì ļ©",
+ "Ġanaly se",
+ "r ose",
+ "Ġpunch ed",
+ "Ġpres que",
+ "Ġastron omy",
+ "Ġschwier ig",
+ "ĠEb ola",
+ "Ġc is",
+ "Ġac et",
+ "ĠF X",
+ "end re",
+ "ĠìĿĮ ìķħ",
+ "Ġweb page",
+ "Ġfre aked",
+ "Ġlat te",
+ "Ġì¿ ł",
+ "Ġë¨ ¸ë",
+ "N ever",
+ "G ra",
+ "íĻĶë ¥¼",
+ "ey ed",
+ "Ġë°ľë Ŀ¼",
+ "Ġesper a",
+ "Ġapare ce",
+ "ra ção",
+ "Ġdisrupt ive",
+ "ĠJo int",
+ "ur ous",
+ "re as",
+ "Ġquer ÃŃa",
+ "Ġdistrib utions",
+ "Ġexpon ent",
+ "ì¹ ĺ를",
+ "Ġd l",
+ "z hou",
+ "ĠHe aring",
+ "å·® ä¸įå¤ļ",
+ "ĠC raw",
+ "Ġflo ats",
+ "oun ced",
+ "L ab",
+ "W orld",
+ "Ġbur dens",
+ "Ġauthor itarian",
+ "ĠB olt",
+ "Ġод нÑĥ",
+ "Ġpige on",
+ "Ġdistract ions",
+ "ĠHeraus forder",
+ "Ġz est",
+ "es c",
+ "Ġsh akes",
+ "at as",
+ "ĠÙħ Ø´",
+ "hol es",
+ "Ġthink ers",
+ "al ta",
+ "Ġar che",
+ "ĠS uk",
+ "an ha",
+ "Ġtempt ing",
+ "Ġyou tuber",
+ "Ġv ì",
+ "Ġdz iaÅĤa",
+ "ĠVatic an",
+ "P ark",
+ "Ġsup ers",
+ "ĠNik ki",
+ "ëĬ IJë",
+ "or ang",
+ "ram ient",
+ "é ¬¼",
+ "Ġê°ĸ ê³ł",
+ "Ġdessert s",
+ "Ġav ere",
+ "ĠGreg ory",
+ "Ġëĵ¤ìĸ´ì ĺ",
+ "Ġcost ing",
+ "ĠClin ic",
+ "Ġreb els",
+ "ĠM ob",
+ "Ġbun lar",
+ "ĠYour s",
+ "ert ime",
+ "Ġret ali",
+ "m ara",
+ "at us",
+ "all es",
+ "Ġд ÑĢ",
+ "Ġд иÑģ",
+ "Ġdiscount s",
+ "ĠGU Y",
+ "Ġкак ое",
+ "ĠExper iment",
+ "re ment",
+ "ĠXi ang",
+ "Ġb ate",
+ "W E",
+ "Ġspecial ize",
+ "Ġde ity",
+ "ĠL oki",
+ "m ag",
+ "ĠN it",
+ "W est",
+ "Ġmater nal",
+ "Ġqu is",
+ "åŁº æľ¬",
+ "bro ken",
+ "Ġlas ers",
+ "Ġha kk",
+ "ĠAng els",
+ "Ġmaster y",
+ "ant is",
+ "T iffany",
+ "ee e",
+ "ç ij",
+ "ore m",
+ "Ġin acc",
+ "Ġjurisd ictions",
+ "ĠKard ash",
+ "æľ º",
+ "I l",
+ "ĠS inn",
+ "åĭķ çĶ»",
+ "Ġathlet ics",
+ "c ÄĻ",
+ "Ġlo osely",
+ "Ġdiet a",
+ "A g",
+ "Ġ? ?",
+ "ĠëĮĢ íijľ",
+ "Ġsuper v",
+ "Ġnut rit",
+ "Ġdr ifting",
+ "ĠìĦłìĥĿ ëĭĺ",
+ "Ġпон Ñıл",
+ "ĠVict ory",
+ "ÙĦ Ø©",
+ "×ķ׳ ×Ķ",
+ "Ġп иÑĪ",
+ "Ġsh aved",
+ "Ġmes ure",
+ "ond en",
+ "Ùĥ ر",
+ "Ġex ile",
+ "ĠDes de",
+ "ĠP interest",
+ "Ġattach ments",
+ "Ġh ombres",
+ "Ġfin es",
+ "ĠìĦ¸ ìĥģ",
+ "Ġsleep s",
+ "ĠT aco",
+ "ĠI RA",
+ "ri os",
+ "Ġo ll",
+ "et es",
+ "Ġun ut",
+ "fashion ed",
+ "Ġtre ball",
+ "ĠNear ly",
+ "ĠÑĢе алÑĮно",
+ "Ġch il",
+ "éĢ ±",
+ "ÄŁ a",
+ "ĠM EL",
+ "ros cop",
+ "ĠC G",
+ "Ġv enge",
+ "Ġdishwas her",
+ "al gic",
+ "Ġmod ifier",
+ "Ġemb assy",
+ "t imer",
+ "em ics",
+ "Ġintric ate",
+ "Ġev et",
+ "ĠëĮĢë °ķ",
+ "Ġis ot",
+ "Ġна ÑĥÑĩ",
+ "ĠQu iz",
+ "res o",
+ "δ Ïİ",
+ "Ġye lled",
+ "Ġfed er",
+ "ELL ER",
+ "Ġexceed ed",
+ "on as",
+ "ic ano",
+ "Ġжив оÑĤ",
+ "ĠMa o",
+ "ĠKaz uto",
+ "Ġ ãħĭãħĭãħĭãħĭ",
+ "Ġfront line",
+ "ĠHung arian",
+ "Ġüber all",
+ "aw at",
+ "Ġgri ps",
+ "i ções",
+ "arn ya",
+ "ĠÍ ¡",
+ "Ġse id",
+ "Ġan ak",
+ "Ġacab ou",
+ "íķ ij",
+ "Ġnot orious",
+ "ĠGod zilla",
+ "Ġover coming",
+ "ĠP end",
+ "Ġol abilir",
+ "ül me",
+ "Ġer halten",
+ "ãĤī ãģĦ",
+ "ê· ¹",
+ "ĠM eter",
+ "Ġsta an",
+ "O l",
+ "Ġch ats",
+ "ĠBu enos",
+ "ÃŃ ve",
+ "alu able",
+ "Ġstrateg ically",
+ "Ġcompr ised",
+ "ĠпеÑĢÑģон аж",
+ "Ġw ann",
+ "ĠC en",
+ "н иÑĤе",
+ "Ł ģ",
+ "ĠÑĤоб ой",
+ "i ad",
+ "ĠkardeÅŁ im",
+ "ĠCongress man",
+ "ream ing",
+ "h omme",
+ "Ġcommun aut",
+ "Ġalcohol ic",
+ "Ġpick led",
+ "Ġac ord",
+ "p osition",
+ "eg ól",
+ "Ġtrou bling",
+ "ĠMarch eg",
+ "Ġzum indest",
+ "Ġseam lessly",
+ "Ġol un",
+ "ĠTV s",
+ "ĠпÑĢакÑĤи ÑĩеÑģки",
+ "Ġback end",
+ "ãģĵãĤĵ ãģ«ãģ¡ãģ¯",
+ "id able",
+ "Ġgad get",
+ "Ġfa ço",
+ "ĠMarcheg iani",
+ "Ġë° ¤",
+ "Ġaccident al",
+ "ĠL P",
+ "Ġeld est",
+ "ĠAd miral",
+ "Ġn Äĥm",
+ "le ver",
+ "Ġpast el",
+ "Ġfond o",
+ "Con nie",
+ "Ġter cer",
+ "Ġp act",
+ "ĠMont e",
+ "Ġme ats",
+ "ĠS MS",
+ "ĠAustral ians",
+ "ç ¼",
+ "Rh ett",
+ "Ġexact ement",
+ "Ġë¹ ¼",
+ "ĠM OD",
+ "ç ¡",
+ "ĠR apt",
+ "ĠNo ch",
+ "Ġab ort",
+ "ĠNav al",
+ "ĠFu ji",
+ "IN TER",
+ "Ġнов Ñĭй",
+ "Ġmiej sce",
+ "ĠIC U",
+ "ĠGrad uate",
+ "ĠGl en",
+ "ard i",
+ "ĠÈ ĺ",
+ "Ġsold er",
+ "Ġprofess ions",
+ "Ġorth og",
+ "om n",
+ "int rodu",
+ "ĠDen ise",
+ "ìŀIJë ¥¼",
+ "Ġcorrespond ence",
+ "AM A",
+ "Ġinf lict",
+ "Ġf and",
+ "ĠG ü",
+ "ĠÑĩ еÑĤ",
+ "Ġtr aced",
+ "Ġpat ents",
+ "Ġamb ush",
+ "Ġlot ta",
+ "ff er",
+ "ĠW agner",
+ "Ġimp erson",
+ "Ġextr êmement",
+ "ÙĤ ت",
+ "cond uct",
+ "A tt",
+ "ĠM ueller",
+ "ĠAl icia",
+ "Ġcy c",
+ "Ġha cker",
+ "Ġt ys",
+ "Ġha il",
+ "Ġз аÑıв",
+ "Ġpas so",
+ "Ġì¶ Ķê°Ģ",
+ "ĠÎ Ī",
+ "Ġpack aged",
+ "ĠC ynthia",
+ "he et",
+ "ä¸Ń åĽ½",
+ "ĠNiss an",
+ "ĠQuest o",
+ "é ¨",
+ "d id",
+ "Ġμ ια",
+ "ĠEll is",
+ "ĠAnal ysis",
+ "ce mos",
+ "Ġas eg",
+ "ĠMy ster",
+ "ĠCa o",
+ "Ġtu v",
+ "ĠIndust ry",
+ "주 ê³ł",
+ "ot al",
+ "Ġpeque ño",
+ "br as",
+ "Ġcompreh end",
+ "ĠSim pson",
+ "ÑģÑĤв ие",
+ "ocr acy",
+ "иÑĩеÑģ ки",
+ "ĠM ush",
+ "ĠLaur ie",
+ "Ġtriang ular",
+ "ĠPres ents",
+ "ĠK unden",
+ "ç´ ¹",
+ "æŃ ¦",
+ "ĠIs s",
+ "ĠDe ck",
+ "á»ĥ n",
+ "ĠDark ness",
+ "Ġinflamm atory",
+ "eremi ah",
+ "Ġwar med",
+ "vey ard",
+ "ĠMem ory",
+ "et ty",
+ "Ġtax payers",
+ "ภĵ",
+ "Ø ¡",
+ "Ġpract ise",
+ "ëĭ ¬ë",
+ "Ġdr illed",
+ "m Ã¼ÅŁ",
+ "log o",
+ "ĠF ach",
+ "¤ë ¡ľ",
+ "Ġübrig ens",
+ "Ġkon nten",
+ "Ġnormal mente",
+ "Ġarg ues",
+ "iling ual",
+ "°ë ¥¼",
+ "eg al",
+ "Ġtrava ill",
+ "ov y",
+ "а ÑĤо",
+ "Ġr uth",
+ "ĠL ights",
+ "Ġconsist ed",
+ "×ijר ×Ļ×Ŀ",
+ "Ġstere otype",
+ "Ġpay er",
+ "ĠRe e",
+ "ĠAir bnb",
+ "Ġdr owned",
+ "ĠZ oe",
+ "Ġcan opy",
+ "Ġbar r",
+ "Ġн оÑĩ",
+ "Ġpag an",
+ "Ġj ars",
+ "Ġr ê",
+ "er ver",
+ "æĪ ¿",
+ "ie ben",
+ "Ġes pect",
+ "ĠF i",
+ "Ġunw illing",
+ "Ġtechn ician",
+ "ặ t",
+ "m ember",
+ "ĠCan al",
+ "س Ùħ",
+ "Ġlie ber",
+ "Ġin ference",
+ "Ġhon oring",
+ "åij µ",
+ "ĠCamp aign",
+ "Ġline age",
+ "ĠSt ress",
+ "Ġvict ories",
+ "Ġde ja",
+ "× £",
+ "ê tes",
+ "bl ick",
+ "Ġмен ее",
+ "oth s",
+ "ĠCou ple",
+ "J ason",
+ "ĠNic olas",
+ "ек Ñģ",
+ "l ib",
+ "Ġher ramient",
+ "Ġ×IJ ×ķ×ŀר",
+ "Ġвид им",
+ "mill imeter",
+ "Ġsil houette",
+ "Ġdrive way",
+ "Ġcher ish",
+ "ãħł ãħł",
+ "Ġrans om",
+ "Ġinter disciplinary",
+ "ĠPort al",
+ "Ġtra g",
+ "th ood",
+ "Ġted ious",
+ "Ġgloss y",
+ "Ġpré par",
+ "ĠC ay",
+ "ĠT ook",
+ "ĠBott om",
+ "Ġz ig",
+ "å «",
+ "åį ±",
+ "re presented",
+ "à¹Ģล ย",
+ "Ġdesar rollo",
+ "ìĦ ľë",
+ "Ġvis cos",
+ "Ġmill igram",
+ "ĠG und",
+ "Ġfer ment",
+ "d rum",
+ "Ġdraw ers",
+ "La ugh",
+ "Ġpel os",
+ "Ġpave ment",
+ "Ġmem oir",
+ "av ait",
+ "Ġ20 50",
+ "¤ë ¥¼",
+ "Ġraz ón",
+ "Ġflour ish",
+ "Ġst ern",
+ "ä¸ Ī",
+ "ĠCh ung",
+ "Ġser pent",
+ "ĠGentle men",
+ "羣çļĦ å¾Ī",
+ "k ook",
+ "Ġl ut",
+ "import e",
+ "p arent",
+ "Ġw sz",
+ "Ġsc ree",
+ "ĠMitar beiter",
+ "å· ´",
+ "m ut",
+ "Ġìĸĺ 기를",
+ "Ġsem ble",
+ "ĠO W",
+ "Ġinvestig ator",
+ "ĠCher yl",
+ "ĠG erald",
+ "Ġpr ere",
+ "Ġcomp ares",
+ "ny t",
+ "Ġdiferen ça",
+ "? -",
+ "Ġqu á",
+ "ר ×Ļ",
+ "S en",
+ "Ġhe ps",
+ "Ġgrat uit",
+ "Ġcons ort",
+ "ĠST OP",
+ "ĠProtest ant",
+ "Ġelectro de",
+ "â Ĺ",
+ "Ġsecure ly",
+ "иÑĩеÑģ кой",
+ "Ġt ää",
+ "Ġreg isters",
+ "ĠHeaven ly",
+ "og ly",
+ "iss ä",
+ "ĠPhys ics",
+ "ĠMer kel",
+ "Ġré v",
+ "éĻ ¢",
+ "Ġer ased",
+ "ĠSac ramento",
+ "Ġcoff in",
+ "Ġex acer",
+ "Ġl anz",
+ "Ġpo ets",
+ "ul if",
+ "Ġì¹ ĺë",
+ "ĠN erd",
+ "ĠN CT",
+ "ĠH our",
+ "neh mer",
+ "ŀ ĺëıĦ",
+ "ĠPrin ci",
+ "S w",
+ "m ies",
+ "ar med",
+ "ĠBeat les",
+ "Ġpropag ation",
+ "Ġexch anged",
+ "Ġcum ulative",
+ "Ġì§ij ìĹIJ",
+ "Ġdefe ating",
+ "æĬ ±",
+ "b els",
+ "Ġw es",
+ "ĠOdys sey",
+ "ä½ł æĥ³",
+ "av ior",
+ "ĠìľĦ ìĹIJ",
+ "Ġbr it",
+ "Ġhij o",
+ "D AY",
+ "ĠاÙĦت ÙĬ",
+ "ĠС еÑĢг",
+ "Ñĥ ка",
+ "eds iÄĻ",
+ "Ġimp os",
+ "Ġell as",
+ "Ġfire arms",
+ "ĠN R",
+ "Ġ×ij× IJ",
+ "ĠÐŁ ока",
+ "aw i",
+ "ĠìĦ± ê³µ",
+ "Ġpup ils",
+ "ĠT ack",
+ "Ġfr ase",
+ "ĠSh ip",
+ "Ġst ad",
+ "ä¸ ľ",
+ "ĠGreat er",
+ "un un",
+ "imm ung",
+ "gr own",
+ "ĠN XT",
+ "ĠAmeric as",
+ "f ox",
+ "Ġmant en",
+ "éłIJ åĤĻ",
+ "ĠÑģ ок",
+ "Ġr ikt",
+ "lect ric",
+ "de ep",
+ "Ġзна еÑĪÑĮ",
+ "Ġben ut",
+ "ĠInf rast",
+ "ĠEm ir",
+ "ĠоÑĤп ÑĢав",
+ "ĠKim chi",
+ "ĠFinn ish",
+ "´ìł ģ",
+ "ina ire",
+ "Ġo ike",
+ "æ¸ħ æ¥ļ",
+ "Ġhost age",
+ "ĠBut ton",
+ "ÙĤ ÙĬ",
+ "ek ing",
+ "ĠKaz akh",
+ "Ġcomfort ing",
+ "Ġso g",
+ "Ġgreet ed",
+ "g uitar",
+ "p ayer",
+ "Ġrel ational",
+ "Ġconstru ir",
+ "çī¹ åĪ¥",
+ "op ian",
+ "ĠVol ume",
+ "iet h",
+ "ÑģÑĤв ом",
+ "ur rection",
+ "li ÅĽmy",
+ "Ġhem isphere",
+ "ĠBe an",
+ "IG N",
+ "Ġköt ü",
+ "ĠFall out",
+ "Ġbr ace",
+ "ç¹¼ çºĮ",
+ "ÏĢ ά",
+ "ĠH AS",
+ "Ġg é",
+ "Ġcharacter ize",
+ "ặ c",
+ "ĠMil ky",
+ "Ġtum ors",
+ "Ġn uit",
+ "ĠG az",
+ "ĠìŀĪ ëĭ¤ëĬĶ",
+ "Ġг аÑĢ",
+ "ess ment",
+ "ĠA be",
+ "Ġë½ ij",
+ "ĠEins atz",
+ "J IN",
+ "j ä",
+ "C ry",
+ "ĠProm ised",
+ "ĠÑģеÑĢ д",
+ "ok us",
+ "Ġscal able",
+ "ĠпоÑģмоÑĤÑĢ еÑĤÑĮ",
+ "ück lich",
+ "Ġreal ism",
+ "Ġmay o",
+ "Ġjuven ile",
+ "Ġhead lights",
+ "Ġgör Ã¼ÅŁ",
+ "ĠRe form",
+ "Ġhal ves",
+ "cz ne",
+ "Ġbreak up",
+ "że j",
+ "Ġr ätt",
+ "D ay",
+ "ĠìĿ¼ë ³¸",
+ "Ġmu erte",
+ "Ġtun es",
+ "ĠSm ile",
+ "rec ord",
+ "Ġrecher che",
+ "atisf ied",
+ "Ġpo zi",
+ "Ġcelebr ations",
+ "ise xual",
+ "ĠRO B",
+ "third s",
+ "ĠF ortune",
+ "ĠÑĤ ой",
+ "Ġbrand ed",
+ "lo o",
+ "Ġd ud",
+ "Ġrandom ized",
+ "Ġcomb in",
+ "ä¸Ģ äºĽ",
+ "ier an",
+ "c zenia",
+ "į ãĥ«",
+ "Ġcur ator",
+ "Ġar tery",
+ "ĠÑĥ ÑĪ",
+ "ĠÑĩ иÑĤ",
+ "Ġsubsid ies",
+ "Ġbloss om",
+ "ĠTw ilight",
+ "Ġhy vä",
+ "ĠPom pe",
+ "ĠC isco",
+ "ĠÐŁÑĢ о",
+ "Ġbir i",
+ "Ġg ern",
+ "Ġre built",
+ "Ġw cze",
+ "Ġbenefic i",
+ "Ġdrum mer",
+ "Ġsol ids",
+ "Ġdi yorsun",
+ "ãģĤãĤĬãģĮãģ¨ãģĨãģĶãģĸ ãģĦãģ¾ãģĹãģŁ",
+ "l ated",
+ "Ġmud dy",
+ "Ġh olog",
+ "Ġcl aps",
+ "ĠR ings",
+ "ĠO key",
+ "ĠBra ve",
+ "Ġvalu ation",
+ "Ġmig rant",
+ "Ġinter mitt",
+ "Ġeig ene",
+ "ili ary",
+ "ãĥ¼ ãĥĪ",
+ "mark t",
+ "k r",
+ "ĠR ib",
+ "á»Ļ i",
+ "Ġaccus ations",
+ "Ġa rab",
+ "w ash",
+ "ĠBard zo",
+ "Ġu gh",
+ "est ers",
+ "oph ren",
+ "Ġaliment os",
+ "ĠU z",
+ "Ö Ĥ",
+ "Ġ6 50",
+ "ĠпÑĢи еÑħ",
+ "F I",
+ "Ġsamp ai",
+ "Ġparl é",
+ "hes ion",
+ "Ġs ır",
+ "Ġapparat us",
+ "Ġcor related",
+ "ĠPrincip al",
+ "Ġcor r",
+ "ĠOffic ial",
+ "иÑĩеÑģ кие",
+ "Ġtermin als",
+ "Sh ould",
+ "Ġvac un",
+ "Ġst ellt",
+ "Ġmo oi",
+ "etz ung",
+ "Ġк ÑĢа",
+ "Ġda i",
+ "Ġп ож",
+ "Te am",
+ "ĠP PE",
+ "ĠÐŀ Ñģ",
+ "ĠLe ah",
+ "ĠI vy",
+ "y st",
+ "Ġuh hh",
+ "Ġnight time",
+ "Ġtrend y",
+ "Ġsec urities",
+ "Ġcontin ents",
+ "Ġfirst hand",
+ "ĠVer on",
+ "ĠëĤ ®",
+ "Ġbrows ing",
+ "ĠC ada",
+ "t ro",
+ "Ġtr amp",
+ "re ib",
+ "Ġerst mal",
+ "irl er",
+ "Ġps ic",
+ "Ġget ir",
+ "ĠN P",
+ "Ġdzie ci",
+ "об ÑĢаз",
+ "Ġmagic ian",
+ "Ġscrut iny",
+ "Ġsl ab",
+ "ĠO T",
+ "ist y",
+ "ir ies",
+ "ore st",
+ "Ġtask ed",
+ "Ġmor ally",
+ "ìķ¼ ì§Ģ",
+ "ust ered",
+ "Ġfool s",
+ "Ġir respons",
+ "Ġein f",
+ "Ġvi á»ĩc",
+ "Ġsc or",
+ "Ġpill ows",
+ "ĠG egen",
+ "Ġtut te",
+ "Ġquarter ly",
+ "Ġdid nt",
+ "ĠG ym",
+ "ĠE ther",
+ "ĠØ «",
+ "лиÑĪ ком",
+ "Ġsign aling",
+ "ĠN ode",
+ "ĠDonc s",
+ "Ġy ah",
+ "ĠKan al",
+ "Ġf ading",
+ "et in",
+ "Ġinfluen cers",
+ "Ġmed als",
+ "Ġengine ered",
+ "Ġfer mented",
+ "ê²ł ì§Ģë§Į",
+ "ĠBeet hoven",
+ "×ŀ× ©",
+ "inent al",
+ "ĠìķĮë ł¤",
+ "üt fen",
+ "al nya",
+ "Ġo vere",
+ "Ġden kt",
+ "ак ÑĤеÑĢ",
+ "Ġâ ĺ",
+ "Ġneces it",
+ "Ġgener ators",
+ "gr ass",
+ "Ġпод Ñĥм",
+ "lie ÃŁen",
+ "B ar",
+ "ľë ıĻ",
+ "ĠдеÑĤ ей",
+ "Ġsuck ing",
+ "Ġsten cil",
+ "Ġprim o",
+ "ĠBreat h",
+ "st rom",
+ "Ġimmens ely",
+ "Ġapp reh",
+ "ìłķ ìĿ´",
+ "P op",
+ "Ġj ong",
+ "ĠGi ul",
+ "ĠAD HD",
+ "Ġhö ren",
+ "Ġe lo",
+ "iv ent",
+ "Ġr us",
+ "Ġoutrage ous",
+ "Ġmaster ed",
+ "Ġì» ¤",
+ "ÙĪ Ùģ",
+ "ip es",
+ "ĠRud y",
+ "Jac ob",
+ "Ġbull ish",
+ "Ġt apped",
+ "Ġfa ud",
+ "iz ophren",
+ "ĠÑģо Ñħ",
+ "ĠDar ling",
+ "Ġ196 3",
+ "ĠPre vention",
+ "² Ķ",
+ "Ġabdom inal",
+ "st ones",
+ "Ġav aient",
+ "á»ķ i",
+ "m ake",
+ "Ġs are",
+ "ĠInst ant",
+ "к ам",
+ "Ġkeep er",
+ "Ġblank ets",
+ "ãģ§ ãģĹãĤĩãģĨ",
+ "Ġswe ats",
+ "ĠMinne apolis",
+ "åħ¨ éĥ¨",
+ "Ġgen ommen",
+ "Ġfast en",
+ "ĠBrus sels",
+ "åij ¼",
+ "Ġcaf eter",
+ "Ġabsor bing",
+ "Ġha go",
+ "ĠEl mo",
+ "Ġgust o",
+ "ĠY ap",
+ "M úsica",
+ "Ġt ert",
+ "Ġband a",
+ "Ġm ily",
+ "Ġthere after",
+ "ĠStock holm",
+ "ĠC arson",
+ "Ġcalib ration",
+ "ava ÅŁ",
+ "ans a",
+ "ik ke",
+ "Ġfore see",
+ "Ġqual che",
+ "Ġdest e",
+ "æ ¤",
+ "ün üz",
+ "Ġfor ge",
+ "D is",
+ "est en",
+ "Ġδ ια",
+ "Ġenca ps",
+ "ĠGes pr",
+ "Ġcher cher",
+ "ick ets",
+ "ÑĤоÑĢ Ñĭ",
+ "C r",
+ "ĠТак же",
+ "Ġrabb its",
+ "ĠD ot",
+ "he iten",
+ "Ġcaus al",
+ "ĠF oster",
+ "ajÄħ c",
+ "Ġbere it",
+ "Ġayud ar",
+ "é« Ļ",
+ "ãģ ³",
+ "s ong",
+ "com b",
+ "Ġfr inge",
+ "Ġcyber security",
+ "Ġëľ ¨",
+ "Ġk ier",
+ "Ġbesch äft",
+ "Ġкон ÑĨе",
+ "Ġfacil it",
+ "ĠNam en",
+ "Ġbil ateral",
+ "t x",
+ "ĠW issenschaft",
+ "Ġnu ances",
+ "Ġr ipping",
+ "Ġf y",
+ "ĠSicher heit",
+ "ĠGh ana",
+ "ol on",
+ "Ġto pped",
+ "ĠMoroc co",
+ "Ġrad ial",
+ "ĠL EE",
+ "ĠAndre as",
+ "ed d",
+ "ĠìĹ ´ë",
+ "ĠAirl ines",
+ "ãģĵ ãĤį",
+ "Ġval ores",
+ "ê· ľ",
+ "H y",
+ "Ġзад аÑĩ",
+ "ĠKend all",
+ "ĠÑħ аÑĢ",
+ "ĠV amp",
+ "Ġpy thon",
+ "Ġmanage able",
+ "ĠG ente",
+ "o ise",
+ "ici ary",
+ "Ġimp oss",
+ "ĠBun ny",
+ "iest a",
+ "And rew",
+ "Ġser t",
+ "ĠC ec",
+ "zz arella",
+ "Ġautom obile",
+ "ĠT iere",
+ "all ows",
+ "åĨ Ĩ",
+ "Ġë° Ģ",
+ "ĠSc orp",
+ "ĠJ elly",
+ "ag ara",
+ "ĠSt retch",
+ "Ġrede f",
+ "Ġexacer b",
+ "ĠS HA",
+ "é f",
+ "ors a",
+ "Ġflaw ed",
+ "ĠNo el",
+ "?! ?",
+ "Ġpro cent",
+ "Ġmen stru",
+ "ĠпÑĢо Ñĩ",
+ "Ġinf ants",
+ "ðŁİ µ",
+ "pa use",
+ "ĠR acing",
+ "Ġ194 8",
+ "Ġsuper intendent",
+ "id ores",
+ "id y",
+ "bra him",
+ "Ġunl ucky",
+ "Ġper k",
+ "an ci",
+ "Ġë§Įë Ĥĺ",
+ "ĠÐľÐ¾Ñģ кв",
+ "Ġfin ans",
+ "Ġdiferen cia",
+ "łĪ ìĿ´",
+ "éħ į",
+ "OR Y",
+ "ĠT ac",
+ "ÛĮ ا",
+ "Ġdes em",
+ "Ġваж но",
+ "ĠJ U",
+ "ĠìŀĪ ìŀĸìķĦìļĶ",
+ "ĠÎ Ŀ",
+ "Ġinform ations",
+ "ĠH EL",
+ "h st",
+ "Ġпог овоÑĢ",
+ "Ġvo iture",
+ "Ġre us",
+ "änd ig",
+ "ĠпоÑħ ож",
+ "j ing",
+ "Ġd ru",
+ "alt ra",
+ "Ġprodu its",
+ "Ġk ite",
+ "Ġeye ball",
+ "ĠB elt",
+ "ĠRestaur ant",
+ "Ġg amb",
+ "Ġpor ridge",
+ "it ters",
+ "Ġconver ts",
+ "Ġyard ım",
+ "Ġmáxim o",
+ "w irtschaft",
+ "Ġíķĺë Ĥĺë",
+ "Ġì¤ Ģ",
+ "Ġice berg",
+ "Ġvor bei",
+ "Ġ25 6",
+ "ocr atic",
+ "Ġreck less",
+ "on ner",
+ "Ġm ús",
+ "Ġlog ically",
+ "ĠPr ison",
+ "ĠNet z",
+ "Ġvac ant",
+ "Ġn immt",
+ "ĠH ARR",
+ "Ġз ов",
+ "ĠDe e",
+ "ring e",
+ "ni est",
+ "ĠR ules",
+ "ìĬ¤ë Ł½",
+ "cuss ions",
+ "Ġfl oral",
+ "Ġconstra ined",
+ "Ġdifferent iation",
+ "ĠQue bec",
+ "ĠÛģ ÛĮÚº",
+ "Ġpúblic a",
+ "it el",
+ "Ġaccommod ations",
+ "ĠGr ü",
+ "í ľ",
+ "Ġpick les",
+ "иÑĩеÑģ киÑħ",
+ "Ġcomm issions",
+ "ĠBa ek",
+ "Ġçoc uÄŁ",
+ "ĠMed ium",
+ "Ġperiod ically",
+ "Ġwonder fully",
+ "Ġstaff ing",
+ "ìĽ IJë",
+ "ri re",
+ "f le",
+ "ĠMc L",
+ "ĠÑĤ еп",
+ "ĠпеÑĢ ек",
+ "н олог",
+ "Ġíģ¬ ê²Į",
+ "çĻ¼ çı¾",
+ "Ġprosper ous",
+ "ĠSpirit ual",
+ "ĠCh ick",
+ "DI A",
+ "ĠÐŁÑĢ ивеÑĤ",
+ "Ġper ÃŃ",
+ "ÑĮ ÑİÑĤ",
+ "Ġconsult ants",
+ "ĠEar l",
+ "ä»Ĭ å¹´",
+ "Ġru ining",
+ "оÑĢ е",
+ "Ġpens er",
+ "Ġtak iej",
+ "Ġstrength ened",
+ "ĠLiqu id",
+ "он еÑĨ",
+ "ав аÑĤÑĮ",
+ "Ġcam er",
+ "Ġdisagre ement",
+ "Ġbat hing",
+ "ĠY osh",
+ "a al",
+ "pre chen",
+ "RIS ADAS",
+ "Ġsuper star",
+ "æģ Ń",
+ "лÑı ÑĤÑĮ",
+ "Ġn ib",
+ "ĠTh erm",
+ "ĠDAN IEL",
+ "Ġp aw",
+ "Ġliqu ids",
+ "Ġcapac it",
+ "ark en",
+ "Ġvag ina",
+ "Ġm ashed",
+ "Ġemer ges",
+ "ys cy",
+ "Ġun related",
+ "ĠGu ild",
+ "Ġin verted",
+ "it ives",
+ "T ra",
+ "Ġbe gr",
+ "Ġal te",
+ "ì§ ķ",
+ "ãĤģ ãģ¦",
+ "ĠÑĢазÑĢ абоÑĤ",
+ "f inder",
+ "Ġдал ее",
+ "Ġблаг одаÑĢ",
+ "walk er",
+ "Ġcr ater",
+ "ass adors",
+ "ren ces",
+ "ins ki",
+ "ĠK IM",
+ "ĠEll iot",
+ "20 17",
+ "ĠS r",
+ "ink a",
+ "ano v",
+ "Ġìŀĺë ª»",
+ "Ġpropriet ary",
+ "display style",
+ "ĠÑģ им",
+ "Ġиз б",
+ "ĠPan el",
+ "Ġinstinct s",
+ "ĠCommun ications",
+ "éº »",
+ "mid t",
+ "Ġë§Įëĵ¤ ìĸ´",
+ "ĠÑģл ова",
+ "ĠGil bert",
+ "缮 åīį",
+ "Т ак",
+ "voor beeld",
+ "е ÑİÑģÑĮ",
+ "ary n",
+ "que z",
+ "Ġd art",
+ "Ñĸ ÑĪ",
+ "ĠH ut",
+ "S al",
+ "Ġs outheast",
+ "Ġpestic ides",
+ "Ġhelicop ters",
+ "Ġend ured",
+ "i ada",
+ "Ġbre wing",
+ "ìĹ ¬ë",
+ "ĠÑģв обод",
+ "ĠS aints",
+ "ĠFr ançais",
+ "ĠEconom ics",
+ "Ġdis loc",
+ "oph obia",
+ "C amer",
+ "Ġnegoti ated",
+ "ĠÑģÑĤ али",
+ "ìĬ¤í ģ",
+ "og ie",
+ "Ġtsun ami",
+ "Ġpeel ed",
+ "Ġmotiv ations",
+ "è¨ Ń",
+ "ost at",
+ "fl an",
+ "ĠD AC",
+ "Ġk av",
+ "' RE",
+ "ĠPe arson",
+ "b be",
+ "c zenie",
+ "Ġaten ção",
+ "íĨµ ëł¹",
+ "ãģ£ ãģ¡",
+ "ĠÑĥд аÑĢ",
+ "Ġintrodu ctory",
+ "ĠI ci",
+ "ë ĮĢë",
+ "ak at",
+ "Ġt rench",
+ "Ġproceed ed",
+ "ĠCo in",
+ "Ġdere cho",
+ "ĠRed e",
+ "æ¯ Ľ",
+ "ан нÑĭй",
+ "Ġincarcer ated",
+ "ĠRich mond",
+ "R ock",
+ "ĠP av",
+ "ĠKar ma",
+ "ug es",
+ "Ġconte ú",
+ "ë ¹Ħ",
+ "Ġê·¸ë §Į",
+ "ĠG one",
+ "Ġwsp óÅĤ",
+ "ĠRah men",
+ "un ken",
+ "Ġì¤ijìļĶ íķľ",
+ "Ġi b",
+ "Ġatt aching",
+ "H ay",
+ "Ġsu ka",
+ "ìį ¹",
+ "Ġpivot al",
+ "ĠRes pect",
+ "ÃŃ da",
+ "I B",
+ "ĠVer antwort",
+ "w iet",
+ "Ġforens ic",
+ "ÑĢи ÑģÑĤ",
+ "ĠпÑĢинÑĨип е",
+ "Ġmark ings",
+ "Ġk ettle",
+ "ĠOper a",
+ "ĠDo ctors",
+ "Ġshred ded",
+ "Ġrec uer",
+ "Ġvig il",
+ "ĠF ail",
+ "Ġentre v",
+ "Ġд ÑĥÑĪ",
+ "Ġout breaks",
+ "èµ° åIJ§",
+ "ĠÏĢ ο",
+ "Ġro gue",
+ "ang led",
+ "Ġyear ly",
+ "ĠCre ed",
+ "Ġw am",
+ "Ġlot us",
+ "ê³ ¼ë",
+ "ãĢģ ãĢģ",
+ "ĠSp it",
+ "ĠIt u",
+ "Ġstra ins",
+ "Ġstamp ed",
+ "Ġpl aint",
+ "Ġpot ion",
+ "Ġconsolid ation",
+ "è© ķ",
+ "оÑĩ кÑĥ",
+ "Ġvlog ging",
+ "Ġsl ate",
+ "ĠAu ft",
+ "ĠInc or",
+ "ừ ng",
+ "§ IJ",
+ "en h",
+ "Ġhe iÃŁ",
+ "Ġdom est",
+ "ĠSt rom",
+ "åį ³",
+ "ak is",
+ "Ġfra gen",
+ "Ġfin er",
+ "ĠS ug",
+ "Ġup hill",
+ "Ġé én",
+ "âĢ¦ )",
+ "ĠÑģ оп",
+ "ĠCore y",
+ "Ġsie bie",
+ "Ġm use",
+ "Ġclo ves",
+ "Ġp ous",
+ "ĠFin anz",
+ "ĠR oute",
+ "am at",
+ "Ġmut ually",
+ "ĠвнÑĥÑĤ ÑĢи",
+ "ĠSel ena",
+ "ë Ķ",
+ "ĠGa ussian",
+ "ë ¶ĢíĦ°",
+ "Ġ×ij× Ľ",
+ "Ġej erc",
+ "å¾ ®",
+ "ke a",
+ "ĠG erry",
+ "ĠS ic",
+ "大 çļĦ",
+ "Ġ196 6",
+ "ies e",
+ "Ġfoss ils",
+ "Ġest ad",
+ "ĠK ane",
+ "ci Äĩ",
+ "Ġìľł íĬľë",
+ "Ġп ам",
+ "ĠCru ise",
+ "int érieur",
+ "Ġbe kannt",
+ "ĠP ode",
+ "Ġdem ander",
+ "R em",
+ "Ġinv ade",
+ "Ġdecor ating",
+ "rop ic",
+ "Ġcow boy",
+ "ĠPh oto",
+ "opol it",
+ "Ġì»¬ë Ł¬ë",
+ "Ġre ap",
+ "Ġhand writing",
+ "à¹Ħ ร",
+ "Ġë ļ",
+ "Ġب عد",
+ "ĠM t",
+ "Ù Ģ",
+ "Ġspaces hip",
+ "Ġnational ism",
+ "Ġcouncil s",
+ "ĠGriff in",
+ "ĠAh med",
+ "Ġcl ich",
+ "ĠO L",
+ "w l",
+ "ĠPil ot",
+ "å® ®",
+ "Ġacron ym",
+ "Ġg els",
+ "Ġelectro ly",
+ "è ĵ",
+ "Ġм ной",
+ "Ġepis od",
+ "ĠDies es",
+ "ĠAT P",
+ "Ġed iyorum",
+ "Ġexpress es",
+ "Ġexhib its",
+ "C omm",
+ "Ġк ÑĢÑĥп",
+ "Ġmat ar",
+ "Ġ20 25",
+ "ĠArt em",
+ "vas ive",
+ "r Ãł",
+ "Ġbe ÅŁ",
+ "é» ĥ",
+ "Ġliz ard",
+ "Ġfill e",
+ "Ġì§ Ī문",
+ "Ġмо Ñī",
+ "Ġt ür",
+ "Ġcul prit",
+ "Ġwo ven",
+ "ĠAN Y",
+ "n im",
+ "Ġt ay",
+ "Ġprom in",
+ "Ġacom pa",
+ "Ġid é",
+ "Ġbo iler",
+ "ĠThe men",
+ "Ġaven ue",
+ "ĠM ud",
+ "Ġнов Ñĭе",
+ "Ġwitness ing",
+ "Ġl ance",
+ "ĠCH AN",
+ "ĠBe ver",
+ "ت Ùħ",
+ "Ġchem otherapy",
+ "K ing",
+ "ĠbÄĻd ÄĻ",
+ "Ġat ual",
+ "Ġt ive",
+ "Ġtalk in",
+ "Ġqued ar",
+ "ie ÃŁ",
+ "ed el",
+ "Ġìĸ´ì łľ",
+ "Ġjog ar",
+ "Ġö r",
+ "Ġundert aking",
+ "ĠStre ngth",
+ "Ġmil hões",
+ "ĠW ine",
+ "ĠM olt",
+ "è® ²",
+ "ãģij ãĤĮ",
+ "Ġunderm ine",
+ "ĠArch ives",
+ "v ana",
+ "mer cial",
+ "M C",
+ "Ġcast e",
+ "п ÑĢ",
+ "Ġlegisl ators",
+ "ul ators",
+ "ên io",
+ "Ġëį °ë",
+ "ĠÑħоÑĤ иÑĤе",
+ "Ġн ек",
+ "Ġs urn",
+ "Ġcons ci",
+ "ĠP OW",
+ "Ġcul inary",
+ "ĠK AT",
+ "ĠFol ks",
+ "Ñĭв аем",
+ "Ġв ок",
+ "ãģij ãĤĭ",
+ "s ervice",
+ "pt s",
+ "Ġпоб ед",
+ "æĺ¯ åķĬ",
+ "Ġt ents",
+ "Ġn ord",
+ "ST E",
+ "Ġrepublic an",
+ "Ġwy k",
+ "Ġmin ions",
+ "èĻ ķ",
+ "Ġmem ang",
+ "j est",
+ "Ġcompar ative",
+ "Ġty le",
+ "car bon",
+ "bed ingt",
+ "ks en",
+ "Ġneg ativity",
+ "Ġsjäl v",
+ "Ġd ú",
+ "æīĢ æľī",
+ "Ġrec alled",
+ "c ra",
+ "ĠT ada",
+ "ĠÑĢÑĥ ки",
+ "ĠопÑĢед ел",
+ "Ġproc rast",
+ "Ġjog os",
+ "ĠO o",
+ "ĠHe arts",
+ "Ġé ch",
+ "Ġksi Äħż",
+ "Ġco arse",
+ "ĠT ube",
+ "ĠG reens",
+ "Ġé n",
+ "Ġdumb bell",
+ "ĠÑĤ и",
+ "Ġquer er",
+ "ا ØŃ",
+ "Ïĥ ει",
+ "ĠпÑĢав илÑĮно",
+ "Ġп ап",
+ "Ġcomp ra",
+ "Ġt ér",
+ "ĠAnt es",
+ "Ġoptim um",
+ "Ġbisc uit",
+ "κ ι",
+ "acz ego",
+ "Ġìĭľê°Ħ ìĿ´",
+ "ĠMar ines",
+ "ver o",
+ "Ġvacc inations",
+ "Ġpet ty",
+ "rit ers",
+ "Ġа л",
+ "count ry",
+ "Ġcoun ters",
+ "Ġattend ant",
+ "ĠH ui",
+ "ãģ¨ãģĦãģĨãģĵãģ¨ ãģ§",
+ "ck a",
+ "ÑģÑĤвен нÑĭй",
+ "gu y",
+ "Ġtrick ed",
+ "ĠR ED",
+ "Ġthr illing",
+ "ÏĢο ι",
+ "Ġpig gy",
+ "Ġan unci",
+ "OR TER",
+ "ĠVal ue",
+ "Ġr ond",
+ "ĠA DA",
+ "Ġpos er",
+ "h ores",
+ "ĠR oland",
+ "ĵ ¯",
+ "Ġno ir",
+ "Ġש ×IJ×",
+ "ë° ľ",
+ "iem and",
+ "ĠпоÑĤ еÑĢ",
+ "ê³ ³",
+ "Ġê± ±",
+ "Ġformat ting",
+ "ĠL ed",
+ "è§Ģ çľ¾",
+ "Ġkill ers",
+ "ĠÄij ấy",
+ "Ġha ar",
+ "ag ain",
+ "! > [",
+ "min ster",
+ "Ġв ли",
+ "Ġident ifier",
+ "ĠLamb da",
+ "Ġtr os",
+ "Ġflaw less",
+ "Ġdetriment al",
+ "Ġbun ları",
+ "W ar",
+ "Ġreg ião",
+ "羣çļĦ æĺ¯",
+ "ĠB ike",
+ "cess ors",
+ "Ġc ùng",
+ "ĠR N",
+ "Ġê½ ĥ",
+ "Ġküç ük",
+ "ĠBegin ning",
+ "íĺ ¸ë",
+ "Ġge we",
+ "Ġden ote",
+ "ĠAlber to",
+ "Ġprob iot",
+ "Ġo de",
+ "Ġmol ar",
+ "Ġburst ing",
+ "ass umed",
+ "Ġfoot prints",
+ "ved a",
+ "Ġstero ids",
+ "Ġfl aming",
+ "ĠE ller",
+ "Ġerk ennen",
+ "ät zen",
+ "Ġlife cycle",
+ "ĠD OU",
+ "ĠK arena",
+ "ĠGuer ra",
+ "è¿ĺ æĺ¯",
+ "Ġsin ister",
+ "Ġpod éis",
+ "Ġpar ab",
+ "Ġok o",
+ "Ġmat éri",
+ "Ġcar ic",
+ "son aro",
+ "Ġpratic amente",
+ "ÑĥÑģ а",
+ "Ġcomun que",
+ "Ġvig ilant",
+ "Ġreg imes",
+ "ĠShoot ing",
+ "Ġra ids",
+ "ĠN ora",
+ "ĠW ieder",
+ "m ens",
+ "ĠÑģ од",
+ "Ġê²½ìļ° ìĹIJëĬĶ",
+ "Ġв Ñħод",
+ "Ġaut obi",
+ "ĠS chn",
+ "ĠRob bie",
+ "ĠF itness",
+ "Ġкон ÑĦ",
+ "Ġpeng uin",
+ "моÑĤÑĢ Ñı",
+ "Ġми ним",
+ "play s",
+ "Ġdeleg ates",
+ "M er",
+ "Ġsist em",
+ "ĠMicha els",
+ "m ale",
+ "ا ع",
+ "Ġcá ch",
+ "ĠH ä",
+ "Ġ×Ļ ×ķ×ĵ×¢",
+ "Ġsuper power",
+ "Ġstr on",
+ "Ġro ver",
+ "Ġdé pend",
+ "éĻ ³",
+ "Ġret iring",
+ "Ġvamp ires",
+ "Ġmer de",
+ "ĠCh anging",
+ "Ġt ame",
+ "Ġspokes person",
+ "Ġc ay",
+ "Ġfl irting",
+ "ĠGr ö",
+ "Ġw är",
+ "Ġwy b",
+ "Ġcoe ur",
+ "ạ nh",
+ "ĠìĻĢ ìĦľ",
+ "Ġconna is",
+ "ĠHundred s",
+ "ĠBe a",
+ "Ġα ÏĢ",
+ "pr uch",
+ "Ġsocied ade",
+ "ĠWh ilst",
+ "ĠK ait",
+ "esp ace",
+ "Ġch ia",
+ "ĠEr m",
+ "Ġë°Ķ ê¿",
+ "Ġf ences",
+ "ĠM ortal",
+ "ê² ģ",
+ "Ġг ÑĢаÑĦ",
+ "ĠHom eland",
+ "ĠJ UN",
+ "is st",
+ "Ġpar lar",
+ "Ġsport y",
+ "é o",
+ "Ġdeep en",
+ "ĠBeh avior",
+ "éĢ ı",
+ "åĵĪåĵĪ åĵĪ",
+ "Ġer rand",
+ "Ġrot ary",
+ "ĠWell ington",
+ "W ind",
+ "Ġmes ela",
+ "ả ng",
+ "iend e",
+ "Ġex cell",
+ "ĠGen ius",
+ "ĠEdu ardo",
+ "æľī 人",
+ "ĠÅŁ unu",
+ "ĠÄ° stanbul",
+ "Ġprod uto",
+ "Ġ ãħİãħİ",
+ "O FF",
+ "Ġwoll t",
+ "çĪ Ĩ",
+ "Ġëī´ì Ĭ¤",
+ "Ġl ass",
+ "Ġher tz",
+ "Ġar omatic",
+ "Ġзв он",
+ "Ġaut oc",
+ "ĠL ust",
+ "Ġ11 2",
+ "ĠÎ Ĺ",
+ "Ġreview ers",
+ "Ġrecept ive",
+ "å°į äºĨ",
+ "â nd",
+ "og lo",
+ "ĠìķĦëĭ Ļ",
+ "Ġn go",
+ "Ñĸ ÑĤи",
+ "Ã¥ t",
+ "con o",
+ "Ġtek rar",
+ "Ġ주 ê³ł",
+ "Ġgel miÅŁ",
+ "Ġbed time",
+ "ĠAr gh",
+ "AD A",
+ "ĠгоÑĢод а",
+ "ĠÄ ĩ",
+ "Ġall iances",
+ "g iggling",
+ "Ġyer de",
+ "Ġsp ies",
+ "Ġg utes",
+ "ç i",
+ "Ġallt id",
+ "ĠL ah",
+ "ŀ IJë",
+ "Ġdo kÅĤad",
+ "ÙĪ ÙĬ",
+ "Ġtoxic ity",
+ "Ġcancell ation",
+ "Ġ195 8",
+ "d ro",
+ "Ġìŀij ìĿĢ",
+ "ĠMotor ola",
+ "Ġmult in",
+ "Ġenthusi asts",
+ "ĠM ighty",
+ "ĠCoc onut",
+ ": ãĢĮ",
+ "ĠPict ures",
+ "Ġsang re",
+ "Ġbl inking",
+ "ol esome",
+ "ĠìĬ¤íĥĢ ìĿ¼",
+ "F P",
+ "Ġboom ing",
+ "ĠдеÑģÑı ÑĤ",
+ "Ġr atchet",
+ "Ġtim elines",
+ "len ess",
+ "Ġc ages",
+ "ĠGood night",
+ "omet imes",
+ "Ġc unning",
+ "ĠR isk",
+ "ul ed",
+ "d ade",
+ "Ġpr ata",
+ "Ġgust arÃŃa",
+ "am us",
+ "ĠJin ping",
+ "Ġest rut",
+ "Ġdescob rir",
+ "ĠM Äģ",
+ "ĠAll an",
+ "Ġ åĪĨ",
+ "Ġ×ľ× §",
+ "Ġpres erv",
+ "ĠStraw berry",
+ "Ä ı",
+ "L u",
+ "Ġk ro",
+ "ĠRep orts",
+ "ìħĶ ìķ¼",
+ "Ġval t",
+ "Ġpouv ait",
+ "Ġapp ar",
+ "ĠB one",
+ "Ġprefer ably",
+ "ĠRep ública",
+ "å°± åĪ°",
+ "Ġher zlich",
+ "Ġchim ney",
+ "Ġç ev",
+ "Ġvis as",
+ "Ġver r",
+ "Ġcultiv ation",
+ "ĠArmen ia",
+ "Ġвд ÑĢÑĥг",
+ "Ġcock ro",
+ "retch ed",
+ "art z",
+ "ĠлÑİд Ñıм",
+ "ĠpolÃŃt icas",
+ "ĠP anz",
+ "ĠA KA",
+ "ĠëĪ Į룬",
+ "Ġer ro",
+ "Ġcam per",
+ "Ġ10 2",
+ "ठ¸",
+ "d one",
+ "Ġho ard",
+ "ĠÐŁÐ¾ÑĤ ом",
+ "je ong",
+ "Ġdest a",
+ "p ak",
+ "Ġin im",
+ "Ġgrow ers",
+ "ĠMess age",
+ "Ġele ctor",
+ "eng age",
+ "ĠFor bes",
+ "ĠCincinn ati",
+ "Ġdiffé rence",
+ "d f",
+ "Ġsp ar",
+ "Ġawait s",
+ "ĠUSS R",
+ "ĠR ising",
+ "ĠHo ÅŁ",
+ "Ġfoot ing",
+ "Ġcond iciones",
+ "ÑĤоÑĢ ов",
+ "Ġclin ician",
+ "ĠDisk uss",
+ "å£ ĵ",
+ "ר ×Ĵ",
+ "× ¥",
+ "ite it",
+ "g ren",
+ "Ġchar isma",
+ "Ġle uke",
+ "Ġirrit ating",
+ "Ġcir ca",
+ "ĠRhod es",
+ "Ġp ior",
+ "Ġhandic ap",
+ "roy able",
+ "Ġv ull",
+ "O G",
+ "Ġin ÃŃcio",
+ "ier i",
+ "Ġspl ashing",
+ "Ġdem ise",
+ "Ġassist ir",
+ "Ñĩ ÑĤо",
+ "Ġcover t",
+ "ĠG ud",
+ "ภī",
+ "kl är",
+ "ĠìŀIJ 꾸",
+ "Ġver ändert",
+ "ĠR EM",
+ "ĠCon ven",
+ "at ge",
+ "Ġpierws ze",
+ "Ġcler gy",
+ "ling ton",
+ "l iv",
+ "V PN",
+ "ĠÑģ ожал",
+ "ĠH ate",
+ "ãģ¨ ãģĵãĤį",
+ "ÏĨ ο",
+ "ĠResp ons",
+ "оз д",
+ "Ġet mek",
+ "Ġchem in",
+ "Ùħ Ø©",
+ "Ġê°Ģ 족",
+ "T re",
+ "Ġum as",
+ "ĠBur ton",
+ "Ġpatri arch",
+ "ĠSmithson ian",
+ "¥ ĺ",
+ "M oon",
+ "A ir",
+ "Ġmed ios",
+ "Ġer aser",
+ "Ġwoll ten",
+ "Ġpare il",
+ "ĠBill ie",
+ "æĬ ½",
+ "еÑĢÑĤ в",
+ "Ġparl ament",
+ "Ġag ony",
+ "ĠQU E",
+ "sequ ently",
+ "An other",
+ "ĠWh ew",
+ "ĠAnn ual",
+ "Ġse ben",
+ "ìĥģ ìĿĦ",
+ "val ues",
+ "ŀľë §Į",
+ "Ġsin on",
+ "ere al",
+ "ĠEn light",
+ "ĠChem istry",
+ "ĠCatal unya",
+ "Ġdoct r",
+ "ant on",
+ "Ġst uk",
+ "ĠPl ate",
+ "ĠKardash ian",
+ "Ġfil os",
+ "ĠW et",
+ "Ġпоп ÑĭÑĤ",
+ "Ġunknown s",
+ "ĠSch on",
+ "ĠBald win",
+ "Ġtelescop es",
+ "ĠG ucci",
+ "ox ide",
+ "ĠConserv ative",
+ "ìĦ± ìĿĦ",
+ "Ġhina us",
+ "P ower",
+ "Ġê±´ ê°ķ",
+ "Ġprev ail",
+ "orm an",
+ "m achine",
+ "Ġ194 6",
+ "Ġun bel",
+ "Ġsch aut",
+ "Ġp iel",
+ "e enth",
+ "Ġobject ively",
+ "Ġch akra",
+ "aud io",
+ "Ġch icos",
+ "ĠV ault",
+ "å° Ī",
+ "Ġmedic inal",
+ "ĠT ail",
+ "Wh ile",
+ "Ġas phalt",
+ "Ġfro ze",
+ "ĠE K",
+ "unch ing",
+ "n osis",
+ "20 15",
+ "ĠG ri",
+ "Ġodd ly",
+ "ĠM är",
+ "ĠA eg",
+ "c olo",
+ "P ar",
+ "Ġëĵ¤ ìĸ´ë",
+ "Ġv inden",
+ "ĠO VER",
+ "Ġ iced",
+ "Ġsc orp",
+ "Ġha c",
+ "qual ified",
+ "ĠÑĥвид еÑĤÑĮ",
+ "erm o",
+ "H EN",
+ "Ġso i",
+ "Ġmulti ples",
+ "Ġlay outs",
+ "Ġblind ness",
+ "ĠB owser",
+ "Ġпод ÑĤ",
+ "ĠÃ İ",
+ "vention al",
+ "Ġm ata",
+ "mad ı",
+ "Ġge ez",
+ "Ġcad ence",
+ "Ġważ ne",
+ "ĠChrist ie",
+ "ven ge",
+ "C all",
+ "Ġturn around",
+ "Ġblo b",
+ "ĠЯ к",
+ "ĠVoice over",
+ "Ġper il",
+ "ĠJa ime",
+ "ĠH OY",
+ "l ane",
+ "Ġse bel",
+ "ĠDu o",
+ "ĠHistor ical",
+ "Ġd ni",
+ "Ġg ema",
+ "y k",
+ "Ġsab em",
+ "ắ ng",
+ "Ġv ars",
+ "ĠRon nie",
+ "ĠRon aldo",
+ "ĠPer què",
+ "ns inn",
+ "h air",
+ "Ġrelent less",
+ "Ġl yn",
+ "Ġtravel er",
+ "æĢİ麼 äºĨ",
+ "n ine",
+ "Ġant im",
+ "Ġì¼ Ģ",
+ "Ġsnow ball",
+ "ĠÑħаÑĢ акÑĤеÑĢ",
+ "Ġintern s",
+ "Ġconstitu ency",
+ "ĠÐĿ ам",
+ "׾ ׾",
+ "V EL",
+ "Ġvikt igt",
+ "Ġap oyo",
+ "ÙĦ ب",
+ "Ġj ard",
+ "Ġheight ened",
+ "ÑĢо ÑģÑĤ",
+ "ĠSM ITH",
+ "Ġдел а",
+ "Ġrepair ing",
+ "Ġr igt",
+ "ĠShe ikh",
+ "ĠBrit ney",
+ "Ġevery time",
+ "Ġadvent urous",
+ "oc key",
+ "er nt",
+ "Ġat aque",
+ "ĠAltern atively",
+ "e ffect",
+ "Ġpalav ras",
+ "ĠElli ott",
+ "Ġréuss i",
+ "Ġhypert ension",
+ "ĠMan ual",
+ "Ġproph etic",
+ "Ġhand c",
+ "ÑĮ е",
+ "Ġref rain",
+ "ĠSqu id",
+ "ìŀ ¡",
+ "Ġком ан",
+ "äll en",
+ "Ġlleg ó",
+ "Ġbas h",
+ "ion y",
+ "ĠÑģк лад",
+ "Ġк аб",
+ "Ġcare less",
+ "ĠP ool",
+ "Ġtr ás",
+ "Ġfil s",
+ "ĠSch r",
+ "Ġsp rawd",
+ "ĠMon aten",
+ "Ġunfor gettable",
+ "ĠCott on",
+ "Ġinconven ient",
+ "ĠR X",
+ "or is",
+ "Ġhum bled",
+ "ת ×Ĺ",
+ "ĠØ¢ Ù¾",
+ "Ġincre ÃŃ",
+ "ĠKomment are",
+ "èĪ Ĵ",
+ "r ación",
+ "Ġv antage",
+ "ĠSe al",
+ "ĠìĿ´ 거를",
+ "Ġjou e",
+ "ãģĿãģĨ ãģ§ãģĻãģŃ",
+ "Ġìĺ¤ë ŀĺ",
+ "ĠиÑģп ÑĭÑĤ",
+ "ob en",
+ "Ġgr ate",
+ "Ġcontro le",
+ "ĠPer cy",
+ "ÅĤ ada",
+ "Ġsimult aneous",
+ "Ġprot oty",
+ "ĠgroÃŁ er",
+ "Ġbew usst",
+ "iniz i",
+ "Ġpass ieren",
+ "ĠHapp iness",
+ "åī ĩ",
+ "sh i",
+ "ge ht",
+ "Ġstation ed",
+ "ĠErgeb nis",
+ "Ġdirect amente",
+ "Ġsurv ives",
+ "Ġperson es",
+ "BER G",
+ "Ġvom iting",
+ "Ġconhe cer",
+ "Ġad jour",
+ "ĠCiv ic",
+ "pe i",
+ "bur st",
+ "Ġëĭ¤ ëĭĪ",
+ "é ı",
+ "Ġsl ed",
+ "Ġplataform a",
+ "ĠS ect",
+ "ĠDe fin",
+ "çĻ» éĮ²",
+ "én om",
+ "chn et",
+ "Ġprofit ability",
+ "Ġerre icht",
+ "á»ı i",
+ "c ation",
+ "Ġì§Ģ ê¸",
+ "Ġperd re",
+ "Ġfel ony",
+ "Ġ195 7",
+ "æĪij å¾Ī",
+ "Ġunsuccess ful",
+ "Ġnag yon",
+ "Ġelastic ity",
+ "Ġfac ade",
+ "Ġearth ly",
+ "ĠамеÑĢик ан",
+ "Ġcon n",
+ "c la",
+ "D u",
+ "Ġpolit iques",
+ "Ġhal o",
+ "iant es",
+ "Ġмо ей",
+ "ãĥ³ ãĥī",
+ "ton es",
+ "el ier",
+ "è® ļ",
+ "ht aking",
+ "Ġwicht ige",
+ "Ġan no",
+ "ĠL ok",
+ "ill ions",
+ "Ġv iver",
+ "Ġsol chen",
+ "Ġsu f",
+ "ĠSal z",
+ "ĠN vidia",
+ "z uge",
+ "ĠSp ike",
+ "V ideo",
+ "Ġtw or",
+ "ĠA la",
+ "èij ī",
+ "Ġh anya",
+ "ĠAd m",
+ "ìĿ µ",
+ "ĠPatient en",
+ "ĠOn ion",
+ "ĠKo be",
+ "ĠSc ene",
+ "ĠR ash",
+ "æ¨ Ļ",
+ "ÑĢа ÑģÑĤ",
+ "ist ani",
+ "Gen eral",
+ "le ye",
+ "imb ap",
+ "Ġconce aled",
+ "ĠFr idays",
+ "ĠW ool",
+ "Ġнов ÑĭÑħ",
+ "ش ر",
+ "Ġê²° ê³¼",
+ "Ġjed och",
+ "´ìĭ ľ",
+ "ĵ¤ ëıĦ",
+ "Ġìŀ¥ ëĤľ",
+ "uk t",
+ "L ou",
+ "Ġ먹 ìĸ´",
+ "ĠEx pect",
+ "Ġдом ой",
+ "Ġirrespons ible",
+ "Ġac erca",
+ "ĠZ ust",
+ "ר ×ĺ",
+ "U I",
+ "Ġyout ubers",
+ "ĠPos itive",
+ "Ġsoci oe",
+ "Ġsn atch",
+ "èĥ Į",
+ "Ġrefresh ed",
+ "Ġnom inations",
+ "ĠP att",
+ "Ġobsol ete",
+ "Ġdem iÅŁ",
+ "åı ¤",
+ "orm uÅŁ",
+ "ĠìĨĶì§ģ íŀĪ",
+ "Ġf la",
+ "Ġcra ziest",
+ "ĠZ ie",
+ "ĠT ú",
+ "z ep",
+ "ic em",
+ "Ġë©ĭ ìŀĪ",
+ "Ġcyn ical",
+ "ãģĿ ãĤĵãģª",
+ "Ġt resp",
+ "Ġcra z",
+ "Õ¥ Õ",
+ "Ġne lle",
+ "Ġm ph",
+ "ĠN ered",
+ "ĠK ob",
+ "ĠE ck",
+ "¨¸ ëĭĪ",
+ "J an",
+ "ĠТ огда",
+ "Ġde ci",
+ "ĠV og",
+ "Ġbubb ling",
+ "éĢ Ģ",
+ "ú a",
+ "Ġproduct os",
+ "iber al",
+ "Ġrepl icated",
+ "ĠImp rove",
+ "ill ary",
+ "C ha",
+ "Ġré du",
+ "ĥIJ íķĺë©´",
+ "Ġcon not",
+ "ĠK rit",
+ "ĠдÑĥÑħ ов",
+ "Ġtread mill",
+ "ĠP W",
+ "Ġзов ÑĥÑĤ",
+ "Ġcl ams",
+ "Ġdra fting",
+ "Ġ195 6",
+ "un ta",
+ "Ġexpend itures",
+ "ĠHoo ver",
+ "W OO",
+ "ÑĪе е",
+ "Ġded uction",
+ "mon ary",
+ "Ġreci b",
+ "Ġpo vo",
+ "Ġëį Ķë",
+ "ĠP AL",
+ "ĠBl ow",
+ "Ġwy p",
+ "Ġdest ac",
+ "de al",
+ "Gra eme",
+ "Ġnécess aire",
+ "Ġdamn ed",
+ "Ġ19 38",
+ "Ġìĭ¤ ìłľë¡ľ",
+ "Ġtro op",
+ "Ġinsight ful",
+ "ĠT J",
+ "ĠоÑģ в",
+ "Ġf idelity",
+ "ĠSk ip",
+ "ĠMay o",
+ "ë§ Ŀ",
+ "app e",
+ "Ġbl as",
+ "ĠW Y",
+ "ĠG N",
+ "ct ar",
+ "S u",
+ "Ġcu ent",
+ "he ws",
+ "Ġcorps es",
+ "A bs",
+ "Ġwaste water",
+ "Ġc iek",
+ "ĠOn u",
+ "Ġexplos ives",
+ "Ġar ma",
+ "ĠSTEP HAN",
+ "polit ik",
+ "ĠOs aka",
+ "ta ÅĤ",
+ "Ġyap ıyor",
+ "Ġiz quier",
+ "Ġbele za",
+ "ĠWy att",
+ "åIJ ¸",
+ "Ġsu k",
+ "Ġspec jal",
+ "Ġdan ke",
+ "wh istle",
+ "ĠfÃŃs ica",
+ "ĠHar riet",
+ "ĠìķĦ íĮĮ",
+ "Ġwill kommen",
+ "ip ing",
+ "ĠÑģмоÑĤÑĢ иÑĤе",
+ "Ġмож еÑĪÑĮ",
+ "Ġinacc urate",
+ "Ġarrog ance",
+ "ĠRem o",
+ "γ ά",
+ "ass ed",
+ "Ġdeliver ies",
+ "Ġst inky",
+ "ĠпеÑĢ еж",
+ "j ay",
+ "Ġtrans itional",
+ "Ġr ere",
+ "ĠNGO s",
+ "ĠAT M",
+ "خ ت",
+ "i ology",
+ "Ġв лад",
+ "Ġsch me",
+ "ĠSh ine",
+ "ìķ ¡",
+ "p ants",
+ "Ġser ge",
+ "Ġsen hor",
+ "Ġab duct",
+ "ĠBry ant",
+ "V ES",
+ "Ġawak ened",
+ "ĠL az",
+ "rop olis",
+ "ĠLa o",
+ "è¾Ľ èĭ¦",
+ "Ġvill a",
+ "Ġsumm ers",
+ "Ġent hal",
+ "Ġ194 9",
+ "V ia",
+ "Ġìĸ´ì ¨",
+ "Ġtend on",
+ "Ġviol et",
+ "Ġintellect ually",
+ "Ġboun ced",
+ "ara us",
+ "Ġ19 19",
+ "Ġvra ag",
+ "Ġsp el",
+ "ĠSch war",
+ "Sc ott",
+ "ĠInd o",
+ "Ġë§ Ŀ",
+ "Ġcanon ical",
+ "ĠI KE",
+ "Ġthat ÃŃs",
+ "Ġme llan",
+ "æ¯ Ĵ",
+ "ig mat",
+ "C ould",
+ "... ?)",
+ "Ġfo arte",
+ "ĠKum ar",
+ "rend o",
+ "Ġél é",
+ "à ´",
+ "val uation",
+ "c ases",
+ "Ġintuit ively",
+ "h ong",
+ "ett ed",
+ "Ġsou ven",
+ "Ġmor b",
+ "Ġc ors",
+ "ĠN V",
+ "ĠHas an",
+ "æĥħ åĨµ",
+ "ie ved",
+ "Ġì§Ģê¸Ī ìĿĢ",
+ "Ġdum pling",
+ "Ġcontr ôle",
+ "Ġambigu ity",
+ "æ©Ł æľĥ",
+ "Ġco g",
+ "ĠScript ures",
+ "Ġc ai",
+ "Ġbe ver",
+ "大家 éĥ½",
+ "Ġhu is",
+ "Ġa ime",
+ "Ġerkl ären",
+ "ĠL M",
+ "ĠF ey",
+ "éļ ¾",
+ "ற த",
+ "Ġsuper vised",
+ "Ġje we",
+ "s pl",
+ "ĠÑĨенÑĤ ÑĢ",
+ "Ġcoll isions",
+ "ÙĦ Ùģ",
+ "ĠHog warts",
+ "ĠDur ham",
+ "×ķ× £",
+ "Ġphosph ate",
+ "Ġoverse e",
+ "Ġinspect ions",
+ "Ġbr inc",
+ "ĠZ ak",
+ "Ġpay off",
+ "Ġch aud",
+ "ĠHung er",
+ "ã os",
+ "v ir",
+ "Ġf iance",
+ "Ġb oug",
+ "l ived",
+ "c ry",
+ "åĽŀ ä¾Ĩ",
+ "Ġjoint ly",
+ "Ġgirl friends",
+ "ĠNe xus",
+ "¦¬ ê²łìĬµëĭĪëĭ¤",
+ "ĠK wang",
+ "åĵĪ åĽī",
+ "å§ ij",
+ "ÅĤ ÄĻ",
+ "ĠN eden",
+ "ie ce",
+ "Ġins erting",
+ "æŁ ĵ",
+ "ĠM ummy",
+ "ĠGlo be",
+ "Ġle e",
+ "Ġg erman",
+ "Ġcre ams",
+ "ach o",
+ "Ġch Æ°a",
+ "ĠGal ile",
+ "Ġfür s",
+ "Ġest iver",
+ "c idos",
+ "Christ ian",
+ "Ġlors qu",
+ "Ġcut est",
+ "v ale",
+ "ĠкÑĢ еп",
+ "Ġw ary",
+ "Ġslic ing",
+ "Ġesper ando",
+ "ĠV ander",
+ "ĠDe ixa",
+ "Ġ195 4",
+ "Ġmów iÄħ",
+ "Ñĸ ÑĶ",
+ "Ġtool ing",
+ "Ġrest or",
+ "Ġpos ición",
+ "Ġintent ar",
+ "ĠAp ache",
+ "OU L",
+ "ĠÙĪ ب",
+ "Ġmat ière",
+ "ãĥ¼ ãĤĵ",
+ "Ġl inen",
+ "Ġestrat ég",
+ "ĠMut ta",
+ "é¡ ¯",
+ "è¡Į äºĨ",
+ "Ġpart ing",
+ "Ġminim izing",
+ "Ġapp rendre",
+ "æľ Ŀ",
+ "Ġан глий",
+ "ĠDo o",
+ "ĠFire fox",
+ "c ómo",
+ "Ġge opolit",
+ "Ġmak an",
+ "Ġmog elijk",
+ "ĠÏĢε Ïģι",
+ "Ġcá» ©",
+ "Ġinstall er",
+ "Ġdib uj",
+ "ĠHe ath",
+ "lo op",
+ "ĠBro ken",
+ "HY UN",
+ "sh elf",
+ "Ġf izer",
+ "Ġenh ances",
+ "ä¾ĭ ãģĪãģ°",
+ "Ġдо ÑģÑĤи",
+ "ĠP UB",
+ "ĠKolleg in",
+ "Ġatt ained",
+ "Ä ¾",
+ "Ġmist ress",
+ "ĠOft entimes",
+ "×ŀ ×Ļ×Ŀ",
+ "Ġbe we",
+ "ĠS ora",
+ "ra uen",
+ "ba um",
+ "Ġroll ers",
+ "Ġm ering",
+ "ĠP AC",
+ "Ġн Ñĸ",
+ "ĠRép ublique",
+ "ĠÑĤ ÑĢав",
+ "ĠV anguard",
+ "uc iones",
+ "Ġ무ë ĮĢ",
+ "Ġg our",
+ "¯ ¤",
+ "ĠÏ ī",
+ "Ġsa una",
+ "Ġpe ine",
+ "ĠVal erie",
+ "ĠS ikh",
+ "fend imiz",
+ "ber o",
+ "ĠÑĩ и",
+ "Ġdo ÅĽwiad",
+ "ĠE uros",
+ "Ġcomment aires",
+ "Ġtwe aks",
+ "ĠF aster",
+ "ĠÑĢаÑģ к",
+ "Ġprogress ively",
+ "ĠE uch",
+ "bor o",
+ "ĠIng red",
+ "C ap",
+ "Ġun check",
+ "Ġìĺ¤ë ¥¸",
+ "Ġw re",
+ "ĠF T",
+ "ör ung",
+ "Ġmemor ized",
+ "ĠD inner",
+ "ĠP hew",
+ "ou bl",
+ "Ġput a",
+ "Ġadm its",
+ "ез де",
+ "op od",
+ "Ġpand a",
+ "Ġhing es",
+ "ci pe",
+ "Ġtrans act",
+ "Ġpod ia",
+ "Ġp ics",
+ "Ġcriter ion",
+ "ĠOrchest ra",
+ "ĠBl og",
+ "Ġsolem n",
+ "ĠPix ar",
+ "Th ree",
+ "Ġв низ",
+ "ĠVol unte",
+ "ĠSav age",
+ "ĠPV C",
+ "ĠC af",
+ "Ġwy kon",
+ "Ġgrad ers",
+ "Ġcr ouch",
+ "Ġcl iche",
+ "Ġsoy beans",
+ "ĠM UR",
+ "ĠGonz alez",
+ "ĠM imi",
+ "ĠBol sonaro",
+ "Ġdi aphrag",
+ "Ġbil ang",
+ "ëIJĺ ëĬĶ",
+ "éĤ£ æĪijåĢij",
+ "Ġregul ating",
+ "M c",
+ "J udge",
+ "Ġн ож",
+ "Ġjak Äħ",
+ "ites se",
+ "ĠW ij",
+ "Ġl ata",
+ "gro aning",
+ "POS ING",
+ "Ġ×IJ×ķת ×ķ",
+ "Ġha ga",
+ "Ġground ing",
+ "Ġviol ently",
+ "Ġt ills",
+ "Ġeng ag",
+ "ĠHo llow",
+ "Ġпоп ÑĥлÑıÑĢ",
+ "Ġw prowad",
+ "Ġrepl aces",
+ "Ġfluores cent",
+ "urg ical",
+ "igg ly",
+ "ĠTrad itional",
+ "t te",
+ "ĠÙĦ Ùĩ",
+ "Ġphosph orus",
+ "Ġapr on",
+ "ĠWat ers",
+ "ĠK ultur",
+ "ав ай",
+ "Ġol ives",
+ "Ġ×Ķ×IJ× ľ",
+ "Ġteil weise",
+ "Ġsen cill",
+ "Ġprend s",
+ "Ġnarr ower",
+ "Ġj ätte",
+ "ĠInformation en",
+ "ìĥģ ìĿ´",
+ "Ġstar ve",
+ "Ġfr ick",
+ "ĠBe weg",
+ "ठ²",
+ "Ġdolph in",
+ "ĠLAUGH TER",
+ "ĠINTER VIE",
+ "åĶ ī",
+ "Ġyan lÄ±ÅŁ",
+ "Ġtor pedo",
+ "Ġshort ages",
+ "ìĿ´ë ĵľ",
+ "ıld ı",
+ "Ġp aws",
+ "Ġo zone",
+ "Ġcultiv ated",
+ "ĠF ot",
+ "Ġnot or",
+ "н оз",
+ "Ġко ÑĪ",
+ "Ġtouch screen",
+ "ĠAll y",
+ "æľĢ è¿ij",
+ "Ġ맼ìŀĪ ìĸ´ìļĶ",
+ "ĠС еÑĢ",
+ "Ġв полне",
+ "Ġpap rika",
+ "ĠDust in",
+ "Ġefect o",
+ "Ġop ini",
+ "Ġmu ut",
+ "Ġhá»į c",
+ "Ġinter ject",
+ "ÄĻ t",
+ "Ġbut ts",
+ "ure z",
+ "ĠP ike",
+ "ĠH ok",
+ "ĠGu inea",
+ "ĠCath edral",
+ "Ġ14 00",
+ "C ra",
+ "+ ,",
+ "ë§ Ľ",
+ "³´ë ıĦë¡Ŀ",
+ "aby rin",
+ "Ġvide og",
+ "Ġо ÑĢÑĥж",
+ "Ġu ž",
+ "Ġbus cando",
+ "ĠAss istance",
+ "éĻ ½",
+ "Ġmel hores",
+ "ì¡ ´",
+ "Ġëģ ¼",
+ "ĠR J",
+ "Ġت Ùħ",
+ "Ġo min",
+ "Ġmotor cycles",
+ "ĠS app",
+ "Ġsupply ing",
+ "ĠAl gun",
+ "Ġaer ospace",
+ "×¢ ׾",
+ "oc cup",
+ "le ist",
+ "Ġê±° ëĬĶ",
+ "Ġcomplet a",
+ "b res",
+ "! (",
+ "ĠÐŁÑĢ ед",
+ "Ġdisadvant aged",
+ "ĠAtt end",
+ "ĠJud ah",
+ "á»ĭ ch",
+ "yl ene",
+ "act ly",
+ "Ġset ups",
+ "Ġammon ia",
+ "ĠSchwe iz",
+ "ĠSh ame",
+ "Ġband e",
+ "ĠF uel",
+ "Ġtroubles ome",
+ "Ġnum ero",
+ "ĠM OM",
+ "ĠпÑĢед лаг",
+ "ment ioned",
+ "ĠболÑĮÑĪ ое",
+ "ĠVikt or",
+ "ĠSty les",
+ "Ġcruc ified",
+ "ructure d",
+ "en viron",
+ "Ġmor als",
+ "Ġmed itating",
+ "Ġax ial",
+ "is ance",
+ "ĠAb st",
+ "G reen",
+ "Ġê± ´ì",
+ "Ġquad rant",
+ "Ġper gi",
+ "Ġcamer aman",
+ "ĠSe qu",
+ "Ġpa used",
+ "ĠLa ughing",
+ "ê· Ģ",
+ "? ..",
+ "ĠÅ» e",
+ "Ġpermit ir",
+ "Ġdetect ors",
+ "ĠH UD",
+ "av al",
+ "ĠìĹ¬ê¸° ê¹Įì§Ģ",
+ "Ġh ubs",
+ "Ġbest immt",
+ "ĠбÑĥдеÑĤ е",
+ "INTER POSING",
+ "Ġten gan",
+ "Ġcra ve",
+ "ĠBundes regierung",
+ "ĠBlo ody",
+ "Ġus ability",
+ "ĠE as",
+ "ĠÄijá»Ļ ng",
+ "Ġ195 5",
+ "Ġkrie gen",
+ "Ġhabit ual",
+ "Ġessential s",
+ "rim inal",
+ "Ġroomm ates",
+ "éĤ£ å°±",
+ "ĠпеÑĢе Ñħод",
+ "Ġng hi",
+ "Ġmen ing",
+ "ĠSym phony",
+ "ĠH ug",
+ "ag gi",
+ "Ġw ied",
+ "Ġmit ad",
+ "ãģ£ãģ¦ ãģĦãģĨ",
+ "te enth",
+ "ida Äĩ",
+ "S ave",
+ "Ġrob iÄĩ",
+ "Ġboun ces",
+ "° ĸìĹIJ",
+ "st ars",
+ "Ġprag matic",
+ "Ġcogn ition",
+ "Ġwra pper",
+ "Ġw arten",
+ "ad h",
+ "Ġpens a",
+ "ĠHert z",
+ "Ġn ÄĽ",
+ "ĠRe id",
+ "ĠPC s",
+ "ĠMo le",
+ "Ġ.. ...",
+ "Ġpre cio",
+ "ĠChampions hips",
+ "ê°Ģë Ŀ½",
+ "Ġv ér",
+ "Ġcorrid ors",
+ "ĠElect ronic",
+ "S l",
+ "Ġа ле",
+ "Ġoverth row",
+ "Ġk abul",
+ "ĠR ES",
+ "ĠCyber punk",
+ "ог од",
+ "ĠÐĿ ав",
+ "Ġw an",
+ "Ġmanifest ations",
+ "Ġcual es",
+ "ĠW ise",
+ "ĠLös ung",
+ "Ġex fol",
+ "Ġearn s",
+ "ÑĥÑģÑĤ иÑĤÑĮ",
+ "Ġsa pp",
+ "ĠBra un",
+ "ĠBRAND ON",
+ "ì¹ Ļ",
+ "Ġs ano",
+ "ĠF EL",
+ "Ñĭв айÑĤеÑģÑĮ",
+ "ожд ениÑı",
+ "Ġse wn",
+ "F un",
+ "Ġrecipro cal",
+ "Ġexpans ive",
+ "ĠTra ffic",
+ "Ġktóre go",
+ "ĠÙĪ س",
+ "æĺ ¥",
+ "Ġë¹ ¨",
+ "pro ve",
+ "ig are",
+ "Ġlo h",
+ "Ø§Ø ¶",
+ "H ope",
+ "Ġdevote es",
+ "ĠG om",
+ "Ġste als",
+ "ĠU ms",
+ "ĠTw ice",
+ "ãĤ ²",
+ "iy im",
+ "Ġrhythm ic",
+ "ĠV orte",
+ "Ġpref ix",
+ "om ination",
+ "Ġdat o",
+ "Ġcust ard",
+ "ĠVO ICE",
+ "å· ŀ",
+ "Ġmen y",
+ "ist ors",
+ "Ġíĺ ij",
+ "ĠìĤ´ì ķĦ",
+ "Ġíĥ Ħ",
+ "Ġk ort",
+ "Ġab a",
+ "ĠV era",
+ "ep y",
+ "Ġì¹´ë©Ķë Ŀ¼",
+ "Ġsubmer ged",
+ "ĠC lock",
+ "Ġthumbna ils",
+ "Ġbo ast",
+ "ĠF are",
+ "!! ]",
+ "ĠÅĽ m",
+ "Ġkaik ki",
+ "ĠTechn ologies",
+ "ìĻ ¸",
+ "ãĥ Ĵ",
+ "иÑĤ ай",
+ "å°ı æĻĤ",
+ "Ġа ÑĤ",
+ "Ġkn obs",
+ "Ġre icht",
+ "ượ ng",
+ "gl io",
+ "Ġ맼 ìĿ´",
+ "ê°IJ ìĿĦ",
+ "Ġjot ka",
+ "ĠHand y",
+ "ĠHab en",
+ "n ous",
+ "Ġin land",
+ "Ġam azon",
+ "ho oting",
+ "S L",
+ "Ġle isten",
+ "~ \"",
+ "Ġprov oke",
+ "ĠTw ist",
+ "Ġ×ij× Ĺ",
+ "Ġdepart ed",
+ "ê° ľë¥¼",
+ "Ġk onse",
+ "ĠCar wyn",
+ "íķĺ ìĭł",
+ "ident al",
+ "ES CO",
+ "Ġt teokbokki",
+ "Ġdiz endo",
+ "ç· ´",
+ "ınd aki",
+ "imas u",
+ "af ar",
+ "Ġland fill",
+ "Ġcorrect ing",
+ "Ġcle ars",
+ "ĠNum mer",
+ "H AM",
+ "Ġcart ridges",
+ "ĠDies el",
+ "p aced",
+ "Ġobl iv",
+ "Ġmoy ens",
+ "ĠSin ne",
+ "ĠPre is",
+ "il iz",
+ "ĠÑģм ож",
+ "Ġbroad en",
+ "ä»ĸ æĺ¯",
+ "x es",
+ "Ġcarbohyd rate",
+ "íĺ ¹",
+ "se ok",
+ "Ġecho es",
+ "Ġc ess",
+ "ë° Ķ",
+ "Ġб изнеÑģ",
+ "Ġllam ado",
+ "Ġess ent",
+ "ĠìĿ¼ë °ĺ",
+ "ĠA ires",
+ "ph en",
+ "Ġze bra",
+ "Ġsymbol ism",
+ "On ce",
+ "Ġr acks",
+ "ĠKaf ka",
+ "ĠÑģеÑĢÑĮ ез",
+ "Ġsin n",
+ "p icious",
+ "ka a",
+ "Ġmotherf ucker",
+ "Ġapprentices hip",
+ "Ġr pm",
+ "Ġtax ation",
+ "Ġfur ry",
+ "ĠSac red",
+ "ĠÑĢаз м",
+ "por a",
+ "eng es",
+ "ĠíĹ Īë",
+ "ĠÑģ ин",
+ "Ġsanit izer",
+ "Ġcr inge",
+ "ĠS ca",
+ "оÑĩ но",
+ "Ġof ere",
+ "Ġmel odies",
+ "ĠVel vet",
+ "ĠIhr er",
+ "ĠHy brid",
+ "ĠG iov",
+ "Ġirgend was",
+ "Ġdep ende",
+ "ĠUs ers",
+ "Ġh ump",
+ "dri ving",
+ "Ġs f",
+ "Ġruth less",
+ "à¹ĢภĦ",
+ "Ġlem ons",
+ "Ġfö ret",
+ "ĠO j",
+ "Ġм ама",
+ "Ġinter personal",
+ "Ġge v",
+ "Ġab norm",
+ "иÑģ л",
+ "Ġин д",
+ "Ġkont roll",
+ "Ġreg res",
+ "Ġled ge",
+ "Ġerzäh lt",
+ "ĠT act",
+ "Ġarri vé",
+ "Ġsubstant ive",
+ "Ġspoon ful",
+ "zw ischen",
+ "oooo o",
+ "Ġconten ido",
+ "Ġbes l",
+ "á»ĥ m",
+ "k ten",
+ "Jam ie",
+ "Ġsand y",
+ "ä¸į åIJĮ",
+ "â ĭ",
+ "Ġp ase",
+ "Ġdet te",
+ "ĠBelg ian",
+ "ê° ľë",
+ "ula res",
+ "r ud",
+ "ig or",
+ "ĠíĮ ¬ë",
+ "Ġremed ies",
+ "Ġblast ing",
+ "ĠS ich",
+ "Ġож ид",
+ "Ġmon str",
+ "Ġmanif old",
+ "Ġglaub en",
+ "ĠE ST",
+ "Ġstream line",
+ "Ġlobb ying",
+ "ĠGoth ic",
+ "to ire",
+ ".. '",
+ "Ġdém ocr",
+ "Ġнаб лÑİд",
+ "Ġwsp ól",
+ "ĠczÄĻ ÅĽÄĩ",
+ "ä¸ĭ éĿ¢",
+ "is és",
+ "g angen",
+ "Ġbez pie",
+ "rem lin",
+ "ê° Ŀ",
+ "St ill",
+ "Ġres ides",
+ "Ġgele cek",
+ "Ġtélé phone",
+ "Ġpe wn",
+ "Ġle opard",
+ "Ġcompliment ary",
+ "Ġc rib",
+ "ĠAnim als",
+ "Ġge il",
+ "ess el",
+ "Ġgard er",
+ "Ġcatch y",
+ "æ¨ ¹",
+ "ĠE ts",
+ "ĠCom mercial",
+ "ĠD ENNIS",
+ "ĠCoordin ator",
+ "ĠAb igail",
+ "ffff ff",
+ "ấ p",
+ "Ġpeque ña",
+ "Ġinject ions",
+ "ce kt",
+ "Ġphilanthrop y",
+ "Ġp uck",
+ "Ġcelebr ates",
+ "ĠD unk",
+ "ĠD latego",
+ "ãģ¾ ãģł",
+ "δ ή",
+ "grad uate",
+ "ĠM obil",
+ "t ill",
+ "ac am",
+ "Ġyol ks",
+ "Ġtang led",
+ "Ġman iac",
+ "Ġoblig ed",
+ "ĠLa ink",
+ "Ġver der",
+ "ĠDam on",
+ "Ġmut ant",
+ "Ġhop ping",
+ "Ġre ins",
+ "Ġinver ter",
+ "Ġcont empt",
+ "׳ ס",
+ "le arning",
+ "M iss",
+ "ĠÐĵ оÑģ",
+ "ĠMe yer",
+ "ê»ĺ ìĦľ",
+ "é£ İ",
+ "×ķ׳ ×Ļ×Ŀ",
+ "ask ing",
+ "Ġtrim ming",
+ "Ġtre asury",
+ "Ġs ente",
+ "A ust",
+ "ĠUnterstüt zung",
+ "ĠCom edy",
+ "ĠAn akin",
+ "é ¹",
+ "ÑĢÑĥ ÑĤ",
+ "ĠH ari",
+ "ograph ers",
+ "Ġoat meal",
+ "ĠB ots",
+ "ä¸į äºĨ",
+ "Ġп алÑĮ",
+ "Ġacknowledge ment",
+ "x ic",
+ "Ġê´Ģ ìĭ¬",
+ "gas ping",
+ "Ġãģ ķ",
+ "Ġterr ace",
+ "Ġor naments",
+ "ĠM ER",
+ "comm ittee",
+ "ĠìĹĨ ìĬµëĭĪëĭ¤",
+ "Ġr ij",
+ "é ³",
+ "צ ×Ŀ",
+ "le me",
+ "Ġlibert ies",
+ "Ġfell as",
+ "ĠCop per",
+ "ben ch",
+ "ĠIde a",
+ "á»į n",
+ "ÑĪ а",
+ "Ġvers ión",
+ "ÏĦο Ïį",
+ "ĠÐľ и",
+ "ĠпÑĢил ож",
+ "Ġbox er",
+ "ĠT anner",
+ "ĠM oy",
+ "ì¹ĺ ëĬĶ",
+ "T hr",
+ "Ġtin ham",
+ "Ġpol ishing",
+ "Ġconsequ ently",
+ "Ġamen ities",
+ "ĠK I",
+ "ĠGRE EN",
+ "ĠFrank ie",
+ "н иÑĤ",
+ "itt el",
+ "Ñģ кое",
+ "urs ed",
+ "Ġup bringing",
+ "Ġth ứ",
+ "ĠìĭĿ ìľ¼ë¡ľ",
+ "Ġwh im",
+ "Ġchin ese",
+ "conf idence",
+ "ĠJ eder",
+ "ãģª ãģ®ãģ§",
+ "aj cie",
+ "ĠT ous",
+ "ĠPow ers",
+ "ừ a",
+ "other mal",
+ "ĠвÑĭ ÑĪе",
+ "r ale",
+ "Ø§Ø ®",
+ "Ġì§Ģ ìĽIJ",
+ "Ġép isode",
+ "Ġsul ph",
+ "Ġenc ara",
+ "k raft",
+ "alar ı",
+ "ĠCom es",
+ "Ġdiv ul",
+ "ĠRud olph",
+ "ĠM use",
+ "Ġut ens",
+ "ĠìŀIJ 주",
+ "Ġp ana",
+ "ĠVeget a",
+ "ĠPH P",
+ "ĠN SA",
+ "ent in",
+ "ĠCarne gie",
+ "ا ÙĬ",
+ "iÄĻ cy",
+ "H arry",
+ "Ġf ır",
+ "С п",
+ "Ġglad ly",
+ "Ġaver aging",
+ "íķĺ ê²łìĬµëĭĪëĭ¤",
+ "лÑı ÑİÑĤÑģÑı",
+ "ĠÐľ енÑı",
+ "Ġquot ation",
+ "ri res",
+ "itch ens",
+ "ay ed",
+ "Ġun att",
+ "ĠP erez",
+ "ĠоÑĤ меÑĤ",
+ "Ġtact ile",
+ "ĠEu h",
+ "is ini",
+ "b uh",
+ "Ġhat ır",
+ "ĠìŀĪ ìľ¼",
+ "Ġpolicy makers",
+ "³´ì Ħ¸ìļĶ",
+ "ac ı",
+ "Ġκ ι",
+ "Ġregister ing",
+ "re to",
+ "ĠSpr inkle",
+ "ĠGram my",
+ "ax ter",
+ "Ġб и",
+ "Ġsit ter",
+ "Ġpred ic",
+ "Ġthin ly",
+ "Ġstr um",
+ "Ġag grav",
+ "Ġa ha",
+ "ر ج",
+ "m ellow",
+ "Ġconst ante",
+ "ĠL aut",
+ "ist on",
+ "Ġtransition ed",
+ "ĠCamb odia",
+ "ãģĦ ãģįãģ¾ãģĻ",
+ "è·Ł 大家",
+ "art ed",
+ "Ġmis f",
+ "ĠPunk te",
+ "Įë ĵł",
+ "Ġtremb ling",
+ "Ġges pannt",
+ "ĠعÙĦÙĬ Ùĩ",
+ "Ġникак иÑħ",
+ "Ġë¶Ģë ĵľë",
+ "ĠÑĢазв иÑĤ",
+ "Ġit chy",
+ "Ġc iento",
+ "Ġpl ains",
+ "Ġk ittens",
+ "Ġback log",
+ "ĠPres iding",
+ "pt a",
+ "Ġha voc",
+ "ĠDarr in",
+ "ĠÐĽÑİ Ð±",
+ "Ġsegreg ated",
+ "Ġg hetto",
+ "Ġerle bt",
+ "Ġdrug iej",
+ "ĠSi xt",
+ "åı ĥ",
+ "ร ะ",
+ "uen cia",
+ "Ġíķĺ 기",
+ "ĠëĨ į",
+ "Ġrob i",
+ "Ġpione ers",
+ "Ġmilli ards",
+ "ĠWitch er",
+ "Ġ무ìĹ ĩ",
+ "or ro",
+ "m ass",
+ "Ġdiver gence",
+ "ĠRiver a",
+ "ĠNo odles",
+ "Ġend roit",
+ "ĠK osten",
+ "ĠдÑĢÑĥг а",
+ "ĠmÃŃn imo",
+ "ĠKazakh stan",
+ "ت Ùĩ",
+ "Ġвоз дÑĥ",
+ "Ġgesch rieben",
+ "ĠN il",
+ "Ñģ ки",
+ "ĠFr üh",
+ "Ġbever ages",
+ "æº IJ",
+ "ĠG on",
+ "æĺ ¨",
+ "Ar in",
+ "ĠInt ro",
+ "ocaly ptic",
+ "Ġexhaust ion",
+ "ĠStat us",
+ "ĠBatter y",
+ "és z",
+ "£ ¼ë",
+ "air y",
+ "Ġë³´ìŬë ĵľë",
+ "Ġdispar ity",
+ "Ù Į",
+ "ĠTuc son",
+ "Ġbright ly",
+ "pro blem",
+ "Ġbiom ass",
+ "éĻ į",
+ "§ ī",
+ "Ġhur dle",
+ "Ġwavelength s",
+ "Ġ< <",
+ "Ġteam ed",
+ "FF FF",
+ "ĠS lim",
+ "om ial",
+ "Ġunve iled",
+ "ĠVere in",
+ "ÙĤ Ø·",
+ "est ry",
+ "Ġcl ás",
+ "Ġch eddar",
+ "Ġaccus ing",
+ "ĠScient ific",
+ "ĠбÑĥд е",
+ "ĠCyr us",
+ "ε ÏĦε",
+ "Ĩĵ ê³ł",
+ "Ġë³ Ħ",
+ "Ġcur d",
+ "Ġrefer rals",
+ "sh ift",
+ "åį ķ",
+ "nik ów",
+ "Ġm ier",
+ "Ġconf ronting",
+ "ê²ĥ ëıĦ",
+ "aw l",
+ "Ġtry in",
+ "Ġê·¸ëŀĺ ìļĶ",
+ "Ġch iar",
+ "Ġìĺ¤ëĬ ĺëıĦ",
+ "æĶ¿ æ²»",
+ "es que",
+ "Ġmism os",
+ "ĠSh ak",
+ "Ġsoci aux",
+ "Ġpi ÅŁ",
+ "ĠkiÅŁ i",
+ "Ġcy an",
+ "h ay",
+ "be w",
+ "b od",
+ "ĠÎ ¹",
+ "ĠMain ly",
+ "Ñİ ÑĤÑĮ",
+ "hab itude",
+ "ĠÑģп окой",
+ "è·Ł æĪij",
+ "Ġpre con",
+ "ĠM andy",
+ "ðŁ¤ £",
+ "ill os",
+ "Ġgr upp",
+ "Ġcr umble",
+ "Ġconstru ctor",
+ "erv ices",
+ "Ġlight house",
+ "ĠCon cept",
+ "ан ÑĤи",
+ "alt ro",
+ "h ope",
+ "ĠAll eg",
+ "ìĸ´ë ¥¼",
+ "pie ces",
+ "oun ter",
+ "Ġíķĺ ëĭĪê¹Į",
+ "ĠìĿ¸ íĦ°ë",
+ "Ġvérit able",
+ "Ġthread ed",
+ "bl ind",
+ "Ĥĺë Ŀ¼",
+ "Ġtr ays",
+ "ĠEd ison",
+ "ĠÃĸ z",
+ "ĠSte vie",
+ "Ġl ender",
+ "Ġbrig ade",
+ "Ġdeuts che",
+ "m uffled",
+ "b art",
+ "Ġinsan ity",
+ "Ġsav vy",
+ "Ġsens ational",
+ "Ġdere chos",
+ "ĠM X",
+ "ĠпÑĢ еп",
+ "Ġthreat ens",
+ "Ġrealt Ãł",
+ "Ġindic ative",
+ "Ġch ops",
+ "Ġbenef iting",
+ "ĠVern on",
+ "ĠSt rand",
+ "n un",
+ "qu ently",
+ "10 1",
+ "Ġe el",
+ "ìĪ Ļ",
+ "r ints",
+ "ĠÙħ س",
+ "Ġب د",
+ "Ġпо ÑģÑĤÑĢо",
+ "Ġyap mÄ±ÅŁ",
+ "Ġol ması",
+ "Ġi edereen",
+ "ol é",
+ "ke f",
+ "Ġë°ľ ìĥĿ",
+ "Ġr ained",
+ "Ġalm ighty",
+ "ĠвÑĭ д",
+ "ĠC PR",
+ "F re",
+ "Ġinhab ited",
+ "Ġarb ets",
+ "Ġa kin",
+ "а ÑģÑĤв",
+ "v ania",
+ "Ġhäuf ig",
+ "ĠMat te",
+ "s orry",
+ "Jen ny",
+ "ĠгÑĢ ад",
+ "Ġwh it",
+ "Ġbro kers",
+ "å¯ Ł",
+ "Ġh ine",
+ "ast en",
+ "Ġг ÑĢÑĥ",
+ "M B",
+ "ĠP RI",
+ "S ab",
+ "Ġwrest ler",
+ "Ġfacil itating",
+ "Ġeh kä",
+ "ĠC red",
+ "Ġ12 7",
+ "Ġnot hin",
+ "Ġmand ated",
+ "å¯ Į",
+ "ÑĥÑĤ ÑģÑĤв",
+ "F rank",
+ "Ġwor s",
+ "Ġdzie ÅĦ",
+ "ĠUnder ground",
+ "Ġznaj du",
+ "ĠB ä",
+ "ĠPrin zip",
+ "аÑĤ елей",
+ "Ġveter inar",
+ "Ġsplend id",
+ "Ġroz p",
+ "Ġpsych opath",
+ "ig on",
+ "Ġh ops",
+ "Ġc ần",
+ "ĠX ian",
+ "Ġtro isième",
+ "Ġproduct o",
+ "ĠdeÄŁ er",
+ "ĠContin uing",
+ "ив ал",
+ "c ık",
+ "Ġmoistur izer",
+ "Wh ite",
+ "Ġsi is",
+ "ĠEver est",
+ "ien ced",
+ "Ġcả m",
+ "ĠJ apon",
+ "´ìł Ħ",
+ "Ġten ÃŃan",
+ "Ġenc anta",
+ "M m",
+ "Ġdrop down",
+ "ĠI ya",
+ "³´ë ©´",
+ "Ġword ing",
+ "ĠSque eze",
+ "ĠMap le",
+ "Ġclar ified",
+ "ĠMun icip",
+ "ĠRou ge",
+ "ĠNick i",
+ "ĠGo o",
+ "v olt",
+ "t ek",
+ "fect ure",
+ "f red",
+ "ar rive",
+ "ãĥ¼ ãģĦ",
+ "te z",
+ "E p",
+ "Ġob ras",
+ "ĠV ID",
+ "ĠR iv",
+ "ĠMod i",
+ "i be",
+ "Ġacontec endo",
+ "Ġim itation",
+ "Ġcamoufl age",
+ "Ġspan ning",
+ "ĠSEC RET",
+ "ĠOre o",
+ "ìĨĮë ¦¬",
+ "Ġh unch",
+ "Ġca ÅĤe",
+ "Ġspont aneously",
+ "ĠPer d",
+ "Ġet ap",
+ "ĠHo le",
+ "ĠDis ability",
+ "Ġafter life",
+ "æģ ©",
+ "Ġtest ified",
+ "Ġpres up",
+ "Ġpet roleum",
+ "Ġcontr ario",
+ "ĠAss essment",
+ "ÄŁ lu",
+ "Ġp ests",
+ "Ġdil ig",
+ "ĠвÑģÑĤÑĢ еÑĤ",
+ "Ġcons équ",
+ "Ġcann ons",
+ "Ġcan oe",
+ "ĠM ile",
+ "Ġcit oy",
+ "Ġbe gged",
+ "ĠMin nie",
+ "ÅĤy ch",
+ "Ġprinci pe",
+ "ÏĢÏĮ ν",
+ "m niej",
+ "Ġw ert",
+ "Ġëĭ¤ë ĵ¤",
+ "an se",
+ "Ġunc les",
+ "Ġprovoc ative",
+ "Ġinter sections",
+ "Ġdemocr ats",
+ "ĠJul ius",
+ "ин ки",
+ "yg usal",
+ "Ġ׾ ×ķ",
+ "Ġgj orde",
+ "Ġg asket",
+ "ĠB ock",
+ "ĠÄ° n",
+ "b reat",
+ "ĠEqu ity",
+ "ard ı",
+ "Ġкан але",
+ "Ġд ней",
+ "Ġt Ỽi",
+ "Ġfi xture",
+ "Ġab uses",
+ "Ġv aya",
+ "Ġou vert",
+ "Ġmultic ultural",
+ "Ġcontext o",
+ "ĠSes ame",
+ "Ġdé pl",
+ "Ġcons omm",
+ "ĠPart e",
+ "Ġp em",
+ "ĠCon an",
+ "Ġб ÑĸлÑĮ",
+ "Ġpersu aded",
+ "Ġdra ins",
+ "M oo",
+ "F ORE",
+ "Ġб аÑĤ",
+ "Ġf od",
+ "ĠProduct s",
+ "ì§Ħ ì§ľ",
+ "Ġ\" [",
+ "ĠW ick",
+ "ĠNar uto",
+ "н али",
+ "ry w",
+ "Ġl odge",
+ "Ġin h",
+ "Ġvont ade",
+ "Ġdi j",
+ "ĠJes ús",
+ "Look ing",
+ "Ġfore arm",
+ "ĠIntegr ation",
+ "ĠHARR IS",
+ "Ġtool bar",
+ "le ader",
+ "Ġsel dom",
+ "Ġб ÑĢоÑģ",
+ "ĠK ook",
+ "он д",
+ "Ġmon opol",
+ "Ġmill et",
+ "Ġl ira",
+ "ĠAs ians",
+ "Ġ18 90",
+ "ci ÄŁim",
+ "Ġed en",
+ "ĠIKE A",
+ "ĠNeigh bor",
+ "ĠKazu ya",
+ "ü d",
+ "Ġpsych edel",
+ "Ġenvision ed",
+ "åĿ Ĺ",
+ "Ġï· »",
+ "Ġw under",
+ "ĠBulgar ia",
+ "B rid",
+ "Ġmar row",
+ "Ġdep iction",
+ "ĠT in",
+ "ĠPhar ise",
+ "Ġeinz ige",
+ "Ġblind ly",
+ "ãģĽ ãģ¦",
+ "Ġdef ens",
+ "D ire",
+ "Ġvibr ating",
+ "Ġtroll s",
+ "Ġdisrespect ful",
+ "Ġw od",
+ "Ġstimul i",
+ "Ġcreep ing",
+ "Ġcla irement",
+ "Ġsc ariest",
+ "Ġdécouv rir",
+ "Ġ10 4",
+ "ĠвеÑĢ Ñħ",
+ "ĠÅĤ at",
+ "Ġróż ne",
+ "Ġbar ley",
+ "ĠRe pl",
+ "ĠT we",
+ "k ke",
+ "ĠãģĿ ãĤĮ",
+ "ĠRed mi",
+ "ĠMet roid",
+ "Ġή ÏĦαν",
+ "Che ck",
+ "ĠS EN",
+ "Ġ ido",
+ "ÑĤоÑĢ ии",
+ "ó p",
+ "UN KNOWN",
+ "Ġänd ern",
+ "ĠJu ice",
+ "ĠGes icht",
+ "å°± æľĥ",
+ "ĠнаÑģÑĤ олÑĮко",
+ "íĥ ķ",
+ "Â Ń",
+ "ex hales",
+ "Ġì´ ī",
+ "Ġj sem",
+ "ÏĢ ÏīÏĤ",
+ "Ġit t",
+ "ëªħ ìĿ´",
+ "Ġrem ix",
+ "Ġbloss oms",
+ "ĠR enee",
+ "is ations",
+ "ìĬ¤í Ħ°",
+ "Ġë³´ ìĿ´ëĬĶ",
+ "uest as",
+ "op edia",
+ "ĠA im",
+ "ìĿ´ì¦ Ī",
+ "sc ene",
+ "Ġleak age",
+ "uck t",
+ "S ad",
+ "A sk",
+ "Ġsusp ense",
+ "Ġimp ost",
+ "ĠStrateg ic",
+ "ĠIt ÃŃs",
+ "âĢ Į",
+ "Ġkey boards",
+ "Ġam using",
+ "og r",
+ "id erman",
+ "ŀ ĸ",
+ "Ġв ижÑĥ",
+ "Ġd ips",
+ "Ġapolog ized",
+ "ĠST AR",
+ "Ġesc uela",
+ "ĠC hing",
+ "н ениÑı",
+ "Ġë¶Ģë¶Ħ ìĿ´",
+ "ĠFle et",
+ "Ġs amb",
+ "Ġentsprech end",
+ "Ġelectrod es",
+ "ĠFrei heit",
+ "æĪij ä¸įçŁ¥éģĵ",
+ "ĠSh rim",
+ "iÃŁ e",
+ "Ġselect ions",
+ "Ġfor di",
+ "Ġd oss",
+ "Ñı Ñĩ",
+ "Ġdiscrimin ate",
+ "ĠAu ÃŁerdem",
+ "Ġdesenvol v",
+ "ĠIntern al",
+ "ĠBened ict",
+ "å¯ Ĩ",
+ "ĠSh iv",
+ "M issy",
+ "Ġоб наÑĢÑĥж",
+ "Ġна ÑģÑĤÑĢо",
+ "Ġcontrol ar",
+ "ĠL ia",
+ "Ġopio ids",
+ "ant u",
+ "Ġcup board",
+ "æģ IJ",
+ "г е",
+ "acht s",
+ "Ġcur ated",
+ "Ġx em",
+ "Ġwe ary",
+ "Ġbre thren",
+ "Ġbudget ing",
+ "Ġpour tant",
+ "éļ »",
+ "ais ia",
+ "ĠоÑĤв еÑĩ",
+ "ĠG IS",
+ "μ αι",
+ "Ġש×Ķ ×ķ×IJ",
+ "Ġsa ud",
+ "Ġl Ỽ",
+ "Ðķ Т",
+ "ub ine",
+ "ĠнÑĥж ен",
+ "Ġkidna pping",
+ "Ġbr at",
+ "ĠTer re",
+ "ĠMon et",
+ "Ġë§Ī ìĬ¤íģ",
+ "Ġflash y",
+ "ĠIS BN",
+ "Ġfreel ance",
+ "i age",
+ "Ġjun ge",
+ "ì¶ ©",
+ "cer al",
+ "ĠÑĤоÑĩ ки",
+ "Ġform ulate",
+ "ĠF ER",
+ "ĠDart mouth",
+ "ìľ¼ë ©´ìĦľ",
+ "å¢ ĥ",
+ "ow iÄħ",
+ "ĠëĶĶ ìŀIJ",
+ "Ġreg iment",
+ "Ġmetabol ismo",
+ "ĠP arr",
+ "Ġ충 ë¶Ħ",
+ "Ġsan ity",
+ "ĠL al",
+ "ĠG ö",
+ "ĠG la",
+ "Ġprot o",
+ "Ġmicroscop ic",
+ "Ġk ang",
+ "ĠSc alia",
+ "Ġp ug",
+ "ĠSc ore",
+ "ĠSav annah",
+ "Ġgard e",
+ "ĠN OR",
+ "å°į åIJ§",
+ "Ġsche int",
+ "Ġp óÅĤ",
+ "Ġcor ri",
+ "Ġbr ute",
+ "Ġ ÅĤad",
+ "ä»ĸ 们",
+ "Ġsucceed ing",
+ "Ġbicy cles",
+ "N on",
+ "Ġseek ers",
+ "Ġuncond itional",
+ "Ġrhy mes",
+ "ĠGar age",
+ "Ġinv oice",
+ "Ġcan vi",
+ "ne ck",
+ "Ġcustom izable",
+ "irit ual",
+ "Que en",
+ "íķĺ ìĭľëĬĶ",
+ "Ġpower less",
+ "Ġcs ak",
+ "ä¸į ä¼ļ",
+ "is oft",
+ "Ġìłķ íĻķ",
+ "Ġnh ân",
+ "ĠM AND",
+ "ĠH af",
+ "Ġrevol ves",
+ "ä¹Ł åı¯ä»¥",
+ "ov an",
+ "ar oo",
+ "ĠGr ind",
+ "éĽ ª",
+ "Ġindispens able",
+ "Ġconsult ed",
+ "ĠClin ical",
+ "A cc",
+ "Ġol hos",
+ "Ġmon ter",
+ "ĠH ana",
+ "et ah",
+ "Ġva an",
+ "Ġt igers",
+ "Ġcau cus",
+ "ðŁĺ Ĥ",
+ "³´ì ŀIJ",
+ "pow ers",
+ "ium s",
+ "ĠíĨ łë",
+ "Ġtrad icional",
+ "Ġreson ated",
+ "Ġìĭł 기",
+ "th em",
+ "Ro bert",
+ "Ġelement o",
+ "Ġant id",
+ "Ġоб Ñģ",
+ "Ġnat ives",
+ "Ġlo ca",
+ "ow ment",
+ "ĠT ight",
+ "Ġ æĢĿ",
+ "Ġmel an",
+ "ĠN ue",
+ "am is",
+ "Ġsor gen",
+ "as ına",
+ "H ome",
+ "ĠPUB G",
+ "Ġaw fully",
+ "ĠSh ore",
+ "ĠPer ché",
+ "ĠL au",
+ "ĠCind erella",
+ "ĠCh est",
+ "Ġsem antic",
+ "Ġdesert ed",
+ "ĠMom o",
+ "ĠHern andez",
+ "gen es",
+ "ĠAd ult",
+ "иÑĩеÑģ кого",
+ "osh ima",
+ "ĠcaracterÃŃst icas",
+ "ĠK L",
+ "´ìŀ ¥",
+ "oc ar",
+ "Ġfeh lt",
+ "Ġd ruk",
+ "ĠPop py",
+ "EN GLISH",
+ "ĠVerg leich",
+ "B rien",
+ "Ġrec omp",
+ "ĠÑģ д",
+ "Ġmer ger",
+ "Ġmarket ers",
+ "Ġhoney moon",
+ "Ġpen so",
+ "Ġbell i",
+ "еÑĤ Ñĥ",
+ "Ġbank er",
+ "Cam era",
+ "ĠSt all",
+ "ĠSt amp",
+ "ĠB ite",
+ "еж де",
+ "Ġs ür",
+ "Ġgü ç",
+ "ĠPas sover",
+ "ĠBug ün",
+ "ĠÑģожал ениÑİ",
+ "Ġн из",
+ "Ġman ure",
+ "Ġglac ier",
+ "è« ĩ",
+ "RA Y",
+ "ter ror",
+ "Ġsal ads",
+ "Ġhur ricanes",
+ "ĠDesign er",
+ "ator io",
+ "Ġfact ual",
+ "ĠTam my",
+ "Ġзв ÑĥÑĩ",
+ "Ġintrodu ctions",
+ "Ġhouse keeping",
+ "Ġh anger",
+ "ëĭ ĺë",
+ "ak te",
+ "ĠCol a",
+ "' ]",
+ "ĠG ender",
+ "оÑĢ он",
+ "ip se",
+ "ic ias",
+ "Ġsuccess ive",
+ "Ġpolit ic",
+ "Ġhö her",
+ "ĠQ iao",
+ "ĠG imme",
+ "Ġл ож",
+ "Ġse b",
+ "ĠWe iter",
+ "ĠSak ura",
+ "ĠB oulder",
+ "ĠAm érica",
+ "peÅĤ nie",
+ "Ġtecn ologÃŃa",
+ "ish ops",
+ "f ur",
+ "Ġmoon light",
+ "Ġdispers ed",
+ "Ġre z",
+ "ен ное",
+ "алÑĮ нÑĥÑİ",
+ "ĠTw elve",
+ "ĠH OR",
+ "ìĭ¤í ŀĪ",
+ "il age",
+ "Ġshad ed",
+ "Ġres umes",
+ "ĠPe anut",
+ "ĠM ILL",
+ "ap ons",
+ "ĠU FC",
+ "ĠSo le",
+ "Ġjoy stick",
+ "ĠOliv ier",
+ "war ming",
+ "Ġsyll abus",
+ "Ġоб Ñīе",
+ "Ġhi á»ĩn",
+ "Ġfest a",
+ "Ġcr adle",
+ "ĠZ ac",
+ "Ġremem brance",
+ "Ġê°Ļ ìķĦìĦľ",
+ "ĠpiÄĻ k",
+ "Ġco exist",
+ "ĠV II",
+ "Ġá reas",
+ "Ġu waż",
+ "Ġobser vers",
+ "Ġmännisk or",
+ "co on",
+ "ĠD AM",
+ "Ġnas zym",
+ "Ġall igator",
+ "ĠFree ze",
+ "ĠEst ate",
+ "ĠÑĤÑĢ ади",
+ "Ġunder cover",
+ "Ġn ies",
+ "ĠFeh ler",
+ "pl in",
+ "ĠK abul",
+ "il ate",
+ "Ġê³ł ìĸij",
+ "Ġm op",
+ "ìĦ ¼",
+ "Ġand erer",
+ "ĠK ELL",
+ "ок и",
+ "Ġж еÑģÑĤ",
+ "Ġgra zing",
+ "Ġda ÃŃ",
+ "Ġcapital ize",
+ "Ġa pex",
+ "Ġnurt uring",
+ "Ġcort ar",
+ "Ġcontr ac",
+ "ımız ı",
+ "Ġtand em",
+ "éĥ½ æľī",
+ "ge ment",
+ "ĠÑģиÑģÑĤем а",
+ "Ġman que",
+ "ia jÄħ",
+ "W OR",
+ "Ġا ب",
+ "Ġcart s",
+ "AN O",
+ "Ġë°Ľ ê³ł",
+ "ĠC ena",
+ "ĠBi ology",
+ "id ar",
+ "Ġa ż",
+ "er ne",
+ "an u",
+ "Ġthank ed",
+ "Ġsubmar ines",
+ "Ġman ic",
+ "Ġм оз",
+ "ä¼ Ĭ",
+ "inst ant",
+ "ess ential",
+ "Ġsam urai",
+ "Ġpast i",
+ "Ġal an",
+ "Ġbro ch",
+ "Ġb aker",
+ "ĠGu ill",
+ "¨ ¼",
+ "Ġwithd rawn",
+ "ëĭ Ŀ",
+ "Per fect",
+ "qu ency",
+ "Ġstream lined",
+ "Ġ13 00",
+ "´ë ıĦ",
+ "Ġëĸ łë",
+ "Ġãģ¯ ãģĦ",
+ "Ġh vad",
+ "ä¸Ģå®ļ è¦ģ",
+ "Ġverb ally",
+ "ĠK ons",
+ "Ġì¡° ìĭ¬",
+ "Ġdie z",
+ "æİ° æİ°",
+ "Ġchuck ling",
+ "ĠM ih",
+ "Ġrall ies",
+ "Ġman ter",
+ "Ġearn est",
+ "s uper",
+ "Ġge ce",
+ "ĠR end",
+ "ĠGer ade",
+ "jen igen",
+ "ĠV all",
+ "Ġìŀ ĪëĤĺ",
+ "ĠÑģказ ала",
+ "Ġtrabal h",
+ "ĠнаÑĪ ем",
+ "Ġм еÑħ",
+ "ik it",
+ "Ġnoun s",
+ "Ġneurolog ical",
+ "Ġmotiv ational",
+ "ĠMcM ahon",
+ "ĠFin ished",
+ "Ġë³´ ìĿ´",
+ "ĠField s",
+ "Ġadoles cents",
+ "ĠT isch",
+ "ĠNe ben",
+ "ĠFl owers",
+ "ĠEner g",
+ "Ġdire t",
+ "ĠTh i",
+ "ĠP icas",
+ "æĥ ľ",
+ "æĢİä¹Ī æł·",
+ "Ġav ete",
+ "ĠF ors",
+ "ĠChap el",
+ "N ão",
+ "E t",
+ "ĠÑģод еÑĢж",
+ "ren o",
+ "Ġs ven",
+ "Ġdost ÄĻp",
+ "ne e",
+ "ĠSnap dragon",
+ "ĠID s",
+ "ìķĺ ëĬĶëį°",
+ "ר ×ļ",
+ "Ġsun flower",
+ "Ġperpet ual",
+ "ç³ ĸ",
+ "Ġkn ights",
+ "Ġg ird",
+ "ĠTo ld",
+ "Ġvolcano es",
+ "Ġadvers ary",
+ "ĠEconom y",
+ "Ġextra pol",
+ "Ġbl uetooth",
+ "Ġzoom ing",
+ "Ġsk ys",
+ "Ġgen ial",
+ "ÃŃcul os",
+ "amb re",
+ "Ġм еÑĢ",
+ "Ġteen y",
+ "Ġstress ing",
+ "ìķ Į",
+ "ON Y",
+ "Ġtransluc ent",
+ "Ġround ing",
+ "Ġgr ues",
+ "×Ļ׳ ×Ķ",
+ "ap rès",
+ "Ġprue ba",
+ "Ġpoly gon",
+ "Ġblue berry",
+ "ĠProgram m",
+ "Ġtren ches",
+ "Ġse bagai",
+ "Ġpal ate",
+ "Ġla ude",
+ "Ġbehav ed",
+ "Ġlongitud inal",
+ "ĠMod ule",
+ "Ġadm ir",
+ "λ ι",
+ "G reg",
+ "Ġwy st",
+ "Ġpropag ate",
+ "Ġmold s",
+ "ĠT ub",
+ "ĠL oud",
+ "ust o",
+ "Ġun stoppable",
+ "Ġreinfor cing",
+ "éĿŀ常 çļĦ",
+ "ĠпÑĢоблем а",
+ "Ġpot encial",
+ "Ġhe mp",
+ "ìŀ Ķ",
+ "ठ¯",
+ "Ġopt ic",
+ "Ġerfolg reich",
+ "Ñģ Ñĭ",
+ "олÑĮ ÑĪе",
+ "ur st",
+ "ĠPo is",
+ "Ġrespond ents",
+ "Ġneh me",
+ "ĠEx ternal",
+ "ol ate",
+ "H yun",
+ "Ġquart z",
+ "Ġmathematic ian",
+ "Ġbás icamente",
+ "Ġa il",
+ "ìł ľë¥¼",
+ "att utto",
+ "Ġno oit",
+ "Ġaff lict",
+ "ĠOl ga",
+ "èŃ ·",
+ "Ġна ÑĤ",
+ "Ġd ites",
+ "Ġreal idade",
+ "Ġk än",
+ "Ġuniqu eness",
+ "Ġpad res",
+ "Ġsubs idi",
+ "Ġpige ons",
+ "β α",
+ "st ad",
+ "Ġder en",
+ "ĠС лед",
+ "d oo",
+ "ĠопиÑģ ании",
+ "Ġam ber",
+ "Ġgoose bumps",
+ "ĠfrÃ¥ gor",
+ "ĠV ital",
+ "ĠIsrael ites",
+ "w asser",
+ "Is n",
+ "Ġcomm its",
+ "ĠSTE VEN",
+ "ĠBev ölker",
+ "uit ive",
+ "Ġleg en",
+ "Ġbr uk",
+ "иÑĢов ан",
+ "yn en",
+ "hel m",
+ "Ġgener ational",
+ "ĠL ändern",
+ "οι ÏĢÏĮν",
+ "uz u",
+ "Ġcall er",
+ "он ÑĮ",
+ "üm ü",
+ "Ġbes ar",
+ "Ġpl ats",
+ "Ġmig rated",
+ "Ġj ap",
+ "ĠW AR",
+ "Ġdis sect",
+ "ĠZus ch",
+ "ĠZe iten",
+ "ĠL ions",
+ "ĠD F",
+ "â Ķ",
+ "ки в",
+ "Ġpedest rians",
+ "ĠMar ilyn",
+ "d ock",
+ "Ġy ht",
+ "Ġre incarn",
+ "ĠSon o",
+ "ĠGrow th",
+ "ÑĥÑģ ов",
+ "Ġdun geons",
+ "Ġbag us",
+ "k ich",
+ "ĠÑĥ кÑĢаÑĹ",
+ "éĨ «",
+ "ĠK eller",
+ "chem istry",
+ "J apanese",
+ "Ġwill st",
+ "Ġdecomp osition",
+ "ĠÑģÑĤ ен",
+ "Ġrev ived",
+ "íķĻ êµIJ",
+ "ĠÅ ĵ",
+ "ä½ IJ",
+ "ìĭ ¸",
+ "ipp y",
+ "Ġhour ly",
+ "j än",
+ "ĠWork shop",
+ "Ŀ¼ ìĦľ",
+ "Ġcu arto",
+ "Ġpat rim",
+ "ĠB urch",
+ "ĠìŀĪ 기",
+ "Ġhe pat",
+ "Ġh Ãłng",
+ "ĠëĮĢ íķ´",
+ "ĠваÑĪ и",
+ "Ġre work",
+ "Ġpar se",
+ "Ġçıkt ı",
+ "ĠS ax",
+ "ĠMong o",
+ "ĠAa ah",
+ "ram ble",
+ "D J",
+ "Ġstabil ized",
+ "ĠSpe ech",
+ "Book s",
+ "Ġhur dles",
+ "ĠW O",
+ "ĠLamb org",
+ "Ġ19 33",
+ "Ġvor bere",
+ "Ġclin ically",
+ "Ġbreat htaking",
+ "ĠGate way",
+ "пеÑĢв ÑĭÑħ",
+ "ut ers",
+ "Ġë¹ µ",
+ "Ġyet er",
+ "Ġpull ey",
+ "Ġmuff in",
+ "ĠPre fer",
+ "ĠP ence",
+ "Ġinform ação",
+ "ìĬ¤í Ĭ¸ë",
+ "ãĤ¸ ãĥ£",
+ "ĠTur tle",
+ "ĠReg ina",
+ "ĠLo ad",
+ "do es",
+ "pan ze",
+ "¸ Ķ",
+ "Ġmin a",
+ "ĠLatin os",
+ "amm ers",
+ "ĠT ort",
+ "ĠBey once",
+ "имо ÑģÑĤи",
+ "ĠвопÑĢоÑģ Ñĭ",
+ "Ġbul un",
+ "èĢĮ å·²",
+ "ine k",
+ "bere ich",
+ "Ġpast ure",
+ "ĠO A",
+ "ĠM elt",
+ "ĠEt t",
+ "ĠD Y",
+ "Ġob wohl",
+ "Ġle agues",
+ "ÑĤ еÑģÑĮ",
+ "Ġк ÑĥÑģ",
+ "Ġv ors",
+ "Ġto pp",
+ "ograph ical",
+ "as st",
+ "Ġl indo",
+ "Ġë°Ŀ íĺĶ",
+ "Ġré fl",
+ "Ġclim bs",
+ "Ġv arsa",
+ "Ġmethy l",
+ "ĠKar ere",
+ "Æ°á» Ł",
+ "R ad",
+ "Ġprepared ness",
+ "он Ñĩ",
+ "ĠO D",
+ "ĠC GI",
+ "Ġठ®",
+ "Ġspeech less",
+ "Ġlas ci",
+ "Ġbol ag",
+ "ĠÑħоÑĩ еÑĤÑģÑı",
+ "Ġgr ieving",
+ "ĠJohann es",
+ "ĠCar roll",
+ "ad aki",
+ "Ī ¬ë",
+ "ĠsÅĤ u",
+ "Ġinner halb",
+ "Ġgymn astics",
+ "п ÑĢи",
+ "if iques",
+ "Ġkar ate",
+ "Ġdom u",
+ "ãģĿãĤĮ ãģ§",
+ "OTH ER",
+ "Ġdemand é",
+ "Ġbook let",
+ "ĠKy oto",
+ "Ġw oh",
+ "ĠMar ÃŃa",
+ "viol ent",
+ "J E",
+ "Ġl óg",
+ "Ġbrut ally",
+ "c ot",
+ "ĠÙħ ÛĮ",
+ "ĠWars z",
+ "å® Ī",
+ "w ol",
+ "Ġmik ä",
+ "ĠPron ounce",
+ "ĠBrend an",
+ "Ġr oup",
+ "Ġital iano",
+ "å¦Ĥ æѤ",
+ "Ġкомп ÑĮÑİÑĤ",
+ "Ġur ging",
+ "ed es",
+ "Ġcarbon o",
+ "ĠRichards on",
+ "ĠÐĿ аÑĩ",
+ "ĠTra iner",
+ "ĠCrime a",
+ "Ġdi apers",
+ "Ġco vet",
+ "ĠMah ar",
+ "ĠH utch",
+ "ĠAus w",
+ "ber ty",
+ "Ġind ifferent",
+ "кÑĢ еÑĤ",
+ "uld ade",
+ "Ġhar ms",
+ "¢ ÙĨ",
+ "les ia",
+ "Ġg io",
+ "ĠMist ress",
+ "ĠK nox",
+ "ĠFRE E",
+ "Ġë £¨ë",
+ "ĠнаÑĪ а",
+ "Ġinvinci ble",
+ "Ġma iden",
+ "ĠJ eez",
+ "Ġbre ve",
+ "po le",
+ "Ġcritic isms",
+ "ĠRus ia",
+ "ठ®",
+ "ph in",
+ "ĠComp are",
+ "ĠB ON",
+ "Ġsne aking",
+ "ĠR ails",
+ "ĠG eral",
+ "Ġ195 3",
+ "H ola",
+ "Ġоп ÑĭÑĤ",
+ "Ġrain forest",
+ "Ġbel um",
+ "ĠOb i",
+ "ĠIS S",
+ "ãĤĮ ãģªãģĦ",
+ "ĠС в",
+ "Ġbl ond",
+ "Ġwz gl",
+ "Ġpowiedz iaÅĤ",
+ "Ġch oking",
+ "ĠSong s",
+ "ĠBir az",
+ "Ġyell s",
+ "Ġstyl ist",
+ "ÏĮ ÏĦε",
+ "Ġsch reiben",
+ "ĠJ aw",
+ "ĠEle ven",
+ "ĠR if",
+ "/ .",
+ "Ġìĺ¤ë ŀľë§Į",
+ "Ġtreat ies",
+ "uff ed",
+ "ĠâĪ Ĵ",
+ "Ġroof s",
+ "à¹Ģภª",
+ "Ġë »",
+ "Ġspark le",
+ "ĠK iev",
+ "ĠAr gu",
+ "ere cht",
+ "ĠÐĿад о",
+ "ĠF IL",
+ "Ġmol ta",
+ "ĠDe vi",
+ "Ġcam pe",
+ "Ġbene vol",
+ "ĠT ough",
+ "Ġmo im",
+ "Ġevac uate",
+ "Ġer rado",
+ "å© Ĩ",
+ "ÑĢÑĥ го",
+ "Ġíİ ĺ",
+ "ĠÎĵ ια",
+ "Ġweak en",
+ "Ġillum inated",
+ "Ġsig lo",
+ "ĠV acc",
+ "и ей",
+ "al is",
+ "ĠÑĥ ÑģÑĤÑĢой",
+ "Ġdon a",
+ "ÅĤ os",
+ "ü man",
+ "Ġprodu cción",
+ "Ġcl ot",
+ "ĠM ango",
+ "Ġune asy",
+ "Ġsh uts",
+ "ĠExam ples",
+ "ve ll",
+ "e be",
+ "Ġprompt ly",
+ "ĠT eles",
+ "ĠпÑĢоÑĪ л",
+ "Ġpu erta",
+ "Ġüber zeug",
+ "Ġco ch",
+ "so cial",
+ "ĠB enson",
+ "ĠM eth",
+ "ĠEx ped",
+ "Ġsupplement al",
+ "Ġconce ive",
+ "Ġ×ĺ ×ķ×ij",
+ "Ġcapt ivity",
+ "ıĻ ìķĪ",
+ "ĠÑħ Ñĥд",
+ "form ing",
+ "Ġupload s",
+ "Ġturbul ence",
+ "j oint",
+ "Ġsatisf actory",
+ "ĠAn ime",
+ "Ġwash es",
+ "Ġliber als",
+ "ĠSun shine",
+ "ĠRE AL",
+ "ub lik",
+ "b inary",
+ "T ony",
+ "Ġpolar ized",
+ "Ġenrich ed",
+ "t aking",
+ "ĠëģĿ ëĤĺ",
+ "Ġple asures",
+ "Ġex termin",
+ "in ese",
+ "at l",
+ "v är",
+ "аÑĢ Ñĭ",
+ "Ġmy ÅĽ",
+ "n arrator",
+ "Ġод ном",
+ "Ġnaj wiÄĻ",
+ "Ġmobil ize",
+ "Ġmill or",
+ "Ġat a",
+ "æ· ·",
+ "ĠpolÃŃt ico",
+ "Ġple ad",
+ "Ġpain ters",
+ "ĠS ow",
+ "о ÑĦ",
+ "ĠìĺĽ ëĤł",
+ "ĠÑĩ ÑĤоб",
+ "Ġs abor",
+ "ĠUnd ert",
+ "ĠJER RY",
+ "Å¡ ÃŃ",
+ "Ġë° ĸìĹIJ",
+ "Ġpréc éd",
+ "Ġannot ation",
+ "ĠI naudible",
+ "Ġtext ured",
+ "Ġfisher man",
+ "v ordan",
+ "icher ung",
+ "Ġìłģ ìĿ´",
+ "Ġge zeigt",
+ "Ġmand ates",
+ "Ġbe ak",
+ "ĠTW O",
+ "ĠAk bar",
+ "il ian",
+ "Ġtiế p",
+ "Ġsuperior ity",
+ "ink u",
+ "Ġl ys",
+ "ĠF CC",
+ "ĠC PA",
+ "ust ering",
+ "nic os",
+ "an ja",
+ "Ġch ills",
+ "ĠC age",
+ "Ġse aling",
+ "Ġsa ç",
+ "Ġded ans",
+ "ĠAl ger",
+ "Ġspe zie",
+ "Ġcol oss",
+ "ıy ı",
+ "clock wise",
+ "Ġexact amente",
+ "Ġ iemand",
+ "am ı",
+ "Ġmand ar",
+ "ra j",
+ "f aced",
+ "ag ua",
+ "Ġê¹ Ķë",
+ "Ġins besondere",
+ "Ġdri zzle",
+ "Ġdimin ish",
+ "ĠY oda",
+ "A I",
+ "Ġbil miyorum",
+ "ĠM MA",
+ "ateg ory",
+ "ĠпеÑĢ еп",
+ "Ġparticip ar",
+ "Ġnormal ized",
+ "Ġcomplex ities",
+ "æ´ ²",
+ "æİ §",
+ "аÑĢ ов",
+ "m ist",
+ "ich a",
+ "Gr oup",
+ "Ġresil iency",
+ "Ġnog le",
+ "ĠCN C",
+ "pr ü",
+ "Ġphysic ists",
+ "н ок",
+ "L I",
+ "Ġstuff s",
+ "Ġsist emas",
+ "Ġinterfer ing",
+ "ĠMar vin",
+ "ér cito",
+ "ĠìĹĨ ê³ł",
+ "Ġson ic",
+ "Ġequ iv",
+ "Ġab ord",
+ "ĠRam en",
+ "Ġ0 9",
+ "med im",
+ "at iques",
+ "Ġдел аÑİÑĤ",
+ "Ġunanim ously",
+ "Ġsk irts",
+ "ĠíĬ¹ ë³Ħ",
+ "ĠP rix",
+ "k ami",
+ "Ġfr uition",
+ "Ġbirthday s",
+ "ик ом",
+ "Ġinaug ural",
+ "Ġcorrel ate",
+ "ĠT ory",
+ "ĠëĤĺ ìģ",
+ "Ġde w",
+ "ĠPre cis",
+ "ih i",
+ "Ġë¬¸ìłľ ê°Ģ",
+ "Ġc iting",
+ "ĠL ana",
+ "ĠK ag",
+ "Ġplay through",
+ "ĠProt ocol",
+ "fr ist",
+ "hov ah",
+ "Ġmerc iful",
+ "Ġb ilingual",
+ "ĠG uitar",
+ "r h",
+ "Ġglam orous",
+ "ĠVik ings",
+ "ĠOoo oh",
+ "íķĺ ëĬĶëį°",
+ "ĠUg anda",
+ "Ġcollaps es",
+ "ent ry",
+ "Ġantioxid ants",
+ "ëĤ ĺë",
+ "ÑĪ аÑı",
+ "Ġtri via",
+ "Ġgä ller",
+ "Ġfun gi",
+ "Ġmil ks",
+ "Ġd icht",
+ "μ η",
+ "po ke",
+ "ĠвÑĭп ÑĥÑģк",
+ "Ġfeed er",
+ "ĠAl cohol",
+ "h ower",
+ "Ġdes erving",
+ "ĠRe bel",
+ "ios is",
+ "Ġ10 3",
+ "Ġhand out",
+ "Ġen m",
+ "Ġland lords",
+ "Ġge ology",
+ "r ils",
+ "Ġco bra",
+ "ĠV old",
+ "ĠP anch",
+ "ĠGRE G",
+ "Ġpr oss",
+ "Ġbrac elets",
+ "ĠV ega",
+ "Ġroz um",
+ "æ¬ ¾",
+ "аз д",
+ "ĠLy nd",
+ "ĠHon ors",
+ "Ġsurrend ered",
+ "Ġlibr arians",
+ "12 5",
+ "ĠÑģ иг",
+ "Ġuniform ly",
+ "ĠE agles",
+ "ìķ Ļ",
+ "иÑĤ ан",
+ "and id",
+ "ĠìłĪë ĮĢ",
+ "ĠØ ¶",
+ "Ġarrest s",
+ "ĠCS V",
+ "ĠAzerbai jan",
+ "ort ic",
+ "ĠD X",
+ "ĠAdvent ures",
+ "Ġab us",
+ "ĠF au",
+ "Ġschlim m",
+ "Ġratt ling",
+ "Ġconsum es",
+ "ĠTol kien",
+ "Ġresurrect ed",
+ "ĠX Y",
+ "íĬ¸ ê°Ģ",
+ "ĠвÑĭ ÑģÑĤÑĥп",
+ "ĠAng ie",
+ "żen ia",
+ "M ic",
+ "ĠShe ila",
+ "acht et",
+ "Ġover st",
+ "Ġl â",
+ "Ġine ffective",
+ "æĿ ¡",
+ "æĢİä¹Ī äºĨ",
+ "å¿ Ļ",
+ "Ġwicht iger",
+ "Ġv ino",
+ "Ġp um",
+ "Ġang led",
+ "ĠP ione",
+ "ĠM ỹ",
+ "ãģĿãĤĮ ãģ¯",
+ "wo ÅĽÄĩ",
+ "d raw",
+ "ั à¹Ī",
+ "mark ets",
+ "Ġcaf es",
+ "ĠC em",
+ "â Ŀ¤",
+ "ĠS uit",
+ "M K",
+ "Ġemphas izes",
+ "Ġtort illa",
+ "Ġmejor ar",
+ "ĠSur viv",
+ "cast ing",
+ "Ġeduc ación",
+ "ĠG um",
+ "u ely",
+ "ĠìĹ¬ê¸° ëĬĶ",
+ "Ġstretch y",
+ "en ça",
+ "Ġwith hold",
+ "Ġex iting",
+ "Ġenthal py",
+ "ĠTrans it",
+ "ıl mÄ±ÅŁ",
+ "al ies",
+ "Ġsal var",
+ "Ġlean ed",
+ "ĠgroÃŁ es",
+ "Ġf itt",
+ "ак и",
+ "S arah",
+ "Ġhost el",
+ "Ġfinger na",
+ "Ġnadzie jÄĻ",
+ "w ives",
+ "R ec",
+ "Ġsp ool",
+ "аÑĤ ов",
+ "ĠEn emy",
+ "Ġf ury",
+ "Ġdet ta",
+ "ĠF ay",
+ "éļ ¨",
+ "Ñı ÑİÑĤ",
+ "Ġaproxim adamente",
+ "Ġsil os",
+ "Ġmag ist",
+ "Ġc ree",
+ "ĠKr ank",
+ "ĠD OWN",
+ "Ġstart led",
+ "Ġre born",
+ "ĠUm welt",
+ "ĠSuz anne",
+ "ни ÑĨÑĭ",
+ "out ez",
+ "ĠJ AC",
+ "y ards",
+ "rad as",
+ "ra u",
+ "ip ts",
+ "h ail",
+ "Ġparagraph s",
+ "Ġme glio",
+ "Ġisol ating",
+ "Ġace ite",
+ "ĠH arsh",
+ "Ġcy st",
+ "ĠBlock chain",
+ "ĠÑħоÑĢоÑĪ ий",
+ "Ġvirt uous",
+ "Ġinvestig ación",
+ "Ġdev oir",
+ "Ġmast urb",
+ "ĠS ale",
+ "ÙĬر Ø©",
+ "ĠÎ §",
+ "ĠStra ÃŁen",
+ "Ġdi kk",
+ "Ġa fore",
+ "ĠJung kook",
+ "Ġcho ciaż",
+ "ĠDebat te",
+ "Ġweird ly",
+ "Ġvia je",
+ "reg ist",
+ "H elp",
+ "Ġkind eren",
+ "Ġform ulated",
+ "Ġenf im",
+ "ĠTow ards",
+ "ко ÑĹ",
+ "iver ing",
+ "ĠдеÑĤ и",
+ "char ger",
+ "Ġpur l",
+ "Ġacadem ically",
+ "ĠNur se",
+ "Ġdel eting",
+ "ay o",
+ "Ġref usal",
+ "Ġdepict s",
+ "ĠDr acula",
+ "Ġtoast ed",
+ "ĠZomb ie",
+ "ĠSuper ior",
+ "ĠB old",
+ "Ġquizz es",
+ "Ġg le",
+ "4 50",
+ "Ġcome ço",
+ "yn n",
+ "Ġver st",
+ "ĠO laf",
+ "Ġpom oc",
+ "ĠS ask",
+ "ë ĺ",
+ "ĠT CP",
+ "ĠProper ty",
+ "íķĺ ì£ł",
+ "à¸ľ ม",
+ "bo om",
+ "ar os",
+ "ĠÑĢоÑģÑģ ий",
+ "ĠбÑĭв аеÑĤ",
+ "åĩº åİ»",
+ "ĠìĿ´ìķ¼ 기를",
+ "Ġcomb ien",
+ "v acc",
+ "Ġeben falls",
+ "par a",
+ "Ġз м",
+ "Ġdesper ation",
+ "ord re",
+ "Ġש׾ ×Ļ",
+ "Ġgener ously",
+ "ĠÐŀ к",
+ "Ġorb iting",
+ "> ",
+ "?",
+ "@",
+ "A",
+ "B",
+ "C",
+ "D",
+ "E",
+ "F",
+ "G",
+ "H",
+ "I",
+ "J",
+ "K",
+ "L",
+ "M",
+ "N",
+ "O",
+ "P",
+ "Q",
+ "R",
+ "S",
+ "T",
+ "U",
+ "V",
+ "W",
+ "X",
+ "Y",
+ "Z",
+ "[",
+ "\\",
+ "]",
+ "^",
+ "_",
+ "`",
+ "a",
+ "b",
+ "c",
+ "d",
+ "e",
+ "f",
+ "g",
+ "h",
+ "i",
+ "j",
+ "k",
+ "l",
+ "m",
+ "n",
+ "o",
+ "p",
+ "q",
+ "r",
+ "s",
+ "t",
+ "u",
+ "v",
+ "w",
+ "x",
+ "y",
+ "z",
+ "{",
+ "|",
+ "}",
+ "~",
+ "\u00a1",
+ "\u00a2",
+ "\u00a3",
+ "\u00a4",
+ "\u00a5",
+ "\u00a6",
+ "\u00a7",
+ "\u00a8",
+ "\u00a9",
+ "\u00aa",
+ "\u00ab",
+ "\u00ac",
+ "\u00ae",
+ "\u00af",
+ "\u00b0",
+ "\u00b1",
+ "\u00b2",
+ "\u00b3",
+ "\u00b4",
+ "\u00b5",
+ "\u00b6",
+ "\u00b7",
+ "\u00b8",
+ "\u00b9",
+ "\u00ba",
+ "\u00bb",
+ "\u00bc",
+ "\u00bd",
+ "\u00be",
+ "\u00bf",
+ "\u00c0",
+ "\u00c1",
+ "\u00c2",
+ "\u00c3",
+ "\u00c4",
+ "\u00c5",
+ "\u00c6",
+ "\u00c7",
+ "\u00c8",
+ "\u00c9",
+ "\u00ca",
+ "\u00cb",
+ "\u00cc",
+ "\u00cd",
+ "\u00ce",
+ "\u00cf",
+ "\u00d0",
+ "\u00d1",
+ "\u00d2",
+ "\u00d3",
+ "\u00d4",
+ "\u00d5",
+ "\u00d6",
+ "\u00d7",
+ "\u00d8",
+ "\u00d9",
+ "\u00da",
+ "\u00db",
+ "\u00dc",
+ "\u00dd",
+ "\u00de",
+ "\u00df",
+ "\u00e0",
+ "\u00e1",
+ "\u00e2",
+ "\u00e3",
+ "\u00e4",
+ "\u00e5",
+ "\u00e6",
+ "\u00e7",
+ "\u00e8",
+ "\u00e9",
+ "\u00ea",
+ "\u00eb",
+ "\u00ec",
+ "\u00ed",
+ "\u00ee",
+ "\u00ef",
+ "\u00f0",
+ "\u00f1",
+ "\u00f2",
+ "\u00f3",
+ "\u00f4",
+ "\u00f5",
+ "\u00f6",
+ "\u00f7",
+ "\u00f8",
+ "\u00f9",
+ "\u00fa",
+ "\u00fb",
+ "\u00fc",
+ "\u00fd",
+ "\u00fe",
+ "\u00ff",
+ "\u0100",
+ "\u0101",
+ "\u0102",
+ "\u0103",
+ "\u0104",
+ "\u0105",
+ "\u0106",
+ "\u0107",
+ "\u0108",
+ "\u0109",
+ "\u010a",
+ "\u010b",
+ "\u010c",
+ "\u010d",
+ "\u010e",
+ "\u010f",
+ "\u0110",
+ "\u0111",
+ "\u0112",
+ "\u0113",
+ "\u0114",
+ "\u0115",
+ "\u0116",
+ "\u0117",
+ "\u0118",
+ "\u0119",
+ "\u011a",
+ "\u011b",
+ "\u011c",
+ "\u011d",
+ "\u011e",
+ "\u011f",
+ "\u0120",
+ "\u0121",
+ "\u0122",
+ "\u0123",
+ "\u0124",
+ "\u0125",
+ "\u0126",
+ "\u0127",
+ "\u0128",
+ "\u0129",
+ "\u012a",
+ "\u012b",
+ "\u012c",
+ "\u012d",
+ "\u012e",
+ "\u012f",
+ "\u0130",
+ "\u0131",
+ "\u0132",
+ "\u0133",
+ "\u0134",
+ "\u0135",
+ "\u0136",
+ "\u0137",
+ "\u0138",
+ "\u0139",
+ "\u013a",
+ "\u013b",
+ "\u013c",
+ "\u013d",
+ "\u013e",
+ "\u013f",
+ "\u0140",
+ "\u0141",
+ "\u0142",
+ "\u0143",
+ "\u0120t",
+ "\u0120a",
+ "\u0120th",
+ "in",
+ "er",
+ "\u0120w",
+ "\u0120s",
+ "ou",
+ "\u0120the",
+ "re",
+ "on",
+ "at",
+ "en",
+ "\u0120c",
+ "it",
+ "is",
+ "\u0120b",
+ "nd",
+ "\u0120d",
+ "\u0120m",
+ "\u0120h",
+ "\u0120o",
+ "ing",
+ "es",
+ "\u0120p",
+ "\u0120to",
+ "an",
+ "\u0120f",
+ "or",
+ "ll",
+ "\u0120I",
+ "\u0120l",
+ "\u0120y",
+ "ar",
+ "\u0120g",
+ "\u0120you",
+ "ed",
+ "\u0120and",
+ "\u0120in",
+ "\u0120of",
+ "as",
+ "\u0120n",
+ "om",
+ "ic",
+ "\u0120that",
+ "us",
+ "et",
+ "ve",
+ "al",
+ "ow",
+ "le",
+ "\u0120is",
+ "\u0120e",
+ "\u0120it",
+ "ot",
+ "'s",
+ "\u0120be",
+ "ion",
+ "\u0120T",
+ "\u0120wh",
+ "\u0120A",
+ "ent",
+ "\u0120S",
+ "\u0120re",
+ "ay",
+ "\u0120we",
+ "\u0120on",
+ "ere",
+ "\u0120ha",
+ "ut",
+ "ac",
+ "id",
+ "ig",
+ "os",
+ "ke",
+ "ver",
+ "im",
+ "\u0120\u00d0",
+ "\u0120Th",
+ "am",
+ "all",
+ "\u0120for",
+ "el",
+ "ch",
+ "ro",
+ "\u0120this",
+ "\u0120st",
+ "\u0120W",
+ "\u0120u",
+ "ad",
+ "out",
+ "ir",
+ "ld",
+ "ct",
+ "\u0120k",
+ "if",
+ "\u0120go",
+ "..",
+ "\u00d0\u00be",
+ "ith",
+ "ly",
+ "ht",
+ "qu",
+ "\u0120-",
+ "\u0120do",
+ "\u0120j",
+ "\u0120have",
+ "\u0120B",
+ "\u0120an",
+ "\u0120with",
+ "\u0120are",
+ "\u0120r",
+ "\u0120de",
+ "\u0120se",
+ "\u0120so",
+ "\u0120v",
+ "st",
+ "ill",
+ "ur",
+ "\u0120li",
+ "\u0120M",
+ "est",
+ "od",
+ "ally",
+ "'t",
+ "ust",
+ "\u0120as",
+ "\u0120C",
+ "ce",
+ "\u0120me",
+ "\u00d0\u00b0",
+ "\u00d0\u00b5",
+ "il",
+ "\u0120H",
+ "\u0120was",
+ "ter",
+ "th",
+ "\u0120can",
+ "ant",
+ "\u0120com",
+ "our",
+ "ight",
+ "\u0120Y",
+ "ation",
+ "\u0120And",
+ "ol",
+ "\u0120sh",
+ "\u00d1\u0124",
+ "op",
+ "se",
+ "\u0120not",
+ "\u0120So",
+ "\u0120ne",
+ "un",
+ "\u0120ab",
+ "\u0120like",
+ "\u0120at",
+ "\u0120D",
+ "ie",
+ "\u0120he",
+ "\u0120con",
+ "\u0120ch",
+ "ore",
+ "\u0120al",
+ "\u0120or",
+ "\u0120qu",
+ "\u0120O",
+ "ome",
+ "ra",
+ "ul",
+ "\u0120N",
+ "pp",
+ "\u0120your",
+ "ould",
+ "\u0120P",
+ "\u0120fr",
+ "ge",
+ "ers",
+ "'re",
+ "\u00d0\u00b8",
+ "\u0120they",
+ "\u0120what",
+ "use",
+ "\u0120all",
+ "\u0120The",
+ "\u0120L",
+ "ess",
+ "em",
+ "\u0120kn",
+ "\u0120just",
+ "art",
+ "\u0120pro",
+ "very",
+ "um",
+ "\u0120lo",
+ "\u0120\u00ec",
+ "\u0120my",
+ "ok",
+ "\u0120ex",
+ "ab",
+ "\u0120there",
+ "\u0120but",
+ "\u0120know",
+ "\u0120su",
+ "\u0120G",
+ "\u00d1\u0123",
+ "\u0120E",
+ "\u0120ma",
+ "\u00d0\u00be\u00d0",
+ "\u0120en",
+ "\u0120about",
+ "\u0120It",
+ "ist",
+ "\u0120wor",
+ "ri",
+ "ind",
+ "\u0120one",
+ "ate",
+ "and",
+ "ink",
+ "\u0120le",
+ "ort",
+ "'m",
+ "\u0120F",
+ "ich",
+ "\u00d1\u0122",
+ "ide",
+ "\u0120get",
+ "\u0120out",
+ "...",
+ "\u0120will",
+ "\u00e3\u0123",
+ "ive",
+ "\u00d0\u00bd",
+ "\u0120from",
+ "ain",
+ "\u0120We",
+ "\u0120up",
+ "pe",
+ "res",
+ "ca",
+ "\u0120R",
+ "\u0120if",
+ "\u0120pl",
+ "\u0120don",
+ "ack",
+ "\u01201",
+ "\u0120\"",
+ "\u0120tr",
+ "\u0120us",
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+ "\u0120went",
+ "ider",
+ "\u0120prov",
+ "\u0120child",
+ "\u0120den",
+ "\u0120light",
+ "br",
+ "\u00b3\u00d0\u00be",
+ "oh",
+ "\u0120book",
+ "\u0120\u00d9",
+ "ution",
+ "\u0120Just",
+ "ene",
+ "\u0120four",
+ "\u0120vis",
+ "\u00ea\u00b0\u0122",
+ "\u0120hope",
+ "\u0120making",
+ "\u0120Le",
+ "\u00ec\u0137",
+ "\u0120opp",
+ "au",
+ "\u0120money",
+ "\u0120program",
+ "\u00c3\u00a8",
+ "\u0120stand",
+ "IN",
+ "\u0120sign",
+ "\u0120learn",
+ "\u00c3\u0142",
+ "\u0120Don",
+ "\u0120team",
+ "\u0120\u00d0\u00bd\u00d0\u00b0",
+ "lud",
+ "\u0120rest",
+ "ices",
+ "\u00e6\u013e",
+ "\u0120\u00d1\u0122",
+ "\u0120aut",
+ "\u0120lead",
+ "ational",
+ "de",
+ "gy",
+ "\u0120nice",
+ "\u0120das",
+ "\u0120dist",
+ "\u0120hum",
+ "\u0120One",
+ "\u00e6\u012a",
+ "\u0120comes",
+ "\u0120jo",
+ "\u0120cent",
+ "\u0120expl",
+ "\u0120mark",
+ "reen",
+ "led",
+ "gin",
+ "\u00ec\u013c\u0136",
+ "\u0120level",
+ "\u0120conf",
+ "ush",
+ "\u0120develop",
+ "\u0120test",
+ "eng",
+ "vious",
+ "ature",
+ "\u00d0\u00b5\u00d0\u00bc",
+ "ret",
+ "\u0120je",
+ "\u0120stuff",
+ "\u0120class",
+ "ows",
+ "\u0120\u00ea\u00b7",
+ "\u0120si",
+ "\u0120les",
+ "rop",
+ "\u00e7\u013c",
+ "\u0120por",
+ "\u0120war",
+ "\u00ec\u0139\u0132",
+ "\u0120everyone",
+ "\u0120ge",
+ "\u0120check",
+ "ott",
+ "\u0120sing",
+ "\u0120art",
+ "\u0120follow",
+ "\u0120201",
+ "\u0120Fr",
+ "ais",
+ "\u00ec\u0138",
+ "\u00ce\u00b1",
+ "\u00e5\u00b0",
+ "\u0120\u00c3\u0142",
+ "imes",
+ "\u0120ret",
+ "\u0120chang",
+ "\u0120pub",
+ "\u0120inf",
+ "\u0120techn",
+ "ada",
+ "ives",
+ "\u0120beh",
+ "\u00e6\u013a\u00af",
+ "\u0120looks",
+ "\u00e3\u0122\u0124",
+ "\u00d0\u00b7",
+ "\u0120Why",
+ "\u00e7\u013c\u0126",
+ "\u0120enough",
+ "\u0120bra",
+ "itch",
+ "\u00e4\u00bb",
+ "\u0120adv",
+ "\u00d0\u00b1",
+ "\u0120without",
+ "wer",
+ "meric",
+ "den",
+ "\u0120complet",
+ "\u0120idea",
+ "ters",
+ "ock",
+ "\u0120defin",
+ "\u0120ever",
+ "\u0120gl",
+ "\u0120once",
+ "\u0120bring",
+ "\u0120saying",
+ "\u0120ans",
+ "\u0120hear",
+ "nect",
+ "\u0120less",
+ "go",
+ "ream",
+ "ado",
+ "\u00ec\u0140",
+ "\u0120mind",
+ "ente",
+ "\u0120full",
+ "\u0120bad",
+ "\u0120wom",
+ "\u0120someone",
+ "\u0120du",
+ "\u0120won",
+ "\u0120contro",
+ "ortun",
+ "\u0120health",
+ "\u0120cho",
+ "\u0120Ar",
+ "\u0120conc",
+ "\u0120information",
+ "\u0120stop",
+ "att",
+ "ately",
+ "\u00e4\u00bd",
+ "\u0120group",
+ "\u0120\u00d1\u0125",
+ "\u0120quite",
+ "\u0120resp",
+ "ER",
+ "ught",
+ "\u00ea\u00b8",
+ "man",
+ "ized",
+ "\u0120Br",
+ "\u0120remember",
+ "\u0120family",
+ "\u0120business",
+ "aw",
+ "\u0120spec",
+ "\u0120au",
+ "\u0120Or",
+ "\u00c4\u0127",
+ "\u0120seen",
+ "\u0120lar",
+ "\u01207",
+ "gg",
+ "bers",
+ "\u0120dra",
+ "\u0120month",
+ "\u0120says",
+ "\u0120iss",
+ "\u0120live",
+ "\u0120line",
+ "\u0120moment",
+ "\u0120exc",
+ "els",
+ "\u0120sound",
+ "\u0120cool",
+ "\u0120loc",
+ "\u0120certain",
+ "\u0120dri",
+ "\u00d0\u00be\u00d1\u0124",
+ "ames",
+ "\u0120must",
+ "ny",
+ "\u00d0\u00b8\u00d1\u0124",
+ "\u0120kid",
+ "\u0120includ",
+ "\u00ec\u013f\u0126",
+ "ator",
+ "\u00c4\u0141",
+ "ha",
+ "ared",
+ "\u0120seem",
+ "\u00d0\u00b9",
+ "\u00ec\u0126",
+ "\u0120else",
+ "\u0120\u00ec\u0142",
+ "irl",
+ "\u01208",
+ "\u0120vo",
+ "\u0120questions",
+ "ines",
+ "ee",
+ "\u00e6\u012a\u0133",
+ "\u00c3\u00bcr",
+ "\u0120Americ",
+ "\u0120story",
+ "\u0120serv",
+ "vern",
+ "ages",
+ "land",
+ "\u0120\u00e2\u0122\u0135",
+ "era",
+ "\u0120Can",
+ "\u0120pop",
+ "ether",
+ "\u0120na",
+ "\u0120order",
+ "\u0120makes",
+ "\u0120since",
+ "con",
+ "ctor",
+ "\u0120though",
+ "\u0120product",
+ "\u00d0\u00bb\u00d0\u00b8",
+ "\u0120leg",
+ "\u0120meet",
+ "alf",
+ "\u00d1\u0123\u00d1\u0131",
+ "unch",
+ "iter",
+ "ove",
+ "\u00d7\u0137\u00d7",
+ "iet",
+ "\u00d0\u00b0\u00d0\u00bc",
+ "ital",
+ "\u0120super",
+ "ling",
+ "\u0120pay",
+ "\u0120para",
+ "\u0120job",
+ "\u0120Here",
+ "\u0120sw",
+ "ks",
+ "ption",
+ "ma",
+ "\u0120believe",
+ "\u00ac\u00eb",
+ "\u0120wait",
+ "\u00d0\u00be\u00d0\u00b9",
+ "\u0120unt",
+ "\u0120quick",
+ "hr",
+ "\u0120\u00d1\u012f",
+ "\u0120Pro",
+ "\u0120men",
+ "\u00e0\u00b9",
+ "\u0120days",
+ "\u0120goes",
+ "\u0120speak",
+ "\u0120At",
+ "ement",
+ "\u0120miss",
+ "\u0120aw",
+ "\u0120design",
+ "\u0120project",
+ "\u00d0\u00be\u00d1\u0122",
+ "ij",
+ "ants",
+ "ats",
+ "\u0120Chr",
+ "\u01209",
+ "\u0120cut",
+ "\u0120requ",
+ "\u0120\u00d0\u00bd\u00d0\u00b5",
+ "\u0120Not",
+ "aster",
+ "\u0120mill",
+ "\u0120particular",
+ "\u0120pie",
+ "\u0120students",
+ "\u0120five",
+ "oun",
+ "\u0120Ne",
+ "\u0120gi",
+ "\u0120pas",
+ "\u0120free",
+ "\u0120Sp",
+ "lich",
+ "\u0120prof",
+ "\u0120eng",
+ "\u0120prot",
+ "\u0120Like",
+ "osed",
+ "\u0120connect",
+ "app",
+ "\u0120\u00eb\u00a7",
+ "iting",
+ "\u0120blo",
+ "\u0120los",
+ "ists",
+ "\u0120experience",
+ "rent",
+ "\u0120stay",
+ "\u0120food",
+ "ton",
+ "ruct",
+ "\u0120hist",
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+ "ining",
+ "most",
+ "ivers",
+ "bo",
+ "\u00e3\u0123\u0126",
+ "\u0120Tr",
+ "gen",
+ "\u0120please",
+ "\u0120community",
+ "\u0120ce",
+ "AN",
+ "no",
+ "\u0120body",
+ "\u0120hour",
+ "\u0120vers",
+ "\u00e1\u00ba",
+ "cer",
+ "\u0120\u00ea\u00b0",
+ "\u0120reason",
+ "\u0120Right",
+ "\u0120later",
+ "\u00cf\u0126",
+ "\u0120house",
+ "\u0120X",
+ "\u00d0\u00be\u00d0\u00bd",
+ "\u0120state",
+ "fic",
+ "\u00e5\u00a4",
+ "\u00c5\u013d",
+ "ield",
+ "\u0120pri",
+ "\u0120past",
+ "\u0120walk",
+ "ology",
+ "ering",
+ "anna",
+ "\u0120ter",
+ "\u0120hold",
+ "\u0120organ",
+ "ben",
+ "\u00ce\u00bf",
+ "\u00c3\u00b3n",
+ "\u0120effect",
+ "\u0120yourself",
+ "\u0120plus",
+ "aj",
+ "ando",
+ "ural",
+ "\u0120room",
+ "lect",
+ "\u00ea\u00b2\u012e",
+ "?\"",
+ "side",
+ "\u0120become",
+ "\u00d1\u0128",
+ "\u0120\u00c2",
+ "ood",
+ "\u0120const",
+ "\u0120night",
+ "utes",
+ "\u00d0\u00b6",
+ "\u0120break",
+ "\u0120pain",
+ "\u0120step",
+ "ired",
+ "\u0120nothing",
+ "\u0120until",
+ "\u00d1\u0138",
+ "\u00d0\u00b0\u00d0\u00b2",
+ "\u00d9\u012c",
+ "\u0120during",
+ "\u00ec\u00a7\u0122",
+ "less",
+ "oll",
+ "\u00d0\u00bd\u00d1\u012d",
+ "\u00ce\u00b9",
+ "fect",
+ "iver",
+ "\u0131\u0126",
+ "ither",
+ "ying",
+ "\u0120begin",
+ "\u00d7\u013b\u00d7",
+ "ivid",
+ "\u0120\u00c3\u00a7",
+ "\u0120sal",
+ "\u0120ta",
+ "\u0120pot",
+ "\u0120$",
+ "\u0120mar",
+ "\u0120clear",
+ "\u0120face",
+ "\u0120grow",
+ "\u0120*",
+ "\u0120inside",
+ "\u0120friends",
+ "\u0120leave",
+ "enn",
+ "\u0120easy",
+ "\u0120area",
+ "ality",
+ "oud",
+ "\u0120eat",
+ "\u00d9\u0128",
+ "\u0120pur",
+ "orn",
+ "\u0120saw",
+ "\u0120answer",
+ "\u0120front",
+ "\u0120beaut",
+ "\u00bc\u00eb",
+ "\u0120matter",
+ "\u0120son",
+ "\u0120New",
+ "\u0120result",
+ "ides",
+ "che",
+ "\u0120fut",
+ "ps",
+ "\u0120focus",
+ "\u0120interesting",
+ "\u00e5\u00a5",
+ "\u0120ap",
+ "\".",
+ "\u0120create",
+ "\u00d0\u00be\u00d1\u0123",
+ "\u0120press",
+ "ross",
+ "\u0120pick",
+ "line",
+ "\u0120took",
+ "\u0120May",
+ "row",
+ "\u0120ich",
+ "\u013a\u00eb",
+ "\u0120ref",
+ "\u0120mor",
+ "ract",
+ "arent",
+ "AR",
+ "\u0120exact",
+ "\u0120space",
+ "work",
+ "\u00d0\u00bd\u00d0\u00b8",
+ "\u0120bir",
+ "\u0120dev",
+ "\u00d0\u00b3",
+ "\u0120told",
+ "\u0120public",
+ "cially",
+ "\u0120view",
+ "\u0120Hey",
+ "med",
+ "llo",
+ "cc",
+ "\u0120fac",
+ "\u0120couple",
+ "\u0120heart",
+ "ler",
+ "\u0120ready",
+ "\u0120almost",
+ "aring",
+ "\u0120half",
+ "\u0120Me",
+ "avor",
+ "ique",
+ "\u0120charac",
+ "\u0120pract",
+ "ON",
+ "ane",
+ "\u0120il",
+ "\u00d0\u00bd\u00d0\u00b0",
+ "\u0120vi",
+ "lish",
+ "head",
+ "\u0120least",
+ "\u0120basically",
+ "ased",
+ "right",
+ "\u0120yet",
+ "\u0120taking",
+ "\u0120country",
+ "\u0120win",
+ "\u0120isn",
+ "\u0120possible",
+ "\u0120cam",
+ "\u0120incre",
+ "\u0120pat",
+ "\u0120wanna",
+ "\u0120consider",
+ "\u0120abs",
+ "\u0120within",
+ "\u0120human",
+ "\u0120thinking",
+ "\u0120oh",
+ "\u00a1\u013e",
+ "\u0120qui",
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+ "\u01200",
+ "itely",
+ "\u00e4\u00b8\u012f",
+ "\u0120kill",
+ "\u0120mil",
+ "\u0120invest",
+ "ister",
+ "\u0120suc",
+ "ional",
+ "elf",
+ "\u0120whether",
+ "\u0120control",
+ "\u0120against",
+ "ots",
+ "\u00eb\u012d\u012a\u00eb\u012d\u00a4",
+ "ior",
+ "\u0120present",
+ "\u0120\u00d8\u00a7",
+ "\u0120watching",
+ "ube",
+ "erv",
+ "\u0120nicht",
+ "\u0120govern",
+ "\u0120These",
+ "\u0120:",
+ "uit",
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+ "\u0120works",
+ "oo",
+ "\u0120wir",
+ "\u0120air",
+ "\u0120Te",
+ "\u00d0\u00b0\u00d0\u00b7",
+ "ision",
+ "where",
+ "\u0120tot",
+ "joy",
+ "\u00ec\u012d",
+ "\u0120vol",
+ "\u0120\u00d0\u00b5",
+ "\u0120close",
+ "\u0120Ad",
+ "\u00d1\u012b",
+ "ined",
+ "\u0120una",
+ "\u0120\u00ea\u00b7\u00b8\u00eb",
+ "\u00b0\u00eb",
+ "orry",
+ "\u0120bro",
+ "\u0120film",
+ "ift",
+ "20",
+ "\u0120type",
+ "\u0120happened",
+ "\u0120Am",
+ "\u0120girl",
+ "\u0120Are",
+ "wards",
+ "\u0120pour",
+ "\u0120color",
+ "elt",
+ "\u00d0\u00b0\u00d1\u0123",
+ "\u0120sense",
+ "lex",
+ "\u0120With",
+ "uss",
+ "rib",
+ "\u0120rese",
+ "\u0120norm",
+ "\u0120future",
+ "\u0120deal",
+ "ending",
+ "ey",
+ "\u0120x",
+ "ero",
+ "\u0120Cl",
+ "uk",
+ "\u0120whatever",
+ "selves",
+ "\u0120young",
+ "\u00ec\u012c",
+ "\u0120Mar",
+ "\u0120Christ",
+ "\u0120guess",
+ "\u0120perform",
+ "\u0120ener",
+ "ron",
+ "\u0120hit",
+ "\u0120wond",
+ "\u0120direct",
+ "\u0120Every",
+ "\u0120often",
+ "\u0120fa",
+ "\u0120along",
+ "\u0120click",
+ "\u0120Look",
+ "\u0120situ",
+ "\u0120happy",
+ "ead",
+ "\u0120ago",
+ "\u0120enc",
+ "\u0120myself",
+ "\u0120cover",
+ "\u00d0\u00be\u00d0\u00b1",
+ "\u0120mid",
+ "\u0120cost",
+ "\u0120ten",
+ "\u0120Sch",
+ "\u0120expect",
+ "\u0120wasn",
+ "\u0120strong",
+ "iful",
+ "\u0120opportun",
+ "inal",
+ "yle",
+ "\u0120share",
+ "\u0120true",
+ "\u0120appro",
+ "\u0120chall",
+ "\u0120minutes",
+ "\u0120chann",
+ "\u0120\u00eb\u0124",
+ "\u00ce\u00b5",
+ "li",
+ "\u0120mess",
+ "ories",
+ "pecially",
+ "\u0120wrong",
+ "\u0120yes",
+ "\u0120\u00ec\u0139",
+ "iron",
+ "\u0120allow",
+ "\u0120subs",
+ "\u0120fore",
+ "\u0120fight",
+ "\u0120social",
+ "\u0120cra",
+ "ana",
+ "\u0120aff",
+ "\u0120ess",
+ "\u0120ways",
+ "\u0120short",
+ "\u0120fall",
+ "\u0120law",
+ "\u0120Who",
+ "\u0120enjoy",
+ "\u0120cal",
+ "\u0120access",
+ "fe",
+ "\u0120non",
+ "\u0120across",
+ "ery",
+ "viously",
+ "\u0120Ex",
+ "ided",
+ "\u0120link",
+ "\u0120Pr",
+ "\u0120terms",
+ "aces",
+ "\u0120land",
+ "azing",
+ "\u012015",
+ "\u0120mult",
+ "\u0120special",
+ "\u00e5\u0122",
+ "iving",
+ "\u00ec\u013f\u0122",
+ "\u0120typ",
+ "\u0120ste",
+ "\u0120\u00c4",
+ "\u0120forward",
+ "\u00e5\u0131",
+ "\u0120fre",
+ "\u00e5\u00a5\u00bd",
+ "\u0120research",
+ "\u00e0\u00af\u012f",
+ "\u00d0\u00b0\u00d1\u0124",
+ "\u0120main",
+ "\u0120record",
+ "\u0120hu",
+ "\u0120definitely",
+ "\u0120either",
+ "\u0120listen",
+ "\u0120key",
+ "\u0120market",
+ "\u0120\u00d1\u0129\u00d1\u0124\u00d0\u00be",
+ "ization",
+ "\u0120videos",
+ "\u0120guy",
+ "\u0120fig",
+ "\u0120stra",
+ "\u0120Pl",
+ "ully",
+ "amos",
+ "\u0120mention",
+ "\u0120song",
+ "\u0120intern",
+ "ral",
+ "urs",
+ "\u0120hon",
+ "\u0120value",
+ "\u0120bar",
+ "cle",
+ "\u00d0\u00be\u00d0\u00b6",
+ "\u00c4\u0129",
+ "\u013e\u00eb",
+ "\u0120zu",
+ "\u00d0\u00b8\u00d0\u00bc",
+ "\u00e4\u00bd\u0142",
+ "\u0120single",
+ "\u0120auch",
+ "cuss",
+ "\u0120gets",
+ "\u0120sometimes",
+ "\u00e5\u00be",
+ "amb",
+ "mm",
+ "cing",
+ "\u0120perfect",
+ "\u0120Bl",
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+ "\u00ec\u0142",
+ "\u0120sci",
+ "par",
+ "\u0120red",
+ "\u0120post",
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+ "\u0120Eu",
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+ "\u0120Some",
+ "\u0120descri",
+ "\u0120current",
+ "\u00c3\u00a9s",
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+ "\u0120En",
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+ "\u012a\u00eb",
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+ "\u0120heard",
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+ "\u0120everybody",
+ "ilar",
+ "\u0120needs",
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+ "\u00d0\u00b0\u00d1\u0124\u00d1\u012e",
+ "ety",
+ "\u0120black",
+ "\u0120given",
+ "ones",
+ "\u0120wel",
+ "\u00e9\u0122",
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+ "\u012030",
+ "AT",
+ "\u0120stat",
+ "ouch",
+ "\u0120Mr",
+ "\u00d0\u00b0\u00d1\u0122",
+ "\u0120sho",
+ "\u0120cond",
+ "\u00d7\u0136",
+ "my",
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+ "\u00d0\u00b5\u00d0\u00b4",
+ "\u00ec\u0137\u0126",
+ "tern",
+ "\u0120uh",
+ "\u0120har",
+ "\u0120prom",
+ "\u0120pull",
+ "rew",
+ "\u0120company",
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+ "\u00d0\u00ba\u00d0\u00b8",
+ "\u0120stre",
+ "\u0120amazing",
+ "ries",
+ "\u0120success",
+ "\u0120mach",
+ "not",
+ "\u0120discuss",
+ "\u0120nat",
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+ "\u0120une",
+ "\u0120difficult",
+ "\u0120ris",
+ "\u00ce\u00bd",
+ "\u0120camp",
+ "\u0120buy",
+ "\u00e4\u00b8\u0122",
+ "\u0120mag",
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+ "\u0120Your",
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+ "ica",
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+ "\u0120OK",
+ "\u0120lang",
+ "\u0120women",
+ "\u0120env",
+ "\u0120rece",
+ "\u0120channel",
+ "ially",
+ "ule",
+ "\u012012",
+ "thers",
+ "\u0120bott",
+ "\u0120report",
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+ "The",
+ "\u0120sent",
+ "\u0120event",
+ "\u0120energy",
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+ "\u0120ahead",
+ "ards",
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+ "\u00e4\u00ba\u0128",
+ "\u0120tool",
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+ "\u0120exactly",
+ "\u0120favor",
+ "\u0120low",
+ "\u0120proper",
+ "\u0120\u00ec\u0140\u012a",
+ "\u0120!",
+ "\u0120relations",
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+ "\u0120mir",
+ "\u0120board",
+ "\u0120sen",
+ "\u0120parents",
+ "\u0120Wow",
+ "\u0120feed",
+ "\u0120save",
+ "\u0120serious",
+ "\u0120init",
+ "EL",
+ "undred",
+ "AS",
+ "\u0120van",
+ "orrow",
+ "\u0120worth",
+ "\u0120search",
+ "\u012016",
+ "\u0120parts",
+ "\u00d1\u0123\u00d1\u0124\u00d1\u012e",
+ "\u0120compan",
+ "\u0120movie",
+ "\u0120method",
+ "\u0120ill",
+ "\u0120wish",
+ "dy",
+ "\u0120item",
+ "\u0120minus",
+ "anger",
+ "\u0120voice",
+ "\u0120skin",
+ "\u0120areas",
+ "\u0120eight",
+ "\u0120obs",
+ "\u0120,",
+ "\u00d0\u00b0\u00d0\u00b9",
+ "\u0120oil",
+ "\u0120cy",
+ "\u0120baby",
+ "sy",
+ "\u0120employ",
+ "\u0120Ke",
+ "\u0120places",
+ "\u0120fix",
+ "\u0120est\u00c3\u00a1",
+ "\u00e3\u0123\u00a8",
+ "ived",
+ "\u0120lots",
+ "\u0120season",
+ "unk",
+ "alt",
+ "\u0120table",
+ "\u0120\u00d0\u00a2",
+ "\u00c3\u00a2",
+ "\u0120attention",
+ "\u00e3\u0123\u00aa",
+ "\u0120Her",
+ "\u0120age",
+ "\u0120pra",
+ "back",
+ "cil",
+ "\u0120network",
+ "rit",
+ "\u0120doc",
+ "\u0120aren",
+ "igen",
+ "\u0120\u00eb\u0126",
+ "\u00d8\u00af",
+ "ender",
+ "\u0120total",
+ "\u0120price",
+ "\u0120crazy",
+ "\u00ec\u013c",
+ "iqu",
+ "though",
+ "You",
+ "\u00d9\u0129",
+ "\u00e3\u0124\u0135",
+ "\u00cf\u0127",
+ "\u0120sat",
+ "\u0120bi",
+ "\u0120Die",
+ "\u0120sha",
+ "\u0120thanks",
+ "uh",
+ "\u0120stage",
+ "\u00d0\u00b0\u00d0\u00b6",
+ "\u0120Fl",
+ "\u0120leav",
+ "\u0120boy",
+ "\u0120af",
+ "\u00c3\u00b6n",
+ "\u0120Get",
+ "\u0120accept",
+ "\u0120enter",
+ "\u0120tur",
+ "\u0120si\u00c4\u013b",
+ "\u0120honest",
+ "\u00e3\u0122\u012e",
+ "\u0120sam",
+ "\u0120repl",
+ "ging",
+ "\u0120development",
+ "\u0120Act",
+ "ora",
+ "\u00e3\u0122\u012f",
+ "\u00e4\u00be",
+ "\u0120knows",
+ "\u0120image",
+ "\u0120Lord",
+ "\u00d0\u00b8\u00d1\u0124\u00d1\u012e",
+ "\u0120weeks",
+ "\u0120sex",
+ "\u0136\u00eb",
+ "\u0120hundred",
+ "\u0120sounds",
+ "\u0120learned",
+ "\u0120bud",
+ "\u0120\u00d1\u0123\u00d1\u0124",
+ "\u0120incred",
+ "\u00e2\u013b",
+ "\u0120nos",
+ "\u0120drop",
+ "\u0120ben",
+ "\u0120\u00d0\u013a",
+ "\u0120safe",
+ "ata",
+ "\u0120fuck",
+ "soci",
+ "\u0120dan",
+ "\u0120cross",
+ "10",
+ "mo",
+ "vert",
+ "\u012017",
+ "zie",
+ "\u00e5\u0137",
+ "\u0120dom",
+ "\u0120Bo",
+ "\u0120setting",
+ "\u0120involved",
+ "arily",
+ "\u0120sind",
+ "\u0120sus",
+ "\u0120worry",
+ "eth",
+ "\u00ea\u00b9\u012e",
+ "\u0120sun",
+ "\u0120hier",
+ "\u0120certainly",
+ "oul",
+ "orts",
+ "\u0120Er",
+ "\u0120Um",
+ "\u0120caus",
+ "\u0120natural",
+ "\u0120\u00c3\u00bc",
+ "\u0120cry",
+ "\u0120Sec",
+ "\u0120som",
+ "\u00e6\u00b2",
+ "\u0120education",
+ "\u00d0\u00b0\u00d0\u00b5\u00d1\u0124",
+ "\u0120multip",
+ "\u0120alone",
+ "\u0120eye",
+ "\u0120rate",
+ "\u0120Europe",
+ "\u00e8\u00bf",
+ "mon",
+ "\u0120fit",
+ "izing",
+ "pped",
+ "\u0120pressure",
+ "the",
+ "\u00d0\u00b8\u00d1\u0123",
+ "ites",
+ "\u0120Af",
+ "reci",
+ "attle",
+ "\u0120services",
+ "\u0120Google",
+ "\u00e9\u0123",
+ "\u0120cases",
+ "\u0120drive",
+ "\u0120challeng",
+ "uz",
+ "\u0120Mo",
+ "\u00ec\u013e\u00bc\u00eb",
+ "val",
+ "\u00e5\u0122\u012d",
+ "\u0120fol",
+ "\u0120\u00ec\u00a2",
+ "ffic",
+ "\u0120ra",
+ "\u0120sin",
+ "\u0120blue",
+ "\u0120affect",
+ "\u0120mis",
+ "\u0120shot",
+ "\u0120\u00d0\u00be\u00d0\u00b1",
+ "asing",
+ "\u0120signific",
+ "\u0120Che",
+ "\u0120\u00ea\u00b3",
+ "\u0120positive",
+ "\u00ec\u00a3",
+ "\u0120wie",
+ "\u012040",
+ "ording",
+ "\u0120From",
+ "\u00ea\u00b5",
+ "\u0120brand",
+ "\u0120trust",
+ "\u0120ple",
+ "\u0120communic",
+ "\u0120weight",
+ "\u0120asking",
+ "\u0120tax",
+ "\u0120Japan",
+ "\u00e3\u0123\u0141",
+ "\u0120\u00ed\u0137\u013a",
+ "ops",
+ "\u00cf\u0124",
+ "\u0120putting",
+ "\u0120roll",
+ "\u0120America",
+ "reg",
+ "\u0140\u00d7",
+ "atures",
+ "ension",
+ "\u0120Somet",
+ "\u0120original",
+ "ping",
+ "\u0120\u00c5\u0141",
+ "\u0120products",
+ "\u00e3\u0125\u00bc",
+ "\u0120contact",
+ "olution",
+ "\u0120goal",
+ "\u0120pow",
+ "\u0120performance",
+ "\u0120blood",
+ "ators",
+ "\u0120Mich",
+ "\u0120temper",
+ "\u0120Dan",
+ "\u0120sugg",
+ "\u00d1\u0124\u00d0\u00b8",
+ "\u0120imm",
+ "\u0120office",
+ "\u0120arri",
+ "\u0120comfort",
+ "\u0120\u00d0\u0136",
+ "\u0120suggest",
+ "\u0120plat",
+ "\u0124\u013a",
+ "19",
+ "\u0120om",
+ "\u0120seven",
+ "\u0120Cent",
+ "ille",
+ "\u0120concept",
+ "\u0120bag",
+ "\u00c3\u00bcn",
+ "ively",
+ "\u0120div",
+ "mos",
+ "\u00e6\u012b",
+ "\u0120feels",
+ "\u0120ir",
+ "akes",
+ "ley",
+ "\u0120particip",
+ "\u0120\u00d0\u013c",
+ "fl",
+ "just",
+ "\u0120sil",
+ "\u0120Pa",
+ "AL",
+ "\u0120gotta",
+ "\u0120fan",
+ "\u0120challenge",
+ "\u0120companies",
+ "\u0120People",
+ "",
+ "\u0120heroes",
+ "\u0120Boston",
+ "\u0120dependent",
+ "\u0120motivation",
+ "flix",
+ "\u0120seam",
+ "\u00d0\u00ba\u00d0\u00b8\u00d0\u00b5",
+ "\u0120drain",
+ "oded",
+ "\u0120guilty",
+ "\u0120Jenn",
+ "ingen",
+ "\u0120granted",
+ "\u0120Kelly",
+ "\u0120Sav",
+ "\u0120Uncle",
+ "\u0120Honestly",
+ "ELI",
+ "\u0120navigate",
+ "\u0120blessed",
+ "core",
+ "\u0120earning",
+ "\u0120signals",
+ "\u0120disk",
+ "ials",
+ "\u0120ages",
+ "\u00e6\u0127",
+ "\u0120particle",
+ "\u0120\u00d1\u0129\u00d0\u00b5\u00d1\u0122",
+ "\u0120cann",
+ "\u0120tier",
+ "\u0120statements",
+ "\u00ea\u00b3\u0142\u00ec\u013c\u0136",
+ "\u0120\u00eb\u0137\u012e\u00eb\u00ac\u00b8\u00ec\u0139\u0132",
+ "\u0120Cho",
+ "\u0120polar",
+ "an\u00c3\u00a7",
+ "\u0120Kenn",
+ "\u0120Ni",
+ "\u0120Fight",
+ "organ",
+ "\u00e9\u0137",
+ "\u0120Cha",
+ "\u0120S\u00c3\u0143",
+ "\u00e3\u0125\u00aa",
+ "\u0120slic",
+ "\u0120certific",
+ "\u0120template",
+ "\u0120Federal",
+ "\u0120consideration",
+ "\u0120explo",
+ "\u0120Main",
+ "\u0120NE",
+ "\u0120alongside",
+ "\u0120dressed",
+ "\u0120Point",
+ "\u0120environments",
+ "\u0120pr\u00c3\u00b3xim",
+ "\u0120daar",
+ "\u0120prompt",
+ "\u0120pursue",
+ "\u0120entertainment",
+ "\u0120throat",
+ "\u0120problema",
+ "\u0120mart",
+ "\u00ec\u00bc",
+ "\u0120provider",
+ "\u00d8\u012e",
+ "\u0120\u00d7\u0139",
+ "inte",
+ "making",
+ "\u0120stroke",
+ "\u0120tissue",
+ "Un",
+ "\u0120precious",
+ "\u0120Arts",
+ "inking",
+ "\u0120\u00d0\u0140\u00d0\u00bd",
+ "\u0120\u00d0\u00b8\u00d1\u0123",
+ "nah",
+ "\u0120\u00d0\u0137\u00d1\u0123\u00d0\u00bb\u00d0\u00b8",
+ "\u0120corners",
+ "\u0120tricky",
+ "inch",
+ "lijk",
+ "\u0120pressing",
+ "level",
+ "ANG",
+ "\u0120radiation",
+ "\u00ec\u0126\u0142",
+ "\u0120confront",
+ "\u0120vet",
+ "\u0120representative",
+ "\u0120propag",
+ "\u0120crap",
+ "\u0120Dec",
+ "\u0120ramp",
+ "\u00d0\u00b5\u00d0\u00bf\u00d0\u00b5\u00d1\u0122\u00d1\u012e",
+ "u\u00c3\u00a9s",
+ "essen",
+ "cription",
+ "\u0120bills",
+ "\u0120Matthew",
+ "\u0120anime",
+ "\u00e1\u00ba\u00a5t",
+ "\u0120lowest",
+ "has",
+ "screen",
+ "ograp",
+ "\u00d0\u00b0\u00d0\u00bb\u00d0\u00be",
+ "inton",
+ "\u0120Jah",
+ "\u00e8\u0122\u0127",
+ "it\u00c3\u0142",
+ "\u0120kay",
+ "\u0120rotation",
+ "\u0120Were",
+ "abei",
+ "\u0120trials",
+ "\u0120lever",
+ "ighty",
+ "\u0120spoon",
+ "\u0120hunt",
+ "cling",
+ "\u0120dism",
+ "\u0120\u00d0\u00b1\u00d0\u00be\u00d0\u00bb\u00d1\u012e\u00d1\u012a",
+ "\u0120assault",
+ "\u0120\u00ed\u013a\u0137",
+ "\u0120weekly",
+ "\u0120mismo",
+ "\u0120genetic",
+ "ulpt",
+ "\u0120Student",
+ "\u0120realistic",
+ "\u0120authentic",
+ "\u00e6\u012b\u0135",
+ "asta",
+ "\u0120arrested",
+ "\u0120guidelines",
+ "\u0120\u00d7\u013e\u00d7\u0132",
+ "\u0120\u00d0\u00b4\u00d0\u00b0\u00d0\u00b2",
+ "\u0120Coming",
+ "f\u00c3\u00bcr",
+ "\u0120requests",
+ "\u0125\u0132",
+ "\u0120analyze",
+ "\u0120interess",
+ "\u0120halt",
+ "\u0120Oper",
+ "onom",
+ "\u0120duck",
+ "\u0120withd",
+ "ser",
+ "\u0120\u00cf\u012e",
+ "\u0120History",
+ "\u0120youtube",
+ "\u00e3\u0124\u012f",
+ "\u0120saber",
+ "walk",
+ "font",
+ "\u0120overview",
+ "39",
+ "\u00c3\u00bcy",
+ "etti",
+ "\u0120frozen",
+ "\u0120flesh",
+ "\u00c4\u0141i",
+ "\u0120PM",
+ "\u0120\u00ec\u013b\u0122",
+ "\u00e9\u00a2",
+ "\u00d1\u0128\u00d0\u00b8\u00d0\u00b8",
+ "\u0120\u00ea\u00b8\u00b0\u00eb",
+ "\u00ed\u0123\u00ac",
+ "\u0120prose",
+ "oooo",
+ "rates",
+ "WS",
+ "\u0120automatic",
+ "\u0120collecting",
+ "\u00c5\u0133",
+ "\u0120neighbors",
+ "\u00c2\u00bb.",
+ "\u0120Expl",
+ "\u0120circul",
+ "cover",
+ "weg",
+ "\u0120sticks",
+ "\u0120eller",
+ "\u0120www",
+ "\u0120dorm",
+ "\u0120Exper",
+ "\u0120statistics",
+ "\u0120emails",
+ "\u0120grave",
+ "imiz",
+ "HS",
+ "\u0120uit",
+ ",'",
+ "\u0120laser",
+ "\u00e8\u012b",
+ "\u0120\u00d1\u0124\u00d0\u00b5\u00d0\u00bc",
+ "\u00d1\u012d\u00d1\u012a",
+ "\u00d1\u012b\u00d1\u0133",
+ "\u0120genau",
+ "\u0120tienen",
+ "\u0120meditation",
+ "\u0120Organ",
+ "\u0120estimate",
+ "\u0120\u00eb\u00ac\u00b4\u00ec",
+ "lets",
+ "\u0120n\u00c3\u0142y",
+ "\u0120mindset",
+ "\u0120reson",
+ "\u0120m\u00c3\u00a9s",
+ "\u0120numerous",
+ "\u0120vielleicht",
+ "\u0120Third",
+ "uous",
+ "\u0120Dead",
+ "\u00d0\u00b0\u00d0\u00bd\u00d0\u00b4",
+ "HN",
+ "\u0120racing",
+ "\u0120agents",
+ "\u0120Ut",
+ "\u0120tear",
+ "\u0120HP",
+ "\u0120chemistry",
+ "\u0120survival",
+ "\u00e6\u0138\u00b0",
+ "\u0120convinced",
+ "\u0120;",
+ "\u0120regulations",
+ "\u0120ES",
+ "\u00e5\u0134\u012e",
+ "300",
+ "\u0120ense",
+ "\u0120\u00ec\u00b5",
+ "\u0120dict",
+ "GA",
+ "\u0120ah\u00c3\u0143",
+ "\u00e5\u012d\u0137",
+ "\u0120tej",
+ "\u0120\u00d0\u00be\u00d1\u0123\u00d1\u0124",
+ "\u0120Elect",
+ "\u0120intellectual",
+ "\u0120bias",
+ "\u0120burden",
+ "\u00e7\u0124\u00b9",
+ "\u0120\u00ec\u0138\u00b4\u00eb\u0138\u00bb",
+ "\u0120cheer",
+ "\u0120soph",
+ "\u0120portfolio",
+ "uba",
+ "\u0120estos",
+ "TV",
+ "For",
+ "\u0120ash",
+ "\u0120kommer",
+ "\u0120collective",
+ "\u0120wrest",
+ "\u0120Jetzt",
+ "\u0120Wat",
+ "reich",
+ "\u0120primer",
+ "active",
+ "\u0120mie",
+ "icked",
+ "\u0120hunting",
+ "\u0120testim",
+ "\u0120compassion",
+ "\u0120\u00d8\u00b1",
+ "\u0120brut",
+ "\u0120salad",
+ "\u00d0\u00be\u00d0\u00b1\u00d1\u012b\u00d0\u00b5",
+ "\u0120solving",
+ "\u0120floating",
+ "\u00e7\u00b7",
+ "\u0120attractive",
+ "\u00d9\u012a\u00d9\u0126",
+ "\u0120perd",
+ "iffer",
+ "\u0120sculpt",
+ "hhh",
+ "\u0120Week",
+ "\u0120enthus",
+ "\u0120nad",
+ "\u0120merch",
+ "\u0120\u00ed\u013b\u0137",
+ "\u0120mile",
+ "\u00e5\u00a5\u00bd\u00e4\u00ba\u0128",
+ "\u0120\u00ce\u00b8",
+ "\u0120\u00eb\u0124\u013a\u00eb",
+ "\u00e9\u0129\u012f",
+ "38",
+ "\u0120chains",
+ "\u0120Almost",
+ "\u0120tickets",
+ "rin",
+ "\u0120CC",
+ "\u0120distributed",
+ "abetes",
+ "\u0120temperatures",
+ "\u0120gained",
+ "\u0120flexibility",
+ "\u0120screaming",
+ "\u0120abroad",
+ "uno",
+ "\u0120entrepreneurs",
+ "\u0120Network",
+ "\u0120Canadian",
+ "\u0120prev",
+ "\u0120s\u00c3\u00b6",
+ "\u0120\u00d1\u0124\u00d0\u00b5\u00d0\u00b1\u00d1\u0131",
+ "\u0120Poke",
+ "\u0120Pod",
+ "\u0120Turkey",
+ "\u00e7\u0131\u00be\u00e5\u013e\u00a8",
+ "\u0120abstract",
+ "\u0120snake",
+ "\u0120Amy",
+ "\u0120\u00eb\u012c\u0132\u00eb\u0124\u012e",
+ "\u0120brave",
+ "\u0120\u00ec\u0140\u012a\u00ec\u0138\u00b4\u00ec\u013c\u0136",
+ "\u0120Kal",
+ "\u01202007",
+ "\u00c3\u00a1rio",
+ "\u0120marked",
+ "gines",
+ "\u0120alloc",
+ "ONG",
+ "\u0120scientist",
+ "\u0120esca",
+ "\u0120racism",
+ "\u00d7\u0133\u00d7",
+ "\u0120Sams",
+ "\u0120Penn",
+ "\u0120loads",
+ "\u0120\u00e0\u00ae\u00a8",
+ "\u00c3\u00bcber",
+ "Me",
+ "ix\u00c3\u00b2",
+ "\u0120per\u00c3\u00b2",
+ "anne",
+ "\u0120expressed",
+ "\u00d0\u00bc\u00d0\u00b5\u00d1\u0122",
+ "\u0120moet",
+ "\u0120returning",
+ "nia",
+ "\u0120expon",
+ "Pro",
+ "\u0120loyal",
+ "ML",
+ "\u0120lamp",
+ "\u0120shy",
+ "\u0120composition",
+ "\u0120Ly",
+ "\u0120magnetic",
+ "\u0120premier",
+ "\u0120measured",
+ "\u0120summary",
+ "\u0120attacked",
+ "\u0120finishing",
+ "\u00d0\u0139",
+ "\u00e7\u00a5",
+ "\u0120sits",
+ "\u0120hydrogen",
+ "\u0120mai",
+ "\u0120Deutsch",
+ "as\u00c4\u00b1",
+ "\u0120obtain",
+ "vie",
+ "\u0120soit",
+ "\u0120\u00eb\u00b0\u0136",
+ "\u0120lane",
+ "\u0120consegu",
+ "\u00d0\u00b2\u00d0\u00be",
+ "\u0120ease",
+ "akin",
+ "\u0120Fa",
+ "\u0120untuk",
+ "\u0120burst",
+ "\u0120cum",
+ "al\u00c4\u00b1m",
+ "\u00c3\u00bablic",
+ "idi",
+ "\u0120Royal",
+ "\u0120Kon",
+ "\u0120commonly",
+ "\u0120removing",
+ "\u0120jur",
+ "ilib",
+ "\u0120anch",
+ "\u00ed\u0138\u012b",
+ "\u00c6\u00b0\u00e1\u00bb\u00a3",
+ "\u0120\u00d0\u013e\u00d1\u012d",
+ "\u0120Anth",
+ "\u0120S\u00c3\u00a5",
+ "\u0120interrupt",
+ "\u0120stere",
+ "\u0120OS",
+ "onym",
+ "tery",
+ "\u0120Maria",
+ "\u00ea\u00b2\u0125",
+ "\u0120exploring",
+ "\u0120transparent",
+ "\u0120fate",
+ "\u0120Jung",
+ "\u0120grup",
+ "\u0120darker",
+ "\u0120Doug",
+ "\u0120mane",
+ "\u00e6\u0136\u00be",
+ "\u00e1\u00ba\u00a1i",
+ "dri",
+ "look",
+ "\u0120Design",
+ "\u0120tutaj",
+ "\u0120horizontal",
+ "reon",
+ "orte",
+ "\u0120Correct",
+ "\u0120Steven",
+ "\u0120vine",
+ "02",
+ "i\u00c4\u0129",
+ "\u0120siempre",
+ "\u0120Key",
+ "\u00e5\u0125\u0131",
+ "\u0120Games",
+ "\u0120naar",
+ "\u0120shocked",
+ "elve",
+ "\u0120Rose",
+ "\u00ec\u012d\u00ac",
+ "\u0120stopping",
+ "ohl",
+ "\u0120Mix",
+ "\u0120suffered",
+ "\u0120sigma",
+ "\u0120weakness",
+ "\u0120Ow",
+ "\u00e0\u00b8\u00b5\u00e0\u00b9\u012a",
+ "IF",
+ "\u0120\u00e0\u00ae\u0127",
+ "aded",
+ "\u0120Netflix",
+ "anes",
+ "\u0120remained",
+ "iry",
+ "\u0120rip",
+ "ellt",
+ "\u0120silent",
+ "\u0120proven",
+ "\u0120toxic",
+ "\u0120alumin",
+ "\u0120multipl",
+ "aland",
+ "\u012034",
+ "06",
+ "\u0120Bru",
+ "\u0120\u00ec\u0142\u0137\u00eb\u00a7\u0132",
+ "Just",
+ "boy",
+ "\u0120shoe",
+ "\u0120creature",
+ "\u0120headed",
+ "\u0120\u00d0\u00be\u00d1\u0124\u00d0\u00ba",
+ "\u00e6\u00b1",
+ "\u0120essence",
+ "\u0120remarkable",
+ "\u0120n\u00c3\u00bamer",
+ "\u0120drew",
+ "\u0120puzzle",
+ "\u0120Library",
+ "\u0120Fu",
+ "ashes",
+ "kk",
+ "\u0120Ist",
+ "\u00a6\u00b0",
+ "\u0120Bry",
+ "\u0120ceremony",
+ "\u0120\u00e0\u00ae\u0130",
+ "\u0120cri",
+ "equ",
+ "\u00e3\u0124\u00a2",
+ "\u0120prize",
+ "\u0120dimensions",
+ "ogram",
+ "\u0120leather",
+ "\u0120populations",
+ "uum",
+ "\u0120vegan",
+ "\u00d1\u0131\u00d0\u00b4",
+ "\u0120c\u00c3\u00b3mo",
+ "\u00e5\u0126",
+ "\u0120strip",
+ "\u00e5\u00a3",
+ "\u0120vacation",
+ "\u0127\u0137",
+ "\u0120meals",
+ "ilipp",
+ "\u0120ents",
+ "aram",
+ "richt",
+ "\u0120grain",
+ "\u0120Spain",
+ "\u0120cheek",
+ "\u0120Aff",
+ "ION",
+ "\u0120Bring",
+ "\u012038",
+ "ielen",
+ "ulu",
+ "\u0120\u00d0\u00b1\u00d0\u00be\u00d0\u00bb\u00d1\u012e\u00d1\u012a\u00d0\u00b5",
+ "\u0120announcement",
+ "\u0120\u00d1\u0124\u00d1\u0125\u00d1\u0124",
+ "\u0120Prophet",
+ "ardo",
+ "37",
+ "\u0120woke",
+ "\u0120translation",
+ "\u0120NOT",
+ "\u0120CL",
+ "\u0120d\u00c3\u00bc\u00c5\u0141",
+ "\u00d1\u0128\u00d1\u0138",
+ "acer",
+ "\u0120Loc",
+ "\u0120perception",
+ "NO",
+ "\u0120diesen",
+ "Look",
+ "heart",
+ "aved",
+ "\u0120boundary",
+ "\u0120flows",
+ "\u00d1\u0133\u00d0\u00bc",
+ "\u0120arguments",
+ "\u0120elections",
+ "\u00c4\u00b1s",
+ "\u0120heck",
+ "\u0120suitable",
+ "\u0120fiber",
+ "\u0120Stra",
+ "xy",
+ "\u0120Hum",
+ "\u0120monthly",
+ "uper",
+ "\u0120golf",
+ "\u0120lately",
+ "\u0120Gard",
+ "\u0120Ren",
+ "\u0120Ast",
+ "\u0120Fant",
+ "\u00d0\u00b0\u00d1\u0123\u00d1\u0123",
+ "\u0120obser",
+ "\u00eb\u00a1\u013e",
+ "\u0120easiest",
+ "\u012f\u0136\u00eb",
+ "\u0120websites",
+ "pol",
+ "\u0120cocon",
+ "\u0120\u00e0\u00ae\u0129",
+ "\u0120Veg",
+ "\u0120walks",
+ "\u0120intro",
+ "\u0120directed",
+ "\u0120Anna",
+ "\u0120\u00eb\u0135\u00a4\u00ec\u0138\u00b4",
+ "\u0120Eastern",
+ "\u0120Saint",
+ "\u0120Bow",
+ "\u0120roast",
+ "\u0120URL",
+ "\u0120jeden",
+ "uras",
+ "aja",
+ "\u0120semi",
+ "\u0120rapidly",
+ "\u0120targets",
+ "\u0120Control",
+ "\u0120bah",
+ "\u0120reflection",
+ "\u0120creativity",
+ "holders",
+ "\u0120\u00ec\u013a\u00ac\u00eb",
+ "\u0120amongst",
+ "\u0120feeding",
+ "\u00d1\u012f\u00d1\u0124\u00d0\u00be\u00d0\u00bc\u00d1\u0125",
+ "\u0120\u00d0\u00b2\u00d0\u00b8\u00d0\u00b4\u00d0\u00b5",
+ "\u0120\u00eb\u00a7\u012e\u00eb\u0135\u00a4",
+ "\u0120Smart",
+ "\u0120reliable",
+ "\u0120vezes",
+ "\u0120\u00d7\u00a8",
+ "chuckles",
+ "azione",
+ "\u0120Williams",
+ "\u0120a\u00c3\u00a7",
+ "\u0120slee",
+ "\u00d0\u00b5\u00d1\u012b",
+ "\u0120timeline",
+ "\u0120thorough",
+ "\u00e1\u00bb\u012f",
+ "\u0120Ot",
+ "\u00e1\u00ba\u00a1n",
+ "\u0120imagination",
+ "\u0120mechanics",
+ "rist",
+ "\u0120claimed",
+ "\u00cf\u0126\u00ce\u00b7",
+ "\u00c3\u00aate",
+ "\u0120Hurry",
+ "\u0120iPad",
+ "\u0120constru",
+ "\u0120Cla",
+ "\u0120Als",
+ "\u00e4\u00bc\u013c",
+ "utz",
+ "\u0120cultures",
+ "\u0120\u00ec\u0138\u00b4\u00eb\u0138\u00bb\u00ea\u00b2\u012e",
+ "\u0120belongs",
+ "\u0120yer",
+ "\u0120Doesn",
+ "\u0120geomet",
+ "\u0120bid",
+ "\u0120foam",
+ "\u0120hob",
+ "\u0120Britain",
+ "\u0120substance",
+ "\u0120anniversary",
+ "\u0120\u00eb\u0126\u012a",
+ "\u0120noted",
+ "\u0120governor",
+ "\u0120stocks",
+ "31",
+ "\u0120diye",
+ "\u00ec\u012c\u00a4\u00eb",
+ "\u0120reb",
+ "zel",
+ "\u0120multiply",
+ "\u0120operator",
+ "\u0126\u00a4\u00ec\u013c\u0136",
+ "\u0120waters",
+ "\u0120d\u00c3\u00a4r",
+ "\u0120unser",
+ "\u0120Elizabeth",
+ "\u00e9\u00ab\u013a",
+ "\u0120increasingly",
+ "\u0120Gro",
+ "\u0120engines",
+ "irs",
+ "\u00d8\u00ab",
+ "\u0120treasure",
+ "PC",
+ "inction",
+ "iri",
+ "\u0120accum",
+ "\u0120variation",
+ "\u0120pom",
+ "\u0120titles",
+ "\u0120Fest",
+ "\u00c3\u00b3s",
+ "\u0120elder",
+ "nym",
+ "run",
+ "\u00d1\u0131\u00d0\u00b2",
+ "\u0120innovative",
+ "\u0120nombre",
+ "\u0120coinc",
+ "\u0120franch",
+ "\u0120entonces",
+ "\u0120nichts",
+ "\u0120exclusive",
+ "\u0120Cheers",
+ "\u0120Bi",
+ "uje",
+ "\u00e6\u0143\u00a1",
+ "\u0120pok",
+ "\u0120Prem",
+ "\u0120rocket",
+ "ELIPE",
+ "\u0120hospitals",
+ "rium",
+ "\u0120juste",
+ "\u0120hammer",
+ "\u0120quantum",
+ "\u0120responses",
+ "lly",
+ "endi",
+ "\u0120actively",
+ "\u0120fridge",
+ "iate",
+ "long",
+ "\u0120quem",
+ "\u0120deaths",
+ "\u0120superior",
+ "cken",
+ "\u00ec\u013f\u00b4\u00ec\u0139\u0132",
+ "ktop",
+ "\u0120gathered",
+ "\u00a3\u00a8",
+ "\u0120dazu",
+ "\u0120recipes",
+ "\u0120buzz",
+ "cen",
+ "\u0120anytime",
+ "onsense",
+ "\u0120circles",
+ "\u0120solved",
+ "\u0120\u00ec\u012d\u0142",
+ "\u0120coronavirus",
+ "\u0120Luke",
+ "\u0120bubb",
+ "\u0120contempor",
+ "rzy",
+ "\u0120Jane",
+ "\u0120\u00d0\u00b4\u00d0\u00be\u00d0\u00bc",
+ "\u0120screws",
+ "\u0120hybrid",
+ "\u0120casual",
+ "\u0120selbst",
+ "being",
+ "\u0120\u00c4\u0132",
+ "\u0120Columb",
+ "\u0120\u00d1\u0127\u00d0\u00be\u00d1\u0129",
+ "\u0120bucket",
+ "\u0120evaluate",
+ "\u0120idol",
+ "\u0120reputation",
+ "\u0120\u00ec\u0128\u012e\u00eb",
+ "\u00d9\u012a\u00d8\u00b1",
+ "\u0120hecho",
+ "\u0120poem",
+ "\u0120subjects",
+ "plant",
+ "\u0120Beh",
+ "\u0120Speaking",
+ "\u0120batteries",
+ "\u0120followers",
+ "\u00c3\u00b6l",
+ "\u0120gently",
+ "\u0120sixt",
+ "\u0120parameter",
+ "\u0120ikke",
+ "\u0120Tour",
+ "\u0120DJ",
+ "otte",
+ "\u0120Jahren",
+ "\u0120preparation",
+ "\u0120\u00d0\u00b4\u00d1\u0125\u00d0\u00bc",
+ "\u0120800",
+ "cop",
+ "iking",
+ "\u0120\u00eb\u00ac\u00b8",
+ "\u0120\u00d0\u00bd\u00d1\u0125",
+ "\u0120\u00d0\u00bb\u00d0\u00b5\u00d1\u0124",
+ "\u00e5\u0132\u012e",
+ "\u0120Ide",
+ "\u0120\u00ec\u00a1\u00b0\u00ea\u00b8\u012a",
+ "\u0120laughter",
+ "\u0120molecules",
+ "\u0120Rest",
+ "\u0120observed",
+ "dzie",
+ "\u0120advertising",
+ "erto",
+ "\u0120moins",
+ "\u0120MIT",
+ "\u0120excit",
+ "\u0120tum",
+ "\u0120tyl",
+ "\u0120invested",
+ "\u0120pharm",
+ "\u0120unexpected",
+ "\u0120phi",
+ "otype",
+ "weise",
+ "\u0120ge\u00c3\u00a7",
+ "jourd",
+ "\u0120horses",
+ "n\u00c4\u0127",
+ "=\"",
+ "\u0120SM",
+ "\u0120fib",
+ "\u0120clips",
+ "\u00e7\u0137\u00b6",
+ "\u00e5\u00a6\u0124\u00e6\u0140\u013e",
+ "\u0120regime",
+ "\u0120rotate",
+ "rou",
+ "nik",
+ "\u0120armor",
+ "\u00f0\u0141\u013a",
+ "\u00d0\u00b5\u00d1\u0122\u00d0\u00b0",
+ "\u00e5\u00ba\u00a6",
+ "\u0120Och",
+ "\u0120richtig",
+ "\u00c3\u00bczel",
+ "aneously",
+ "mek",
+ "\u00e9\u012e\u00af",
+ "\u0120Xiao",
+ "\u0120existed",
+ "worth",
+ "\u00e3\u0123\u00a3\u00e3\u0123\u00a8",
+ "\u0120naught",
+ "\u0120hei\u00c3\u0141t",
+ "\u0120Bal",
+ "\u0120resid",
+ "ivot",
+ "omatic",
+ "\u0120hired",
+ "\u0120gradually",
+ "\u0120onions",
+ "\u0120compat",
+ "\u0120intim",
+ "\u0120jew",
+ "\u0120contribution",
+ "\u0120Ire",
+ "acji",
+ "\u0120slice",
+ "\u0120immun",
+ "\u0120Rus",
+ "\u0120grows",
+ "\u0120Similarly",
+ "\u0120hardest",
+ "\u0120struck",
+ "\u0120measurement",
+ "...]",
+ "they",
+ "\u0120\u00ec\u0142\u0122\u00eb",
+ "\u0120sneak",
+ "\u0120applies",
+ "\u0120\u00d0\u00bd\u00d0\u00b5\u00d0\u00bc",
+ "\u00e6\u0135",
+ "\u00d7\u0133\u00d7\u00a8",
+ "\u0120\u00d0\u00a7\u00d1\u0124\u00d0\u00be",
+ "\u0120outro",
+ "\u0120innocent",
+ "\u0120mog",
+ "\u0120Samsung",
+ "\u0120mercy",
+ "\u0120handling",
+ "\u0120intervention",
+ "idays",
+ "got",
+ "\u0120curric",
+ "\u0120boundaries",
+ "\u0120confusing",
+ "\u013f\u00bc\u00eb\u012c\u0136",
+ "\u00e6\u0129",
+ "\u0120stitches",
+ "\u00c3\u0143vel",
+ "\u0120tunnel",
+ "it\u00c3\u00a4",
+ "\u0120gost",
+ "imy",
+ "\u0120czas",
+ "\u0120m\u00c3\u00a9",
+ "\u0120catal",
+ "\u0120Simon",
+ "\u0120LIAM",
+ "mic",
+ "\u0120\u00d0\u00a4",
+ "\u0120eyel",
+ "isas",
+ "\u0120CPU",
+ "\u0120Dou",
+ "\u0120n\u00c3\u00a4ch",
+ "\u0120infinity",
+ "\u0120rif",
+ "\u0120Peace",
+ "\u0120Cu",
+ "\u0120minimal",
+ "\u0120listened",
+ "\u0120pole",
+ "halb",
+ "\u0120loaded",
+ "\u0120steady",
+ "\u0120Besides",
+ "\u00c3\u00aam",
+ "\u0120lap",
+ "\u0120coop",
+ "\u0120friendship",
+ "world",
+ "\u0120geh",
+ "\u0120tylko",
+ "\u0120Laura",
+ "\u0120surrounded",
+ "\u0120Event",
+ "\u0120chap",
+ "\u0120Wonder",
+ "break",
+ "\u0120drove",
+ "\u0120broader",
+ "\u0120chi",
+ "Fi",
+ "\u0120gehen",
+ "\u0120western",
+ "\u0120intelligent",
+ "\u0120persist",
+ "\u0120founded",
+ "\u00e3\u0123\u0135\u00e3\u0123\u00a8",
+ "\u0120historic",
+ "\u0120fr\u00c3\u00a5",
+ "cks\u00c3\u00a5",
+ "\u0120handy",
+ "\u0120symp",
+ "\u0120rows",
+ "\u0120nutri",
+ "bur",
+ "\u0120Leon",
+ "\u0120sistema",
+ "\u0120extensive",
+ "\u0120\u00d1\u0125\u00d0\u00b2",
+ "\u00ed\u0131",
+ "\u0120nights",
+ "\u0120c\u00c3\u00a1c",
+ "\u0120counting",
+ "\u0120Must",
+ "allow",
+ "\u00d0\u00b5\u00d1\u0123\u00d1\u0123",
+ "Mom",
+ "\u0120\u00d0\u00bd\u00d0\u00b0\u00d0\u00b4\u00d0\u00be",
+ "\u0120barrel",
+ "\u00e3\u0125\u0140",
+ "ARD",
+ "\u0120installation",
+ "\u0120insect",
+ "\u0120\u00eb\u0127\u00b8\u00eb",
+ "uj\u00c4\u0127",
+ "\u0120\u00c4\u0133i",
+ "\u0120packed",
+ "\u0120fiction",
+ "Now",
+ "\u0120Yay",
+ "\u0120pert",
+ "rons",
+ "unde",
+ "aches",
+ "\u0120styles",
+ "\u0120apr\u00c3\u00a8s",
+ "oku",
+ "\u0120Vice",
+ "\u00c4\u00b1n\u00c4\u00b1z",
+ "comm",
+ "\u0120assigned",
+ "\u0120interactions",
+ "\u0120acab",
+ "FELIPE",
+ "\u0120rescue",
+ "\u0120industries",
+ "\u0120Andy",
+ "\u0120praise",
+ "\u0120flame",
+ "\u0120snack",
+ "\u00ed\u0124",
+ "\u00e7\u0123",
+ "\u0120swo",
+ "render",
+ "\u0120boards",
+ "\u0120\u00d1\u0124\u00d0\u00be\u00d0\u00bc",
+ "enne",
+ "\u0120pasta",
+ "\u0120devil",
+ "\u0120Fel",
+ "\u0120hatte",
+ "\u0120colleg",
+ "eh",
+ "\u00ec\u00bb",
+ "\u00e3\u0123\u0135\u00e3\u0123\u00ae",
+ "\u0120productive",
+ "forward",
+ "\u00d0\u00b8\u00d0\u00bf",
+ "\u0120smartphone",
+ "\u0120invis",
+ "\u0120bum",
+ "\u0120whoa",
+ "\u00ec\u0140\u0126",
+ "\u0120ocks\u00c3\u00a5",
+ "\u0120Lang",
+ "\u0120Syria",
+ "\u0120sesi",
+ "\u00ce\u00af\u00ce\u00b1",
+ "\u0120approval",
+ "48",
+ "\u0120\u00d0\u00be\u00d0\u00b4\u00d0\u00b8\u00d0\u00bd",
+ "\u0120\u00eb\u0138",
+ "\u0120Harr",
+ "\u0120Administ",
+ "\u0120\u00d7\u00a4",
+ "\u0120Dean",
+ "fi",
+ "\u0120citizen",
+ "\u0120shark",
+ "05",
+ "\u0120boil",
+ "\u0120indicate",
+ "\u00e5\u00a1",
+ "Are",
+ "\u0120layout",
+ "\u0120refr",
+ "\u0120Pacific",
+ "AAAA",
+ "\u0120Australian",
+ "gression",
+ "Voice",
+ "\u00d0\u00b0\u00d0\u00bb\u00d1\u0123\u00d1\u0131",
+ "\u0120shelter",
+ "To",
+ "aupt",
+ "\u0120evaluation",
+ "apor",
+ "\u0120currency",
+ "\u0120\u00d0\u00bc\u00d0\u00bd\u00d0\u00be\u00d0\u00b3\u00d0\u00be",
+ "igos",
+ "\u00e3\u0123\u00b0",
+ "\u0120oct",
+ "\u0120royal",
+ "\u00e8\u00b3",
+ "asil",
+ "\u0120Children",
+ "\u0120rien",
+ "\u0120\u00eb\u0135\u013e\u00eb",
+ "\u0120barrier",
+ "\u0120ejemplo",
+ "\u0120ek",
+ "ND",
+ "esp",
+ "\u00d0\u00b5\u00d0\u00bd\u00d0\u00b0",
+ "\u0120pic",
+ "\u0120killer",
+ "\u0120integrate",
+ "\u0120fewer",
+ "\u0120disabilities",
+ "\u0120....",
+ "\u0120triangle",
+ "\u0120fees",
+ "\u0120widely",
+ "emi",
+ "\u0120overwhelming",
+ "\u0120zomb",
+ "\u0120bere",
+ "\u0120hood",
+ "\u0120Aye",
+ "\u0120Harvard",
+ "ev",
+ "\u0120\u00cf\u0126\u00ce\u00bf\u00cf\u0127",
+ "\u0120cups",
+ "\u0120Auch",
+ "zona",
+ "\u01201990",
+ "\u0120wei\u00c3\u0141",
+ "\u0120crunch",
+ "\u00e6\u00a5",
+ "\u0120\u00d0\u00b7\u00d0\u00b0\u00d0\u00b2",
+ "\u0120measuring",
+ "\u0120stations",
+ "\u0120Stephen",
+ "\u0120shortly",
+ "\u0120signing",
+ "\u0120comedy",
+ "omo",
+ "\u0120suggestions",
+ "\u0120signature",
+ "\u0120\u00d0\u00bf\u00d1\u0122\u00d0\u00b8\u00d0\u00b2",
+ "\u0120disorder",
+ "aska",
+ "\u0120worlds",
+ "\u0120precisely",
+ "norm",
+ "rav",
+ "\u0120Civil",
+ "Inter",
+ "\u0120Certain",
+ "\u0120injured",
+ "\u0120suggests",
+ "\u0120Golden",
+ "\u0120cyber",
+ "\u0120\u00d8\u00b4",
+ "\u0120temporary",
+ "\u0120cooper",
+ "\u0120voted",
+ "\u0120ought",
+ "\u00e1\u00ba\u00a5y",
+ "xual",
+ "\u0120panels",
+ "\u012095",
+ "\u0120handsome",
+ "\u0120\u00d0\u00bf\u00d1\u0122\u00d0\u00be\u00d0\u00b2",
+ "\u0120permit",
+ "\u0120kein",
+ "\u0120badly",
+ "\u0120notifications",
+ "iza",
+ "\u0120Notice",
+ "\u0120inclusive",
+ "\u0120answering",
+ "\u0120\u00ed\u0139",
+ "uld",
+ "\u00ed\u0127\u012e",
+ "\u0120nowadays",
+ "\u012037",
+ "\u0120bolt",
+ "\u0120static",
+ "\u0120Hop",
+ "\u0120avant",
+ "ajo",
+ "\u0120\u00eb\u00a7\u013d\u00ec\u0140\u012a",
+ "\u0120fifty",
+ "\u0120Final",
+ "\u0120scores",
+ "\u0120Tap",
+ "\u0120cyl",
+ "\u0120convince",
+ "\u0120anyways",
+ "oda",
+ "\u0120\u00ec\u0137\u00bc",
+ "\u0120serves",
+ "\u0120\u00d1\u0124\u00d0\u00b0\u00d0\u00ba\u00d0\u00be\u00d0\u00b9",
+ "\u0120Zoom",
+ "\u0120savings",
+ "ulo",
+ "\u0120southern",
+ "viewer",
+ "\u0120hoje",
+ "\u0120seja",
+ "\u0120representing",
+ "\u012a\u00eb\u012f\u013a",
+ "lik",
+ "\u0120Somebody",
+ "\u0120beast",
+ "\u0120sticking",
+ "\u0120insist",
+ "\u0120talented",
+ "\u0120explaining",
+ "\u0120attorney",
+ "\u00e9\u0125\u00a8",
+ "\u0120stairs",
+ "\u0120Dog",
+ "\u00ed\u012d",
+ "\u0120cig",
+ "\u0120shaped",
+ "\u0120sons",
+ "\u00cf\u0123\u00ce\u00b9",
+ "utt",
+ "\u0120\u00ec\u0136",
+ "\u0120parad",
+ "\u00ec\u013f\u00b8\u00eb\u012f\u00b0",
+ "\u0120horn",
+ "\u0120Jour",
+ "anno",
+ "\u0120worldwide",
+ "\u00e5\u012c\u013d",
+ "\u0120participation",
+ "\u00a6\u0126",
+ "\u0120m\u00c3\u00b3w",
+ "\u0120burned",
+ "\u0120writers",
+ "allah",
+ "\u0120Fund",
+ "\u0120clever",
+ "\u0120Leute",
+ "bin",
+ "\u0120beating",
+ "foot",
+ "\u0120\u00ec\u013d\u0132",
+ "\u0120Studio",
+ "\u0120vag",
+ "bey",
+ "rze",
+ "\u0120opposition",
+ "\u0120\u00d0\u00b6\u00d0\u00b8\u00d0\u00b7",
+ "who",
+ "\u0120\u00ea\u00b1\u00b4",
+ "\u0120trace",
+ "\u0120\u00d0\u00b4\u00d0\u00b5\u00d0\u00bd\u00d1\u012e",
+ "\u0120epid",
+ "\u0120gesch",
+ "\u0120Nar",
+ "\u0120BE",
+ "\u00d1\u0125\u00d0\u00b9",
+ "\u0120Sign",
+ "edly",
+ "\u0120clay",
+ "\u0120instantly",
+ "\u0120gathering",
+ "\u0120Galaxy",
+ "\u0120bored",
+ "\u0120Buddh",
+ "c\u00c3\u00a9",
+ "\u0120mam",
+ "\u0120slope",
+ "\u0120\u00eb\u012d\u00a4\u00ec\u013f\u012e",
+ "\u0120sch\u00c3\u00b6n",
+ "\u0120pir",
+ "gef",
+ "amer",
+ "\u0120h\u00c3\u00b6",
+ "\u0120colleague",
+ "\u0120presents",
+ "adium",
+ "\u0120\u00e0\u00ae\u00b5",
+ "\u0120falar",
+ "beep",
+ "\u0120dried",
+ "isms",
+ "\u0120rope",
+ "\u0120workshop",
+ "\u0120estud",
+ "\u0120bands",
+ "\u0120themes",
+ "\u00e5\u0127\u00ac",
+ "\u00d9\u012c\u00d8\u00b1",
+ "\u00e5\u0132\u0130",
+ "\u0120reminder",
+ "\u00d1\u0124\u00d1\u0125",
+ "\u0120Bh",
+ "\u0120coconut",
+ "\u0120\u00d1\u0123\u00d1\u0124\u00d0\u00be",
+ "\u0120Channel",
+ "\u0120immigration",
+ "\u00c3\u00a4s",
+ ".....",
+ "\u00e4\u00b8\u00bb",
+ "\u00e7\u013b\u00bd",
+ "stop",
+ "\u0120\u00d0\u00ba\u00d0\u00b0\u00d1\u0122",
+ "\u0120coins",
+ "\u0120\u00d1\u0129\u00d0\u00b0\u00d1\u0123",
+ "\u0120destruction",
+ "lined",
+ "\u0120barriers",
+ "antine",
+ "\u0120printed",
+ "\u0120congratulations",
+ "\u0120Heart",
+ "\u0120inqu",
+ "tha",
+ "\u0120hardly",
+ "\u0120Aven",
+ "\u0120tinha",
+ "\u0120Sony",
+ "\u0120NF",
+ "\u0120graduates",
+ "\u0120squeeze",
+ "eremy",
+ "\u00cf\u0126\u00ce\u00b9",
+ "\u0120epic",
+ "\u0120Ju",
+ "\u0120olm",
+ "\u0120Laughter",
+ "\u0120beliefs",
+ "\u0120Cru",
+ "\u0120True",
+ "\u0120Soul",
+ "oween",
+ "\u0120romantic",
+ "\u0120\u00d0\u00b7\u00d0\u00b2",
+ "\u0120anos",
+ "\u0120Yup",
+ "\u00e9\u013a\u00bf",
+ "dim",
+ "\u0120infer",
+ "\u0120\u00d0\u00b7\u00d0\u00b0\u00d0\u00bc",
+ "\u0120soc",
+ "uka",
+ "\u0120precise",
+ "\u0120dropping",
+ "\u0120clue",
+ "\u0120errors",
+ "charge",
+ "\u0120Pu",
+ "ometer",
+ "\u0120lambda",
+ "acional",
+ "\u0120Dong",
+ "\u0120chamber",
+ "\u0120thankful",
+ "\u0120Nu",
+ "\u0120Hawai",
+ "\u0120info",
+ "\u0120activate",
+ "\u0120Qual",
+ "\u0120qued",
+ "\u00d1\u0125\u00d0\u00bb\u00d1\u012e",
+ "\u0120cloth",
+ "\u00e5\u0138\u013e",
+ "\u0120wichtig",
+ "55",
+ "\u0120otra",
+ "ographer",
+ "\u0120curios",
+ "\u01201980",
+ "\u0120empres",
+ "dess",
+ "eur",
+ "\u0120cluster",
+ "arter",
+ "obile",
+ "\u0120Yan",
+ "\u0120Adv",
+ "\u0120discipline",
+ "\u0120\u00ec\u0142\u0137\u00eb\u0131\u0126",
+ "\u0120Place",
+ "\u0120Select",
+ "TE",
+ "\u0120\u00d0\u00b1\u00d1\u012d\u00d0\u00bb\u00d0\u00b0",
+ "\u0120whis",
+ "\u0120bay",
+ "\u0120Dor",
+ "encing",
+ "\u0120repet",
+ "\u0120ficar",
+ "pad",
+ "\u0120fog",
+ "uyor",
+ "\u0120snap",
+ "ibt",
+ "\u0120sobie",
+ "\u0120appointment",
+ "\u0120Ry",
+ "\u0120ceiling",
+ "ourse",
+ "\u0120writes",
+ "\u0120Afghanistan",
+ "\u0120mos",
+ "aze",
+ "\u0120penal",
+ "\u0120crystal",
+ "ICE",
+ "\u00ea\u00b0\u0132",
+ "\u00e9\u0141",
+ "\u0120Tesla",
+ "\u0120theories",
+ "\u0120appeal",
+ "\u0120newspaper",
+ "\u0120cookies",
+ "\u00e6\u00a9",
+ "\u0120\u00d8\u00a7\u00d9\u0126\u00d9\u0126",
+ "\u0120maj",
+ "\u0120Getting",
+ "kommen",
+ "\u0120Heaven",
+ "ells",
+ "\u0120divine",
+ "\u00c4\u00ab",
+ "\u0120akt",
+ "\u0120hopes",
+ "\u0120Chen",
+ "wegen",
+ "***",
+ "\u0120Frage",
+ "\u0120\u00d0\u00bd\u00d0\u00b8",
+ "\u00e0\u00b8\u00b9",
+ "minister",
+ "nesota",
+ "which",
+ "\u0120explicit",
+ "\u0120verdad",
+ "\u0120graduated",
+ "\u0120Philipp",
+ "QL",
+ "\u0120MI",
+ "\u0120devot",
+ "\u0120cure",
+ "\u0120closest",
+ "\u0120\u00c3\u0126",
+ "\u0120sexy",
+ "\u00e3\u0123\u013d",
+ "\u0120Death",
+ "oko",
+ "ugu",
+ "\u0120Anne",
+ "itarian",
+ "esa",
+ "\u00d0\u00b5\u00d0\u00b3\u00d0\u00be\u00d0\u00b4",
+ "\u0120Dur",
+ "\u0120000",
+ "zeit",
+ "\u0120tournament",
+ "\u0120melhor",
+ "\u00e0\u00b8\u00aa",
+ "\u0120indu",
+ "\u0120flaw",
+ "\u0120wars",
+ "\u0120Mind",
+ "\u0120Iron",
+ "\u00d1\u0124\u00d0\u00b0\u00d0\u00ba",
+ "\u0120VR",
+ "\u0120siz",
+ "\u0120Southern",
+ "\u0120\u00ea\u00b7\u00b8\u00eb\u0141\u00ac\u00eb",
+ "\u0120awak",
+ "\u0120\u00ec\u0137\u0140",
+ "\u0120cube",
+ "believable",
+ "ifall",
+ "dis",
+ "\u0120abandoned",
+ "mind",
+ "\u0120parl",
+ "\u0120classical",
+ "\u00e8\u012d",
+ "\u00e1\u00bb\u013bt",
+ "\u0120Auto",
+ "\u0120Bor",
+ "\u00e7\u00a9",
+ "400",
+ "\u0120Society",
+ "\u0120subtle",
+ "\u0120missions",
+ "\u0120remembered",
+ "\u0120Either",
+ "\u0120daf\u00c3\u00bcr",
+ "ORD",
+ "\u0120intensity",
+ "ESIN",
+ "\u0120Cup",
+ "\u0120rarely",
+ "\u0120toys",
+ "\u0120Charlie",
+ "\u00e1\u00bb\u0141",
+ "\u0120glaube",
+ "\u0120rounds",
+ "TIN",
+ "\u0120capability",
+ "\u0120derivative",
+ "\u0120referring",
+ "\u0120d\u00c3\u00a5",
+ "\u0120TALI",
+ "\u0120cotton",
+ "\u0120confer",
+ "\u0120columns",
+ "\u0120liberal",
+ "\u0120nunca",
+ "\u0120\u00ce\u00bc\u00ce\u00b5",
+ "\u0120indo",
+ "iben",
+ "\u0120Beispiel",
+ "\u0120\u00ea\u00b7\u00b8\u00eb\u0142\u0129",
+ "\u0120\u00d1\u0125\u00d1\u0129",
+ "\u0120hoy",
+ "\u0120fry",
+ "\u0120Scottish",
+ "\u00e8\u012c",
+ "\u0120civ",
+ "\u0120conservative",
+ "\u0120airpl",
+ "\u0120sar",
+ "rus",
+ "\u0120investments",
+ "\u0120infinite",
+ "\u0120\u00e0\u00ae\u0137",
+ "\u0120TALIESIN",
+ "\u0120Gary",
+ "uell",
+ "\u0120\u00d0\u00b0\u00d0\u00ba",
+ "\u0120Cir",
+ "\u0120ritual",
+ "\u0120>>>",
+ "\u0120tempt",
+ "\u0120Tech",
+ "\u0120Pokemon",
+ "\u0120improvements",
+ "\u0120spare",
+ "\u0120translate",
+ "\u0120sonra",
+ "\u0120Film",
+ "wort",
+ "\u0120\u00d0\u00bc\u00d0\u00b8",
+ "\u0120periods",
+ "\u0120jealous",
+ "\u00e3\u0123\u0126\u00e3\u0123\u0126",
+ "\u0120tir",
+ "MI",
+ "\u0120conducted",
+ "\u0120\u00ec\u0137\u012a\u00eb\u0127\u0137",
+ "09",
+ "\u0120Polit",
+ "\u0120Whereas",
+ "\u0120moisture",
+ "\u0120sins",
+ "\u0120kap",
+ "\u0120\u00d1\u012f\u00d0\u00ba",
+ "\u0120benim",
+ "\u0120eliminate",
+ "\u0120athletes",
+ "\u0120Manager",
+ "\u0120featured",
+ "apore",
+ "\u00e4\u00ba\u013d",
+ "\u0120\u00eb\u00b0\u013e",
+ "\u0120perf",
+ "\u0120Thus",
+ "\u0120debut",
+ "\u00d0\u00be\u00d0\u00b1\u00d1\u0122",
+ "\u0120se\u00c3\u00b1",
+ "\u0120mysterious",
+ "words",
+ "\u0136\u00ea\u00b0\u0122",
+ "\u0120checks",
+ "\u0120volunteer",
+ "\u0120washing",
+ "\u0120Marvel",
+ "\u0120AB",
+ "issors",
+ "!'",
+ "\u0120Full",
+ "yeon",
+ "\u0120weigh",
+ "\u0120JOHN",
+ "\u0120vos",
+ "\u0120procedures",
+ "\u0120addressed",
+ "\u0120Berlin",
+ "puter",
+ "\u0120Ban",
+ "\u0120medication",
+ "\u0120drone",
+ "\u0120\u00d1\u0125\u00d0\u00b1",
+ "\u0120Jean",
+ "\u0120caps",
+ "\u0120disappointed",
+ "\u0120wore",
+ "\u0120\u00ea\u00b5\u0143",
+ "\u0120organize",
+ "\u0120Halloween",
+ "\u0120fantasy",
+ "yard",
+ "\u0120nosotros",
+ "\u0120jumped",
+ "\u0120photography",
+ "\u0120Name",
+ "rec",
+ "AB",
+ "\u0120blessing",
+ "\u0120Shut",
+ "\u0120bitter",
+ "pop",
+ "\u00e3\u0123\u013f\u00e3\u0124\u012e",
+ "\u0120dei",
+ "\u0120fulfill",
+ "\u00e7\u0132\u0128",
+ "\u0120dengan",
+ "\u0120belo",
+ "\u0120Meanwhile",
+ "\u0120depois",
+ "\u0120diabetes",
+ "\u0120bund",
+ "\u0120Zealand",
+ "\u0120digest",
+ "\u0120tires",
+ "\u0120dod",
+ "agne",
+ "\u00e1\u00ba\u00bft",
+ "\u0120peel",
+ "\u0120\u00d0\u00b7\u00d0\u00b0\u00d0\u00b1",
+ "\u0120nodes",
+ "\u0120trends",
+ "\u0120Switch",
+ "\u0120Award",
+ "\u0120Orig",
+ "\u0120Hal",
+ "\u0120estas",
+ "\u0120360",
+ "\u0120simult",
+ "\u0120comic",
+ "\u0120m\u00c3\u0142",
+ "\u0120balanced",
+ "\u0120Princess",
+ "\u0120kilometers",
+ "\u00e1\u00bb\u00a9",
+ "\u0120partir",
+ "\u00ec\u00a4\u0133",
+ "soft",
+ "\u0120View",
+ "\u0120biological",
+ "inst",
+ "44",
+ "\u0120manera",
+ "\u0120comprehensive",
+ "\u0120Sab",
+ "\u0120crimes",
+ "yers",
+ "\u0120Company",
+ "\u0120Phot",
+ "\u0120pouco",
+ "iac",
+ "\u0120beim",
+ "inate",
+ "\u0120subsequ",
+ "\u0120Mayor",
+ "\u0120centuries",
+ "\u00c3\u00a8res",
+ "\u00ec\u0140\u0138\u00ec\u0137\u0126\u00ec\u013c\u0136",
+ "\u0120\u00ea\u00b7\u00b8\u00eb\u0141\u00bc",
+ "\u0120Frau",
+ "\u0120OH",
+ "\u0120\u00eb\u0123\u013f",
+ "\u0120Nah",
+ "\u0120Series",
+ "\u0120overnight",
+ "\u00ed\u0134\u012a",
+ "\u0120\u00e2\u0122\u00a2",
+ "\u0120trave",
+ "attered",
+ "\u0120warri",
+ "\u0120Grund",
+ "\u0120Indones",
+ "\u0120scra",
+ "oby",
+ "\u0120Brook",
+ "\u0120curs",
+ "\u0120\u00eb\u00b8",
+ "\u0120explains",
+ "ramatic",
+ "\u0120participating",
+ "\u0120minut",
+ "\u0120contracts",
+ "\u0120gegen",
+ "\u0120disappeared",
+ "\u0120SN",
+ "\u0120robust",
+ "aph",
+ "\u0120shrim",
+ "\u0120devast",
+ "cope",
+ "\u0120meets",
+ "\u0120peaceful",
+ "mate",
+ "\u0120weld",
+ "\u0120\u00d7\u00aa",
+ "don",
+ "\u00d1\u0125\u00d1\u0124\u00d1\u012e",
+ "\u0120registered",
+ "\u0120Nik",
+ "jin",
+ "\u0120cav",
+ "\u0120echt",
+ "iox",
+ "\u0120flowing",
+ "\u00d0\u00bd\u00d0\u00be\u00d1\u0123\u00d1\u0124\u00d0\u00b8",
+ "\u0120toe",
+ "\u0120entity",
+ "\u00d0\u00be\u00d0\u00b2\u00d0\u00b0",
+ "fits",
+ "\u0120Patrick",
+ "\u00d1\u0124\u00d1\u0122",
+ "\u0120leverage",
+ "\u0120correl",
+ "iah",
+ "\u0120strings",
+ "istinct",
+ "\u0120gue",
+ "archy",
+ "\u0120tengo",
+ "\u00c4\u00b1m\u00c4\u00b1z",
+ "\u0120orbit",
+ "\u00e4\u00b8\u00ba",
+ "\u0120\u00d0\u00b5\u00d1\u012b\u00d1\u0133",
+ "cake",
+ "\u0120\u00d7\u013e\u00d7\u0136",
+ "\u0120Minnesota",
+ "\u0120brake",
+ "owie",
+ "\u0120craw",
+ "\u00ea\u00b8\u00b0\u00eb\u00a5\u00bc",
+ "\u0120programme",
+ "\u0120\u00d1\u0123\u00d0\u00bb\u00d1\u0125\u00d1\u0129",
+ "\u00e5\u0131\u00aa",
+ "iences",
+ "\u0120Oui",
+ "\u0120Pers",
+ "imiento",
+ "\u0120Invest",
+ "\u0120slower",
+ "\u00e6\u013b\u0124\u00e5\u0122\u013b",
+ "\u0120Beth",
+ "\u0120nurse",
+ "\u0120Spring",
+ "Sp",
+ "\u0120unemploy",
+ "\u00d0\u00b4\u00d0\u00b8",
+ "\u0120genius",
+ "\u0120Aaron",
+ "\u0120\u00ea\u00b7\u00b8\u00eb\u0141\u00ac",
+ "\u0120ei",
+ "\u00e3\u0123\u0139\u00e3\u0124\u0129",
+ "\u0120tanks",
+ "\u0120aujourd",
+ "\u0120complexity",
+ "\u0120\u00d1\u0122\u00d0\u00b5\u00d1\u012a",
+ "\u0120oldest",
+ "\u0120letz",
+ "\u00e5\u0127\u00a5",
+ "\u0120phenomenon",
+ "print",
+ "\u0120Bundes",
+ "itat",
+ "\u00ea\u00bb\u013a",
+ "\u012042",
+ "\u0120Wi",
+ "\u0120incom",
+ "\u0120gek",
+ "\u0120embrace",
+ "\u0120ties",
+ "oute",
+ "\u0120dose",
+ "\u0120Friends",
+ "\u00d1\u012d\u00d1\u0124",
+ "\u00d0\u00b5\u00d0\u00b3\u00d0\u00be\u00d0\u00b4\u00d0\u00bd\u00d1\u0131",
+ "\u0120org",
+ "\u0126\u00eb\u00a1\u013e",
+ "\u00c3\u00b3g",
+ "\u0120exceed",
+ "\u0120gods",
+ "\u0120\u00ea\u00b1\u00b0\u00ec\u013a\u012a\u00ec\u013c\u0136",
+ "\u0120societ",
+ "\u0120Univers",
+ "it\u00c3\u00a4t",
+ "\u0120worden",
+ "\u0120smoking",
+ "\u0120intens",
+ "abul",
+ "emia",
+ "\u00e8\u0133",
+ "47",
+ "fly",
+ "\u01202006",
+ "\u0120Seriously",
+ "\u0120przez",
+ "\u00e6\u00bc",
+ "cre",
+ "\u0120nan",
+ "\u0120modes",
+ "\u00d0\u00be\u00d0\u00b2\u00d0\u00b0\u00d1\u0124\u00d1\u012e",
+ "\u0120Hang",
+ "emen",
+ "\u0120beneficial",
+ "\u0120voters",
+ "\u0120Broad",
+ "\u0120bent",
+ "Wow",
+ "\u0120mul",
+ "\u00e5\u0135\u00a5",
+ "\u0120UC",
+ "\u0120damaged",
+ "\u0120Ukraine",
+ "\u0120wipe",
+ "\u0120stones",
+ "\u0120managers",
+ "\u0120rab",
+ "\u00d1\u0123\u00d1\u0124\u00d1\u0122\u00d0\u00be",
+ "lat",
+ "\u0120dece",
+ "\u0120graphic",
+ "\u0120foss",
+ "\u0120disagree",
+ "\u0120Amen",
+ "\u0120secrets",
+ "hole",
+ "inkle",
+ "\u0120fortunate",
+ "\u0120\u00ec\u00b1",
+ "\u00ec\u013e\u0126",
+ "\u00e8\u0132\u00ac",
+ "\u0120habits",
+ "\u0120buried",
+ "\u0120hin",
+ "\u0120virtually",
+ "olas",
+ "\u0120RP",
+ "\u0120Tab",
+ "low",
+ "\u0120sacrific",
+ "\u0120estimated",
+ "oln",
+ "\u00d9\u012d",
+ "cur",
+ "\u0120Feel",
+ "\u0120castle",
+ "\u0120useless",
+ "\u0120disg",
+ "\u0120Jacob",
+ "\u0120gaan",
+ "\u0120upside",
+ "\u0120parece",
+ "\u00e3\u0125\u00b3\u00e3\u0125",
+ "\u0120shipping",
+ "\u0120CR",
+ "\u0120disrupt",
+ "acter",
+ "UND",
+ "fu",
+ "\u00e5\u00ae\u012e",
+ "\u0120Pick",
+ "\u0120Charl",
+ "\u0120Bull",
+ "\u0120enterprise",
+ "\u0120punishment",
+ "acking",
+ "\u0120fraction",
+ "\u0120tablet",
+ "\u0120chord",
+ "\u0120similarly",
+ "\u00e5\u0127\u00b6\u00e5\u00af\u00a6",
+ "\u0120Toronto",
+ "\u0120courts",
+ "\u00c4\u0141l",
+ "eszcze",
+ "\u0120pronoun",
+ "\u0120Sister",
+ "\u0120MP",
+ "\u0120greatly",
+ "\u0120Dank",
+ "icop",
+ "\u0120garbage",
+ "\u0120resolve",
+ "\u0120Saf",
+ "\u0120Gun",
+ "\u0120compound",
+ "\u0120\u00eb\u00b0\u00b0",
+ "\u0120Musik",
+ "\u00e2\u013b\u00ab",
+ "\u0120chaos",
+ "\u0120Whenever",
+ "\u0120euros",
+ "\u0120orchest",
+ "\u0120refriger",
+ "alan",
+ "\u00e0\u00b8\u00b7",
+ "\u0120Amazing",
+ "\u0120pud",
+ "agan",
+ "\u0120jeszcze",
+ "isy",
+ "\u0120accuracy",
+ "\u0120Ama",
+ "isode",
+ "\u00eb\u012e\u0122",
+ "\u0120interpretation",
+ "\u0120Liber",
+ "\u00e6\u00b7",
+ "cam",
+ "\u0120evolved",
+ "\u0120Kay",
+ "\u00d1\u0128\u00d1\u012d",
+ "\u0120creator",
+ "itas",
+ "\u0120alarm",
+ "\u0120celebration",
+ "zent",
+ "\u0120funcion",
+ "\u0120ov",
+ "umbling",
+ "\u0120%",
+ "\u00e0\u00b8\u012a",
+ "\u0120restrictions",
+ "\u0120\u00d0\u00bd\u00d0\u00b0\u00d0\u00b2",
+ "\u0120Kinder",
+ "\u0120banana",
+ "\u00d1\u012e\u00d1\u0131",
+ "\u0120diameter",
+ "\u0120northern",
+ "urers",
+ "\u0120Pas",
+ "\u00e6\u012a\u0133\u00e7\u013c\u0126",
+ "\u0120workforce",
+ "\u0120jung",
+ "\u0120guarante",
+ "\u0120equilib",
+ "\u0120suite",
+ "\u0120euro",
+ "\u0120deliber",
+ "Ste",
+ "\u0120downtown",
+ "\u0120chin",
+ "\u0120codes",
+ "edia",
+ "\u0120sheep",
+ "reshold",
+ "wnie",
+ "\u00c3\u00b3b",
+ "\u0120underlying",
+ "lia",
+ "jer",
+ "\u00cf\u0122\u00cf\u012e",
+ "\u00e7\u013f",
+ "throp",
+ "\u0120zap",
+ "\u0120vacuum",
+ "\u0120Hab",
+ "\u0120wrapped",
+ "\u00ec\u00a2",
+ "\u0120inventory",
+ "\u00d0\u00bc\u00d0\u00b0",
+ "\u0120coord",
+ "\u0120plates",
+ "\u0120symm",
+ "Te",
+ "\u0120w\u00c5\u0124a\u00c5\u013dnie",
+ "\u0120reaches",
+ "\u0120lonely",
+ "Script",
+ "lee",
+ "esser",
+ "\u0120\u00ea\u00b1\u00b8",
+ "\u0120Gesch",
+ "\u0120Moving",
+ "\u0120r\u00c3\u00a9p",
+ "\u0120Vill",
+ "\u00e5\u0132\u012a",
+ "\u0120Rachel",
+ "\u0120temos",
+ "ONE",
+ "\u0120strain",
+ "\u0120angel",
+ "\u0120f\u00c3\u00a5",
+ "Tr",
+ "\u0120acho",
+ "\u0120highlights",
+ "\u0120Wer",
+ "\u0120Carl",
+ "\u0120blur",
+ "\u0120regards",
+ "\u00c2\u00b7",
+ "\u00d0\u00b8\u00d0\u00bb\u00d1\u0123\u00d1\u0131",
+ "\u0120recre",
+ "\u0120Yani",
+ "UCK",
+ "\u0142\u00b8",
+ "\u0120electrons",
+ "\u0120Spiel",
+ "\u0120ved",
+ "\u00da\u00be",
+ "\u0120beam",
+ "\u0120idiot",
+ "\u00eb\u0135\u00a4",
+ "\u00d0\u00bd\u00d0\u00b0\u00d1\u0129",
+ "idd",
+ "\u0120ski",
+ "itative",
+ "\u0120hypothes",
+ "\u00e3\u0123\u00a7\u00e3\u0123\u013b\u00e3\u0123\u0143",
+ "enter",
+ "\u0120\u00ec\u0137\u0126\u00eb\u012d\u012a\u00eb",
+ "\u0120ihre",
+ "\u0120preview",
+ "angel",
+ "\u0120demon",
+ "\u0120dus",
+ "\u0120dic",
+ "\u0120Kom",
+ "LEY",
+ "...!",
+ "\u0120sieht",
+ "\u0120Sonic",
+ "\u0120tenho",
+ "anas",
+ "\u0120digit",
+ "\u0120Maar",
+ "\u0120undergrad",
+ "ouncer",
+ "uffy",
+ "\u0120conversion",
+ "\u0120disconnect",
+ "\u0120echo",
+ "omer",
+ "\u0120curriculum",
+ "\u0120perch\u00c3\u00a9",
+ "\u0120wand",
+ "..?",
+ "\u0120rolled",
+ "\u0120entrepreneur",
+ "\u0120theoret",
+ "\u0120\u00d1\u012b\u00d0\u00be",
+ "\u0120insights",
+ "\u0120zusammen",
+ "oin",
+ "rett",
+ "produ",
+ "\u0120visitors",
+ "eous",
+ "\u0120grandmother",
+ "\u0120humor",
+ "\u0120\u00d0\u00bd\u00d0\u00b8\u00d1\u0127",
+ "zenia",
+ "inson",
+ "\u0120reset",
+ "\u0120baseball",
+ "\u0120matching",
+ "\u00eb\u012d\u00a4\u00ea\u00b0\u0122",
+ "\u0120punto",
+ "\u00ec\u00a1",
+ "\u0120rede",
+ "\u0120addressing",
+ "\u0120forecast",
+ "\u0120Bol",
+ "\u0120colored",
+ "\u0120documentation",
+ "\u0120expectation",
+ "\u0120Northern",
+ "\u0120creo",
+ "\u0120\u00e0\u00ae\u013c",
+ "fon",
+ "\u0120unsere",
+ "UM",
+ "\u0120copies",
+ "\u0120expanded",
+ "\u0120veterans",
+ "\u0120Alm",
+ "\u0120\u00d0\u00b2\u00d0\u00be\u00d0\u00be\u00d0\u00b1\u00d1\u012b\u00d0\u00b5",
+ "\u0120psychological",
+ "\u0120nosso",
+ "\u0120payments",
+ "imeters",
+ "\u0120-->",
+ "\u0120Jennifer",
+ "\u0120volunteers",
+ "osse",
+ "orious",
+ "\u0120\u00d0\u00b1\u00d1\u012d\u00d0\u00bb\u00d0\u00b8",
+ "\u00e8\u0124",
+ "\u0120Ess",
+ "ws",
+ "\u0120BC",
+ "\u0120IC",
+ "Woman",
+ "\u0120vont",
+ "\u0120ethnic",
+ "ENN",
+ "\u00d0\u00b8\u00d0\u00bc\u00d0\u00be",
+ "\u0120lob",
+ "\u0120oui",
+ "cs",
+ "\u0120rehe",
+ "\u0120\u00ec\u0142\u0123",
+ "\u0120chick",
+ "\u00c3\u00basica",
+ "\u0120kont",
+ "\u0120District",
+ "\u0120pile",
+ "\u0120\u00d0\u00b0\u00d0\u00b2",
+ "\u00d0\u00b5\u00d0\u00b9\u00d1\u0123\u00d1\u0124\u00d0\u00b2",
+ "\u0120\u00c2\u00a3",
+ "\u0120issued",
+ "\u0120\u00d0\u00ba\u00d0\u00be\u00d0\u00bc\u00d0\u00bf",
+ "\u0120prosper",
+ "\u0120profound",
+ "\u0120Dear",
+ "\u0120\u00e3\u0123\u0135",
+ "\u0120funded",
+ "\u0120bisa",
+ "\u0140\u013a\u00eb",
+ "\u00d7\u0141",
+ "\u0120\u00ec\u013f\u013a",
+ "\u0120twelve",
+ "\u0120Champions",
+ "\u00e9\u013f\u0140\u00e5\u00b8\u00b8",
+ "\u00d1\u0123\u00d0\u00bb",
+ "\u01202005",
+ "pm",
+ "\u0120onde",
+ "\u0120diff\u00c3\u00a9",
+ "\u0120Chall",
+ "\u0120difficulties",
+ "\u0120garage",
+ "\u0120d\u00c3\u00a1",
+ "\u00c3\u00bcnk",
+ "\u0120\u00eb\u00ac\u00bc",
+ "\u0120tran",
+ "\u0120submitted",
+ "zw",
+ "\u00d9\u012a\u00d8\u00a7",
+ "\u0120ark",
+ "\u0120\u00ec\u0126\u00b1",
+ "\u0120grocery",
+ "\u00d0\u00be\u00d0\u00bd\u00d0\u00b0",
+ "iere",
+ "\u0120aest",
+ "\u0120exhibition",
+ "\u0120r\u00c3\u00a9s",
+ "\u0120consistency",
+ "\u0120cookie",
+ "\u00d0\u00bd\u00d0\u00b5\u00d0\u00b9",
+ "\u0120replacement",
+ "\u00e6\u00b2\u00b9",
+ "\u0120Sem",
+ "\u0120\u00ec\u0124\u00ac\u00ec\u013c\u00a9",
+ "800",
+ "\u0120genes",
+ "\u0120transaction",
+ "\u0120EL",
+ "\u0120durante",
+ "ibles",
+ "\u0120Eat",
+ "tail",
+ "issance",
+ "\u0120toss",
+ "\u0120survived",
+ "\u0120offices",
+ "\u0120supportive",
+ "Where",
+ "\u0120toutes",
+ "\u0120\u00eb\u00a7\u012b",
+ "\u0120jokes",
+ "ieron",
+ "apers",
+ "\u0120mature",
+ "\u0120Marsh",
+ "\u0120sido",
+ "kind",
+ "\u0120realmente",
+ "\u0120Chef",
+ "\u0120quelque",
+ "\u0120judges",
+ "eft",
+ "ERS",
+ "\u0120jet",
+ "\u0120persons",
+ "\u00e8\u00bb",
+ "izations",
+ "rik",
+ "\u0120shops",
+ "\u0120Wy",
+ "\u0120eleg",
+ "qu\u00c3\u00a8",
+ "quoi",
+ "\u0120juga",
+ "\u0120\u00ed\u0137\u013e\u00eb\u00b2\u012a",
+ "\u0120Question",
+ "\u0120Global",
+ "\u0120\u00ec\u0137\u00bd\u00ea\u00b0\u0126",
+ "\u0120Station",
+ "\u00e6\u0130\u00a5",
+ "\u0120Ohio",
+ "\u0120sticky",
+ "\u0120stressed",
+ "\u0120g\u00c3\u00bcn",
+ "\u0120\u00ed\u013f",
+ "\u00d1\u0123\u00d1\u0124\u00d1\u0125\u00d0\u00bf",
+ "\u00e9\u00a1\u012e",
+ "\u0120PhD",
+ "immer",
+ "\u0120mentor",
+ "\u0120invented",
+ "\u0120reun",
+ "\u0120inevit",
+ "\u0120pol\u00c3\u0143t",
+ "\u0120execute",
+ "\u0120Story",
+ "\u0120outstanding",
+ "\u0120guer",
+ "\u0120Rain",
+ "\u0120choses",
+ "\u0120Tit",
+ "\u0120\u00d1\u0123\u00d0\u00b5\u00d1\u0122",
+ "\u0120Singapore",
+ "\u0120None",
+ "\u0120chronic",
+ "\u00b0\u00eb\u012f\u00b0",
+ "\u0120ego",
+ "\u00e6\u0142\u00b7",
+ "EST",
+ "\u00e3\u0123\u0124\u00e3\u0124\u012c",
+ "\u0120Wang",
+ "\u0120NAT",
+ "\u0120aug",
+ "\u0120desktop",
+ "\u0120eternal",
+ "\u0120\u00ec\u0124\u00ac\u00ec\u012d\u00a4",
+ "\u0120Constitution",
+ "\u00ec\u0124\u00ac\u00eb",
+ "\u00d7\u013b\u00d7\u013e",
+ "pres",
+ "\u0120\u00d0\u00a2\u00d1\u012d",
+ "\u0120interf",
+ "\u0120lists",
+ "\u0120fights",
+ "ften",
+ "\u0120Iowa",
+ "\u0120motivated",
+ "\u0120Hosp",
+ "\u0120elsewhere",
+ "\u0120paths",
+ "\u0120instances",
+ "Bl",
+ "range",
+ "\u00e1\u00bb\u00b1",
+ "\u0120Sit",
+ "mana",
+ "\u0120\u00ec\u012d\u013e\u00ec\u0140\u0133",
+ "\u0120m\u00c3\u00acnh",
+ "ansas",
+ "\u0120sna",
+ "\u0120philosoph",
+ "\u0120passe",
+ "\u00c6\u00b0\u00e1\u00bb\u013fi",
+ "akh",
+ "ental",
+ "\u0120ihn",
+ "ructor",
+ "\u0120\u00d0\u00b2\u00d0\u00b0\u00d1\u012a",
+ "\u0120generous",
+ "\u0120pivot",
+ "\u00d0\u00bf\u00d0\u00be\u00d0\u00bb",
+ "\u0120jamais",
+ "\u0120coment",
+ "\u0120Lew",
+ "odzi",
+ "\u0120Xbox",
+ "\u0120\u00d0\u00b2\u00d0\u00be\u00d0\u00b4",
+ "\u0120consent",
+ "\u012b\u00ec\u0140\u00a5",
+ "\u0120dispar",
+ "lass",
+ "\u0120Governor",
+ "Beifall",
+ "\u0120\u00ea\u00b0\u013e",
+ "\u0120beloved",
+ "\u00d7\u0142\u00d7\u0137",
+ "sell",
+ "\u0120honored",
+ "leh",
+ "\u0120w\u00c3\u00a4re",
+ "unting",
+ "\u0120fraud",
+ "\u0120RAM",
+ "\u00ea\u00b1\u00b8",
+ "\u0120kills",
+ "\u0120economics",
+ "04",
+ "\u00d0\u00bf\u00d0\u00b5\u00d1\u0122",
+ "\u0120coisas",
+ "\u0120\u00d0\u00b8\u00d0\u00b3\u00d1\u0122",
+ "\u00c3\u0143m",
+ "\u0120m\u00c3\u00b6chte",
+ "\u0120\u00ec\u00b5\u013e",
+ "\u0120stimul",
+ "\u0120fastest",
+ "lv",
+ "\u0120g\u00c3\u00a9n",
+ "\u0120Sounds",
+ "\u01201970",
+ "\u0120homework",
+ "speaking",
+ "\u0120encouraging",
+ "\u0120query",
+ "\u0120revers",
+ "profit",
+ "\u0120dy",
+ "\u0120\u00ec\u0140\u0133",
+ "\u00eb\u012c\u0136\u00eb\u012f\u00b0\u00ec\u013c\u0136",
+ "\u0120soap",
+ "\u0120Gall",
+ "\u0120CN",
+ "\u0120Ans",
+ "\u0120fic",
+ "anks",
+ "\u0120dessert",
+ "\u0120\u00ec\u0142\u0122\u00ed\u013f\u00ac",
+ "\u0120Making",
+ "\u0120come\u00c3\u00a7",
+ "\u00ea\u00b3\u0126",
+ "\u0120association",
+ "Dad",
+ "hee",
+ "\u0120hogy",
+ "\u0120apro",
+ "\u0120invisible",
+ "American",
+ "\u00ed\u0130",
+ "\u0120vibe",
+ "\u0120emissions",
+ "\u0120advocate",
+ "\u0120kicked",
+ "\u0120vel",
+ "\u0120summar",
+ "\u0120freaking",
+ "chron",
+ "\u0120pinch",
+ "\u0120wszystk",
+ "iscal",
+ "\u0120proved",
+ "\u0120mindful",
+ "\u0120t\u00c3\u00a4",
+ "\u0120noises",
+ "\u0120isolated",
+ "\u0120crossed",
+ "\u0120\u00ea\u00b0\u0137",
+ "\u0120voil\u00c3\u0142",
+ "\u0120chore",
+ "\u0120RA",
+ "Com",
+ "\u0120relaxed",
+ "atro",
+ "\u0120prevention",
+ "Voiceover",
+ "OD",
+ "\u0120Covid",
+ "\u0120separation",
+ "\u0120-[",
+ "\u00d0\u00b8\u00d1\u0129\u00d0\u00b5\u00d0\u00b3\u00d0\u00be",
+ "\u00e7\u013b\u00bc",
+ "\u0120SD",
+ "bleep",
+ "\u0120independence",
+ "\u0120partial",
+ "\u0120algorithms",
+ "\u0120Anyone",
+ "\u0120associate",
+ "hum",
+ "icular",
+ "\u0120b\u00e1\u00ba\u00a1n",
+ "\u0120battles",
+ "Good",
+ "Applause",
+ "\u0120bastante",
+ "\u0120advant",
+ "\u0120Sweet",
+ "\u0120refused",
+ "\u00e3\u0124\u00b8",
+ "\u0120\u00d1\u0124\u00d0\u00b5\u00d0\u00b1\u00d0\u00b5",
+ "plet",
+ "\u0120encouraged",
+ "\u00e5\u0135\u00a6",
+ "\u0120miracle",
+ "\u0120Bun",
+ "\u0120Var",
+ "rimination",
+ "elect",
+ "\u0120Mult",
+ "\u0120delivering",
+ "eing",
+ "\u0120cm",
+ "nehmen",
+ "\u0120Line",
+ "\u0120\u00eb\u00a7\u012e",
+ "enced",
+ "\u0120Sound",
+ "\u0120Contin",
+ "ijd",
+ "UNG",
+ "kle",
+ "\u0120threshold",
+ "\u0120compact",
+ "adt",
+ "\u0120toes",
+ "\u0120Pur",
+ "owned",
+ "mented",
+ "\u0120designing",
+ "\u0120vaccinated",
+ "\u0120exhaust",
+ "\u0120basics",
+ "\u0120consists",
+ "\u0120Guy",
+ "aczy",
+ "\u0120m\u00c3\u0143",
+ "won",
+ "\u00e5\u00ae\u00b3",
+ "\u012085",
+ "\u00e6\u0124",
+ "\u0120mum",
+ "\u0120ignor",
+ "\u0120printing",
+ "acular",
+ "pow",
+ "\u0120expanding",
+ "\u0120gir",
+ "\u0120Cab",
+ "\u00ed\u013a\u00b8",
+ "\u00d1\u0124\u00d1\u012e\u00d1\u0123\u00d1\u0131",
+ "\u0120\u00ec\u0139\u00ac\u00eb\u0141\u00ac\u00eb\u00b6\u0126",
+ "\u0120angles",
+ "\u0120terminal",
+ "\u0120Won",
+ "\u0120Interesting",
+ "\u0120crossing",
+ "\u0120bonds",
+ "\u0120pueden",
+ "\u0120orb",
+ "lar\u00c4\u00b1n",
+ "\u0120creepy",
+ "\u0120nutrition",
+ "\u0120allies",
+ "\u0120wireless",
+ "\u0120desired",
+ "\u0120compute",
+ "\u0120Arizona",
+ "\u0120Beautiful",
+ "\u0120produces",
+ "\u0120nuestro",
+ "ted",
+ "\u0120eligible",
+ "\u0120\u00d1\u0123\u00d0\u00be\u00d0\u00b7",
+ "icial",
+ "\u0120Hero",
+ "\u0120consume",
+ "\u0120robots",
+ "\u0120purchased",
+ "cci\u00c3\u00b3n",
+ "\u0120iz",
+ "\u00c6\u00b0\u00e1\u00bb\u00a3c",
+ "\u00ce\u00af\u00ce\u00bd\u00ce\u00b1\u00ce\u00b9",
+ "\u0120\u00d8\u00a3\u00d9\u0128",
+ "\u0120shadows",
+ "\u0120Media",
+ "\u0120princess",
+ "\u0120klar",
+ "\u0120wooden",
+ "\u0120usar",
+ "\u0120g\u00c3\u00bczel",
+ "\u0120slot",
+ "rade",
+ "\u0120\u00eb\u0134",
+ "\u0120harmon",
+ "\u0120ingredient",
+ "orship",
+ "eki",
+ "\u0120grandfather",
+ "\u0120excitement",
+ "\u0120politicians",
+ "..!",
+ "\u0120outs",
+ "\u0120separately",
+ "\u0120\u00d1\u0131\u00d0\u00ba",
+ "\u0120Welt",
+ "\u0120Pow",
+ "jan",
+ "\u0120orientation",
+ "\u00e5\u0131\u012d",
+ "LC",
+ "agem",
+ "\u00db\u012e\u00da\u00ba",
+ "\u00e5\u0132\u0139",
+ "\u0120branches",
+ "aden",
+ "rente",
+ "\u0120Ihr",
+ "asm",
+ "\u0120est\u00c3\u00a3o",
+ "\u0120Nic",
+ "\u0120slave",
+ "\u0120compress",
+ "crowd",
+ "\u0120climbing",
+ "\u0120Management",
+ "\u0120Bah",
+ "\u0120panic",
+ "\u0120kor",
+ "\u0120cooling",
+ "\u0120bind",
+ "\u0120\u00d0\u00b7\u00d0\u00b0\u00d0\u00b4",
+ "\u0120rack",
+ "\u0120entit",
+ "\u0120sends",
+ "\u0120yourselves",
+ "des",
+ "\u0120Muslims",
+ "\u0120\u00ed\u013c",
+ "isma",
+ "cycle",
+ "unkt",
+ "\u0120Core",
+ "\u0120injuries",
+ "\u0120identical",
+ "\u00d0\u00ba\u00d0\u00b0\u00d1\u0131",
+ "\u0120Deutschland",
+ "\u0120\u00d0\u00b5\u00d0\u00b5",
+ "isan",
+ "\u0120truc",
+ "leton",
+ "\u0120backup",
+ "\u0120ultra",
+ "\u0120abund",
+ "illeurs",
+ "\u0120by\u00c5\u0124o",
+ "\u00e5\u0127\u0125",
+ "orted",
+ "\u0120earthqu",
+ "\u0120\u00d0\u00ba\u00d0\u00bb",
+ "\u0120observation",
+ "\u0120maintenant",
+ "elen",
+ "\u0120settled",
+ "\u0120pela",
+ "\u0120Econom",
+ "\u0120\u00d5",
+ "\u0120steering",
+ "\u0120ALL",
+ "\u0120Cher",
+ "\u0120patience",
+ "\u0120Snow",
+ "\u0120bor",
+ "\u0120worthy",
+ "\u0120c\u00c3\u00a1i",
+ "\u0120\u00d7\u00a7",
+ "\u0120\u00ce\u00ba\u00ce\u00b1",
+ "dog",
+ "\u0120Karen",
+ "illes",
+ "\u00ce\u00b2",
+ "\u0120agriculture",
+ "\u00d7\u0137\u00d7\u0141",
+ "\u0120Sean",
+ "\u0120sensors",
+ "\u00ed\u0137\u00b4\u00eb",
+ "agh",
+ "\u0120publicly",
+ "\u0120peux",
+ "\u0120Alexander",
+ "\u0120priorit",
+ "\u0120lazy",
+ "ardon",
+ "attering",
+ "\u0120costume",
+ "\u00d8\u00b3\u00d8\u00aa",
+ "\u00e8\u00bf\u013a",
+ "\u0120unw",
+ "\u00d0\u013d",
+ "\u0120thickness",
+ "quito",
+ "gunt",
+ "istas",
+ "neys",
+ "\u0120\u00eb\u0132\u013a\u00ea\u00b2\u012e",
+ "\u0120Brasil",
+ "\u0120token",
+ "\u0120affili",
+ "lon",
+ "\u0120f\u00c3\u00a5r",
+ "\u0120Beach",
+ "\u0120witch",
+ "\u0120Seven",
+ "\u0120pant",
+ "\u00ce\u00bb\u00ce\u00bb",
+ "\u0120captain",
+ "\u00e5\u013f",
+ "\u0120veut",
+ "\u0120pouvoir",
+ "acz",
+ "\u0120Barb",
+ "\u0120utility",
+ "\u0120contemporary",
+ "\u0120obtained",
+ "\u0120paintings",
+ "ear",
+ "\u0120pean",
+ "\u0120Og",
+ "\u0120cust",
+ "\u00d0\u00bb\u00d0\u00b5\u00d0\u00bc",
+ "\u0124\u013a\u00eb",
+ "\u0120Isso",
+ "\u0120aconte",
+ "\u0120Tele",
+ "\u0120Assistant",
+ "\u00c3\u012b",
+ "\u00ed\u0138\u012a\u00ec\u012c\u00b5\u00eb\u012d\u012a\u00eb\u012d\u00a4",
+ "\u0120counts",
+ "\u0120buck",
+ "\u0120Deep",
+ "\u0120tackle",
+ "\u0120harsh",
+ "\u0120decides",
+ "\u00e9\u0139\u013e",
+ ".\u00e2\u0122\u012d",
+ "\u00e9\u0124\u012c",
+ "\u0120Angel",
+ "\u0120laying",
+ "\u0120calories",
+ "\u0120controlling",
+ "\u0120advantages",
+ "\u0120\u00d1\u012f\u00d1\u0124\u00d0\u00be\u00d0\u00b9",
+ "\u0120approaching",
+ "\u0120threats",
+ "akan",
+ "ematic",
+ "mann",
+ "\u00ea\u00b3\u00b5",
+ "mumbles",
+ "aci\u00c3\u00b3",
+ "\u0120maintaining",
+ "\u0120founder",
+ "lah",
+ "fight",
+ "\u0120admitted",
+ "\u00e2\u0122\u00a6.",
+ "\u0137\u012e",
+ "abol",
+ "\u0120usage",
+ "\u0120nonsense",
+ "\u0120Palest",
+ "\u0120contre",
+ "\u0120Democratic",
+ "\u0120ER",
+ "jekt",
+ "\u0120arbit",
+ "\u0120\u00d0\u00b3\u00d0\u00be\u00d0\u00bb",
+ "\u0120Michelle",
+ "icher",
+ "esh",
+ "\u0120Pho",
+ "\u00d0\u00ba\u00d0\u00be\u00d0\u00bc",
+ "49",
+ "\u0120Energy",
+ "\u00ce\u00bf\u00cf\u012f",
+ "\u0120cents",
+ "\u0120refers",
+ "\u0120gospel",
+ "\u0120Sha",
+ "\u0120Share",
+ "\u00d7\u013b\u00d7\u0142",
+ "\u0120clinic",
+ "\u0120\u00eb\u0126\u00a3",
+ "\u0120equality",
+ "ugs",
+ "\u0120shed",
+ "\u0120planes",
+ "\u0120toute",
+ "reck",
+ "\u0120strand",
+ "\u0120biology",
+ "\u0120league",
+ "\u0120Pok",
+ "\u0120n\u00c3\u00bamero",
+ "\u0120Coast",
+ "\u0120consistently",
+ "\u0120nucle",
+ "OOOO",
+ "\u0120objet",
+ "\u0120chor",
+ "\u0120ginger",
+ "\u0120dabei",
+ "\u0120cooperation",
+ "\u00e0\u00af\u012f.",
+ "nten",
+ "\u00e7\u00a4",
+ "l\u00c3\u0142",
+ "\u00ec\u0138\u0133",
+ "rado",
+ "\u0120passive",
+ "\u0120gloves",
+ "\u0120underground",
+ "\u0120logical",
+ "\u0120ket",
+ "\u0120functionality",
+ "\u00b8\u00eb\u00a6\u00ac",
+ "\u0120portal",
+ "eller",
+ "\u00d7\u013b\u00d7\u00a8",
+ "\u0120Ted",
+ "\u0120Gre",
+ "\u0132\u013e",
+ "\u0120personnel",
+ "\u0120emerging",
+ "\u0120F\u00c3\u00bcr",
+ "\u0120meantime",
+ "usalem",
+ "\u0120Clear",
+ "\u0120trapped",
+ "\u0120\u00ec\u013c\u00b0",
+ "\u0120displ",
+ "\u0120mettre",
+ "\u0120municip",
+ "\u0120withdraw",
+ "\u0120spat",
+ "unes",
+ "\u0120accessibility",
+ "\u00e6\u012a\u0133\u00e4\u00bb\u00ac",
+ "\u0120apare",
+ "\u0120prospect",
+ "\u0120\u00d0\u00bd\u00d0\u00b0\u00d0\u00b7",
+ "\u0120copper",
+ "\u0120PRO",
+ "\u00cf\u0127\u00cf\u0126",
+ "\u0120attacking",
+ "\u0120Vin",
+ "\u0120Stone",
+ "\u0120investigate",
+ "style",
+ "\u0120\u00ce\u00bb",
+ "\u00eb\u00a1\u013f",
+ "\u00eb\u00a7\u012a",
+ "\u0120inspect",
+ "\u0120liver",
+ "\u00d0\u00b0\u00d0\u00bb\u00d0\u00b8\u00d1\u0123\u00d1\u012e",
+ "\u0120sera",
+ "halten",
+ "eman",
+ "\u0120ministry",
+ "''",
+ "\u0120dots",
+ "\u00e3\u0127\u012d\u00e3\u0127\u012d\u00e3\u0127\u012d\u00e3\u0127\u012d",
+ "\u00d1\u0125\u00d1\u0123\u00d1\u0124",
+ "\u0120Jak",
+ "AKE",
+ "\u0120gaps",
+ "ucker",
+ "\u0120\u00d0\u00b8\u00d0\u00bd\u00d1\u0124\u00d0\u00b5\u00d1\u0122\u00d0\u00b5\u00d1\u0123",
+ "\u0120Emily",
+ "\u0120interval",
+ "\u0120tender",
+ "\u0120Technology",
+ "game",
+ "\u0120trib",
+ "\u00d9\u0126\u00d8\u00a7",
+ "\u0120Development",
+ "\u00d9\u0127\u00d8\u00a7",
+ "\u0120wrist",
+ "\u0120fires",
+ "\u0120targeted",
+ "\u00ec\u0142\u0132",
+ "\u0120sod",
+ "\u00ed\u013c\u012e",
+ "\u0120oldu\u00c4\u0141",
+ "\u0120seasons",
+ "ventions",
+ "\u0120\u00d0\u00bd\u00d0\u00b5\u00d0\u00b3\u00d0\u00be",
+ "\u0120sometime",
+ "\u00d0\u00bb\u00d0\u00b8\u00d0\u00b2",
+ "n\u00c3\u00a9",
+ "\u0120t\u00c3\u00ba",
+ "\u0120Deus",
+ "\u0120execution",
+ "\u00c3\u00a1p",
+ "\u0120Change",
+ "\u0120Indeed",
+ "\u0120regulation",
+ "\u0120Hung",
+ "\u00c3\u00a9is",
+ "\u0120wishes",
+ "\u0120jazz",
+ "\u0120structural",
+ "\u0120blowing",
+ "\u0120by\u00c4\u0129",
+ "\u0120thermal",
+ "phant",
+ "\u00d1\u0122\u00d1\u0125\u00d0\u00b7",
+ "\u00d0\u00b0\u00d0\u00bd\u00d1\u0124",
+ "\u0120Pull",
+ "\u0120confusion",
+ "\u00d0\u00bd\u00d1\u012d\u00d0\u00bc\u00d0\u00b8",
+ "\u0120scenarios",
+ "\u00ec\u0142\u0123\u00ec\u013e\u00bc\u00eb\u00a1\u013e",
+ "\u0120\u00d0\u00b4\u00d0\u00b5\u00d1\u0124",
+ "\u0120tattoo",
+ "\u0120autre",
+ "\u0120heating",
+ "\u0120treating",
+ "\u0120\u00d0\u00bf\u00d0\u00be\u00d0\u00bd\u00d0\u00b8\u00d0\u00bc",
+ "\u0120exclus",
+ "\u0120LOL",
+ "wear",
+ "agle",
+ "\u0120zur\u00c3\u00bcck",
+ "\u0120rational",
+ "su",
+ "\u0120deter",
+ "\u0120Native",
+ "\u00e0\u00ae\u0137\u00e0\u00ae\u00b3",
+ "ached",
+ "\u0120\u00e3\u0125",
+ "\u0120Entonces",
+ "\u0120hora",
+ "\u00ec\u013f\u00b4\u00ec\u0139\u0132\u00ec\u013c\u0136",
+ "\u0120lite",
+ "\u00c3\u00ab",
+ "\u0120sixth",
+ "\u0120\u00d0\u00b1\u00d0\u00be\u00d0\u00bb\u00d0\u00b5\u00d0\u00b5",
+ "actor",
+ "\u0120psychology",
+ "\u00e7\u013d\u00b8",
+ "\u0120demands",
+ "\u0120peer",
+ "\u0120newly",
+ "\u0120WWE",
+ "Donald",
+ "\u0120Box",
+ "\u0120pine",
+ "\u0120loading",
+ "\u0120Nico",
+ "\u0120s\u00c5\u0124",
+ "omme",
+ "ART",
+ "\u0120recruit",
+ "\u0120bugs",
+ "arents",
+ "\u0120\u00d0\u00bf\u00d1\u0122\u00d0\u00be\u00d0\u00b1",
+ "\u0120Inside",
+ "ipper",
+ "dramatic",
+ "\u0120planets",
+ "orde",
+ "\u0120yoga",
+ "child",
+ "\u0120Marie",
+ "\u0120\u00e3\u0123\u0124",
+ "\u0120BL",
+ "\u0120filmed",
+ "\u0120refresh",
+ "\u0120tomatoes",
+ "\u0120fet",
+ "Qu\u00c3\u00a9",
+ "\u0120!!",
+ "\u0120\u00eb\u0124\u00b4\u00eb",
+ "rine",
+ "\u0120interactive",
+ "sal",
+ "annah",
+ "pez",
+ "\u00e7\u00b6\u0135",
+ "\u0120understands",
+ "\u0120Tokyo",
+ "\u0120libraries",
+ "\u0120reader",
+ "\u0133\u0132",
+ "oz",
+ "\u0120Ende",
+ "\u0120Flo",
+ "\u0120mild",
+ "\u0120poetry",
+ "\u0120\u00d0\u00b6\u00d0\u00b8\u00d0\u00b2",
+ "\u00e6\u0126\u013d",
+ "\u0120behave",
+ "\u0120doen",
+ "\u0120Susan",
+ "page",
+ "raham",
+ "\u0120communications",
+ "\u0120tuning",
+ "\u0120pac",
+ "\u0120anxious",
+ "IO",
+ "Mark",
+ "\u0120hi\u00c3\u00a7",
+ "books",
+ "\u0120piss",
+ "\u0120enabled",
+ "achelor",
+ "\u0120FOR",
+ "\u0120\u00c3\u00a9c",
+ "\u0120TR",
+ "ilst",
+ "hat",
+ "\u0120\u00ec\u013f\u012e",
+ "\u0120tych",
+ "\u0120jar",
+ "\u0120builds",
+ "\u0120Argent",
+ "\u0120intermedi",
+ "\u0120lou",
+ "\u0120ara",
+ "\u0120assignment",
+ "\u0120cabinet",
+ "\u0120retirement",
+ "\u00e3\u0123\u00bb",
+ "\u0120disabled",
+ "rica",
+ "\u0120awards",
+ "\u0120boots",
+ "\u0120acknowled",
+ "\u0120thy",
+ "\u0120\u00ea\u00b5\u00ac",
+ "\u0120synd",
+ "\u00d0\u00bd\u00d0\u00b8\u00d0\u00b9",
+ "ilton",
+ "\u0120probl",
+ "\u0120Fal",
+ "\u0120verdade",
+ "\u0120700",
+ "\u0120Learning",
+ "ocus",
+ "\u0120palace",
+ "Not",
+ "tain",
+ "cm",
+ "\u0120magnet",
+ "incoln",
+ "\u0120figuring",
+ "\u0120Lyn",
+ "\u0120Boss",
+ "\u0120VO",
+ "\u0120diagnosis",
+ "\u0120equipped",
+ "watch",
+ "inos",
+ "aders",
+ "\u0120shelf",
+ "\u0120organis",
+ "\u0120nod",
+ "\u0120k\u00c4\u00b1z",
+ "ppers",
+ "\u0120restore",
+ "\u0120artic",
+ "\u0120Voice",
+ "\u00c4\u00b1yorum",
+ "\u00ea\u00b2\u00a9",
+ "\u0120spreading",
+ "\u0120hips",
+ "\u0120ward",
+ "ureau",
+ "\u0120intersection",
+ "66",
+ "\u012039",
+ "\u00e7\u00b3",
+ "\u0120waited",
+ "\u00ec\u00b4",
+ "hhhh",
+ "\u0120dys",
+ "\u0120EN",
+ "\u0120batch",
+ "\u0120caf",
+ "\u0120marker",
+ "\u00e5\u00a4\u00a7\u00e5\u00ae\u00b6\u00e5\u00a5\u00bd",
+ "orable",
+ "\u00c3\u00b3ria",
+ "\u0120stepped",
+ "\u0120celebrating",
+ "\u00d0\u00b0\u00d0\u00bd\u00d0\u00b0",
+ "\u0120worn",
+ "\u0120Fol",
+ "\u0120pla",
+ "\u0120attempts",
+ "\u0120tweet",
+ "\u0120rust",
+ "gence",
+ "\u00ed\u0128\u00b5",
+ "\u0120revel",
+ "\u0120recept",
+ "eness",
+ "\u0120((",
+ "\u00e3\u0125\u00bc\u00e3\u0125",
+ "!\u00e2\u0122\u012d",
+ "\u0120\u00ec\u0128\u0132",
+ "\u0120influenced",
+ "\u00d0\u00b8\u00d0\u00b6",
+ "\u0120\u00d0\u00ba\u00d0\u00be\u00d0\u00bd\u00d0\u00b5\u00d1\u0129\u00d0\u00bd\u00d0\u00be",
+ "\u0120colleges",
+ "ioni",
+ "\u0120sag",
+ "Ann",
+ "olar",
+ "\u0120expressions",
+ "\u0120suits",
+ "\u0120ownership",
+ "eland",
+ "piece",
+ "\u00e6\u0122\u0130\u00e4\u00b9\u012a",
+ "\u0120despu\u00c3\u00a9s",
+ "\u0120tel",
+ "\u0120insult",
+ "\u0120\u00ea\u00b5\u012b\u00ec\u0140\u00a5",
+ "\u0120Small",
+ "\u0120FR",
+ "oka",
+ "berries",
+ "\u0120Anton",
+ "\u00d0\u00b5\u00d0\u00bb\u00d1\u0131",
+ "\u00d1\u0131\u00d1\u0123",
+ "\u0120valve",
+ "acts",
+ "\u0120woods",
+ "\u00e0\u00ae\u00a3",
+ "\u0120cultiv",
+ "\u0120f\u00c3\u00a1",
+ "\u00e3\u0123\u00a8\u00e3\u0123\u0126\u00e3\u0123\u0128",
+ "\u0120cheers",
+ "\u0120assumption",
+ "\u0120fitness",
+ "\u00c3\u0143cul",
+ "\u0120podr",
+ "\u0120weit",
+ "\u0120Hind",
+ "\u0120dign",
+ "\u0120\u00d0\u00b7\u00d0\u00bd",
+ "\u0120squad",
+ "\u0120destro",
+ "cere",
+ "shirt",
+ "immt",
+ "engers",
+ "\u0120s\u00c3\u00a4",
+ "k\u00c5\u0124ad",
+ "\u0120\u00c8\u013b",
+ "\u0120occas",
+ "\u0120\u00ec\u00a4\u0126",
+ "\u0120processor",
+ "\u0120DM",
+ "\u0120Daddy",
+ "\u0120sooner",
+ "\u0120straightforward",
+ "\u0120departments",
+ "\u0120Chrome",
+ "\u0120workplace",
+ "\u0120Python",
+ "\u0120meng",
+ "\u0120DAN",
+ "\u0120Ice",
+ "\u0120\u00eb\u012a\u012a",
+ "\u0120Gi",
+ "\u0120hiring",
+ "\u0120landed",
+ "\u0120democratic",
+ "iedz",
+ "\u00e3\u0123\u013a\u00e3\u0124\u0125",
+ "\u0120sev",
+ "icia",
+ "\u0120especial",
+ "\u0120Nous",
+ "\u0120h\u00c3\u00a4t",
+ "\u0120bou",
+ "pert",
+ "iesz",
+ "\u00e5\u0133\u0122",
+ "\u0120vil",
+ "\u00c5\u013dli",
+ "\u0120\u00c3\u00aen",
+ "\u0120losses",
+ "\u00e9\u0137\u00b7",
+ "\u0120toast",
+ "\u0120realm",
+ "\u0120Austin",
+ "\u0120Information",
+ "\u0120resume",
+ "\u0120chase",
+ "\u0120salary",
+ "\u0120\u00eb\u00b6\u0126",
+ "\u00d0\u00bb\u00d0\u00b8\u00d1\u0129",
+ "\u0120\u00d1\u0123\u00d0\u00bb\u00d0\u00b5\u00d0\u00b4",
+ "\u0120Further",
+ "\u0120caring",
+ "\u0120vig",
+ "\u0120valor",
+ "\u00e8\u00bf\u013b\u00e4\u00b8\u00aa",
+ "\u0120\u00d1\u0129\u00d0\u00b0",
+ "\u0120analytics",
+ "\u0120globe",
+ "\u0120MAN",
+ "\u0120nel",
+ "\u00ec\u013f\u00b4\u00ec\u0137\u00bc",
+ "\u0141\u00bc",
+ "\u0120oy",
+ "\u00ed\u0137\u013a\u00ec\u0126\u00b8\u00ec\u013c\u0136",
+ "jen",
+ "\u0120troubles",
+ "ahaha",
+ "\u0120churches",
+ "uet",
+ "\u0120measurements",
+ "bil",
+ "\u00ec\u00bd",
+ "ifully",
+ "\u00d0\u00b8\u00d0\u00bd\u00d1\u0125",
+ "\u0120Wilson",
+ "\u00a6\u00b4",
+ "\u0120\u00ed\u012e\u012e",
+ "\u0120\u00ec\u00b0\u00a8",
+ "\u0120p\u00c3\u00bablic",
+ "\u0120Jerusalem",
+ "\u0120nails",
+ "\u0120spine",
+ "\u0120hemos",
+ "\u0120zn",
+ "quis",
+ "\u0120Leben",
+ "\u0120references",
+ "ITH",
+ "iper",
+ "\u0120\u00d1\u0123\u00d0\u00b5\u00d0\u00b1\u00d1\u0131",
+ "\u00ec\u0123",
+ "\u0120Wa",
+ "state",
+ "\u00a7\u013f",
+ "\u00e5\u0127\u00b1",
+ "\u0120Gener",
+ "\u0120actress",
+ "\u0120Enjoy",
+ "\u00e0\u00b9\u0125",
+ "\u0120\u00d7\u0134",
+ "\u0120infected",
+ "\u0120shaking",
+ "\u0120nick",
+ "\u00e0\u00b8\u00b8",
+ "\u0120fot",
+ "\u0120accomplished",
+ "uke",
+ "\u0120sheets",
+ "\u0120fence",
+ "\u0120nursing",
+ "\u0120introducing",
+ "\u0120feat",
+ "One",
+ "TO",
+ "\u0120clubs",
+ "\u0120Bruce",
+ "onge",
+ "change",
+ "\u0120Batman",
+ "\u00e5\u0131\u00b0",
+ "\u0120Officer",
+ "\u0120hydro",
+ "\u0120supplement",
+ "\u0120cela",
+ "\u0120longest",
+ "\u0120competing",
+ "\u0120conhe",
+ "giving",
+ "\u0120brains",
+ "\u0120loans",
+ "\u0120wage",
+ "\u0120Clinton",
+ "\u0120s\u00c4\u0125",
+ "aneous",
+ "\u0120lord",
+ "\u00d1\u0122\u00d1\u0125\u00d0\u00b6",
+ "\u0120quiz",
+ "\u0120stiff",
+ "\u0120LGB",
+ "sz",
+ "ME",
+ "mare",
+ "there",
+ "\u0120n\u00c3\u00a4r",
+ "\u0120Mand",
+ "last",
+ "\u0120dag",
+ "\u0120halfway",
+ "\u0120Band",
+ "\u0120\u00eb\u012d\u00a4\u00ec\u012d\u013e",
+ "\u0120Aren",
+ "\u0120ile",
+ "PN",
+ "ento",
+ "\u0120algum",
+ "\u0120soccer",
+ "\u0120blocked",
+ "\u0120Jonathan",
+ "\u0120sew",
+ "\u0120Testament",
+ "\u0120vale",
+ "\u0120behavi",
+ "\u00e5\u00a7\u012d",
+ "\u0120conna",
+ "ICH",
+ "\u0120audiences",
+ "ml",
+ "ammad",
+ "\u0120\u00ec\u0124\u00b4\u00ec",
+ "IGH",
+ "\u0120races",
+ "emed",
+ "\u0120m\u00e1\u00bb\u013bt",
+ "\u00c3\u00af",
+ "\u0120overs",
+ "\u0120declared",
+ "\u0120sana",
+ "\u0120Una",
+ "\u0120\u00d1\u0122\u00d0\u00b5",
+ "ucks",
+ "\u0120pairs",
+ "\u0120ange",
+ "Ne",
+ "\u0120ups",
+ "avy",
+ "\u00c3\u00b8r",
+ "reek",
+ "\u0120behaviors",
+ "\u0120reflected",
+ "\u0120priorities",
+ "\u0120condu",
+ "\u0120retreat",
+ "\u0120expenses",
+ "\u0120\u00eb\u00b4\u0132",
+ "\u0120triple",
+ "\u0120\u00ea\u00b5\u012b\u00ec\u0140\u00a5\u00ed\u0140\u012a",
+ "\u00c3\u00a4lt",
+ "\u0120indigenous",
+ "\u0120mining",
+ "\u0120acceptable",
+ "\u0120ruin",
+ "CA",
+ "uine",
+ "\u0120pipeline",
+ "ctic",
+ "\u00c3\u00aat",
+ "\u0120\u00d0\u00b2\u00d1\u0123\u00d0\u00b5\u00d0\u00b3\u00d0\u00be",
+ "\u0120boun",
+ "\u0120Digital",
+ "\u0120Boom",
+ "\u00d1\u0128\u00d0\u00b5",
+ "\u0120\u00d0\u00bb\u00d1\u0125\u00d1\u0129",
+ "\u0120asc",
+ "\u012e\u0122\u00eb\u00a1\u013e",
+ "\u0120Goodbye",
+ "\u0120render",
+ "enez",
+ "arre",
+ "\u0120THAT",
+ "bour",
+ "ici\u00c3\u00b3n",
+ "\u00e3\u0124\u0143",
+ "Every",
+ "\u0120wires",
+ "\u0120Parliament",
+ "nung",
+ "ateur",
+ "\u0120Save",
+ "\u0120Phys",
+ "\u0120amor",
+ "\u0120Eve",
+ "\u0120fright",
+ "\u0120gamma",
+ "\u0120micros",
+ "mitt",
+ "\u0120Code",
+ "\u0120Bey",
+ "pled",
+ "\u0120\u00d0\u00b8\u00d1\u0123\u00d0\u00bf\u00d0\u00be\u00d0\u00bb\u00d1\u012e\u00d0\u00b7",
+ "\u00e7\u0139",
+ "\u00ec\u0125\u012b",
+ "\u00e5\u00a5\u00b9",
+ "\u0120monet",
+ "\u0120Jahre",
+ "\u0120luxury",
+ "\u0120deaf",
+ "\u0120betray",
+ "\u0120\u00ea\u00b2\u00b0",
+ "\u00d0\u00b8\u00d0\u00ba\u00d0\u00b8",
+ "\u0120defeated",
+ "\u0120undert",
+ "\u0120weg",
+ "\u0120cooler",
+ "\u00e3\u0123\u0137\u00e3\u0124\u0135",
+ "iami",
+ "\u00e9\u0124\u0126\u00e6\u013e\u012b",
+ "\u0120Jessica",
+ "\u0120Joy",
+ "\u0120sophistic",
+ "\u00d0\u00b5\u00d0\u00bd\u00d0\u00b8\u00d0\u00b8",
+ "\u00f0\u013f\u013a",
+ "\u0120chili",
+ "\u0120Type",
+ "\u0120proteins",
+ "\u0120presenting",
+ "alia",
+ "\u00ec\u013c\u00b8",
+ "\u0120Major",
+ "\u0120molecule",
+ "umer",
+ "\u0120collapse",
+ "\u0120Anyways",
+ "\u0120Mountain",
+ "anted",
+ "\u00e3\u0122\u0132",
+ "\u0120\u00d0\u00b2\u00d0\u00b8\u00d0\u00b4\u00d0\u00b5\u00d0\u00be",
+ "\u00e6\u00b0\u00b4",
+ "Aud",
+ "\u0120conqu",
+ "\u0120voll",
+ "\u0120knit",
+ "\u0120membr",
+ "\u0120Market",
+ "\u0120dari",
+ "\u0120calculated",
+ "\u00d0\u00b3\u00d0\u00b8",
+ "\u0120shrimp",
+ "\u0120Mu",
+ "\u0120\u00d0\u00bf\u00d1\u0122\u00d0\u00be\u00d1\u0124",
+ "\u0120\u00ec\u013a\u0123\u00ec\u0125\u0123",
+ "\u0120productivity",
+ "\u0120cognitive",
+ "\u0120Heb",
+ "ictions",
+ "\u00ea\u00b2\u00bd",
+ "\u0120cr\u00c3\u00a9",
+ "f\u00c3\u00b6r",
+ "\u0120praying",
+ "ashi",
+ "\u0120Tik",
+ "\u00c3\u00b3r",
+ "wen",
+ "\u00d1\u012e\u00d1\u0130",
+ "ixo",
+ "\u0120(\"",
+ "\u0120\u00d1\u0124\u00d0\u00b5\u00d0\u00bb",
+ "\u0120\u00ec\u0138\u00b4\u00eb\u0138\u00a4",
+ "\u0120\u00d0\u00bf\u00d0\u00b5\u00d1\u0122\u00d0\u00b5\u00d0\u00b4",
+ "\u0120Drive",
+ "\u00e3\u0122\u0133",
+ "\u0120Equ",
+ "\u0120equilibrium",
+ "\u0120describes",
+ "\u00d0\u00bd\u00d0\u00b5\u00d0\u00b5",
+ "42",
+ "\u0120Current",
+ "yy",
+ "\u0120absorb",
+ "\u0120soldier",
+ "ders",
+ "\u0120testimony",
+ "\u0120decline",
+ "\u013e\u00eb\u00a1\u013e",
+ "gage",
+ "\u0120inspire",
+ "lapping",
+ "\u0120spinning",
+ "\u0120slavery",
+ "\u0120facial",
+ "\u0120traditions",
+ "\u00c3\u00a1rios",
+ "\u0120Hospital",
+ "\u0120nest",
+ "\u0120\u00eb\u012a\u0126",
+ "\u0120toi",
+ "\u0120fears",
+ "\u00ec\u0127\u00a8",
+ "\u0120Muh",
+ "\u0120graduation",
+ "\u0120impacted",
+ "\u0120aunt",
+ "\u0120Lets",
+ "\u0120aluminum",
+ "\u0120dominant",
+ "\u0120Davis",
+ "\u0120Navy",
+ "\u0120compt",
+ "oples",
+ "\u0120estava",
+ "\u00e8\u00a5",
+ "\u0120scal",
+ "\u0120preserve",
+ "\u0120Opp",
+ "\u0120practically",
+ "\u0120magnitude",
+ "\u0120fitting",
+ "\u0120coordinate",
+ "\u0120furniture",
+ "\u0120Famil",
+ "\u0120explosion",
+ "\u0120documentary",
+ "\u0120Script",
+ "\u0120portray",
+ "mat",
+ "\u0120scheduled",
+ "\u0120dynamics",
+ "phy",
+ "aky",
+ "\u0120UI",
+ "Che",
+ "\u0120continuously",
+ "\u0120Prov",
+ "\u00e5\u00b0\u0133",
+ "\u00d1\u0125\u00d0\u00b7",
+ "rah",
+ "\u0120gerne",
+ "proof",
+ "\u0120secretary",
+ "\u0120Patreon",
+ "scream",
+ "\u0120Kids",
+ "\u00e1\u00bb\u0135i",
+ "\u0120kg",
+ "\u0120uncertainty",
+ "\u0120\u00d0\u00ba\u00d0\u00b0\u00d0\u00b6\u00d0\u00b4",
+ "\u0120mitig",
+ "\u0120reads",
+ "\u00e5\u00b7\u00b2",
+ "\u0120Ru",
+ "\u0120priest",
+ "\u0120\u00d0\u00bd\u00d0\u00b5\u00d0\u00b4",
+ "\u0120limitations",
+ "\u0120float",
+ "600",
+ "\u0120Toy",
+ "\u0120Jimmy",
+ "\u0120offensive",
+ "eni",
+ "\u0120Xi",
+ "\u0120eyebr",
+ "\u0120Turk",
+ "\u0120accidentally",
+ "\u0120ohne",
+ "\u0120Saud",
+ "95",
+ "\u0120Dutch",
+ "\u00d0\u00b0\u00d0\u00bd\u00d1\u0123",
+ "\u0120Seattle",
+ "\u0120\u00eb\u0135\u00b1",
+ "check",
+ "k\u00c4\u013b",
+ "\u0120contributions",
+ "\u0120beside",
+ "\u0120quindi",
+ "\u0120flew",
+ "\u00e6\u0139\u00b6",
+ "\u00d8\u00b0\u00d8\u00a7",
+ "\u0120LO",
+ "\u0120waist",
+ "\u0120EV",
+ "\u0120holidays",
+ "jon",
+ "\u0120misunder",
+ "\u00d1\u0131\u00d0\u00bd",
+ "\u0120bout",
+ "\u0120dimin",
+ "\u00e1\u00ba\u00bd",
+ "\u00c3\u00b3l",
+ "\u0120Grace",
+ "\u0120inputs",
+ "\u0120deny",
+ "\u0120forming",
+ "\u0120Bild",
+ "\u0120adequ",
+ "\u0120folk",
+ "\u0120rejected",
+ "semb",
+ "\u0120frustrated",
+ "open",
+ "\u0120Better",
+ "ilon",
+ "\u0120towel",
+ "\u0120differential",
+ "\u0120sacred",
+ "\u0120sail",
+ "\u00e9\u0129\u012e",
+ "entimes",
+ "\u0120gentleman",
+ "\u0120iconic",
+ "\u0120comparing",
+ "\u0120sagt",
+ "\u0120texts",
+ "\u0120grandma",
+ "\u0120rolls",
+ "\u0120contents",
+ "\u00e4\u00b8\u012f\u00e5\u00a5\u00bd",
+ "\u00d0\u00be\u00d1\u0123\u00d1\u0123",
+ "\u0120suspension",
+ "roit",
+ "\u00a6\u00bc",
+ "\u0120assez",
+ "\u0120dort",
+ "\u0120Math",
+ "\u0120Victor",
+ "\u0120JavaScript",
+ "\u00e4\u00b8\u012f\u00e5\u00b0\u012f",
+ "\u0120enhan",
+ "\u00c5\u013b",
+ "\u0120Bush",
+ "\u0120promotion",
+ "\u0120kin",
+ "\u0120monsters",
+ "\u0120Colorado",
+ "\u0120\u00ce\u00b2",
+ "\u00ed\u0137\u00b4\u00ec\u013c\u0136",
+ "\u00e6\u0143\u00a3",
+ "ifferent",
+ "\u0120naked",
+ "\u0120prod",
+ "etics",
+ "\u0120Woman",
+ "\u0120treatments",
+ "\u0120estoy",
+ "v\u00c3\u00a9",
+ "\u0120lifting",
+ "\u0120yapt",
+ "\u0120Rober",
+ "\u0120\u00ec\u00b9\u013e",
+ "\u0120substitute",
+ "aku",
+ "ridge",
+ "\u0120\u00ea\u00b1\u00b0\u00eb",
+ "\u0120responded",
+ "\u0120b\u00c3\u00a9",
+ "\u0120Engineer",
+ "\u0120transferred",
+ "\u00eb\u00b2",
+ "\u0120haber",
+ "oop",
+ "\u0120WE",
+ "\u0120vest",
+ "\u0120forty",
+ "\u0120DS",
+ "\u01202004",
+ "\u0120coaching",
+ "nom",
+ "\u0120Bab",
+ "\u0120nossa",
+ "\u0120Jake",
+ "\u0120gy",
+ "\u0120deleg",
+ "\u0120\u00ec\u0140\u0142",
+ "\u0120\u00d0\u00ba\u00d1\u0122\u00d0\u00b0\u00d1\u0123",
+ "\u0120standpoint",
+ "\u0120disad",
+ "\u0120artwork",
+ "Ad",
+ "illo",
+ "\u0120\u00c4\u0133\u00c6\u00b0\u00e1\u00bb\u00a3c",
+ "\u0120Prom",
+ "\u0120Lib",
+ "\u0120criticism",
+ "\u0120contacts",
+ "\u00d1\u0122\u00d0\u00b0\u00d0\u00bc",
+ "\u0120achievement",
+ "\u00d0\u0136\u00d0\u00b0",
+ "\u0120dissol",
+ "\u0120Vegas",
+ "\u0120streams",
+ "\u0120Kent",
+ "\u0120\u00d8\u00b9\u00d9\u0126\u00d9\u012b",
+ "\u0120radius",
+ "\u0120sucks",
+ "\u0120Ach",
+ "\u0120fi",
+ "oust",
+ "\u0120\u00d0\u00bb\u00d1\u0130\u00d0\u00b4\u00d0\u00b8",
+ "\u0120palette",
+ "\u0120Haz",
+ "\u0120Anthony",
+ "\u0120tema",
+ "\u0120Cos",
+ "\u0120safer",
+ "\u00ce\u00b1\u00cf\u0124",
+ "\u0120contrad",
+ "\u0120maior",
+ "\u0120inflation",
+ "\u0120Silver",
+ "\u0120attending",
+ "\u00ed\u0137\u013e\u00ed\u0127\u012e",
+ "arto",
+ "\u0120applauding",
+ "\u0120computing",
+ "\u0120Hat",
+ "\u00e6\u00bb",
+ "know",
+ "makers",
+ "\u0120conoc",
+ "\u0120educated",
+ "\u0120modified",
+ "\u0120inclusion",
+ "mental",
+ "\u0140\u0132",
+ "isia",
+ "\u0120\u00cf\u0122\u00ce\u00bf\u00cf\u0127",
+ "\u0120aun",
+ "\u0120Ireland",
+ "\u0120k\u00c3\u00b6",
+ "\u0120compliance",
+ "\u0120inspiring",
+ "\u00d0\u00b8\u00d1\u0124\u00d0\u00b5\u00d0\u00bb\u00d1\u012e\u00d0\u00bd\u00d0\u00be",
+ "\u0120dispos",
+ "\u00ec\u00b0\u00a8",
+ "\u0120wip",
+ "rical",
+ "rawd",
+ "\u0120tres",
+ "\u0120mobil",
+ "olutions",
+ "BO",
+ "\u0120bounce",
+ "\u0120assumed",
+ "\u0120Medical",
+ "\u0120fiscal",
+ "\u0120ng\u00c6\u00b0\u00e1\u00bb\u013fi",
+ "itionally",
+ "\u0120stolen",
+ "\u0120BM",
+ "\u0120mechanisms",
+ "\u00ce\u00b5\u00ce\u00af",
+ "\u0120qualified",
+ "\u0120\u00ec\u0140\u0132\u00eb",
+ "ughters",
+ "\u0120HIV",
+ "\u0120Lots",
+ "\u0120servers",
+ "\u0120carr",
+ "\u0120Together",
+ "\u0120attracted",
+ "\u0120kr",
+ "\u00e6\u012a\u0133\u00e6\u013a\u00af",
+ "thur",
+ "inin",
+ "\u0120Half",
+ "\u00c8\u013d",
+ "\u0120Pap",
+ "\u0120reminded",
+ "ALL",
+ "\u0120helmet",
+ "\u0120bottles",
+ "\u0120professors",
+ "\u0120seine",
+ "\u00c5\u0124\u00c4\u0127",
+ "\u00e3\u0125\u0131",
+ "\u0120\u00ea\u00b1\u00b0\u00ec\u0137\u00bc",
+ "\u0120\u00d7\u00a2\u00d7\u013e",
+ "fun",
+ "\u0120Bird",
+ "\u0120fighter",
+ "\u0120\u00eb\u0136\u00b0\u00eb",
+ "\u0120Tool",
+ "\u0120tin",
+ "inois",
+ "\u00eb\u00b6\u0126",
+ "\u00d7\u013b\u00d7\u0141",
+ "\u0120CAR",
+ "\u00e5\u0132\u012f",
+ "irsty",
+ "\u0120outdoor",
+ "\u0120NS",
+ "\u00e3\u0127\u0130",
+ "ffen",
+ "\u0120lud",
+ "Hello",
+ "\u0120roller",
+ "iele",
+ "\u0120Poland",
+ "\u0120apa",
+ "exp",
+ "\u0120certificate",
+ "\u0120Town",
+ "\u00d0\u00b0\u00d1\u0130\u00d1\u0124\u00d1\u0123\u00d1\u0131",
+ "ilde",
+ "\u0120determin",
+ "PR",
+ "\u0120freeze",
+ "\u0120mainstream",
+ "\u0120objectives",
+ "blo",
+ "\u0120takie",
+ "\u00e5\u0135\u012a\u00e5\u0135\u012a",
+ "\u0120\u00eb\u00b0\u0136\u00eb\u00a1\u013e",
+ "elet",
+ "\u0120IV",
+ "\u0120Fast",
+ "\u0120dere",
+ "emp",
+ "\u0120Dra",
+ "\u0120\u00ec\u0140\u012a\u00ec\u0139\u012a",
+ "\u0120discrimination",
+ "\u0120\u00ce\u00b5\u00ce\u00af\u00ce\u00bd\u00ce\u00b1\u00ce\u00b9",
+ "necess",
+ "\u00e6\u00ae",
+ "\u00c4\u00b1\u00c4\u0141\u00c4\u00b1",
+ "\u0120posting",
+ "wi\u00c5\u013dcie",
+ "\u0120lub",
+ "\u0120olive",
+ "\u0120rim",
+ "\u0120modeling",
+ "\u0120a\u00c3\u00b1o",
+ "\u0120Pakistan",
+ "\u0120overl",
+ "\u0120inflam",
+ "NE",
+ "\u00ec\u0139\u0132\u00ea\u00b2\u012e",
+ "\u0120attended",
+ "\u0120dealt",
+ "\u0120Alt",
+ "\u0120Lincoln",
+ "\u0120awake",
+ "\u0120filters",
+ "\u0120Within",
+ "czywi\u00c5\u013dcie",
+ "\u0120s\u00c3\u00bb",
+ "\u0120Johnny",
+ "\u0120integrity",
+ "\u0120isolation",
+ "\u0120Easy",
+ "\u0120\u00d0\u00bf\u00d1\u0122\u00d0\u00b8\u00d0\u00bd",
+ "\u0120Alice",
+ "\u0120smiling",
+ "enix",
+ ",...",
+ "\u00ce\u00b6",
+ "\u0120begun",
+ "\u0120jewel",
+ "\u0120conventional",
+ "\u0120statist",
+ "\u0120handed",
+ "\u0120irre",
+ "\u0120prohib",
+ "\u0120satellite",
+ "\u00e9\u00a6\u013b",
+ "\u0120Indust",
+ "\u0120traged",
+ "\u0120trava",
+ "\u0120ihm",
+ "\u0120cruel",
+ "\u0120Agora",
+ "\u0120Doc",
+ "\u0120zones",
+ "\u0120mall",
+ "\u0120tray",
+ "\u00d7\u0137\u00d7\u0142",
+ "\u0120irrit",
+ "\u0120kans",
+ "\u0120Beat",
+ "udge",
+ "ielle",
+ "\u0120trusted",
+ "\u0120bikes",
+ "\u0120\u00d1\u0125\u00d0\u00bf",
+ "\u0120Member",
+ "wick",
+ "\u0120creators",
+ "\u0120heritage",
+ "indistinct",
+ "\u0120resur",
+ "ennen",
+ "Come",
+ "\u0120firing",
+ "\u0120Bueno",
+ "\u0120\u00d0\u00a2\u00d0\u00be",
+ "ikan",
+ "ettes",
+ "\u0120kes",
+ "\u0120trips",
+ "\u0120divorce",
+ "\u0120Kl",
+ "\u0120consol",
+ "keep",
+ "\u00ea\u00b8\u00b0\u00ea\u00b0\u0122",
+ "\u0120Report",
+ "\u0120hosting",
+ "\u0120diamond",
+ "\u0120complic",
+ "\u0120helicop",
+ "\u0120depuis",
+ "ds",
+ "\u0120Chan",
+ "\u00d1\u0131\u00d0\u00bb",
+ "\u0120scissors",
+ "ilation",
+ "\u0120proportion",
+ "ERE",
+ "\u0120\u00d9\u012a\u00d8\u00a7\u00d9\u0126",
+ "inta",
+ "\u0120muchas",
+ "uation",
+ "itis",
+ "\u00e6\u012c\u012c",
+ "\u00d1\u0131\u00d1\u012b",
+ "\u0120niin",
+ "\u0120emphasize",
+ "uela",
+ "\u0120producers",
+ "\u0120rze",
+ "\u00c3\u00a4nder",
+ "ETH",
+ "\u00e6\u00ba",
+ "\u0120constitu",
+ "\u00e5\u013d\u00bd",
+ "\u0120performances",
+ "istle",
+ "gov",
+ "\u0120Liter",
+ "\u0120incorporate",
+ "\u0120educate",
+ "\u0120Nin",
+ "\u00ec\u00aa\u00bd",
+ "\u00d9\u0129\u00d9\u0127",
+ "eleration",
+ "\u00d7\u0137\u00d7\u0133",
+ "\u0120ya\u00c5\u0141",
+ "orous",
+ "\u0120Cas",
+ "\u0120grants",
+ "\u00eb\u012c\u00a5",
+ "amel",
+ "\u0120\u00ea\u00b7\u00b8\u00eb\u0142\u0129\u00ea\u00b2\u012e",
+ "\u0120Este",
+ "\u00d1\u0127\u00d0\u00be\u00d0\u00b4\u00d0\u00b8\u00d1\u0124",
+ "\u0120\u00d0\u00bf\u00d0\u00be\u00d1\u0123\u00d0\u00bb\u00d0\u00b5",
+ "\u0120gent",
+ "\u0120focuses",
+ "alities",
+ "\u0120Rh",
+ "\u00eb\u00b3\u00b4",
+ "\u00e6\u00b0\u0133",
+ "\u0120Dance",
+ "rr",
+ "\u0120amer",
+ "\u0120utilize",
+ "\u0120l\u00c3\u0143",
+ "\u0120Among",
+ "\u0120pregnancy",
+ "\u0120loops",
+ "\u00d0\u00b0\u00d0\u00bb\u00d0\u00be\u00d1\u0123\u00d1\u012e",
+ "\u0120Moh",
+ "\u0120catching",
+ "\u0120glob",
+ "\u0120ajud",
+ "\u0120[?",
+ "\u0120Anal",
+ "looking",
+ "\u0120surfaces",
+ "\u0120progressive",
+ "\u0120viral",
+ "08",
+ "\u00ce\u00be",
+ "KA",
+ "\u0120\u00c5\u00bcy",
+ "\u0120picks",
+ "annon",
+ "\u0120bulk",
+ "\u0120Ross",
+ "\u0120describing",
+ "\u0120Gel",
+ "\u0120locally",
+ "\u0120endless",
+ "\u0120massage",
+ "\u0120cleaned",
+ "\u0120traveled",
+ "\u00d0\u00b5\u00d0\u00bd\u00d1\u012d",
+ "\u0120sentiment",
+ "igma",
+ "\u0120Nas",
+ "\u0120chemicals",
+ "\u0120righteous",
+ "\u0120Magic",
+ "\u0120relates",
+ "\u0120trucks",
+ "\u01201960",
+ "\u00e5\u012a\u00a5",
+ "\u0120appet",
+ "\u0120snacks",
+ "\u0120Summer",
+ "\u0120y\u00c3\u00bcz",
+ "\u0120pris",
+ "\u0120Mexican",
+ "\u0120transparen",
+ "\u0120minority",
+ "\u0120verte",
+ "\u0120lassen",
+ "46",
+ "\u00d0\u00bb\u00d0\u00b5\u00d0\u00ba",
+ "\u00c3\u00a9p",
+ "\u0120\u00d1\u0126\u00d0\u00b8\u00d0\u00bb\u00d1\u012e",
+ "\u0120iyi",
+ "\u0120span",
+ "\u00ed\u0137\u013a\u00ec\u00a7\u0122",
+ "\u0120indicated",
+ "quar",
+ "\u0120scholarship",
+ "\u0120LGBT",
+ "\u0120historically",
+ "\u00c3\u00b3\u00c5\u0124",
+ "\u0120minist",
+ "\u0120penet",
+ "\u0120Rap",
+ "\u0120conservation",
+ "\u00e7\u013d\u00b4",
+ "\u0120Honey",
+ "\u0120Bei",
+ "idel",
+ "\u0120responsibilities",
+ "\u0120messy",
+ "\u0120Except",
+ "ORE",
+ "\u0120initiatives",
+ "\u0120junior",
+ "\u0120designers",
+ "\u0120exploration",
+ "\u0120sponsor",
+ "\u0120mobility",
+ "\u0120integ",
+ "lando",
+ "\u0120bark",
+ "\u0120indicates",
+ "\u00e0\u00b6",
+ "\u0120employer",
+ "\u00e5\u00ae\u012b",
+ "\u0120cousin",
+ "\u0120boiling",
+ "\u0120chrom",
+ "\u0120\u00c3\u00a7al",
+ "\u0120perpet",
+ "\u0120contained",
+ "\u0120parks",
+ "\u00d0\u00ab",
+ "\u0120Engineering",
+ "Please",
+ "\u0120Starting",
+ "hero",
+ "\u0120lawyers",
+ "\u00e8\u00a5\u00bf",
+ "\u0120zd",
+ "\u0120franchise",
+ "rage",
+ "\u0120intuit",
+ "\u0120GL",
+ "reach",
+ "\u0120Elle",
+ "\u0120nh\u00c6\u00b0",
+ "\u0120Nord",
+ "\u0120bean",
+ "07",
+ "\u0120pleasant",
+ "\u00e5\u00bd\u0135",
+ "viron",
+ "\u0120gradient",
+ "zus",
+ "\u0120EM",
+ "\u0120essay",
+ "\u00ec\u0139\u0132\u00ec\u013c\u0136",
+ "\u00e1\u00ba\u00bfn",
+ "nu",
+ "\u00e1\u00bb\u00ab",
+ "\u0120\u00c3\u012bs",
+ "\u0120denomin",
+ "\u0120Girls",
+ "\u0120personnes",
+ "\u0120\u00d8\u00a7\u00d9\u0126\u00d8\u00a3",
+ "bild",
+ "\u0120Stat",
+ "\u0120compliment",
+ "\u0120Kate",
+ "\u0120optimal",
+ "\u0120hid",
+ "\u00d8\u00af\u00d9\u012c",
+ "\u0120quicker",
+ "wall",
+ "En",
+ "INE",
+ "???",
+ "\u00ec\u00b2\u00b4",
+ "\u0120Action",
+ "\u00e5\u0141",
+ "\u0120penalty",
+ "\u0120Kaz",
+ "'?",
+ "\u0120cried",
+ "\u0120canvas",
+ "fte",
+ "\u0120exclud",
+ "\u00b8\u00eb\u00a1\u013e",
+ "\u0120emphasis",
+ "\u0120enzy",
+ "\u0120Hou",
+ "\u0120overseas",
+ "\u00c3\u0143amos",
+ "\u00e5\u00b8\u00ab",
+ "\u00c3\u00b6glich",
+ "\u0120headphones",
+ "cn",
+ "\u0120Age",
+ "\u0120akan",
+ "\u0120characteristic",
+ "\u00ed\u0137\u013a\u00eb\u00a9\u00b4",
+ "gets",
+ "\u0120\u00eb\u00b6\u012a",
+ "\u0120rival",
+ "\u0120borders",
+ "emente",
+ "em\u00c3\u00a1s",
+ "\u0120yol",
+ "\u0120compe",
+ "enders",
+ "\u00c4\u00b1ndan",
+ "\u0120m\u00c3\u00b6glich",
+ "\u0120bubbles",
+ "natural",
+ "\u0120armed",
+ "\u0120elabor",
+ "\u0120\u00ec\u013f\u00b4\u00eb\u00b2\u012a",
+ "\u0120washed",
+ "\u00ce\u00bf\u00cf\u0127\u00ce\u00bc\u00ce\u00b5",
+ "\u00e8\u00ab\u012d",
+ "\u0120flavors",
+ "\u0120existe",
+ "\u0120prest",
+ "\u0120Thema",
+ "\u00d0\u00be\u00d0\u00bf\u00d1\u0122\u00d0\u00be\u00d1\u0123",
+ "eron",
+ "UE",
+ "eri",
+ "\u0120concer",
+ "\u0120aix\u00c3\u00b2",
+ "\u00e5\u0127\u00a9",
+ "\u0120protective",
+ "\u0120\u00d0\u00b7\u00d0\u00bd\u00d0\u00b0\u00d1\u0130",
+ "\u0120\u00eb\u0124\u0142",
+ "\u0120III",
+ "\u0120meer",
+ "\u0120Shop",
+ "lli",
+ "\u0120Order",
+ "\u0120MY",
+ "\u0120Ghost",
+ "\u00e3\u0124\u0124\u00e3\u0123\u0128",
+ "adel",
+ "\u0120stole",
+ "\u0120releasing",
+ "\u0120Comment",
+ "\u0120trains",
+ "\u00eb\u00aa\u0127",
+ "\u0120wissen",
+ "ensed",
+ "\u0120descend",
+ "\u0120fier",
+ "\u0120radi",
+ "\u0120persu",
+ "\u00e7\u00a2",
+ "\u0120\u00d0\u00bc\u00d0\u00bd",
+ "\u0120Dest",
+ "\u0120worries",
+ "itet",
+ "bas",
+ "\u0120stab",
+ "name",
+ "oric",
+ "\u0120Close",
+ "\u0120alumni",
+ "\u0120Self",
+ "ffe",
+ "itating",
+ "atherine",
+ "\u0120Rights",
+ "\u0120ellos",
+ "\u0120warrant",
+ "\u0120nerve",
+ "\u0120vegetable",
+ "\u0120Teil",
+ "\u0120\u00ea\u00b0\u013b\u00ec\u013f\u00b4",
+ "RY",
+ "\u0120sustainability",
+ "\u0120steht",
+ "\u0120brid",
+ "ada\u00c5\u0141",
+ "\u0120tv",
+ "\u0120duration",
+ "\u0120pessoa",
+ "\u0120metrics",
+ "\u0120adam",
+ "cas",
+ "\u00d0\u00b0\u00d1\u0122\u00d0\u00b8",
+ "\u0120evident",
+ "\u0120displayed",
+ "\u00d8\u00a7\u00d8\u00a6",
+ "\u0120reck",
+ "\u0120Buddha",
+ "\u0120dele",
+ "\u0120Diego",
+ "osph",
+ "\u0120bla",
+ "\u0120Mik",
+ "ulator",
+ "\u01202001",
+ "\u0120promoting",
+ "ych",
+ "\u0120EX",
+ "\u0120lastly",
+ "\u0120outline",
+ "\u0120spirits",
+ "\u0120veux",
+ "\u0120subtract",
+ "\u0120\u00c5\u0141imdi",
+ "\u0120pins",
+ "\u0120burger",
+ "\u0120molto",
+ "\u0120hab\u00c3\u0143a",
+ "\u0120\u00eb\u00b0\u013a",
+ "igu",
+ "erst",
+ "\u0120nen",
+ "\u0120bacon",
+ "itious",
+ "\u0120carries",
+ "\u0120promises",
+ "nde",
+ "\u0120Left",
+ "\u0120Lim",
+ "\u00e6\u00a3",
+ "\u012044",
+ "\u0120careers",
+ "\u0120\u00ec\u00a3\u00bc\u00eb",
+ "\u0120speeds",
+ "qu\u00c3\u00a9",
+ "mad",
+ "market",
+ "isme",
+ "\u01202003",
+ "\u0120recess",
+ "\u0120JUD",
+ "\u0120racist",
+ "\u0120Schl",
+ "\u0120parler",
+ "\u0120otros",
+ "ishes",
+ "\u0120converted",
+ "aaaa",
+ "\u00d0\u00b0\u00d0\u00bd\u00d0\u00b8\u00d0\u00b8",
+ "\u0120Ark",
+ "\u0120Chance",
+ "\u0120elementary",
+ "\u00ce\u00b5\u00ce\u00bd",
+ "inks",
+ "Interviewer",
+ "\u0120freely",
+ "alah",
+ "\u0120\u00eb\u012d\u00a4\u00eb\u00a5\u00b8",
+ "\u0120requested",
+ "\u0120torque",
+ "no\u00c5\u013dci",
+ "oured",
+ "\u0120Staff",
+ "\u0120stain",
+ "\u0120Alan",
+ "\u0120vere",
+ "\u0120Winter",
+ "\u0120defect",
+ "iedy",
+ "\u0120beats",
+ "\u0120h\u00c3\u00a1",
+ "umn",
+ "oons",
+ "itudes",
+ "\u0120seit",
+ "oly",
+ "\u0120reserv",
+ "\u0120extr",
+ "\u0120physician",
+ "visor",
+ "\u0120handful",
+ "\u0120Nations",
+ "\u0120\u00ec\u00a2\u012d\u00ec\u013f\u0122",
+ "uccess",
+ "\u0120upstairs",
+ "\u0120Square",
+ "\u0120hein",
+ "\u0120Season",
+ "olis",
+ "\u0120prince",
+ "\u0120defensive",
+ "\u00e7\u00bd",
+ "\u0120\u00d0\u00bc\u00d0\u00b5\u00d1\u0123\u00d1\u0124",
+ "\u00d1\u0138\u00d0\u00b9",
+ "\u0120\u00d8\u00a7\u00d9\u0128",
+ "umble",
+ "\u00ea\u00b9\u012e\u00ec\u013c\u0136",
+ "\u0120assass",
+ "\u0120circular",
+ "\u0120qualities",
+ "\u0120hmm",
+ "\u0120blown",
+ "\u0120Liz",
+ "\u0120Kur",
+ "\u0120SA",
+ "\u0120findings",
+ "\u0120colours",
+ "\u0120delle",
+ "\u0120IR",
+ "\u0120Ath",
+ "\u0120Dub",
+ "\u0120Ox",
+ "\u0120\u00d8\u00ae",
+ "\u0120pockets",
+ "\u0120grill",
+ "\u0120switching",
+ "\u0120preferred",
+ "\u0120Wales",
+ "\u0120exemplo",
+ "\u0120chopped",
+ "\u0120vaccination",
+ "\u0120neuro",
+ "\u0120specify",
+ "ivos",
+ "\u0120ser\u00c3\u00a1",
+ "\u0120zie",
+ "\u0120\u00e0\u00ae\u00ae",
+ "\u0120resulting",
+ "\u0120Ugh",
+ "\u0120messed",
+ "CD",
+ "\u0120paar",
+ "\u0120comer",
+ "\u0120couch",
+ "\u0120Festival",
+ "\u012049",
+ "vous",
+ "zens",
+ "\u00e7\u00a8\u00ae",
+ "\u0120Kennedy",
+ "\u0120Ts",
+ "\u0120\u00eb\u00b3\u00b4\u00ec\u0139",
+ "\u0120demonstration",
+ "\u0120unto",
+ "\u0120frustrating",
+ "\u0120laboratory",
+ "\u0120egy",
+ "\u0120beautifully",
+ "\u0120\u00ec\u0140\u00ac\u00eb",
+ "\u0120algu",
+ "\u0120\u00c3\u00b6yle",
+ "\u00e4\u00bd\u0142\u00e7\u013e\u012d",
+ "\u0120PH",
+ "\u0120fortune",
+ "\u0120cleaner",
+ "\u0120Robin",
+ "\u0120saus",
+ "\u0120Geld",
+ "\u0120kat",
+ "obs",
+ "\u0120olur",
+ "\u0120matt",
+ "\u0120questa",
+ "\u0120suggestion",
+ "encer",
+ "\u00d0\u00be\u00d1\u0123\u00d1\u0124",
+ "\u0120radar",
+ "\u0120\u00ec\u0140\u00a1",
+ "isha",
+ "\u00e0\u00ae\u00a8",
+ "\u00e3\u0124\u0135\u00e3\u0123\u00aa",
+ "jes",
+ "\u0120veel",
+ "\u00ec\u0124\u00b0",
+ "\u0120authors",
+ "\u00e3\u0122\u0130",
+ "plan",
+ "\u0120collaborative",
+ "\u0120instinct",
+ "\u0120farming",
+ "auge",
+ "Edu",
+ "\u0120membership",
+ "\u0120simultaneously",
+ "\u0120bake",
+ "\u0120k\u00c3\u00a4",
+ "\u0120lectures",
+ "\u00d1\u0129\u00d0\u00b5\u00d1\u0123",
+ "\u0120prendre",
+ "\u0120collaps",
+ "\u0120Saya",
+ "\u0120Fut",
+ "\u0120yog",
+ "\u0120Rather",
+ "\u00d8\u00b1\u00d9\u012c",
+ "\u0120camps",
+ "\u00d0\u00be\u00d0\u00bb\u00d0\u00be\u00d0\u00b4",
+ "\u0120simulation",
+ "\u0120Mak",
+ "Laughs",
+ "\u0120grey",
+ "\u0120sentences",
+ "yen",
+ "\u0120Unless",
+ "Je",
+ "\u0120Satan",
+ "\u0120\u00d1\u0124\u00d0\u00b0\u00d0\u00ba\u00d0\u00b6\u00d0\u00b5",
+ "\u0120NA",
+ "\u0120bron",
+ "\u0120?]",
+ "\u0120souls",
+ "\u0120lightning",
+ "\u0120imagined",
+ "\u0120czyli",
+ "psilon",
+ "etta",
+ "\u0120believing",
+ "\u0120strongest",
+ "\u0120CON",
+ "\u0120quelques",
+ "\u0120immigrants",
+ "\u0120wallet",
+ "\u00e9\u0122\u013b\u00e6\u013a\u00af",
+ "\u0120Jersey",
+ "\u0120implications",
+ "\u0120forb",
+ "\u00e3\u0122\u0131",
+ "\u0120unbelievable",
+ "\u00d8\u00a7\u00d8\u00a1",
+ "\u0120operational",
+ "\u00c3\u00bcs",
+ "\u0120GM",
+ "\u0120\u00ea\u00b7\u00b8\u00eb\u0141\u00b0\u00eb\u012f\u00b0",
+ "\u0120gracias",
+ "\u0120entend",
+ "\u0120Regard",
+ "rob",
+ "\u0120\u00d1\u0124\u00d0\u00b5\u00d1\u0127",
+ "\u00e8\u0131",
+ "\u0120Revolution",
+ "\u0120waar",
+ "\u0120Biz",
+ "theless",
+ "\u0120sponsored",
+ "quier",
+ "\u0120\u00ec\u013f\u00bc\u00eb",
+ "\u0120tek",
+ "\u0120\u00eb\u0132\u0142",
+ "igkeit",
+ "\u0120Luck",
+ "\u0120Certainly",
+ "\u0120toll",
+ "\u0120\u00d0\u00bd\u00d0\u00b8\u00d1\u0129\u00d0\u00b5\u00d0\u00b3\u00d0\u00be",
+ "\u0120Money",
+ "\u0120\u00d1\u0123\u00d1\u0124\u00d0\u00be\u00d1\u0122",
+ "\u0120Double",
+ "\u0120Wolf",
+ "\u0120chunk",
+ "\u00ce\u00ac\u00ce\u00bd",
+ "it\u00c3\u00a9s",
+ "oning",
+ "Mar",
+ "\u0120grandes",
+ "\u0120collections",
+ "\u0120Europa",
+ "\u0120\u00d0\u00b0\u00d1\u0122",
+ "\u0120\u00e2\u0122\u012d\u00e2\u0122\u012d\u00e2\u0122\u012d",
+ "\u0120\u00ea\u00b7\u00b8\u00eb\u0141\u00ac\u00eb\u00a9\u00b4",
+ "\u0120\u00d0\u00be\u00d0\u00b1\u00d1\u012c",
+ "\u0120\u00e3\u0123\u00aa",
+ "\u0120\u00ec\u012d\u013e\u00ea\u00b0\u0126",
+ "\u0120Custom",
+ "\u0120\u00ec\u00b2\u013a",
+ "\u00d1\u0138\u00d0\u00bb\u00d1\u012e",
+ "\u0120individually",
+ "\u00ed\u0139",
+ "\u0120dozen",
+ "\u0120owe",
+ "\u0120Victoria",
+ "\u00e5\u0131\u00af\u00e8\u0125\u00bd",
+ "\u0120beet",
+ "urb",
+ "\u0120analog",
+ "i\u00c3\u00a7\u00c3\u00a3o",
+ "\u0124\u013e",
+ "soever",
+ "\u0120modo",
+ "\u0120subscribed",
+ "\u00ec\u0140\u00ac",
+ "\u0120entities",
+ "\u00e7\u012b\u0129",
+ "\u0120closet",
+ "\u0120responding",
+ "\u0120printer",
+ "\u0120Stephan",
+ "\u0120by\u00c5\u0124",
+ "\u0120Dom",
+ "\u0120Fern",
+ "\u0120Pier",
+ "\u0120wi\u00c4\u013bc",
+ "\u0120hence",
+ "\u0120modules",
+ "\u00e3\u0125\u00ac",
+ "\u0120\u00eb\u0136\u00b1",
+ "\u0120Danny",
+ "\u0120\u00d1\u0123\u00d0\u00b5\u00d0\u00b1\u00d0\u00b5",
+ "\u0120vad",
+ "\u0120\u00ec\u0139\u0126",
+ "\u0120sous",
+ "\u0120sphere",
+ "BY",
+ "\u0120Ped",
+ "igned",
+ "\u0120wheat",
+ "\u0120unders",
+ "\u0120evolve",
+ "\u0120declar",
+ "\u0120lightly",
+ "\u0120identifying",
+ "\u00e6\u0126\u0131\u00e6\u0122\u013f",
+ "\u0120legendary",
+ "\u0120genuine",
+ "\u0120grind",
+ "\u0120Une",
+ "geben",
+ "\u0120bicy",
+ "\u0120jumps",
+ "\u0120province",
+ "zi\u00c4\u013b",
+ "\u0120\u00d7\u0132\u00d7\u0142\u00d7\u013b",
+ "\u0120hoc",
+ "\u0120\u00d0\u00b1\u00d0\u00bb",
+ "\u0120Grad",
+ "\u0120revenge",
+ "\u0120\u00d8\u00a7\u00d9\u0126\u00d8\u00aa",
+ "ooh",
+ "\u00e6\u012d\u013e",
+ "\u00d0\u00b0\u00d1\u0128\u00d0\u00b8\u00d0\u00b8",
+ "\u00e5\u00b9\u00b3",
+ "\u0120electro",
+ "\u0120\u00eb\u0132\u0132",
+ "\u00e3\u0123\u00a7\u00e3\u0123\u00af",
+ "\u0120fals",
+ "riel",
+ "oker",
+ "\u0120Excellent",
+ "\u0120Morgan",
+ "\u0120brick",
+ "\u0120substantial",
+ "\u0120pollution",
+ "\u0120T\u00c3\u00bcr",
+ "\u0120Evet",
+ "\u0120lung",
+ "\u00e3\u0123\u0138",
+ "\u00d7\u013b\u00d7\u00a9",
+ "ommes",
+ "\u0120realizing",
+ "\u0120humble",
+ "\u0120Lock",
+ "\u0120bod",
+ "\u0120\u00ec\u0138\u00b8",
+ "\u0120peers",
+ "uzz",
+ "\u0120embedded",
+ "\u0120claro",
+ "\u0120aggreg",
+ "\u0120employers",
+ "\u0120Raj",
+ "\u0120\u00e3\u0123\u00a8",
+ "\u0120Yi",
+ "\u0120jeu",
+ "aters",
+ "\u0120strikes",
+ "nos",
+ "autres",
+ "dr",
+ "opher",
+ "\u0120Apparently",
+ "\u00ed\u013a\u0126",
+ "\u0120infant",
+ "\u00d8\u00a7\u00d8\u00a8",
+ "\u00d1\u0124\u00d1\u012d",
+ "\u00ed\u013d",
+ "\u00da\u00af",
+ "\u0120redes",
+ "aca\u00c4\u0141\u00c4\u00b1m",
+ "\u0120DAVID",
+ "\u0120Chicken",
+ "\u0120perspectives",
+ "\u0120viewer",
+ "\u0120shar",
+ "\u0120\u00d0\u00bf\u00d1\u0122\u00d0\u00be\u00d0\u00b8\u00d0\u00b7",
+ "ligt",
+ "eros",
+ "itable",
+ "\u00d0\u00b8\u00d0\u00bb\u00d0\u00be\u00d1\u0123\u00d1\u012e",
+ "\u0120dif\u00c3\u0143",
+ "\u00b4\u00eb\u012f\u00b0",
+ "\u0120retired",
+ "\u0120thats",
+ "zenie",
+ "beiten",
+ "\u0120mycket",
+ "\u0120Rab",
+ "\u0120inflamm",
+ "\u00ec\u00b0\u00ae",
+ "\u0120dum",
+ "\u0120daddy",
+ "\u00e6\u013e\u0141",
+ "\u0120immers",
+ "\u0120playlist",
+ "\u00e0\u00af\u0128",
+ "\u0120traum",
+ "\u0120refuse",
+ "step",
+ "\u00e0\u00ae\u013c",
+ "cup",
+ "\u0120pops",
+ "rimin",
+ "ay\u00c4\u00b1m",
+ "\u0120ald",
+ "\u0120unnecess",
+ "\u0120dah",
+ "\u0120Irish",
+ "\u0120compr",
+ "la\u00c5\u0141",
+ "TP",
+ "\u0120translated",
+ "Sc",
+ "ce\u00c4\u0141im",
+ "\u00b4\u0132",
+ "\u0120drei",
+ "\u0120\u00d0\u00bb\u00d1\u0130\u00d0\u00b4\u00d0\u00b5\u00d0\u00b9",
+ "\u0120quiero",
+ "\u0120hele",
+ "zlich",
+ "\u0120apples",
+ "\u0120districts",
+ "\u0120credits",
+ "\u0120asp",
+ "\u0120\u00eb\u012d\u00a8",
+ "oral",
+ "\u00e5\u00bd\u00b1",
+ "\u0120stepping",
+ "\u0120Va",
+ "\u0120gains",
+ "65",
+ "\u0120nuestra",
+ "eday",
+ "assador",
+ "\u0120Lind",
+ "\u0120crops",
+ "ciendo",
+ "igue",
+ "\u0120bana",
+ "Am",
+ "\u0120pent",
+ "\u0120addiction",
+ "\u0120packaging",
+ "\u00c3\u00a4d",
+ "\u00aa\u00a8",
+ "\u0120perqu\u00c3\u00a8",
+ "\u0120campaigns",
+ "\u0120steep",
+ "\u0120neue",
+ "\u0120embarrassed",
+ "\u0120distinction",
+ "itzer",
+ "\u00e5\u0133\u012c",
+ "\u0120registration",
+ "\u0120llam",
+ "\u0120Almighty",
+ "liest",
+ "\u0120uz",
+ "nak",
+ "\u00e7\u00ba",
+ "\u0120teraz",
+ "iamente",
+ "\u0120transactions",
+ "\u0120c\u00c3\u00b4t",
+ "\u0120switched",
+ "\u0120combo",
+ "\u0120prayers",
+ "\u0120internship",
+ "\u0120addresses",
+ "\u0120charity",
+ "\u0120WOO",
+ "\u0120bait",
+ "\u00e8\u00bf\u0129",
+ "\u0120\u00ef\u00bf\u00bd",
+ "\u0120fica",
+ "\u0120Tyler",
+ "aru",
+ "\u0120atoms",
+ "\u0120Level",
+ "\u0120\u00d0\u00bf\u00d0\u00be\u00d1\u0124\u00d0\u00be\u00d0\u00bc",
+ "\u0120fame",
+ "ulk",
+ "\u0120teaches",
+ "\u0120rebuild",
+ "\u00d0\u00b5\u00d0\u00b4\u00d1\u012e",
+ "\u0120Indonesia",
+ "ushi",
+ "\u0120Short",
+ "\u0120ensuring",
+ "fs",
+ "ele",
+ "\u0120marginal",
+ "\u0120conclude",
+ "amt",
+ "\u0120verify",
+ "\u0120McDonald",
+ "\u0120skal",
+ "\u0120reconst",
+ "\u0120Mann",
+ "\u0120basement",
+ "\u0120transformed",
+ "\u0120occasionally",
+ "zone",
+ "\u0120Dans",
+ "\u0120\u00d0\u00ba\u00d0\u00b0\u00d0\u00ba\u00d0\u00be\u00d0\u00b9",
+ "\u0120diagnosed",
+ "\u0120\u00cf\u0126\u00ce\u00b1",
+ "\u0120commands",
+ "\u0120presidential",
+ "\u0120abb",
+ "\u0120bracket",
+ "\u0120Lem",
+ "\u00c3\u00a5ng",
+ "\u0120favorites",
+ "\u0120revol",
+ "\u0120\u00ed\u012c\u00b9",
+ "\u0120harass",
+ "\u00e9\u0127",
+ "\u0120cleans",
+ "st\u00c3\u00a4nd",
+ "\u0120knocked",
+ "\u0120peoples",
+ "\u0120musicians",
+ "\u0120mutual",
+ "\u0120Cold",
+ "88",
+ "zej",
+ "atie",
+ "\u0120Honor",
+ "\u0120obsessed",
+ "\u0120MUSIC",
+ "\u0120Break",
+ "\u00c3\u00bang",
+ "\u0120modify",
+ "\u0120s\u00c3\u00b6yle",
+ "\u0120\u00d7\u0140\u00d7\u0136",
+ "\u0120Online",
+ "fo",
+ "\u0120Miller",
+ "\u0120liking",
+ "\u0120inhab",
+ "\u0120gratitude",
+ "\u0120Journal",
+ "arness",
+ "John",
+ "\u0120Git",
+ "\u00e5\u012b\u013d",
+ "\u0120sincere",
+ "\u0120Sci",
+ "\u0120Eli",
+ "\u0120symbols",
+ "\u0120manually",
+ "\u00ce\u00b5\u00cf\u0124",
+ "\u0120\u00d0\u00b2\u00d1\u0138\u00d0\u00b4",
+ "\u0120Fat",
+ "\u0120labels",
+ "\u0120sophisticated",
+ "umps",
+ "\u0120releases",
+ "\u012047",
+ "\u0120OM",
+ "\u00ea\u00b0\u0122\u00eb",
+ "\u0120Bien",
+ "\u0120Ref",
+ "\u00e8\u00a8\u013a",
+ "\u0120Sta",
+ "\u0120Egg",
+ "\u0120indicator",
+ "pson",
+ "\u0120nas\u00c4\u00b1l",
+ "Right",
+ "\u0120convey",
+ "\u0120knot",
+ "\u0120connects",
+ "ulas",
+ "\u0120preced",
+ "\u0120inequality",
+ "amiento",
+ "\u0120reply",
+ "OY",
+ "\u0120dismiss",
+ "\u0120\u00eb\u0132\u013e",
+ "\u00e7\u0126\u00a1",
+ "\u0120\u00d1\u0127\u00d0\u00be\u00d1\u0122\u00d0\u00be\u00d1\u012a\u00d0\u00be",
+ "\u0120m\u00c3\u00a9d",
+ "\u0120randomly",
+ "\u0120Ont",
+ "uard",
+ "\u0120pulls",
+ "\u0120\u00d1\u0124\u00d0\u00b5\u00d0\u00bf\u00d0\u00b5\u00d1\u0122\u00d1\u012e",
+ "\u0120Need",
+ "\u0120Soft",
+ "\u0120strengths",
+ "\u0120goed",
+ "umen",
+ "\u00e6\u0143\u00bb",
+ "\u0120\u00ed\u0130\u00b8",
+ "\u0120\u00d0\u00b4\u00d0\u00be\u00d0\u00b1",
+ "\u0120clarity",
+ "\u0120Ai",
+ "\u0120balloon",
+ "\u0120Pand",
+ "\u0120\u00ec\u0137\u0126\u00eb\u012d",
+ "\u0120shiny",
+ "\u0120smallest",
+ "onia",
+ "hill",
+ "oting",
+ "\u0120eing",
+ "\u0120merely",
+ "\u0120seus",
+ "\u0120\u00d0\u00bd\u00d0\u00b5\u00d0\u00bf",
+ "\u0120\u00ed\u0128\u00b5",
+ "\u0120guides",
+ "\u0120specialist",
+ "\u0120steak",
+ "\u00e3\u0124\u012a\u00e3\u0123\u0128",
+ "\u0120migration",
+ "quele",
+ "\u0120ruined",
+ "\u0120pupp",
+ "\u00e5\u00a5\u00b3",
+ "\u0120kend",
+ "angan",
+ "\u0120palm",
+ "\u0120unfair",
+ "\u0120zm",
+ "\u0120DV",
+ "chester",
+ "\u00d0\u00b8\u00d1\u0130",
+ "\u0120ooh",
+ "erg",
+ "ATH",
+ "\u00b0\u00a9",
+ "\u00e5\u0135\u00aa",
+ "rison",
+ "\u0120involving",
+ "\u0120partly",
+ "an\u00c3\u00a7ais",
+ "\u0120vow",
+ "\u0120prominent",
+ "\u0120cryst",
+ "iba",
+ "\u0120deserves",
+ "\u0120overt",
+ "\u0120sensit",
+ "\u0120Whe",
+ "\u0120tighten",
+ "\u0120intimid",
+ "\u0120aliment",
+ "will",
+ "\u0120strengthen",
+ "\u0120Tan",
+ "\u00e5\u0131\u012a",
+ "\u00e3\u0123\u0139\u00e3\u0123\u00be\u00e3\u0123\u013b",
+ "oni",
+ "\u0120Mun",
+ "\u0120proph",
+ "\u0120rehears",
+ "\u0120Kle",
+ "\u0120veces",
+ "\u0120wondered",
+ "oki",
+ "\u0120senses",
+ "\u00b4\u00ec\u012d",
+ "\u00c6\u00b0\u00e1\u00bb\u013d",
+ "\u0120\u00c8\u013bi",
+ "\u0120muchos",
+ "\u0120watches",
+ "ortunate",
+ "\u0120Juan",
+ "\u00ec\u0140\u0138\u00ec\u0137\u0126",
+ "\u00d1\u0122\u00d0\u00b5",
+ "ei",
+ "ionen",
+ "\u0120experimental",
+ "\u0120daughters",
+ "\u00e0\u00b8\u013d",
+ "\u0120mentally",
+ "becca",
+ "aware",
+ "\u00ec\u0126\u013f",
+ "\u0120whatsoever",
+ "\u0120enables",
+ "\u0120Low",
+ "oid",
+ "\u00e0\u00b8\u012c",
+ "\u00c3\u00b3d",
+ "\u00d8\u00ba",
+ "\u0120constructed",
+ "\u0120Ladies",
+ "\u0120accused",
+ "\u0120\u00d0\u00b0\u00d0\u00bd",
+ "Dan",
+ "\u0120spawn",
+ "\u0120containers",
+ "\u0120artistic",
+ "\u00c4\u00b1p",
+ "\u0120discl",
+ "\u0120autres",
+ "inas",
+ "\u0120Nation",
+ "\u0120nag",
+ "bean",
+ "whe",
+ "\u013e\u00eb\u0131\u0126",
+ "\u0120Seoul",
+ "\u0120\u00ed\u0131\u00ac",
+ "\u0120Nich",
+ "\u0120complement",
+ "\u0120interven",
+ "\u0120Model",
+ "\u0120Orange",
+ "namon",
+ "\u0120calculation",
+ "see",
+ "\u0120ustedes",
+ "\u0120leb",
+ "\u0120doct",
+ "\u00d1\u0138\u00d0\u00bd",
+ "\u0120foster",
+ "\u0120elastic",
+ "\u0120Ahh",
+ "\u0120ace",
+ "\u0120Pink",
+ "\u0120Jeg",
+ "\u0120deer",
+ "\u00e3\u0123\u0139\u00e3\u0123\u0126",
+ "sis",
+ "\u0120jako",
+ "\u0120Emma",
+ "\u00d1\u0123\u00d1\u0124\u00d0\u00b2\u00d0\u00b5\u00d0\u00bd\u00d0\u00bd\u00d0\u00be",
+ "\u0120portrait",
+ "\u0120maker",
+ "\u0120aument",
+ "\u00d1\u0122\u00d0\u00be\u00d0\u00b1",
+ "\u0120airplane",
+ "\u0120transparency",
+ "\u0120adjustment",
+ "\u0120CDC",
+ "\u00c3\u00a7on",
+ "\u0120uploaded",
+ "\u0120\u00d0\u00b4\u00d0\u00b5\u00d0\u00b9\u00d1\u0123\u00d1\u0124\u00d0\u00b2",
+ "\u0120\u00d0\u00b3\u00d0\u00be\u00d1\u0124\u00d0\u00be\u00d0\u00b2",
+ "\u0120iter",
+ "\u0120curse",
+ "\u00c3\u00b4n",
+ "merce",
+ "aran",
+ "\u0120leak",
+ "\u00e7\u00b5\u0132",
+ "\u0120absence",
+ "\u00d1\u0123\u00d0\u00ba\u00d0\u00b8\u00d0\u00b9",
+ "\u0120readers",
+ "aler",
+ "\u0120beneath",
+ "ango",
+ "hetic",
+ "\u0120finns",
+ "\u0120poop",
+ "\u0120duplic",
+ "Hi",
+ "igs",
+ "ologically",
+ "opp",
+ "\u0120dizer",
+ "\u0120Allen",
+ "\u0120gli",
+ "\u0120acceleration",
+ "\u0120vitamin",
+ "\u00e3\u0125\u0143",
+ "v\u00c3\u00a4",
+ "\u0120Access",
+ "\u00e0\u00ae\u013b",
+ "r\u00c3\u00a1s",
+ "\u0120appreciated",
+ "\u0120nah",
+ "\u0120poster",
+ "\u0120tale",
+ "\u0120highlighted",
+ "\u00e6\u0138\u0129",
+ "\u00c5\u00bceli",
+ "\u0120blockchain",
+ "\u0120microw",
+ "\u0120cinema",
+ "\u0120Chang",
+ "\u0120Search",
+ "usters",
+ "\u0120Zero",
+ "\u0120Division",
+ "\u00d1\u0122\u00d0\u00b0\u00d1\u0123",
+ "\u0120scare",
+ "\u0120jelly",
+ "\u0120Administration",
+ "SO",
+ "\u0120lined",
+ "\u0120\u00ea\u00b0\u0126",
+ "\u0120geben",
+ "\u0120soda",
+ "\u0120winners",
+ "\u00b3\u00bc",
+ "\u00d9\u0134",
+ "\u0120Amb",
+ "\u00e5\u0137\u0131\u00e9\u00a1\u012e",
+ "\u00e5\u0136",
+ "\u0120peg",
+ "\u00e5\u00b7\u00b1",
+ "43",
+ "\u0120raus",
+ "\u0120rewards",
+ "\u0120inclus",
+ "\u0120highway",
+ "\u0120hah",
+ "\u0120multiplied",
+ "\u0120s\u00e1\u00ba\u00bd",
+ "\u0120disciples",
+ "\u0120ning",
+ "\u0120dressing",
+ "\u0120attributes",
+ "\u0120Mosc",
+ "\u0120Greece",
+ "\u0120sek",
+ "\u0120Learn",
+ "\u0120jus",
+ "rendre",
+ "\u0120personne",
+ "plete",
+ "\u0120placing",
+ "\u0120luego",
+ "illance",
+ "\u0120\u00d0\u00be\u00d0\u00b1\u00d1\u012b",
+ "\u0120provision",
+ "\u0120lion",
+ "tra",
+ "boards",
+ "\u0120behaviour",
+ "hey",
+ "\u0120subscription",
+ "\u0120protagon",
+ "\u00e3\u0125\u00a3",
+ "\u0120vara",
+ "\u0120\u00c5\u0141u",
+ "\u0120haha",
+ "\u0120teaspoon",
+ "\u00e6\u0141",
+ "avoir",
+ "\u0120crypto",
+ "\u0120\u00d1\u0123\u00d1\u0124\u00d0\u00b0\u00d1\u0122",
+ "\u0120Store",
+ "abs",
+ "\u0120Students",
+ "\u0120laund",
+ "into",
+ "\u0120approached",
+ "\u00b0\u013e",
+ "\u00d1\u0125\u00d1\u0130\u00d1\u012b",
+ "\u0120Labor",
+ "otes",
+ "iatric",
+ "\u0120gro\u00c3\u0141",
+ "utive",
+ "\u0120\u00d0\u00b8\u00d0\u00b4",
+ "\u0120Gib",
+ "\u0120placement",
+ "\u0120dif\u00c3\u0143cil",
+ "\u0120frog",
+ "\u0120\u00d0\u00b2\u00d1\u0123\u00d0\u00b5\u00d1\u0127",
+ "\u0120Jr",
+ "azed",
+ "\u00d1\u0125\u00d1\u012b",
+ "\u0120\u00ea\u00bc",
+ "frame",
+ "\u00d0\u00b0\u00d0\u00b5\u00d1\u012a\u00d1\u012e",
+ "\u0120lockdown",
+ "\u00e5\u0133\u00b3",
+ "\u0120medi",
+ "\u0120\u00d7\u0136\u00d7\u0140\u00d7",
+ "\u00d0\u00b5\u00d0\u00bd\u00d0\u00b8\u00d0\u00b9",
+ "emale",
+ "\u00ec\u00a2\u0127",
+ "ateral",
+ "\u0120distant",
+ "\u0120bears",
+ "\u0120journalist",
+ "\u00e8\u00a7\u00a3",
+ "\u0120Marshall",
+ "\u0120Ihnen",
+ "uetooth",
+ "bag",
+ "\u0120\u00c4\u0133\u00c3\u00a3",
+ "\u0120Highness",
+ "\u0120\u00ec\u00b0\u012f",
+ "\u00d0\u00b8\u00d0\u00ba\u00d0\u00b0",
+ "\u0120Wu",
+ "\u0120Fran",
+ "\u0120peng",
+ "\u0120fon",
+ "\u0120hypothesis",
+ "\u0120\u00d1\u0122\u00d1\u0125",
+ "\u0120ly",
+ "\u00d7\u013c",
+ "\u00ec\u013d\u0136",
+ "\u0120Radio",
+ "\u00e0\u00b8\u0140",
+ "Dav",
+ "\u0120embarrassing",
+ "\u0120\u00ec\u0140\u012a\u00ec\u0138\u00b4",
+ "\u0120casting",
+ "\u0120cage",
+ "\u0120Psych",
+ "\u0120\u00ec\u013f\u00bc\u00eb\u012d\u00a8",
+ "\u0120\u00c5\u00be",
+ "imb",
+ "\u0120directors",
+ "SH",
+ "\u0120\u00cf\u0126\u00ce\u00b7\u00ce\u00bd",
+ "\u00e1\u00bb\u0123u",
+ "\u0120konu\u00c5\u0141",
+ "\u0120optional",
+ "quarters",
+ "iker",
+ "\u0120Sant",
+ "\u0120verses",
+ "\u00eb\u00b6\u0122",
+ "\u0120olar",
+ "\u0120\u00cf\u0129",
+ "\u00e3\u0125\u0137",
+ "\u0120\u00ce\u00b3\u00ce\u00b9\u00ce\u00b1",
+ "\u0120Imm",
+ "\u0120controversial",
+ "\u0120ersten",
+ "\u0120recip",
+ "\u0120Christianity",
+ "\u0120\u00ea\u00b4\u013e",
+ "ordon",
+ "\u00d7\u0137\u00d7\u00a9",
+ "\u0120slash",
+ "\u0120Pf",
+ "\u00d1\u0125\u00d0\u00b4\u00d1\u012e",
+ "\u00d7\u0137\u00d7\u013f",
+ "\u0120Perry",
+ "\u0120mamy",
+ "\u0120backgrounds",
+ "\u0120\u00e0\u00ae\u0130\u00e0\u00ae\u00a9",
+ "\u0120pendant",
+ "\u0120Columbia",
+ "\u0120inverse",
+ "\u0120\u00d1\u0129\u00d0\u00b5\u00d1\u0122\u00d0\u00b5\u00d0\u00b7",
+ "\u0120sv",
+ "\u0120digging",
+ "41",
+ "chem",
+ "\u0120navigation",
+ "\u0120Shin",
+ "\u0120Front",
+ "PD",
+ "\u0120bearing",
+ "\u0120Wasser",
+ "\u0120wax",
+ "\u0120CHRIS",
+ "ching",
+ "\u0120pressed",
+ "El",
+ "\u0120Dal",
+ "onsin",
+ "\u0120binding",
+ "\u00d1\u0123\u00d0\u00ba\u00d0\u00be\u00d0\u00b9",
+ "poons",
+ "\u0120mock",
+ "arest",
+ "\u00d0\u00ba\u00d1\u0122\u00d0\u00b0",
+ "MM",
+ "\u0120corrupt",
+ "storm",
+ "\u0120refres",
+ "\u0120Coach",
+ "ll\u00c3\u00a4",
+ "\u0120THIS",
+ "\u0120parag",
+ "\u0120\u00ec\u0135\u00b0",
+ "pool",
+ "\u0120billions",
+ "\u0120\u00ea\u00b9\u0122",
+ "group",
+ "\u0120welcoming",
+ "cellence",
+ "\u0120Duke",
+ "\u00ea\u00b8\u00b4",
+ "\u0120primera",
+ "\u00ec\u0142\u00b8",
+ "\u0120pond",
+ "\u0120statue",
+ "\u0120\u00ea\u00b5\u00ac\u00eb",
+ "\u0120hatch",
+ "\u0120instrumental",
+ "\u0120residential",
+ "\u00ec\u00bb\u00a4",
+ "\u0120accepting",
+ "oshi",
+ "date",
+ "\u0120\u00ec\u0136\u00a8",
+ "\u0120planted",
+ "\u0120joking",
+ "\u0120\u00ec\u0126\u013e",
+ "\u0120hated",
+ "\u0120\u00d1\u0122\u00d0\u00b0\u00d1\u0123\u00d1\u0123\u00d0\u00ba",
+ "\u0120slept",
+ "\u0120packages",
+ "\u0120islands",
+ "esen",
+ "\u00c4\u0141\u00c4\u00b1",
+ "\u0120diagon",
+ "\u0120Osc",
+ "\u0120mesh",
+ "\u0120scales",
+ "arity",
+ "\u0120Defense",
+ "\u00e3\u0123\u00a1\u00e3\u0124\u0129",
+ "\u0120Lewis",
+ "\u0120\u00d1\u0123\u00d0\u00b5\u00d0\u00b3\u00d0\u00be\u00d0\u00b4\u00d0\u00bd\u00d1\u0131",
+ "\u0120flies",
+ "uinely",
+ "\u0120Consider",
+ "\u0120stark",
+ "hew",
+ "\u0120As\u00c3\u0143",
+ "\u00b3\u00b4\u00eb",
+ "\u0120propose",
+ "\u0120\u00ed\u0137\u013a\u00eb\u00a9\u00b4",
+ "odo",
+ "\u0120Normally",
+ "\u0120heeft",
+ "\u0120Harris",
+ "gro",
+ "\u0120Blood",
+ "base",
+ "\u0120iOS",
+ "\u0120touches",
+ "\u0120inspir",
+ "\u0120\u00d7\u0135",
+ "\u0120binary",
+ "\u0120\u00ec\u00b6\u0136",
+ "\u0120serial",
+ "\u0120ion",
+ "\u0120unemployment",
+ "\u0120odds",
+ "\u0120Fab",
+ "\u0120FBI",
+ "BRUN",
+ "\u0120weights",
+ "\u00ce\u00bd\u00ce\u00bf",
+ "atile",
+ "\u0120nurses",
+ "\u0120involvement",
+ "\u0120\u00ed\u0136\u00bc",
+ "\u0120governance",
+ "\u0120\u00e2\u0124\u00ac",
+ "\u00d1\u0122\u00d1\u0125\u00d0\u00bf",
+ "ierra",
+ "\u00ed\u013a\u0137",
+ "\u0120Jerry",
+ "\u0120beard",
+ "\u0120salvation",
+ "\u0120Along",
+ "gentle",
+ "\u0120Ki",
+ "bol",
+ "\u0120Plat",
+ "\u0120hasht",
+ "\u00e8\u00bf\u0133",
+ "\u0120ware",
+ "\u0120partie",
+ "ycz",
+ "\u0120intr",
+ "Fih",
+ "nent",
+ "\u0120cheat",
+ "ilen",
+ "\u0120\u00eb\u00af",
+ "orie",
+ "\u0120f\u00c3\u00a1cil",
+ "etric",
+ "\u0120affecting",
+ "unciation",
+ "\u0120affairs",
+ "\u0120bee",
+ "\u0120viewing",
+ "\u0120orang",
+ "\u0120Lan",
+ "\u0120\u00d0\u00a1\u00d1\u0124",
+ "\u00e4\u00b8\u0138",
+ "\u0120Mes",
+ "\u0125\u0123",
+ "erie",
+ "\u0120espa",
+ "\u0120interpre",
+ "\u0120possess",
+ "\u0120purely",
+ "rito",
+ "found",
+ "asma",
+ "\u00ec\u0142\u0123\u00ec\u013f\u00b8",
+ "\u0120examine",
+ "\u0120\u00d1\u0125\u00d0\u00bc",
+ "\u0120besch",
+ "\u0120Tomorrow",
+ "\u0120Block",
+ "\u0120variant",
+ "\u0120preference",
+ "\u0120coaches",
+ "\u0120medications",
+ "\u0120\u00ed\u013a\u0126",
+ "\u0120empire",
+ "\u00eb\u0126\u00a4",
+ "\u0120Illinois",
+ "\u0120crispy",
+ "\u0120th\u00c3\u00ac",
+ "\u0120bees",
+ "77",
+ "\u0120glow",
+ "\u00e8\u00ba",
+ "\u0120Studies",
+ "\u00e5\u0132\u0126",
+ "\u0120Challenge",
+ "\u0120unlikely",
+ "\u00d0\u00a7",
+ "\u00c4\u00b1yorsun",
+ "DIE",
+ "\u0120minimize",
+ "izard",
+ "\u0120\u00c3\u00ban",
+ "\u0120encontrar",
+ "\u0120Kill",
+ "\u00e5\u00bb",
+ "\u0120vanilla",
+ "\u0120Grant",
+ "\u0120GT",
+ "sea",
+ "\u0120sought",
+ "\u00d0\u00b2\u00d0\u00be\u00d0\u00b4",
+ "\u0120n\u00c3\u00a4m",
+ "\u0120Aunt",
+ "OWN",
+ "\u0120pumpkin",
+ "stellen",
+ "\u0120rag",
+ "\u00d0\u00b5\u00d0\u00b3\u00d0\u00b4\u00d0\u00b0",
+ "\u0120storyt",
+ "\u0120forum",
+ "\u00e6\u00a9\u0141",
+ "\u0120estaba",
+ "uche",
+ "\u0120congress",
+ "\u0120Rey",
+ "\u0120dramatically",
+ "\u0120Sport",
+ "\u0120Yellow",
+ "\u0120\u00ea\u00b3\u0126\u00ec\u0128\u012f",
+ "\u0120disgusting",
+ "\u0120Recent",
+ "\u0120acquired",
+ "\u0120cables",
+ "\u00e7\u0136\u013c",
+ "din",
+ "\u0120visto",
+ "\u0120communicating",
+ "\u00d1\u0123\u00d1\u0124\u00d0\u00b0\u00d0\u00b2\u00d0\u00bb\u00d1\u0131",
+ "\u00d0\u00b5\u00d1\u0123\u00d1\u0124\u00d0\u00be",
+ "\u00e3\u0125\u00bb\u00e3\u0125\u00bb\u00e3\u0125\u00bb",
+ "\u0120r\u00c3\u00a9g",
+ "\u0120socks",
+ "\u0120proces",
+ "because",
+ "\u0120utter",
+ "\u0120colocar",
+ "\u0120newest",
+ "\u0120gramm",
+ "\u00e8\u00a1\u00a8",
+ "\u00e4\u00b8\u012f\u00e7\u0141\u00a5\u00e9\u0123\u0135",
+ "\u0120shifting",
+ "\u0120carrier",
+ "\u0120\u00d1\u0123\u00d0\u00ba\u00d0\u00be\u00d1\u0122",
+ "\u0120Schw",
+ "\u0120executed",
+ "\u0120maintained",
+ "\u0120\u00cf\u0128",
+ "\u0120Moses",
+ "\u0120disse",
+ "\u0120horr",
+ "\u00e3\u0122\u013e",
+ "\u0120rally",
+ "\u0120allem",
+ "\u0120Eventually",
+ "\u0120diyor",
+ "lvania",
+ "\u0120schnell",
+ "\u0120\u00ea\u00b3\u00bc",
+ "\u0120\u00eb\u00a7\u00a4",
+ "\u0120struggles",
+ "late",
+ "\u0120clarify",
+ "\u00c3\u00a9ment",
+ "\u0120multiplic",
+ "\u00d0\u00b8\u00d0\u00b1\u00d0\u00be",
+ "\u0120journ",
+ "\u0120fragr",
+ "\u0120surprisingly",
+ "\u0120desperate",
+ "52",
+ "\u0120sul",
+ "\u0120Read",
+ "\u0120Fried",
+ "\u0120mond",
+ "woo",
+ "\u0120organizing",
+ "\u00e3\u0123\u0139\u00e3\u0124\u0129\u00e3\u0123\u0128",
+ "\u0120Soon",
+ "\u0120\u00d0\u00b2\u00d0\u00be\u00d0\u00bf\u00d1\u0122\u00d0\u00be\u00d1\u0123",
+ "\u0120Nur",
+ "\u0120\u00d0\u0139\u00d0\u00b4",
+ "\u0120spider",
+ "\u00d0\u00b5\u00d1\u0123\u00d1\u0131",
+ "\u0120tutorials",
+ "\u0120nutrients",
+ "orer",
+ "\u0120coefficient",
+ "\u0120arrangement",
+ "\u0120pricing",
+ "nan",
+ "yu",
+ "BL",
+ "\u0120tribe",
+ "\u0120Howard",
+ "unks",
+ "\u0120newer",
+ "\u0120provin",
+ "\u0120prediction",
+ "hos",
+ "\u0120olsun",
+ "\u0120Around",
+ "\u0120vier",
+ "\u0120\u00d1\u0123\u00d1\u0124\u00d0\u00be\u00d1\u0122\u00d0\u00be\u00d0\u00bd",
+ "\u0120valley",
+ "\u0120Ela",
+ "ifi",
+ "\u0120galaxy",
+ "\u0120tranqu",
+ "\u0120advers",
+ "\u0120Temple",
+ "iffs",
+ "igence",
+ "\u00e8\u0129\u00aa\u00e5\u00b7\u00b1",
+ "\u0120k\u00c3\u00b6nnte",
+ "\u0120\u00c4\u0133\u00c3\u00b3",
+ "Did",
+ "\u0120photographs",
+ "\u0120AWS",
+ "\u00d1\u0128\u00d0\u00b8\u00d1\u0131",
+ "\u0120guards",
+ "\u0120appointed",
+ "\u0120Gil",
+ "\u0120\u00d0\u00bc\u00d0\u00be\u00d0\u00bc",
+ "\u0120cod",
+ "\u0120Unlike",
+ "\u0120evenly",
+ "isconsin",
+ "\u0120estou",
+ "\u0120mnie",
+ "\u0120Exec",
+ "\u0120MV",
+ "\u0120Eine",
+ "\u00e4\u00bf\u00a1",
+ "\u0120Roger",
+ "\u0120Fac",
+ "\u0120List",
+ "\u0120fuer",
+ "\u00d0\u00b0\u00d0\u00b5\u00d1\u0124\u00d0\u00b5",
+ "omed",
+ "\u0120attraction",
+ "\u00e8\u012b\u00b2",
+ "\u0120terrain",
+ "\u0120Drop",
+ "\u0120corporations",
+ "\u0120sciences",
+ "\u0120throne",
+ "\u00e3\u0123\u0126\u00e3\u0123\u0141",
+ "\u0120aj",
+ "\u0120Rot",
+ "\u00e7\u012b\u00b9",
+ "\u0120supporters",
+ "\u0120Bere",
+ "Here",
+ "\u0120diferentes",
+ "\u0120significance",
+ "\u00cf\u0125\u00ce\u00b7",
+ "\u00e6\u012a\u0133\u00e8\u00a6\u00ba\u00e5\u00be\u0139",
+ "\u0120clamp",
+ "\u0120\u00eb\u012e\u0122\u00eb",
+ "\u0120fabulous",
+ "rez",
+ "\u00e6\u012e\u0123",
+ "\u0120assumptions",
+ "uther",
+ "wid",
+ "pot",
+ "\u00e8\u00bf\u0130",
+ "\u0120yan",
+ "ulin",
+ "\u00d1\u0122\u00d1\u012d\u00d0\u00b2",
+ "\u0120Slow",
+ "\u0120Pennsy",
+ "\u0120\u00ed\u0137\u00b4\u00ec\u0126\u013e",
+ "\u0120meio",
+ "\u0120wealthy",
+ "\u0120Eight",
+ "\u0120pulse",
+ "\u0120friction",
+ "idity",
+ "\u0120Holl",
+ "iyorum",
+ "\u0120sounded",
+ "\u0120Carr",
+ "\u0120fork",
+ "\u00e2\u013a",
+ "\u0120PA",
+ "\u0120conspir",
+ "\u0120coding",
+ "rt",
+ "\u0120Typ",
+ "\u0120\u00ec\u0138\u0133",
+ "\u0120\u00d0\u00bf\u00d0\u00be\u00d0\u00b3",
+ "\u0120miser",
+ "\u0120\u00d1\u0123\u00d0\u00bc\u00d0\u00be\u00d1\u0124\u00d1\u0122",
+ "\u0120Sweden",
+ "\u0120olarak",
+ "\u0120Zhang",
+ "\u0120Chi",
+ "\u0120Titan",
+ "\u0120screening",
+ "\u0120Spider",
+ "\u0120\u00c5\u0140imdi",
+ "\u0120obstacles",
+ "lara",
+ "\u0120challenged",
+ "pse",
+ "TON",
+ "\u00e1\u00bb\u00a5",
+ "\u0120Pi",
+ "\u0120lagi",
+ "ieurs",
+ "\u0120hurting",
+ "\u0120neglect",
+ "\u0120generating",
+ "\u0120youngest",
+ "\u0120audit",
+ "\u0120\u00d1\u0122\u00d0\u00b5\u00d0\u00b7",
+ "\u00cf\u0123\u00ce\u00ac",
+ "\u0120donate",
+ "\u0120PDF",
+ "\u0120visits",
+ "\u0120cruise",
+ "PP",
+ "aser",
+ "\u0120wsp",
+ "backs",
+ "ivals",
+ "\u00e3\u0123\u0128\u00e3\u0124\u0135",
+ "\u0120deve",
+ "\u0120proport",
+ "\u0120cath",
+ "\u0120Effect",
+ "\u0120winds",
+ "\u0120\u00ec\u013b\u0136",
+ "\u0120charts",
+ "\u0120sama",
+ "\u0120automation",
+ "\u0120\u00d0\u00bf\u00d0\u00be\u00d0\u00ba\u00d0\u00b0",
+ "\u0120olan",
+ "\u0120boats",
+ "\u0120cafe",
+ "\u0120denied",
+ "\u0120Mama",
+ "\u0120blocking",
+ "\u0120Thor",
+ "\u0120phenomenal",
+ "\u0120stakeholders",
+ "\u0120unos",
+ "\u00d1\u0125\u00d0\u00b5\u00d1\u0124",
+ "\u0120Abraham",
+ "\u00e3\u0123\u00a7\u00e3\u0124\u0124",
+ "\u0120detection",
+ "\u0120juris",
+ "\u0120powered",
+ "zial",
+ "\u0120welfare",
+ "\u0120upgrad",
+ "\u0120mo\u00c5\u00bcna",
+ "\u0120Case",
+ "cular",
+ "\u0136\u00ec\u013f\u00b4",
+ "\u00e3\u0125\u0123",
+ "\u0120Guess",
+ "\u0120cycles",
+ "\u00e4\u00be\u012d",
+ "\u00e7\u00b5\u00a6",
+ "rock",
+ "umi",
+ "\u0120elite",
+ "\u0120qu\u00c3\u00a8",
+ "\u00e5\u0142\u00b1",
+ "\u00d1\u0124\u00d0\u00be\u00d0\u00bc",
+ "\u0120shore",
+ "gunta",
+ "\u0120ku",
+ "\u0120faithful",
+ "\u0120Jeremy",
+ "aid",
+ "\u00e0\u00b7",
+ "ugal",
+ "\u00e5\u00b0\u012f\u00e5\u0137\u012c",
+ "\u0120Vel",
+ "\u0120vrai",
+ "stell",
+ "\u00a8\u00b8",
+ "\u0120kol",
+ "\u00e8\u00bd",
+ "\u0120quanto",
+ "\u0120\u00d0\u00b7\u00d0\u00b0\u00d1\u0122",
+ "\u01202002",
+ "esy",
+ "\u0120reserve",
+ "\u0120\u00d0\u00bc\u00d0\u00be\u00d0\u00bc\u00d0\u00b5\u00d0\u00bd\u00d1\u0124",
+ "\u0120deployed",
+ "\u0120defining",
+ "\u0120sau",
+ "\u0120gaat",
+ "\")",
+ "\u0120transmit",
+ "\u0120publishing",
+ "\u0120ranking",
+ "\u0120offense",
+ "\u012046",
+ "pin",
+ "\u0120Taking",
+ "\u0120entitled",
+ "\u0120genuinely",
+ "\u0120variations",
+ "\u0120finde",
+ "\u0120tau",
+ "\u0120unfortunate",
+ "\u0120Rah",
+ "ports",
+ "\u0120c\u00c5",
+ "\u0120monkey",
+ "\u0120brac",
+ "wei",
+ "lung",
+ "\u0120artif",
+ "\u0120syrup",
+ "\u0120\u00d0\u0136\u00d0\u00b0\u00d0\u00b2",
+ "\u0120lifted",
+ "\u0120chez",
+ "\u0120Advent",
+ "\u0120Stock",
+ "\u0120dol",
+ "\u00d0\u00bc\u00d0\u00b5\u00d0\u00bd",
+ "\u00d0\u00b8\u00d1\u012a\u00d1\u012e",
+ "\u0120yn",
+ "gio",
+ "det",
+ "\u0120desse",
+ "\u0120gri",
+ "\u0120Chairman",
+ "\u00e7\u0127",
+ "\u0120cuenta",
+ "anim",
+ "\u0120crab",
+ "\u0120escal",
+ "\u0120premi\u00c3\u00a8re",
+ "\u0120Gef",
+ "\u0120dining",
+ "\u0120seventh",
+ "\u0120chasing",
+ "\u0120Tower",
+ "\u0120brutal",
+ "\u0120fundamentally",
+ "\u00e3\u0123\u00a8\u00e3\u0123\u0128",
+ "\u00d0\u00bb\u00d0\u00b5\u00d0\u00bd\u00d0\u00b8\u00d1\u0131",
+ "stage",
+ "\u0120acquis",
+ "\u0120cylinder",
+ "\u0120commander",
+ "mem",
+ "\u0120UV",
+ "happy",
+ "\u0120epsilon",
+ "\u0120invitation",
+ "\u0120farmer",
+ "chair",
+ "\u0120destiny",
+ "\u0120sovere",
+ "\u0120Hebrew",
+ "\u0120servant",
+ "\u0120bew",
+ "\u0120gast",
+ "uties",
+ "\u0120administrative",
+ "\u0120Command",
+ "\u00c3\u00a9ta",
+ "\u0120nitrogen",
+ "\u00ea\u00b7\u00bc",
+ "\u0120abi",
+ "\u0120villain",
+ "\u0120blanket",
+ "\u0120Send",
+ "\u0120beaten",
+ "\u00b2\u0126",
+ "\u0120volunt",
+ "\u0120scholar",
+ "\u0120Emperor",
+ "\u012043",
+ "vable",
+ "\u0120Dus",
+ "\u0120GU",
+ "\u0120targeting",
+ "www",
+ "\u0120amendment",
+ "\u00ec\u0128\u012e\u00eb",
+ "\u0120ting",
+ "\u0120nasty",
+ "\u0120gauge",
+ "\u0120\u00d1\u0122\u00d0\u00be\u00d0\u00b4",
+ "\u0120Hans",
+ "Your",
+ "\u00ce\u00b1\u00ce\u00bd",
+ "\u0120projet",
+ "\u0120Hawaii",
+ "\u0120suspicious",
+ "\u0120schw",
+ "\u0120removal",
+ "\u0120intrig",
+ "\u0120MU",
+ "\u0120ponto",
+ "\u00e0\u00a4\u00be",
+ "\u0120\u00d0\u00be\u00d0\u00b1\u00d1\u0122\u00d0\u00b0\u00d0\u00b7",
+ "\u0120guessing",
+ "pace",
+ "\u0120mothers",
+ "\u0120millimeter",
+ "\u00d0\u00bb\u00d0\u00b5\u00d0\u00bd\u00d0\u00b8\u00d0\u00b5",
+ "\u00e6\u00b2\u00a1\u00e6\u013e\u012b",
+ "\u0120availability",
+ "icz",
+ "\u00e6\u0143\u00a4",
+ "\u0120fract",
+ "\u0120bases",
+ "km",
+ "\u0120BTS",
+ "\u0120Field",
+ "\u0120dzie",
+ "\u0120segundo",
+ "\u0120\u00eb\u0124\u013a\u00eb\u012c\u0136",
+ "\u0120legitimate",
+ "imas",
+ "\u0120\u00d0\u00b2\u00d0\u00bd",
+ "\u0120corruption",
+ "\u0120smash",
+ "\u0120Valent",
+ "\u0120aligned",
+ "\u0120Pennsylvania",
+ "\u0120gab",
+ "\u0120Eun",
+ "enth",
+ "\u0120Morning",
+ "\u0120candle",
+ "\u0120backpack",
+ "\u0120Islamic",
+ "a\u00c3\u00a7\u00c3\u00b5es",
+ "\u0120encry",
+ "\u0120mushrooms",
+ "\u00ed\u012e\u012e",
+ "dit",
+ "\u0120transit",
+ "\u0120Wisconsin",
+ "\u0120participated",
+ "\u0120Ils",
+ "\u0120unfold",
+ "\u00b6\u0122\u00eb",
+ "\u0120profits",
+ "\u0120warming",
+ "\u0120Gang",
+ "\u0120networking",
+ "\u0120mega",
+ "\u0120thoroughly",
+ "lements",
+ "\u0120Hm",
+ "\u0120deciding",
+ "\u0120emotionally",
+ "\u0120exhausted",
+ "\u0120\u00d0\u0141\u00d0\u00be\u00d1\u0124",
+ "cido",
+ "\u0120HTML",
+ "\u0120copyright",
+ "\u0120melody",
+ "yim",
+ "\u0120anders",
+ "oshop",
+ "\u0120\u00eb\u00b3\u00bc",
+ "\u0120athlete",
+ "\u0120GE",
+ "\u0120frequent",
+ "\u0120desires",
+ "\u0120needing",
+ "\u0120Yun",
+ "\u0120rifle",
+ "\u0120lover",
+ "'T",
+ "\u0120dense",
+ "\u0120t\u00c3\u00a3o",
+ "\u0120notified",
+ "\u0120idi",
+ "\u00ec\u0139\u0143",
+ "\u00ed\u0128",
+ "\u0120interacting",
+ "\u0120rapport",
+ "\u00d0\u00b5\u00d1\u0122\u00d0\u00b8",
+ "ski",
+ "\u0120besser",
+ "\u0120manufacturer",
+ "\u0120Kyle",
+ "\u0120accountable",
+ "\u0120Sak",
+ "\u0120Pil",
+ "\u0120Domin",
+ "\u0120presum",
+ "\u0120\u00d0\u0134\u00d1\u0123\u00d0\u00b5",
+ "\u0120vinegar",
+ "\u0120guaranteed",
+ "\u00e7\u013e\u012d\u00e5\u012a\u00b0",
+ "\u0120handled",
+ "\u00e9\u0141\u00b3",
+ "cat",
+ "\u0120civilization",
+ "\u0120accomp",
+ "\u0120VM",
+ "\u00c3\u00a9mon",
+ "\u0120deze",
+ "\u0120grades",
+ "\u0120sollte",
+ "\u0120staring",
+ "\u00d7\u0132\u00d7\u00aa",
+ "arnt",
+ "\u0120horizon",
+ "\u0120travail",
+ "hour",
+ "\u00e7\u00ac\u00ac\u00e4\u00b8\u0122",
+ "\u0120ED",
+ "\u0120Dak",
+ "\u0120ny",
+ "\u0120conve",
+ "\u0120Cham",
+ "\u0120firms",
+ "\u0120Liu",
+ "\u0120\u00d1\u0123\u00d1\u0124\u00d1\u0122\u00d0\u00b0\u00d0\u00bd",
+ "\u0120libert",
+ "\u0120lenses",
+ "\u0120intake",
+ "\u0120\u00d0\u00b2\u00d1\u012d\u00d0\u00b1",
+ "\u0120mensen",
+ "hel",
+ "\u0120practition",
+ "\u0120350",
+ "\u00e3\u0124\u00b3",
+ "FO",
+ "\u0120beds",
+ "\u0120ancestors",
+ "\u0120\u00ec\u0139\u0126\u00ec\u00b2\u0143",
+ "\u0120disturb",
+ "\u0120Lastly",
+ "\u0120Support",
+ "\u00e0\u00b8\u00b5\u00e0\u00b9\u012b",
+ "\u0120Corona",
+ "\u0120enthusi",
+ "\u0120\u00d0\u00b2\u00d0\u00be\u00d0\u00b7\u00d0\u00bc",
+ "\u0120\u00ec\u0124\u00ac\u00eb\u0140\u012e\u00eb",
+ "\u012052",
+ "bird",
+ "\u0120reduces",
+ "\u0120\u00ec\u0140\u012a\u00ec\u013f\u0126",
+ "\u0120Gene",
+ "\u00ea\u00b5\u0132",
+ "\u00c4\u013bp",
+ "\u0120\u00c3\u013eber",
+ "\u0120concerning",
+ "user",
+ "\u0120concentrate",
+ "\u0120WHAT",
+ "ishop",
+ "onymous",
+ "nold",
+ "\u0120suggesting",
+ "\u00a9\u00b0",
+ "\u0120Fish",
+ "........",
+ "\u0120vessel",
+ "\u0120trabajo",
+ "\u00e3\u0123\u00b5",
+ "\u0120Ocean",
+ "\u00e5\u00a7\u0132",
+ "yg",
+ "\u0120towns",
+ "del",
+ "\u0120terrifying",
+ "\u0120\u00c3\u00a7al\u00c4\u00b1\u00c5\u0141",
+ "\u0120sino",
+ "\u0120eats",
+ "\u0120gez",
+ "\u0120geme",
+ "\u0120\u00ec\u013b\u0126",
+ "\u0120compart",
+ "\u0120implementing",
+ "\u0120Potter",
+ "\u0120Germans",
+ "\u0120g\u00c5\u0124",
+ "\u0120tennis",
+ "\u0120carpet",
+ "auer",
+ "\u0120Saudi",
+ "yeong",
+ "\u0120curry",
+ "\u0120Forest",
+ "\u00d1\u012d\u00d0\u00bb",
+ "\u0120fifteen",
+ "\u0120bolts",
+ "\u0120{\\",
+ "\u00ac\u00b4",
+ "\u0120settlement",
+ "\u0120lange",
+ "\u0120bam",
+ "Get",
+ "\u00ed\u0137\u013b",
+ "\u0120swap",
+ "\u0120Khan",
+ "\u0120commence",
+ "\u0120quarantine",
+ "\u0120scored",
+ "\u00e7\u0138",
+ "\u01201950",
+ "\u0120thicker",
+ "\u0120s\u00c3\u00bbr",
+ "\u00e5\u0131\u00a3",
+ "\u0120Larry",
+ "\u0120allez",
+ "\u00ec\u012d\u013e\u00eb\u012c\u0136",
+ "\u0120g\u00c3\u00bc",
+ "\u0120spectacular",
+ "//",
+ "both",
+ "\u0120stats",
+ "\u00e5\u00a6\u00b3",
+ "\u0120Nancy",
+ "\u0120bunu",
+ "\u0120crust",
+ "\u0120activated",
+ "\u0120\u00ea\u00b7\u00b8\u00eb\u0140",
+ "outhe",
+ "\u0120ports",
+ "\u0120neural",
+ "\u0120jaw",
+ "\u0120observations",
+ "\u0120voit",
+ "aban",
+ "\u00e1\u00ba\u00a3i",
+ "\u00a6\u00ac\u00eb\u00a5\u00bc",
+ "omes",
+ "\u00e0\u00af\u012d",
+ "qui",
+ "\u0120kindness",
+ "\u00d0\u0133",
+ "\u012041",
+ "\u0120moderate",
+ "\u0120angels",
+ "\u0120Tamb",
+ "\u00c3\u00a8t",
+ "\u0120chlor",
+ "\u0120Billy",
+ "\u00ec\u00b2\u013a\u00eb",
+ "acon",
+ "\u0120selecting",
+ "\u0120Delta",
+ "\u0120null",
+ "denly",
+ "\u0120ciud",
+ "\u0120tendency",
+ "\u0120breakdown",
+ "\u0120mint",
+ "\u00d1\u0126\u00d0\u00be\u00d1\u0122\u00d0\u00bc",
+ "orph",
+ "\u0120dawn",
+ "spr",
+ "\u0120WILL",
+ "\u00c3\u00a4chlich",
+ "\u0120puppy",
+ "700",
+ "\u0120\u00e0\u00ae\u00a4",
+ "\u0120fails",
+ "\u0120Conc",
+ "\u0120relatives",
+ "\u0120inviting",
+ "\u0120autonom",
+ "\u0120composed",
+ "\u0120unity",
+ "\u0120decis",
+ "\u0120accessories",
+ "\u0120Cass",
+ "\u0120bist",
+ "\u0120Tip",
+ "\u00ec\u00a7\u00b8",
+ "\u0120punt",
+ "\u0120r\u00c3\u00a1p",
+ "\u00e9\u0122\u00b2",
+ "ANK",
+ "\u00e3\u0123\u013c",
+ "exist",
+ "\u0120compatible",
+ "\u0120ner",
+ "\u0120\u00d0\u00b5\u00d0\u00bc\u00d1\u0125",
+ "\u0120aplic",
+ "\u0120bapt",
+ "\u0120failing",
+ "\u0120Tamam",
+ "\u0120oscill",
+ "\u0120letzten",
+ "\u0120repeatedly",
+ "\u0120jungle",
+ "\u0120Push",
+ "hai",
+ "\u0120\u00ce\u00b7",
+ "\u0120deadly",
+ "\u00d1\u0131\u00d0\u00b6",
+ "wi\u00c4\u0127",
+ "\u0120Common",
+ "\u0120\u00ce\u0137",
+ "\u0120skate",
+ "TC",
+ "\u0120Mini",
+ "\u0120hobby",
+ "\u00e1\u00ba\u00a7n",
+ "\u0120routes",
+ "\u0120amigos",
+ "\u0120conjun",
+ "\u0120partnerships",
+ "\u0120novo",
+ "\u0120aver",
+ "\u0120pouvez",
+ "bridge",
+ "\u0120preoc",
+ "him",
+ "\u0120turb",
+ "\u0120sob",
+ "\u0120Snap",
+ "\u0120\u00ec\u00b0\u00b8",
+ "minute",
+ "\u0120traject",
+ "uj\u00c4\u013b",
+ "\u0120eager",
+ "\u0120regulatory",
+ "\u0120banking",
+ "bling",
+ "\u00d1\u012a\u00d1\u012e",
+ "a\u00c5\u00bc",
+ "\u0120bizarre",
+ "itated",
+ "dire",
+ "\u0120threatened",
+ "\u0120shining",
+ "\u0120nesse",
+ "\u0120corps",
+ "\u0120\u00d1\u0123\u00d1\u0125",
+ "\u0120teles",
+ "\u0120temp",
+ "tem",
+ "\u0120\u00d0\u00ba\u00d0\u00b0\u00d0\u00bd",
+ "\u0120fever",
+ "New",
+ "\u0120heavier",
+ "\u0120Sah",
+ "bud",
+ "\u0120outros",
+ "\u0120\u00ec\u00b0\u00be",
+ "\u0120\u00eb\u00aa\u0127",
+ "arring",
+ "\u0120\u00ea\u00b4\u013e\u00ec\u00b0\u00ae",
+ "\u0120Nap",
+ "\u0120semin",
+ "\u0120Than",
+ "ifs",
+ "\u0120desen",
+ "\u0120\u00d1\u0124\u00d0\u00b0\u00d0\u00ba\u00d0\u00be\u00d0\u00b5",
+ "\u0120loses",
+ "\u0120Balt",
+ "kon",
+ "\u0120\u00d0\u00bd\u00d0\u00b0\u00d0\u00bf\u00d1\u0122",
+ "\u0120vois",
+ "\u0120Moscow",
+ "\u0120chairs",
+ "his",
+ "\u0120refugees",
+ "kg",
+ "\u0120kole",
+ "\u012f\u00a8",
+ "\u00d0\u00b0\u00d1\u0123\u00d0\u00b8\u00d0\u00b1\u00d0\u00be",
+ "\u00a6\u00bd",
+ "\u0120Universe",
+ "\u0120Direct",
+ "\u0120cheating",
+ "\u0120Cin",
+ "\u0120patri",
+ "\u0120advise",
+ "\u0120Nether",
+ "\u0120primeiro",
+ "\u0120mentioning",
+ "nut",
+ "56",
+ "ar\u00c4\u00b1",
+ "\u0120petite",
+ "bled",
+ "\u0120pensar",
+ "icio",
+ "IND",
+ "\u0120veteran",
+ "\u0120ladder",
+ "\u0120consequence",
+ "\u00d0\u00be\u00d0\u00b6\u00d0\u00b0\u00d0\u00bb",
+ "\u0120Burn",
+ "\u0120rug",
+ "\u0120Made",
+ "\u0120git",
+ "\"...",
+ "\u0120competitors",
+ "\u0120przed",
+ "\u0120apparent",
+ "\u0120Argentina",
+ "\u0120Working",
+ "\u0120collaborate",
+ "woman",
+ "\u0120retain",
+ "\u0120leurs",
+ "\u0120dashboard",
+ "\u00d7\u013b\u00d7\u0135",
+ "\u0120Early",
+ "BM",
+ "\u0120\u00d0\u00b5\u00d1\u0133",
+ "\u00d0\u00be\u00d0\u00bb\u00d0\u00be\u00d0\u00b3",
+ "\u0120satisfying",
+ "\u0120oftentimes",
+ "\u0120mapping",
+ "\u00c3\u00bcnk\u00c3\u00bc",
+ "arth",
+ "fold",
+ "\u0120launching",
+ "\u0120aura",
+ "\u0120precision",
+ "works",
+ "God",
+ "\u0120strap",
+ "\u0120Imper",
+ "\u0120rivers",
+ "\u0120|",
+ "\u0120cuer",
+ "regon",
+ "\u0120arrival",
+ "\u00d0\u00ba\u00d0\u00b0\u00d1\u0127",
+ "\u0120Miami",
+ "\u00d0\u00b0\u00d0\u00bd\u00d1\u012d",
+ "\u0120survivors",
+ "\u0120Senior",
+ "David",
+ "\u0120estado",
+ "\u0120sectors",
+ "\u0120popping",
+ "\u0120chim",
+ "ay\u00c4\u00b1",
+ "\u0120kunnen",
+ "\u0120gallery",
+ "\u0120sunlight",
+ "esehen",
+ "\u0120yelling",
+ "\u0120Mein",
+ "\u0120Phoenix",
+ "\u0120mano",
+ "\u0120historia",
+ "\u0120occurring",
+ "\u00e6\u00ac\u00b8",
+ "\u00ec\u00b8",
+ "\u00d0\u00b0\u00d0\u00b4\u00d0\u00b8",
+ "\u00e5\u00be\u0127",
+ "\u0120institutional",
+ "\u0120Tut",
+ "\u00e7\u00b2",
+ "\u0120slaves",
+ "\u00e3\u0123\u00a9\u00e3\u0123\u0128",
+ "\u0120forgiveness",
+ "\u0120twin",
+ "\u0120Hyun",
+ "\u00d0\u00bd\u00d1\u012e",
+ "\u0120Komm",
+ "andra",
+ "shot",
+ "ss\u00c3\u00a4",
+ "\u0120\u00d1\u0128\u00d0\u00b5",
+ "atta",
+ "\u0120expense",
+ "\u0120GPU",
+ "\u0120Past",
+ "ribly",
+ "\u0120\u00eb\u0143\u0132\u00ec\u0137\u00bc",
+ "\u0120\u00d0\u00b3\u00d0\u00be\u00d0\u00b4\u00d0\u00b0",
+ "\u0120respir",
+ "\u00e6\u013f\u00b1",
+ "\u0120Queens",
+ "hops",
+ "\u0120s\u00c3\u00a9rie",
+ "\u0120pref",
+ "\u0120comed",
+ "\u0120plut",
+ "\u0120Overall",
+ "\u0120\u00e3\u0123\u013f",
+ "\u0120cush",
+ "\u0120ringing",
+ "\u0120incorrect",
+ "\u0120\u00d1\u0123\u00d1\u0124\u00d1\u0122",
+ "\u0120geometry",
+ "\u0120advertis",
+ "\u0120\u00d0\u00a8",
+ "\u0120reviewed",
+ "\u00e3\u0123\u0124\u00e3\u0123\u0124",
+ "\u0120dozens",
+ "\u0120determination",
+ "\u0120Phill",
+ "\u0120contributed",
+ "\u0120Cit",
+ "\u0120passengers",
+ "\u0120c\u00c3\u00b4t\u00c3\u00a9",
+ "\u0120rever",
+ "\u0120technological",
+ "\u0120allen",
+ "\u0120raining",
+ "avi",
+ "\u0120salty",
+ "\u0120typing",
+ "\u0120\u00d1\u0124\u00d0\u00b5",
+ "\u0120tilt",
+ "\u0120\u00ec\u00b9\u013a",
+ "\u0120\u00d0\u00be\u00d1\u0122",
+ "\u0120\u00d0\u00bf\u00d1\u0122\u00d1\u0131\u00d0\u00bc",
+ "\u0120rou",
+ "\u0120arena",
+ "arat",
+ "\u00e5\u012a\u00ab",
+ "HHHH",
+ "\u0120manufacturers",
+ "\u0120Edward",
+ "\u0120tuck",
+ "\u0120blows",
+ "ingo",
+ "\u0120Marc",
+ "\u00ec\u0137\u0126\u00ec\u0126\u013e",
+ "Mich",
+ "\u0120Clean",
+ "\u00e8\u00b4",
+ "esto",
+ "\u0120Pack",
+ "\u0120shaft",
+ "BRUNO",
+ "\u0120aven",
+ "uur",
+ "\u00d1\u0123\u00d0\u00ba\u00d0\u00be\u00d0\u00bb\u00d1\u012e\u00d0\u00ba\u00d0\u00be",
+ "\u00ea\u00b4\u0122",
+ "\u0120automated",
+ "\u0120venture",
+ "\u0120surveillance",
+ "\u0120Grow",
+ "\u0120Emer",
+ "\u0120\u00d0\u00b4\u00d0\u00be\u00d1\u0122",
+ "\u0120investor",
+ "\u0120Yok",
+ "\u0120latter",
+ "\u0120NI",
+ "\u0120functioning",
+ "\u0120Hamilton",
+ "\u012051",
+ "\u0120murdered",
+ "\u0120anchor",
+ "\u0120cuc",
+ "\u0120SCP",
+ "\u0120Madam",
+ "\u0120constraints",
+ "\u0120barn",
+ "anken",
+ "\u0120\u00eb\u00a7\u0130\u00ec\u013f\u0122",
+ "\u0120Motor",
+ "\u0120Doing",
+ "\u0120amen",
+ "etts",
+ "\u0120instructor",
+ "egt",
+ "ako",
+ "\u0120posture",
+ "ivia",
+ "\u0120Polish",
+ "\u0120\u00d0\u00b4\u00d0\u00b2\u00d0\u00b0",
+ "\u0120colorful",
+ "\u0120elbow",
+ "\u0120parle",
+ "\u0120passer",
+ "\u0120condem",
+ "ortal",
+ "\u0120fertil",
+ "\u00d8\u00a7\u00d8\u00af",
+ "\u0120Colomb",
+ "\u0120alignment",
+ "\u0120astronaut",
+ "\u0120Mut",
+ "\u0120salmon",
+ "\u0120structured",
+ "\u0140\u00d7\u00a8",
+ "\u0120clicks",
+ "\u0120miej",
+ "\u00e6\u0136\u00bf",
+ "\u00e3\u0123\u0126\u00e3\u0124\u0126",
+ "\u0120Round",
+ "\u0120rainbow",
+ "\u0120VA",
+ "\u00e3\u0123\u0136\u00e3\u0123\u0138",
+ "\u00ec\u00a7\u012a",
+ "otz",
+ ",",
+ "\u0120chords",
+ "\u0120Sanders",
+ "\u0120\u00eb\u00b6\u0126\u00eb",
+ "Ben",
+ "\u0120dar\u00c3\u00bcber",
+ "ilians",
+ "\u0120ordering",
+ "\u0120Manh",
+ "\u0120kilogram",
+ "\u0120kar\u00c5\u0141",
+ "\u0120grasp",
+ "\u0120ghosts",
+ "alen",
+ "\u0120Jedi",
+ "\u0120\u00d0\u00b1\u00d0\u00bb\u00d0\u00b8",
+ "\u0120downloaded",
+ "\u0120conducting",
+ "\u0120Hak",
+ "\u0120researcher",
+ "ilan",
+ "good",
+ "\u0120Hannah",
+ "\u0120d\u00c3\u00bc\u00c5\u0141\u00c3\u00bcn",
+ "\u0120Messiah",
+ "uity",
+ "iona",
+ "\u0120probable",
+ "\u0120YE",
+ "\u0120independently",
+ "\u0120buffer",
+ "burn",
+ "ourd",
+ "\u0120McK",
+ "\u0120lingu",
+ "ujemy",
+ "\u00d0\u00b5\u00d1\u0122\u00d1\u0124",
+ "\u0120intuitive",
+ "\u0120cracks",
+ "appropri",
+ "nty",
+ "\u0120geen",
+ "\u0120lend",
+ "\u0120certification",
+ "IDS",
+ "unter",
+ "pees",
+ "\u0120trump",
+ "\u0120bankrupt",
+ "\u0120feas",
+ "\u00e8\u0139",
+ "\u0120du\u00c5\u00bc",
+ "\u00e6\u00b8\u0127",
+ "\u0120viruses",
+ "\u012058",
+ "god",
+ "\u0120\u00d0\u00b6\u00d0\u00b5\u00d0\u00bb",
+ "\u0120stalk",
+ "Ind",
+ "achi",
+ "\u0120CF",
+ "\u0120Cond",
+ "\u0120sanct",
+ "\u0120conten",
+ "\u0120freed",
+ "\u0120RT",
+ "\u0120mentors",
+ "\u00ec\u00a1\u00b1",
+ "\u0120portable",
+ "\u0120Paulo",
+ "rane",
+ "HAHA",
+ "\u0120Section",
+ "\u00e7\u0128",
+ "hyun",
+ "\u0120\u00ce\u0143\u00cf\u0129",
+ "\u0120Pub",
+ "\u0120Independ",
+ "\u0120compounds",
+ "\u0120\u00d1\u0123\u00d1\u012d",
+ "\u0120messaging",
+ "\u0120dedication",
+ "\u0120noticing",
+ "\u0120devoted",
+ "\u00d1\u0130\u00d1\u0124\u00d1\u0123\u00d1\u0131",
+ "\u0120snakes",
+ "\u0120battlefield",
+ "pers",
+ "\u0120dela",
+ "92",
+ "\u0120hai",
+ "ill\u00c3\u00a4",
+ "\u00c3\u00a9rer",
+ "every",
+ "\u0120responsive",
+ "\u00d7\u013b\u00d7\u0137",
+ "opf",
+ "\u00e9\u012b",
+ "\u012c\u00b8",
+ "Because",
+ "\u0120tourism",
+ "\u0120\u00ea\u00b7\u00b8\u00ea\u00b2\u012e",
+ "\u00d7\u0137\u00d7\u00a6",
+ "\u0120cans",
+ "st\u00c3\u00bct",
+ "\u0120donne",
+ "\u0120Dios",
+ "\u0120Uber",
+ "actory",
+ "\u0120oriented",
+ "\u0120Herm",
+ "\u0120patron",
+ "urf",
+ "bei",
+ "\u0120programa",
+ "\u0120Ohh",
+ "gener",
+ "\u0120fist",
+ "\u0120Wendy",
+ "\u0120anda",
+ "\u0120guessed",
+ "\u0120freak",
+ "\u00e4\u00b8\u0143\u00e5\u013e\u012d",
+ "\u0120Kings",
+ "chool",
+ "\u0120offline",
+ "\u0120Indiana",
+ "\u0120Alliance",
+ "\u012053",
+ "\u0120particul",
+ "\u0120Focus",
+ "\u0120inhabit",
+ "\u0120\u00ea\u00b0\u013b\u00ec\u013f\u0122\u00eb\u012f\u00b0",
+ "\u0120McG",
+ "owski",
+ "\u0120\u00ec\u013f\u00b4\u00ea\u00b1\u00b4",
+ "\u0120pa\u00c5\u0126st",
+ "\u00d0\u00be\u00d0\u00bd\u00d0\u00b8",
+ "itta",
+ "\u0120confirmation",
+ "\u0120Brooklyn",
+ "\u0120noodle",
+ "fund",
+ "itud",
+ "\u0120grandparents",
+ "\u0120barbecue",
+ "\u00ce\u00b5\u00ce\u00b9\u00cf\u0124",
+ "\u0120\u00e1",
+ "\u0120ballot",
+ "\u0120Veter",
+ "\u0120pipes",
+ "igious",
+ "\u0120Graph",
+ "ested",
+ "\u0120\u00eb\u00b8\u012e\u00eb",
+ "\u0120KE",
+ "\u00e3\u0123\u00a1\u00e3\u0124\u0129\u00e3\u0123\u00a3\u00e3\u0123\u00a8",
+ "\u0120eins",
+ "\u0120hatred",
+ "\u00e3\u0123\u0133\u00e3\u0123\u00a9",
+ "\u0120dang",
+ "eeee",
+ "\u0120archae",
+ "\u0120Jesse",
+ "\u0120detected",
+ "\u0120seni",
+ "burgh",
+ "\u0120displacement",
+ "\u0120dop",
+ "\u0120conditioning",
+ "\u0120\u00d0\u00bd\u00d0\u00b5\u00d1\u0123\u00d0\u00ba\u00d0\u00be\u00d0\u00bb\u00d1\u012e\u00d0\u00ba\u00d0\u00be",
+ "\u0120disturbing",
+ "PH",
+ "\u0120thinner",
+ "\u0120wounded",
+ "\u0120Cuando",
+ "\u0120cushion",
+ "\u0120whites",
+ "\u0120preferences",
+ "\u0120\u00ec\u00a4\u0122\u00eb\u00b9\u0126",
+ "\u0120ka\u00c5\u00bc",
+ "\u0120Gate",
+ "\u0120Path",
+ "dles",
+ "\u00e0\u00b8\u0126\u00e0\u00b8\u00a3",
+ "imore",
+ "\u0120\u00eb\u00b3\u00b4\u00ec\u0139\u00ac",
+ "\u0120disciplines",
+ "\u00e1\u00bb\u0131",
+ "\u0120mesma",
+ "\u0120\u00ec\u0125\u012a\u00eb",
+ "\u0120\u00ec\u012d\u00ac",
+ "\u0120ging",
+ "\u0120umbrella",
+ "IGHT",
+ "\u0120pension",
+ "\u0120combining",
+ "SS",
+ "\u0120rectangle",
+ "\u00e1\u00bb\u0129t",
+ "\u0120proxim",
+ "\u0120Cow",
+ "\u00b8\u012e",
+ "\u0120intentional",
+ "\u00e6\u0137\u013b",
+ "\u0120decid",
+ "\u0120\u00d1\u0123\u00d0\u00ba\u00d0\u00b0\u00d0\u00b6",
+ "\u0120Uma",
+ "iasm",
+ "buz",
+ "\u0120debris",
+ "\u0120cass",
+ "\u0120Prop",
+ "iska",
+ "\u00eb\u0142\u00a5",
+ "esterol",
+ "ussian",
+ "\u00ec\u013f\u00b4\u00eb\u0140\u0133",
+ "\u0120unlimited",
+ "\u0120admire",
+ "\u0120tightly",
+ "\u0120genome",
+ "\u0120Junior",
+ "venir",
+ "gus",
+ "\u0120c\u00c4\u0125",
+ "\u0120Vlad",
+ "\u0120\u00ed\u0124",
+ "\u0120relativ",
+ "inci",
+ "\u0120aunque",
+ "\u0120Boys",
+ "\u00d1\u0128\u00d0\u00b8\u00d0\u00be\u00d0\u00bd",
+ "\u0120Swiss",
+ "\u0120physicians",
+ "\u0120\u00ed\u0131\u012b",
+ "\u0120PET",
+ "\u0120wounds",
+ "about",
+ "\u00c3\u0142i",
+ "onz",
+ "urities",
+ "\u0120\u00d1\u0125\u00d0\u00b2\u00d0\u00b8\u00d0\u00b4",
+ "\u00e5\u00b7\u00a6",
+ "\u0120mentality",
+ "\u0120variance",
+ "\u0120segunda",
+ "\u0120volcano",
+ "alie",
+ "\u00e0\u00a5\u0129",
+ "\u0120tiles",
+ "\u0120Terry",
+ "\u0120\u00d8\u00a7\u00d9\u0126\u00d9\u0126\u00d9\u0129",
+ "\u0120canon",
+ "\u0120scattered",
+ "pton",
+ "\u0120definitions",
+ "\u0120algebra",
+ "oten",
+ "ablo",
+ "ijuana",
+ "\u0120wrapping",
+ "\u0120sesame",
+ "\u0120\u00d0\u00bd\u00d0\u00b0\u00d1\u0129\u00d0\u00b8\u00d0\u00bd\u00d0\u00b0",
+ "\u0120Alf",
+ "\u0120\u00d0\u0142\u00d0\u00be\u00d1\u0123\u00d1\u0123",
+ "orno",
+ "\u0120ankle",
+ "\u0120specialty",
+ "\u0120attempting",
+ "iliation",
+ "\u01201920",
+ "\u0120phenomena",
+ "\u0120Product",
+ "\u0120Buck",
+ "\u0120Aww",
+ "seen",
+ "\u0120void",
+ "\u0120Franklin",
+ "\u0120advocacy",
+ "\u0120Sep",
+ "\u0120coolest",
+ "\u0120\u00d1\u0123\u00d1\u0122\u00d0\u00b0\u00d0\u00b7\u00d1\u0125",
+ "\u0120Quand",
+ "\u0120900",
+ "\u0120Trad",
+ "dies",
+ "\u0120hash",
+ "\u00e6\u012a\u0133\u00e5\u00b0\u00b1",
+ "\u00e4\u00b9\u0141\u00e6\u013a\u00af",
+ "\u0120pots",
+ "\u0120sadly",
+ "\u0120viable",
+ "\u0120Tiger",
+ "\u0120ONE",
+ "\u0120neurons",
+ "owanie",
+ "\u00c4\u0139",
+ "\u0120Shar",
+ "\u0120Landes",
+ "\u0120conferences",
+ "\u00e8\u00a9\u00b2",
+ "\u0120credential",
+ "\u0120lime",
+ "inee",
+ "xit",
+ "pay",
+ "\u0120incons",
+ "\u0120>>:",
+ "\u00e8\u00aa\u012f",
+ "\u0120\u00ed\u0140\u013a\u00eb",
+ "\u0120lesser",
+ "\u0120spill",
+ "\u0120premise",
+ "\u0120365",
+ "\u0120Host",
+ "\u0120tomar",
+ "\u00d7\u0132\u00d7\u013e",
+ "\u00eb\u00b2\u012a",
+ "\u0120Whats",
+ "\u0120lightweight",
+ "\u0120Map",
+ "fia",
+ "ellschaft",
+ "\u0120vendors",
+ "uesto",
+ "\u0120Mister",
+ "\u0120\u00d0\u0141\u00d1\u0122\u00d0\u00b8",
+ "\u00e5\u0131\u00b3",
+ "hma",
+ "\u0120intentionally",
+ "\u0120Tang",
+ "\u00e9\u0139\u00ae",
+ "\u0120identification",
+ "\u0120etcetera",
+ "\u0120Nee",
+ "\u0120\u00d1\u0124\u00d1\u0122\u00d0\u00b8",
+ "\u00ea\u00b7\u00b8",
+ "\u0120cryptocur",
+ "\u0120inhale",
+ "\u0120addict",
+ "\u00e5\u0132\u0126\u00e4\u00bd\u012f",
+ "\u0120mau",
+ "\u0120\u00d1\u0124\u00d0\u00b0\u00d0\u00ba\u00d0\u00b0\u00d1\u0131",
+ "\u0120\u00eb\u00b2\u0126",
+ "\u0120comprar",
+ "iedzie\u00c4\u0129",
+ "\u0120\u00d0\u00be\u00d1\u0124\u00d0\u00bd\u00d0\u00be",
+ "\u0120beginner",
+ "\u0120\u00d0\u00bc\u00d1\u0125\u00d0\u00b6",
+ "\u0120obsc",
+ "\u0120limiting",
+ "ascular",
+ "\u0120inspection",
+ "aci",
+ "\u0120rejo",
+ "Mus",
+ "\u0120zaten",
+ "\u0120szcz",
+ "\u0120Madrid",
+ "\u0120varieties",
+ "\u0120est\u00c3\u0142",
+ "\u0120Shakes",
+ "\u0120kits",
+ "\u0120administer",
+ "\u0120lava",
+ "\u0120g\u00c3\u00a5",
+ "\u00e8\u00a9\u00a6",
+ "\u00d7\u00aa\u00d7\u013b",
+ "\u0120Wayne",
+ "\u0120instagram",
+ "\u0120rated",
+ "paper",
+ "\u0120bild",
+ "\u0120pretending",
+ "\u0120observing",
+ "\u0120\u00d1\u0123\u00d0\u00b0\u00d0\u00bc\u00d0\u00be\u00d0\u00bc",
+ "\u0120tror",
+ "\u0120organisms",
+ "\u0120falta",
+ "\u0120hometown",
+ "\u00e7\u00b1",
+ "\u0120\u00ed\u012d",
+ "\u0120cheg",
+ "\u0120\u00ec\u00a1",
+ "\u0120comma",
+ "is\u00c3\u00a9",
+ "\u0120likelihood",
+ "avored",
+ "\u0120geldi",
+ "\u00d0\u00bd\u00d0\u00b8\u00d0\u00ba\u00d0\u00be\u00d0\u00b2",
+ "\u0120medio",
+ "\u0120jakie",
+ "\u0120Jup",
+ "\u0120greenhouse",
+ "\u0120spit",
+ "\u00d0\u00ba\u00d0\u00be\u00d0\u00b5",
+ "\u0120\u00d0\u00ba\u00d0\u00b0\u00d0\u00b6",
+ "\u0120Gram",
+ "\u0120Conference",
+ "\u0120deficit",
+ "s\u00c4\u00b1n",
+ "inse",
+ "u\u00c4\u0141",
+ "\u0120richt",
+ "\u0120coincidence",
+ "\u00e5\u0131\u012f",
+ "\u0120europ",
+ "\u0120butterfly",
+ "pread",
+ "\u0120\u00ec\u0138\u00bc",
+ "\u00e8\u0122\u00b6",
+ "\u0120wavel",
+ "\u0120Infin",
+ "\u0120Planet",
+ "\u0120selfie",
+ "ientras",
+ "\u0120arrog",
+ "oser",
+ "idal",
+ "\u0142\u00d7\u0139\u00d7\u0142\u00d7\u0137",
+ "\u00c3\u00bct\u00c3\u00bcn",
+ "\u0120freshman",
+ "\u0120Machine",
+ "\u00cf\u0125\u00cf\u0126",
+ "\u0120Dia",
+ "\u00ec\u013f\u00b4\u00eb\u012d\u00a4",
+ "\u00e3\u0123\u0135\u00e3\u0123\u0128",
+ "nea",
+ "\u0120listing",
+ "\u0120configure",
+ "utor",
+ "Up",
+ "tschaft",
+ "ri\u00c3\u00a8re",
+ "\u0120upwards",
+ "\u0120\u00d1\u0127\u00d0\u00be\u00d1\u0129\u00d1\u0125",
+ "\u0120sweep",
+ "Br",
+ "\u0120expressing",
+ "\u0120unhappy",
+ "\u0120mandatory",
+ "gender",
+ "\u0120A\u00c3\u0143",
+ "\u0120indicators",
+ "\u0120oils",
+ "note",
+ "\u0120segur",
+ "\u00d0\u00be\u00d0\u00b6\u00d0\u00b5\u00d1\u0124",
+ "ynasty",
+ "\u0120distances",
+ "\u0120merge",
+ "BERT",
+ "\u0120surrender",
+ "\u0120buat",
+ "\u0120Awards",
+ "\u0120se\u00c3\u00b1or",
+ "odox",
+ "\u0120flavour",
+ "\u0120abdom",
+ "\u0120configur",
+ "86",
+ "\u0120DIY",
+ "\u0120rigid",
+ "\u00b0\u013a",
+ "\u0120corporation",
+ "\u0120groom",
+ "jaw",
+ "\u0120Near",
+ "\u00d0\u00b8\u00d0\u00bb\u00d0\u00be",
+ "\u0120opera",
+ "\u0120Innov",
+ "\u00d0\u00b8\u00d1\u0122\u00d0\u00b0",
+ "\u0135\u00b1",
+ "\u0120specified",
+ "\u0120cosm",
+ "\u0120Freedom",
+ "\u0120clown",
+ "\u0120Nem",
+ "\u0120\u00d0\u00b2\u00d0\u00be\u00d0\u00bb",
+ "\u00d1\u0133\u00d0\u00bd",
+ "\u0120charger",
+ "\u00e0\u00b9\u0123\u00e0\u00b8\u00a5",
+ "\u0120influential",
+ "\u00c3\u00a4sident",
+ "\u00e9\u00a4",
+ "\u0120\u00ec\u0126\u0142\u00eb",
+ "\u0120volumes",
+ "\u00e6\u0132",
+ "\u0120outras",
+ "\u0120Twitch",
+ "\u0120founding",
+ "\u0120awhile",
+ "\u0120coil",
+ "\u00ea\u00b0\u013b",
+ "\u0120c\u00e1\u00ba\u00a3",
+ "\u0120Throw",
+ "\u0120Hence",
+ "ommt",
+ "\u0120Benjamin",
+ "\u00d0\u00b3\u00d0\u00bb\u00d1\u0131\u00d0\u00b4",
+ "Time",
+ "obic",
+ "\u0120mour",
+ "\u0120dread",
+ "\u0120L\u00c3\u0142",
+ "\u0120Chile",
+ "\u0120preval",
+ "\u0120vain",
+ "\u0120art\u00c4\u00b1k",
+ "\u0120preserved",
+ "\u0120\u00d0\u00be\u00d1\u0124\u00d0\u00b4",
+ "\u0120warehouse",
+ "\u0120beste",
+ "\u0120Several",
+ "\u0120Situation",
+ "\u0120cardboard",
+ "Tod",
+ "erna",
+ "\u0120garant",
+ "\u0120gesture",
+ "\u0120hen",
+ "\u0120spelling",
+ "osexual",
+ "\u0120anne",
+ "\u0120mice",
+ "\u0120Meine",
+ "card",
+ "\u0120rebell",
+ "\u0120certo",
+ "\u0120\u00ec\u013e\u0142\u00eb",
+ "\u0120verschied",
+ "\u0120Bos",
+ "\u0120invention",
+ "\u0120trze",
+ "\u0120mani\u00c3\u00a8re",
+ "\u0120Chad",
+ "\u0120spre",
+ "\u0120organisations",
+ "\u0120poorly",
+ "\u0120anterior",
+ "\u0120stair",
+ "\u00d0\u00ba\u00d1\u0122",
+ "\u0120atomic",
+ "\u0120sympath",
+ "\u0120continually",
+ "\u0120kleine",
+ "\u00c3\u00a8te",
+ "\u00d0\u00b8\u00d1\u012b",
+ "\u00ce\u00bf\u00cf\u0124",
+ "peut",
+ "\u0120reposit",
+ "\u0120entra",
+ "Em",
+ "\u0120financing",
+ "\u0120\u00d0\u00bc\u00d0\u00bd\u00d0\u00be\u00d0\u00b3",
+ "\u0120thesis",
+ "\u0120Computer",
+ "eau",
+ "\u0120Tree",
+ "\u0120bride",
+ "onsieur",
+ "shire",
+ "wic",
+ "DE",
+ "\u0120\u00ec\u012a\u013a\u00eb",
+ "\u0120acom",
+ "\u0120PO",
+ "ersch",
+ "\u0120\u00d0\u00bf\u00d0\u00be\u00d0\u00bc\u00d0\u00be\u00d1\u012b",
+ "\u0120Armen",
+ "\u0120\u00ec\u00a3\u00bd",
+ "\u0120zor",
+ "\u0120prints",
+ "\u0120Dass",
+ "\u00e6\u00b8\u00af",
+ "\u0120durable",
+ "\u0120Transport",
+ "\u00ec\u0140\u0132\u00ea\u00b0\u0122",
+ "\u0120\u00d0\u00bb\u00d0\u00b5\u00d0\u00b3",
+ "\u0120d\u00c3\u00a9t",
+ "\u00c3\u00b4le",
+ "amous",
+ "YN",
+ "\u0120cliff",
+ "\u0120grammar",
+ "\u0120\u00d0\u0141\u00d0\u00be\u00d1\u012f\u00d1\u0124\u00d0\u00be\u00d0\u00bc\u00d1\u0125",
+ "\u0120l\u00c3\u0142m",
+ "esch",
+ "\u0120miserable",
+ "\u0120volts",
+ "\u0120Cad",
+ "ukan",
+ "\u00d1\u0124\u00d0\u00b8\u00d0\u00b2",
+ "rust",
+ "\u0120\u00ec\u013a\u00ac\u00eb\u013f\u00bc",
+ "\u0120verk",
+ "\u0120chickens",
+ "\u0120Yoo",
+ "\u0120outfits",
+ "code",
+ "\u0120hierarchy",
+ "netes",
+ "\u0120counterpart",
+ "\u0120t\u00c3\u00b4i",
+ "\u0120ted",
+ "\u0120Bart",
+ "\u0120\u00eb\u013f\u00bc",
+ "\u0120Genau",
+ "\u0120incoming",
+ "\u0120ABC",
+ "rique",
+ "\u0120\u00d0\u00be\u00d1\u0124\u00d0\u00bf",
+ "qual",
+ "\u0120incentive",
+ "\u0120ihren",
+ "\u00d7\u0142\u00d7\u013b",
+ "loe",
+ "\u01201930",
+ "\u0120barg",
+ "\u0120diction",
+ "\u0120\u00c3\u00b6nce",
+ "INS",
+ "\u0120reh",
+ "isiaj",
+ "mouth",
+ "\u0120scoring",
+ "l\u00c4\u00b1k",
+ "\u0120\u00ec\u0137\u0126\u00ec\u00a3\u00bc",
+ "ORIA",
+ "\u0120Estados",
+ "\u0120companion",
+ "\u0120assemble",
+ "\u0120punished",
+ "\u0120ital",
+ "\u0120prevents",
+ "istes",
+ "\u0120Kentucky",
+ "\u0120locate",
+ "\u0120fasting",
+ "\u00e3\u0123\u00a8\u00e6\u0122\u013f",
+ "\u0125\u0122",
+ "\u0120Seb",
+ "\u0120Crown",
+ "opia",
+ "\u0120whip",
+ "usz",
+ "\u00d0\u00ba\u00d0\u00b0\u00d0\u00bc\u00d0\u00b8",
+ "\u0120databases",
+ "\u00e5\u0143\u0139",
+ "\u0120prosec",
+ "\u01201997",
+ "\u0120\u00ec\u0124\u00b4\u00ec\u00a7\u013f",
+ "\u0120Solar",
+ "\u0120Pues",
+ "\u0120Zen",
+ "ollo",
+ "\u0120Guru",
+ "\u0120squeez",
+ "\u0120\u00d0\u0139\u00d0\u00b0",
+ "\u0120\u00c4\u012f",
+ "ceptions",
+ "cca",
+ "izable",
+ "mand",
+ "\u0120breakthrough",
+ "\u0120tablespoon",
+ "\u0120SEC",
+ "ikh",
+ "\u0120S\u00c3\u00a3o",
+ "\u0120\u00d0\u00bf\u00d0\u00bb\u00d0\u00be",
+ "amen",
+ "\u0120prac",
+ "\u0120darling",
+ "\u0120taller",
+ "\u0120rendering",
+ "\u0120\u00ec\u013c\u00b0\u00eb\u00a6\u00ac\u00ea\u00b0\u0122",
+ "\u0120\u00cf\u0126\u00ce\u00b7\u00cf\u0124",
+ "\u0120m\u00c3\u00a3",
+ "\u0120esos",
+ "uerdo",
+ "\u0120\u00d1\u0123\u00d1\u0129\u00d0\u00b8\u00d1\u0124",
+ "aller",
+ "\u00ec\u0139\u012a\u00ec\u0138\u00b4\u00ec\u013c\u0136",
+ "\u0120millones",
+ "lerin",
+ "\u0120pegar",
+ "onne",
+ "\u0120enrollment",
+ "\u0120liegt",
+ "\u0120boa",
+ "wi\u00c4\u013b",
+ "bsp",
+ "\u0120cycling",
+ "\u0120Bernie",
+ "\u01201989",
+ "\u0120\u00d0\u00b4\u00d0\u00b0\u00d0\u00bb\u00d1\u012e",
+ "\u0120Dakota",
+ "\u0120\u00d1\u0123\u00d0\u00b2\u00d1\u0131\u00d0\u00b7",
+ "\u0120CP",
+ "\u0120stare",
+ "\u00ed\u0124\u00a4",
+ "\u0120prosperity",
+ "\u0120arrangements",
+ "\u0120arriving",
+ "m\u00c3\u00a4",
+ "\u0120kayak",
+ "ipt",
+ "\u0120pardon",
+ "\u0120relat",
+ "\u0120verste",
+ "\u0120Fig",
+ "\u0120foil",
+ "\u0120Talking",
+ "peare",
+ "\u0120noi",
+ "\u0120\u00d0\u00bf\u00d1\u0122\u00d0\u00b8\u00d1\u012a",
+ "\u0120hockey",
+ "\u0120ado",
+ "\u0120OUT",
+ "67",
+ "\u0120hormones",
+ "\u0120Avenue",
+ "\u0120Superman",
+ "\u0120prescription",
+ "ubernetes",
+ "CL",
+ "otive",
+ "NIS",
+ "ienen",
+ "\u0120sadness",
+ "\u0120Vit",
+ "Ty",
+ "\u0120starter",
+ "\u0120bede",
+ "\u0120foundations",
+ "\u0120sore",
+ "\u00e5\u00ba\u0139",
+ "\u00d1\u012b\u00d0\u00b5\u00d1\u0123\u00d1\u0124\u00d0\u00b2",
+ "\u00ec\u013c\u00b0\u00eb",
+ "\u0120\u00d1\u0129\u00d1\u0125\u00d0\u00b2",
+ "link",
+ "\u0120maneu",
+ "working",
+ "\u00c3\u0142n",
+ "\u0120Attack",
+ "\u0120Cart",
+ "veis",
+ "\u0120Resp",
+ "ensing",
+ "\u0120\u00ec\u00a2\u012d\u00ec\u0137\u0126\u00ec\u013c\u0136",
+ "\u0120escuch",
+ "\u0120RNA",
+ "\u0124\u00b4",
+ "\u0120adop",
+ "\u0120bending",
+ "\u00d8\u00b9\u00d8\u00af",
+ "\u0120manages",
+ "usp",
+ "\u0120tart",
+ "\u0120router",
+ "Bo",
+ "\u0120establishing",
+ "\u0120balancing",
+ "\u0120athletic",
+ "\u0120Slo",
+ "\u0120fills",
+ "\u0120\u00d0\u00bd\u00d0\u00b0\u00d0\u00b1",
+ "\u0120\u00d0\u00b4\u00d0\u00b0\u00d0\u00bb",
+ "\u0120posso",
+ "\u0120Vielen",
+ "\u0120critics",
+ "\u0120lawsuit",
+ "\u0120Isaac",
+ "\u0120\u00d1\u0126\u00d0\u00b8\u00d0\u00bb\u00d1\u012e\u00d0\u00bc",
+ "\u0120tras",
+ "\u0120praw",
+ "\u0120Crazy",
+ "\u0120neu",
+ "\u0120kull",
+ "\u0120tumor",
+ "\u0120APP",
+ "gate",
+ "\u0120ARE",
+ "98",
+ "\u0120Steam",
+ "\u0120fucked",
+ "lage",
+ "\u0120\u00e2\u013b\u00ac",
+ "\u0120MD",
+ "fy",
+ "\u0120shells",
+ "\u0120Seems",
+ "izers",
+ "\u0120ranges",
+ "\u0120Antonio",
+ "ATION",
+ "\u0120Baba",
+ "\u0120\u00ec\u0125\u012b",
+ "kun",
+ "\u0120prayed",
+ "\u00d1\u0122\u00d1\u0131",
+ "\u0120\u00d0\u00bf\u00d1\u0122\u00d0\u00be\u00d1\u0124\u00d0\u00b8\u00d0\u00b2",
+ "\u0120seas",
+ "bury",
+ "\u0120\u00d7\u0136\u00d7\u00a9",
+ "\u0120trait",
+ "\u0120Depending",
+ "\u0120dre",
+ "\u0120k\u00c3\u00b6nnt",
+ "\u00d1\u0128\u00d1\u0125",
+ "\u0120lipstick",
+ "eez",
+ "\u0120\u00d0\u00bf\u00d1\u0122\u00d0\u00b8\u00d0\u00bc\u00d0\u00b5\u00d1\u0122",
+ "\u0120assignments",
+ "Bob",
+ "\u0120metals",
+ "\u0120specially",
+ "\u00e5\u00b0\u012f\u00e4\u00b8\u012f\u00e5\u00b0\u012f",
+ "\u0120\u00ec\u013a\u012a\u00eb",
+ "\u0120\u00c5\u00a1",
+ "\u0120vista",
+ "\u0120\u00ce\u00ac",
+ "\u0120twins",
+ "\u0120notable",
+ "\u0120Sau",
+ "\u0120d\u00c3\u00a9velop",
+ "\u0120\u00c3\u00a7ek",
+ "\u0120polynom",
+ "avam",
+ "\u0120tamb\u00c3\u00a9",
+ "\u00d0\u00be\u00d0\u00bd\u00d0\u00be\u00d0\u00bc",
+ "\u0120plasma",
+ "\u0120efect",
+ "\u0120l\u00c3\u00a4ng",
+ "\u0120casi",
+ "\u00d1\u0123\u00d0\u00b0",
+ "\u00c4\u00b1m\u00c4\u00b1",
+ "\u00e3\u0123\u013b\u00e3\u0124\u012d",
+ "\u0135\u00a4\u00ec\u013f\u0122",
+ "\u0120labour",
+ "ossen",
+ "\u0120Pun",
+ "rif",
+ "\u0120doses",
+ "\u0120operates",
+ "\u00d0\u00b8\u00d0\u00bb\u00d0\u00bb\u00d0\u00b8",
+ "\u0120jaar",
+ "staw",
+ "\u0120\u00ec\u0124\u00ac\u00eb\u0140\u0133",
+ "\u0120atm",
+ "\u0120protects",
+ "\u0120imped",
+ "HO",
+ "\u0120cima",
+ "\u0120toch",
+ "abis",
+ "\u0120sendo",
+ "laus",
+ "\u0120curl",
+ "\u0120Num",
+ "\u0120sponsors",
+ "\u0120d\u00c3\u00a9but",
+ "\u0120Alexa",
+ "\u0120B\u00c3\u00bcr",
+ "\u0120Amer",
+ "\u0120cope",
+ "\u0120\u00d0\u00b8\u00d0\u00b7\u00d0\u00b2",
+ "jal",
+ "\u01201995",
+ "apat",
+ "resse",
+ "\u0120Prize",
+ "\u0120Claire",
+ "\u0120Brandon",
+ "\u0120wszystko",
+ "\u0120valued",
+ "\u00e0\u00b8\u013b\u00e0\u00b8\u00b0",
+ "\u0120sect",
+ "\u0120secretly",
+ "\u0120diamonds",
+ "\u0120Evan",
+ "\u0120RPG",
+ "\u00e3\u0123\u00ab\u00e3\u0123\u00aa",
+ "\u012a\u00eb\u0131\u0126",
+ "\u0120Universal",
+ "\u0120doubts",
+ "\u0120Pin",
+ "wi\u00c4\u0127z",
+ "\u013c\u00a9",
+ "\u0120albo",
+ "\u0120braucht",
+ "AUL",
+ "\u0120Mobile",
+ "grades",
+ "\u0120schem",
+ "why",
+ "\u0120Nicht",
+ "pi",
+ "gle",
+ "\u0120chorus",
+ "\u0120gly",
+ "\u0120reinforce",
+ "\u0120muff",
+ "\u0120Shen",
+ "\u0120Hola",
+ "\u00d1\u0125\u00d0\u00b3",
+ "videmment",
+ "vial",
+ "acious",
+ "laimed",
+ "\u0120Rico",
+ "\u0120vegg",
+ "\u0120illustration",
+ "\u0120Butter",
+ "owad",
+ "\u0120eux",
+ "\u0120enfants",
+ "\u0120Leader",
+ "\u0120Village",
+ "etically",
+ "\u00d9\u0128\u00d9\u012c",
+ "\u0120stew",
+ "\u0120surprises",
+ "\u0120cue",
+ "\u0120Grandma",
+ "\u0120Celsius",
+ "\u0120Richt",
+ "enc",
+ "\u0120petition",
+ "\u0120herb",
+ "\u0120wicked",
+ "\u0120schle",
+ "ocaly",
+ "\u0120transf",
+ "\u0120tokens",
+ "\u0120Gray",
+ "\u0120BBC",
+ "IK",
+ "\u01201500",
+ "zn",
+ "\u0120Nev",
+ "\u0120koy",
+ "\u0120zar",
+ "\u0120bullshit",
+ "\u0120Colombia",
+ "ulative",
+ "\u0120widespread",
+ "yect",
+ "kit",
+ "\u0120empresa",
+ "\u0120nour",
+ "\u0120burns",
+ "atin",
+ "aired",
+ "\u0120revolutionary",
+ "\u0120\u00d0\u00b3\u00d0\u00be\u00d0\u00b4\u00d1\u0125",
+ "\u0120Logan",
+ "\u01201996",
+ "\u0120Graham",
+ "reb",
+ "\u0120NHS",
+ "\u00e6\u013e\u013d",
+ "\u0120costumes",
+ "\u0120nawet",
+ "\u0120lovers",
+ "\u0120Lucy",
+ "\u0120Indigenous",
+ "\u00ed\u0137\u013a\u00ea\u00b8\u00b0",
+ "\u0120immunity",
+ "\u00a5\u00b4\u00eb",
+ "uito",
+ "\u0120excessive",
+ "\u0120donations",
+ "\u0120\u00d7\u0136\u00d7\u00a8",
+ "\u0120\u00ec\u00b2\u00ab",
+ "\u00e9\u012b\u0126",
+ "\u0120drying",
+ "melon",
+ "\u0120surveys",
+ "\u0120\u00eb\u00ac\u00b4\u00ec\u012c\u00a8",
+ "\u00e9\u00a2\u00a8",
+ "aaa",
+ "\u0120probe",
+ "ancial",
+ "\u0120louder",
+ "\u0120hotels",
+ "\u00c3\u00bc\u00c4\u0141",
+ "agner",
+ "\u0120origins",
+ "\u0120\u00eb\u00a7\u012a\u00ec\u00a7\u0122\u00eb\u00a7\u012b",
+ "\u0120**",
+ "\u0120strangers",
+ "\u0120Haus",
+ "comed",
+ "\u0120anthrop",
+ "\u0120uso",
+ "\u0120\u00ec\u0137\u0126\u00ec\u00a7\u0123",
+ "\u0120Yuan",
+ "\u0120\u00ed\u0137\u0126\u00ec\u013c\u0136",
+ "pler",
+ "ressive",
+ "\u0120spraw",
+ "\u0120Stew",
+ "\u01201994",
+ "\u0120elders",
+ "\u0120meinen",
+ "\u0120junt",
+ "\u0120acoust",
+ "\u0120Wohn",
+ "\u0120bananas",
+ "\u0120projection",
+ "\u0120Stick",
+ "legt",
+ "speed",
+ "\u0120c\u00c5\u00a9ng",
+ "\u0120Wort",
+ "\u0120Baltimore",
+ "\u0120\u00d1\u0128\u00d0\u00b5\u00d0\u00bb",
+ "\u0120dunno",
+ "\u00e5\u00bc\u00b7",
+ "?,",
+ "\u00e3\u0125\u012b\u00e3\u0125\u00b3",
+ "\u0120Local",
+ "osto",
+ "\u00d0\u0143",
+ "\u00d0\u00be\u00d0\u00b4\u00d0\u00b0",
+ "\u0120Portuguese",
+ "\u0120theirs",
+ "\u0120d\u00c3\u00a9m",
+ "\u00e5\u0131\u00a6",
+ "\u0120drauf",
+ "\u0120Buddhist",
+ "erta",
+ "Ge",
+ "\u0120carrot",
+ "\u0120Wonderful",
+ "\u0120soak",
+ "\u0120chairman",
+ "ggi",
+ "ICA",
+ "fried",
+ "\u0120flick",
+ "\u0120Throughout",
+ "\u0120\u00ec\u013c\u00b0\u00eb",
+ "\u0120cough",
+ "\u0120fluffy",
+ "school",
+ "\u0120ripped",
+ "--------",
+ "\u0120Zukunft",
+ "\u0120\u00d0\u00bd\u00d0\u00b5\u00d0\u00b1",
+ "\u0120sto",
+ "\u0120BO",
+ "pent",
+ "\u0120Lawrence",
+ "\u00cf\u012b\u00cf\u0124",
+ "sticks",
+ "\u0120Eins",
+ "\u0120\u00d1\u0122\u00d1\u012d",
+ "\u0120Strong",
+ "\u0120caramel",
+ "\u0120spite",
+ "azar",
+ "\u00e9\u0125\u00bd\u00e6\u013a\u00af",
+ "\u0120critically",
+ "\u0120obra",
+ "owitz",
+ "\u0120Zone",
+ "\u0120\u00d1\u0122\u00d0\u00b5\u00d0\u00ba",
+ "\u0120sug",
+ "arded",
+ "\u0120g\u00c3\u00ac",
+ "ffentlich",
+ "anche",
+ "\u00d8\u0141",
+ "astically",
+ "\u00ec\u013f\u00bc\u00eb",
+ "\u00d0\u00bb\u00d0\u00b0\u00d0\u00b2",
+ "\u0120simplest",
+ "\u0120Friend",
+ "\u0120quello",
+ "\u0120ambition",
+ "\u0120abbiamo",
+ "\u00e5\u00ba\u0137",
+ "\u0120\u00d1\u0126\u00d0\u00be\u00d1\u0122\u00d0\u00bc",
+ "\u0120Essa",
+ "\u0120educators",
+ "\u0120statistical",
+ "\u00e9\u0122\u013b\u00e9\u0124\u012c",
+ "\u0120changer",
+ "\u0120atau",
+ "\u00c3\u00a9tais",
+ "\u0120Shakespeare",
+ "\u00eb\u0132\u013a",
+ "\u0120triggers",
+ "\u0120realiz",
+ "\u0120celui",
+ "wheel",
+ "\u0120loyalty",
+ "\u0120screams",
+ "kehr",
+ "\u0120Mega",
+ "east",
+ "\u0120tops",
+ "\u0120Totally",
+ "ountain",
+ "lord",
+ "\u0120violation",
+ "\u0120GA",
+ "\u0120nicer",
+ "\u0120Fresh",
+ "\u0120Melissa",
+ "function",
+ "\u0120rape",
+ "\u0120exceptions",
+ "\u0120silicon",
+ "\u0120liberty",
+ "\u0120households",
+ "\u00e3\u0123\u012f\u00e3\u0123\u00be\u00e3\u0123\u013b",
+ "\u0120CA",
+ "\u0120\u00d0\u0140\u00d0\u00b1",
+ "\u0120lib",
+ "\u0140\u012e",
+ "cific",
+ "\u0120tropical",
+ "\u0120investigating",
+ "HD",
+ "\u0120adapter",
+ "\u0120Pitt",
+ "ancia",
+ "\u0120Shell",
+ "friendly",
+ "\u0120conclusions",
+ "\u0120turtle",
+ "\u0120decomp",
+ "\u0120animations",
+ "\u0120\u00d1\u0123\u00d0\u00b5\u00d0\u00ba",
+ "insi",
+ "\u0120retention",
+ "kie",
+ "\u0120injection",
+ "\u0120Madison",
+ "\u00ec\u00b0\u00b0",
+ "\u0120vient",
+ "\u0120varied",
+ "\u0120violin",
+ "\u0120Bil",
+ "\u0120luckily",
+ "\u0120htt",
+ "l\u00c3\u00a4",
+ "\u0120ranch",
+ "\u00e7\u013e\u012d\u00e7\u013e\u012d",
+ "\u0120s\u00c3\u00b3lo",
+ "\u00ec\u0137\u0127",
+ "\u0120Derek",
+ "\u0120Scripture",
+ "\u00d0\u00be\u00d1\u0122\u00d0\u00b0",
+ "\u0120classrooms",
+ "avil",
+ "formed",
+ "\u0120beforehand",
+ "\u0120Gem",
+ "prech",
+ "\u0120lin",
+ "\u0120greens",
+ "\u00d1\u0128\u00d0\u00b5\u00d0\u00b2",
+ "\u0120Mercedes",
+ "\u0120drought",
+ "gasps",
+ "\u0120abortion",
+ "\u0120terribly",
+ "\u0120spos\u00c3\u00b3b",
+ "\u0120secured",
+ "\u0120atr\u00c3\u00a1s",
+ "\u0120wavelength",
+ "\u0120grains",
+ "ective",
+ "\u0120spacecraft",
+ "\u0120tours",
+ "\u0120profes",
+ "\u0120surgeon",
+ "\u0120Pie",
+ "\u0120ideally",
+ "arner",
+ "UP",
+ "opard",
+ "sce",
+ "\u0120immense",
+ "\u0120Ort",
+ "roller",
+ "\u0120Dallas",
+ "\u0120Nicholas",
+ "\u0120sulf",
+ "\u0120Toyota",
+ "\u0120quantities",
+ "ceans",
+ "\u0120cui",
+ "an\u00c3\u00a7a",
+ "\u0120CAN",
+ "itzerland",
+ "\u00e5\u0126\u00bf",
+ "\u0120zou",
+ "\u0120Cyber",
+ "legen",
+ "\u0120Init",
+ "edu",
+ "\u0120apert",
+ "\u0120adjac",
+ "ouv",
+ "\u00e8\u0122\u012e\u00e4\u00b8\u0136",
+ "rs",
+ "\u0120cabbage",
+ "\u0120wheelchair",
+ "inyl",
+ "\u0120Dynam",
+ "\u0120\u00ec\u0137\u0126\u00eb\u012d\u012a\u00eb\u013f\u00bc",
+ "\u0120ling",
+ "hl",
+ "\u0120\u00d0\u00bc\u00d0\u00be\u00d0\u00b3\u00d1\u0125",
+ "\u0120crisp",
+ "\u0120mij",
+ "\u0120dug",
+ "nin",
+ "\u0120bloss",
+ "\u0120belonging",
+ "\u0120loudly",
+ "\u0120minerals",
+ "\u0120concluded",
+ "\u0120searched",
+ "96",
+ "\u0120Meet",
+ "\u0120SEO",
+ "\u0120\u00d0\u00a1\u00d0\u00ba",
+ "\u0120Hob",
+ "otta",
+ "\u0120propaganda",
+ "\u0120cinnamon",
+ "\u0120hunter",
+ "\u0120gemeins",
+ "\u0120sculpture",
+ "ulsion",
+ "\u0120v\u00c3\u00a4l",
+ "\u0120magazines",
+ "\u0120controversy",
+ "\u00e4\u00b8\u0122\u00e6\u00a8\u00a3",
+ "\u0120sequences",
+ "\u00e3\u0123\u0126\u00e3\u0124\u012d",
+ "\u0120\u00ed\u013c\u012e",
+ "\u0120deleted",
+ "\u00e4\u00bd\u00bf",
+ "\u0132\u00eb\u0131\u0126",
+ "\u0120varying",
+ "\u00e3\u0125\u0128",
+ "\u0120mounting",
+ "\u0120affair",
+ "\u0120pathways",
+ "\u00e6\u00a6",
+ "\u0120digo",
+ "\u00e4\u00ba\u00ae",
+ "\u0120\u00d0\u00b4\u00d0\u00be\u00d0\u00ba",
+ "Alex",
+ "\u0120tobacco",
+ "\u0120CV",
+ "\u0120bothered",
+ "\u0120ambient",
+ "inky",
+ "\u0120SL",
+ "\u0120hates",
+ "\u0120je\u00c5\u00bceli",
+ "\u0120congreg",
+ "\u0120elas",
+ "\u0120deuts",
+ "\u0120Studios",
+ "ch\u00c4\u013b",
+ "\u0120documented",
+ "\u0120Cruz",
+ "\u0120Len",
+ "\u0120Douglas",
+ "\u0120Portugal",
+ "enti",
+ "\u0120spouse",
+ "\u0120analys",
+ "avia",
+ "\u0120edited",
+ "\u0120l\u00e1\u00ba\u00a1i",
+ "built",
+ "\u0120ville",
+ "adora",
+ "\u0120bracelet",
+ "\u0120sushi",
+ "\u0120pm",
+ "\u0120trails",
+ "\u0120lug",
+ "\u0120\u00c3\u00b6ver",
+ "\u0120sorrow",
+ "\u0120colony",
+ "adox",
+ "\u0120serie",
+ "anyak",
+ "\u0120\u00d8\u00b7",
+ "\u0120Gulf",
+ "\u00e6\u013a\u00af\u00e4\u00b8\u012f\u00e6\u013a\u00af",
+ "\u0120PV",
+ "\u0120Samuel",
+ "\u0120Kit",
+ "\u0120Ral",
+ "ontin",
+ "expl",
+ "\u0120entries",
+ "\u0120activists",
+ "Ps",
+ "\u0120sant",
+ "\u0120\u00d1\u0124\u00d0\u00be\u00d1\u0129",
+ "\u0120Bruno",
+ "keley",
+ "\u0120tutto",
+ "\u00e9\u0136",
+ "\u0120vintage",
+ "\u0120terrified",
+ "\u0120\u00d0\u00bf\u00d0\u00be\u00d1\u0127",
+ "usive",
+ "owers",
+ "\u00d0\u00b0\u00d0\u00b9\u00d1\u0124",
+ "\u00eb\u0131\u013b",
+ "\u0120twisted",
+ "\u0120Thought",
+ "\u0120tah",
+ "\u0120shrink",
+ "\u0120sheer",
+ "lit",
+ "\u0120dalam",
+ "\u0120dib",
+ "\u0120vard",
+ "owane",
+ "\u0120dobr",
+ "\u0120Rena",
+ "\u0120\u00d1\u0123\u00d0\u00b2\u00d0\u00be\u00d1\u0130",
+ "\u0120pa\u00c3\u0143ses",
+ "\u0120Era",
+ "\u00e3\u0123\u00ae\u00e3\u0123\u00a7",
+ "\u0120BUT",
+ "sighs",
+ "\u0120\u00ea\u00b7\u00b8\u00ea\u00b1\u00b0",
+ "\u0120gro\u00c3\u0141en",
+ "\u0120\u00eb\u00b9\u00a8\u00eb\u00a6\u00ac",
+ "\u0120nerves",
+ "\u0120constit",
+ "\u0120preocup",
+ "\u0120Gay",
+ "\u0120Xu",
+ "keeper",
+ "heure",
+ "..)",
+ "\u0120Calm",
+ "\u0120Unidos",
+ "\u0120\u00ec\u013f\u00b4\u00ea\u00b2\u0125",
+ "\u0120Aqui",
+ "\u0120\u00ec\u0142\u013e\u00ec\u013f\u00bc",
+ "d\u00c4\u00b1r",
+ "\u00ec\u00a6\u013a",
+ "your",
+ "\u0120\u00d1\u012f\u00d1\u0124\u00d0\u00b8\u00d0\u00bc",
+ "2020",
+ "\u0120rund",
+ "\u0120HO",
+ "\u0120Catherine",
+ "ieli",
+ "\u0120fusion",
+ "\u0120ideology",
+ "\u0120foram",
+ "shaped",
+ "\u0120\u00ed\u013d\u0126\u00eb",
+ "\u0120wt",
+ "\u0120retr",
+ "\u0120pr\u00c3\u00a9c",
+ "\u0120\u00ea\u00b0\u0133",
+ "\u0120openly",
+ "vity",
+ "\u00ea\u00b5\u00ac\u00ec\u013c\u0136",
+ "\u0120obstacle",
+ "\u0120boo",
+ "\u0120seiner",
+ "icorn",
+ "\u0120eigenlijk",
+ "\u0120header",
+ "aremos",
+ "\u0120softer",
+ "\u0120\u00d0\u0141\u00d0\u00be\u00d0\u00b4",
+ "\u0120prejud",
+ "\u0120defines",
+ "ierte",
+ "\u0120blending",
+ "\u0120believers",
+ "\u0120Wochen",
+ "\u0120\u00d0\u00bd\u00d0\u00b8\u00d0\u00ba\u00d0\u00b0\u00d0\u00ba",
+ "\u0120\u00d0\u013c\u00d0\u00be\u00d0\u00b3\u00d0\u00b4\u00d0\u00b0",
+ "\u0120Typically",
+ "\u0120\u00ed\u0123\u00ac",
+ "\u00e7\u00ae\u00a1",
+ "cios",
+ "\u0120missiles",
+ "\u0120sponge",
+ "\u0120Kitchen",
+ "\u0120tren",
+ "ningen",
+ "\u0120scrap",
+ "\u0120serait",
+ "\u00b4\u00ec\u0142",
+ "\u00e7\u00b9",
+ "\u0120\u00eb\u00b0\u013a\u00eb",
+ "\u0120restored",
+ "\u0120przyk\u00c5\u0124ad",
+ "\u0120Kubernetes",
+ "\u0120sait",
+ "\u0120uw",
+ "\u0120enabling",
+ "\u0120travers",
+ "amps",
+ "\u00e5\u0131\u0139",
+ "\u0120OMG",
+ "ensor",
+ "\u0120zosta",
+ "\u0120pronounced",
+ "Ang",
+ "normal",
+ "\u0120economies",
+ "tin",
+ "\u0120Champion",
+ "izen",
+ "\u0120arbeiten",
+ "\u0120Gospel",
+ "\u0120Zu",
+ "nga",
+ "\u0120literacy",
+ "\u0120Mans",
+ "\u0120circulation",
+ "\u0120adap",
+ "\u0120Total",
+ "\u0120mereka",
+ "\u0120olacak",
+ "\u00d1\u0123\u00d1\u0124\u00d0\u00b0\u00d1\u0124\u00d0\u00b8",
+ "Jack",
+ "\u0120mund",
+ "\u0120thief",
+ "bies",
+ "\u0120\u00ea\u00b2\u0123",
+ "aque",
+ "\u0120\u00da\u00a9\u00db\u012e",
+ "\u0120Scar",
+ "\u00e5\u00b2",
+ "\u0120abol",
+ "\u0120devote",
+ "\u012001",
+ "\u0120sitten",
+ "\u0120Visual",
+ "week",
+ "some",
+ "ingt",
+ "\u0120journalism",
+ "\u0120Hir",
+ "\u0120Bachelor",
+ "inery",
+ "\u00c3\u013eND",
+ "\u00e3\u0125\u0141",
+ "\u00e7\u00bb\u013b",
+ "\u0120coloring",
+ "\u0120Crist",
+ "\u0120celebrities",
+ "\u0120\u00d1\u0129\u00d0\u00b8\u00d1\u0123",
+ "\u0120Crit",
+ "\u0120differentiate",
+ "\u0120\u00d0\u013e\u00d0\u00bd\u00d0\u00b5",
+ "elim",
+ "\u0120seafood",
+ "\u0120algumas",
+ "otherapy",
+ "\u00e6\u012a\u00b0",
+ "\u0120glaub",
+ "\u0120arbitrary",
+ "gens",
+ "\u0120\u00d0\u00b1\u00d1\u0125\u00d0\u00b4\u00d0\u00b5\u00d0\u00bc",
+ "\u0120tav",
+ "\u0120creamy",
+ "\u0120Country",
+ "a\u00c3\u00b1",
+ "\u00d0\u00bc\u00d0\u00b5\u00d1\u0124",
+ "\u0120hinter",
+ "\u0120mism",
+ "\u0120illustrate",
+ "\u00c3\u013eNDNIS",
+ "\u0120decreasing",
+ "\u0120weniger",
+ "AKI",
+ "ixon",
+ "\u0120\u00d0\u00bd\u00d0\u00b5\u00d0\u00b9",
+ "\u0120fatto",
+ "\u0120nerd",
+ "\u00e7\u0142",
+ "\u0120bitte",
+ "Per",
+ "\u0120tane",
+ "\u0120g\u00c3\u00b6z",
+ "\u0120forte",
+ "\u0120Ey",
+ "\u0120\u00d0\u00bd\u00d0\u00b0\u00d0\u00b2\u00d0\u00b5\u00d1\u0122",
+ "\u00e8\u00a2\u00ab",
+ "\u0120WordPress",
+ "\u0120Mis",
+ "\u00c5\u00af",
+ "z\u00c3\u00a4h",
+ "\u0120int\u00c3\u00a9ress",
+ "osaurs",
+ "\u0120Falls",
+ "\u0120nessa",
+ "97",
+ "\u0120museums",
+ "\u0120corresponds",
+ "\u0120sings",
+ "four",
+ "\u0120eder",
+ "\u0120Communist",
+ "oa",
+ "nek",
+ "\u0120WHO",
+ "\u0120corpo",
+ "\u0120messing",
+ "\u00cf\u0126\u00ce\u00b1\u00ce\u00b9",
+ "\u0120brushes",
+ "\u0120bisc",
+ "\u0120Arbeits",
+ "\u0120Tax",
+ "\u0120sele",
+ "\u0120flags",
+ "oupe",
+ "\u0120anticipated",
+ "\u00e3\u0125\u0133",
+ "\u0120Nad",
+ "\u0120poured",
+ "\u0120ml",
+ "\u0120llama",
+ "\u0120visualize",
+ "\u0120listeners",
+ "\u00d9\u0126\u00d9\u0125",
+ "alten",
+ "Michael",
+ "\u0120cos\u00c3\u00ac",
+ "\u00d5\u00a1\u00d5",
+ "opus",
+ "\u0120\u00ed\u0137\u00b4\u00ec\u00a3\u00bc",
+ "\u0120hike",
+ "\u0120Attorney",
+ "\u0120Hillary",
+ "uded",
+ "\u0120\u00ed\u0137\u013a\u00ec\u00a7\u0122\u00eb\u00a7\u012e",
+ "\u0120dove",
+ "\u0120storms",
+ "\u00d0\u00b0\u00d0\u00ba\u00d1\u0123",
+ "\u0120doctrine",
+ "\u0120hex",
+ "iks",
+ "no\u00c5\u013d\u00c4\u0129",
+ "\u0120scripts",
+ "\u0120\u00ce\u00b4\u00ce\u00b5\u00ce\u00bd",
+ "\u0120\u00d1\u012f\u00d1\u0124\u00d0\u00b8\u00d1\u0127",
+ "\u0120\u00d0\u0128",
+ "aber",
+ "\u0120Vas",
+ "\u0120centimeters",
+ "\u00d7\u0140\u00d7\u0136",
+ "\u00d0\u00bd\u00d0\u00b8\u00d0\u00b1",
+ "\u0120riders",
+ "\u0120Trib",
+ "\u00e5\u012e\u0127",
+ "\u0120tak\u00c5\u00bce",
+ "\u0120noun",
+ "\u0120icons",
+ "\u0120solely",
+ "minded",
+ "\u0120dispon",
+ "\u0120Switzerland",
+ "\u0120clusters",
+ "\u0120queda",
+ "ailing",
+ "\u0120manga",
+ "\u012068",
+ "\u0126\u012a",
+ "\u0120tet",
+ "gins",
+ "haus",
+ "\u00e7\u00a9\u00ba",
+ "\u00e5\u00b7\u00a5",
+ "\u0120OP",
+ "oted",
+ "\u0120nouveau",
+ "ALLY",
+ "\u00d9\u012a\u00d8\u00af",
+ "\u00c3\u00b2n",
+ "\u0120mortality",
+ "\u0120GitHub",
+ "drop",
+ "\u0120disgu",
+ "\u0120recom",
+ "\u0120locals",
+ "\u0120homemade",
+ "amba",
+ "\u0120pronunciation",
+ "\u0120alphabet",
+ "\u00d0\u00b0\u00d0\u00bd\u00d1\u012e",
+ "owany",
+ "iras",
+ "idency",
+ "OME",
+ "\u0120\u00d1\u0122\u00d0\u00b0\u00d1\u0123\u00d1\u0123",
+ "arak",
+ "viamente",
+ "\u0120nonprofit",
+ "\u0120YouTuber",
+ "\u0120parenth",
+ "\u0120Boo",
+ "vat",
+ "\u0120Stir",
+ "\u0120precip",
+ "\u0120ants",
+ "\u0120ally",
+ "\u0120Maori",
+ "\u0120\u00eb\u012e\u0122\u00ed\u0137\u013e",
+ "\u00e5\u0131\u00af\u00e6\u013a\u00af",
+ "ogene",
+ "\u0120Labour",
+ "arette",
+ "\u0120recycling",
+ "ensa",
+ "\u0120pursuit",
+ "\u0120sak",
+ "\u0120\u00d0\u0139\u00d0\u00b4\u00d0\u00b5\u00d1\u0123\u00d1\u012e",
+ "\u0120tolerance",
+ "\u0120saat",
+ "\u0120clicked",
+ "\u00e2\u013b\u00a5",
+ "\u0120facebook",
+ "\u0120Into",
+ "\u0120incentives",
+ "\u00ea\u00b8\u00b0\u00eb\u012c\u0136",
+ "\u0120Dennis",
+ "\u0120Wik",
+ "gesch",
+ "\u00e0\u00b9\u0122\u00e0\u00b8\u013d",
+ "\u0120\u00cf\u0122\u00ce\u00b1",
+ "\u0120Whoo",
+ "\u0120rounded",
+ "\u0120dope",
+ "\u0120capturing",
+ "\u0120Warri",
+ "\u0120civilian",
+ "\u0120charming",
+ "\u0120esas",
+ "\u0120sustained",
+ "\u0120leaning",
+ "\u0120abundance",
+ "\u00c3\u0143lia",
+ "\u00d0\u00b0\u00d0\u00bb\u00d1\u012e\u00d0\u00bd\u00d1\u012d\u00d0\u00b9",
+ "\u0120ph\u00e1\u00ba\u00a3i",
+ "acja",
+ "\u0120\u00ea\u00b0\u013b\u00ec\u0137\u0126",
+ "activ",
+ "\u00e0\u00b8\u00b2\u00e0\u00b8\u00a2",
+ "\u012097",
+ "\u0120\u00d0\u00bc\u00d0\u00be\u00d0\u00b9",
+ "cro",
+ "\u0120Jackie",
+ "ittees",
+ "bracht",
+ "ulent",
+ "\u0120\u00ec\u0142\u013e\u00eb",
+ "\u0120plugin",
+ "vantage",
+ "party",
+ "\u0120suas",
+ "\u0120ante",
+ "\u00d1\u0125\u00d0\u00bb",
+ "\u00d0\u013f\u00d0\u0132",
+ "\u00e6\u0124\u00a8",
+ "\u0120\u00cf\u0125\u00cf\u0127",
+ "\u0120meth",
+ "\u0120enthusiasm",
+ "\u00d1\u0131\u00d1\u0124\u00d1\u0123\u00d1\u0131",
+ "\u00ed\u013b\u0136\u00eb",
+ "\u0120synthetic",
+ "\u0120seasoning",
+ "\u0120Lost",
+ "onomy",
+ "\u0120Spark",
+ "\u0120bure",
+ "\u0120assured",
+ "\u0120imagin",
+ "\u0120carro",
+ "Sha",
+ "\u00c4\u0127t",
+ "\u00d0\u00bd\u00d1\u0125\u00d1\u0124\u00d1\u012e",
+ "\u00c3\u00a1tica",
+ "TY",
+ "\u0120kern",
+ "\u0120Brazilian",
+ "\u00c3\u00b0",
+ "\u0120suspended",
+ "\u0120Carib",
+ "\u0120bizim",
+ "\u0120Oliver",
+ "\u00e3\u0123\u00b6",
+ "Tom",
+ "\u0120\u00d0\u00bf\u00d0\u00bb\u00d0\u00b0\u00d0\u00bd",
+ "\u0120nope",
+ "omething",
+ "\u0120beiden",
+ "\u00d1\u0128\u00d0\u00b5\u00d0\u00bd",
+ "\u0120fluct",
+ "\u0120\u00ce\u00bc\u00ce\u00bf\u00cf\u0127",
+ "\u0120fathers",
+ "\u0120Blake",
+ "\u0120upward",
+ "\u0120Dash",
+ "\u0120Lil",
+ "\u0120\u00ec\u012a\u013a\u00eb\u0131\u0126",
+ "\u0120revelation",
+ "\u0120elevated",
+ "\u0120Jiang",
+ "LED",
+ "\u0120Thompson",
+ "\u0120\u00d0\u00bc\u00d0\u00be\u00d0\u00b3\u00d1\u0125\u00d1\u0124",
+ "\u00d1\u0123\u00d1\u0124\u00d1\u0122\u00d1\u0125",
+ "ifiers",
+ "\u0120comeback",
+ "\u0120buyers",
+ "\u00ea\u00b2\u00b0",
+ "\u0120Sales",
+ "\u00d0\u00b8\u00d1\u0129\u00d0\u00b5",
+ "ciones",
+ "\u0120whistle",
+ "\u0120dull",
+ "LEX",
+ "\u0120\u00ed\u0137\u013a\u00ea\u00b2\u0142\u00ec\u012c\u00b5\u00eb\u012d\u012a\u00eb\u012d\u00a4",
+ "\u0120criminals",
+ "\u0120descent",
+ "ipple",
+ "mas\u00c4\u00b1",
+ "\u0120foolish",
+ "\u0120\u00d0\u00b4\u00d1\u0125\u00d0\u00bc\u00d0\u00b0\u00d1\u0130",
+ "tar",
+ "\u0120mango",
+ "\u0120choreography",
+ "Matt",
+ "\u0120territor",
+ "\u0120acaba",
+ "\u0120Einstein",
+ "\u0120IBM",
+ "\u0120Metal",
+ "\u0120Crystal",
+ "\u0120rah",
+ "\u0120foul",
+ "\u0120Islands",
+ "\u0120intact",
+ "\u0120Rail",
+ ".:",
+ "\u0120ac\u00c3\u00a1",
+ "\u0120\u00d0\u00bf\u00d1\u0122\u00d0\u00be\u00d0\u00bf",
+ "\u00d0\u00b5\u00d1\u0122\u00d0\u00b5",
+ "\u0120Write",
+ "hehe",
+ "\u0120FO",
+ "\u0120\u00cf\u0125\u00cf\u0126\u00ce\u00b7",
+ "\u0120doin",
+ "held",
+ "\u0120appropriately",
+ "\u0120deliberately",
+ "\u0120archive",
+ "\u0120giveaway",
+ "\u00e3\u0123\u0135\u00e3\u0123\u0135",
+ "\u0120finale",
+ "\u00d0\u00bb\u00d0\u00b0\u00d1\u0123",
+ "\u00d0\u00b5\u00d0\u00bd\u00d0\u00be",
+ "\u00c6\u00a1n",
+ "\u00e6\u00a3\u0134",
+ "ogo",
+ "\u00e7\u012b\u00a9",
+ "\u0120Audience",
+ "\u00e3\u0127\u0142",
+ "\u0120subur",
+ "\u0120headache",
+ "\u00d0\u00b0\u00d0\u00bd\u00d0\u00bd\u00d1\u0131",
+ "\u0120Witch",
+ "\u0120Swedish",
+ "\u0120BI",
+ "\u0120erase",
+ "\u0120khi",
+ "\u0120commentary",
+ "\u0120Sultan",
+ "\u00ed\u0125\u013f",
+ "\u0120Leban",
+ "\u0120\u00eb\u00b3\u00b4\u00ec\u012d",
+ "\u0120Pam",
+ "pekt",
+ "month",
+ "\u0120grounded",
+ "\u00ea\u00be",
+ "\u0120\u00c5\u0141ekilde",
+ "250",
+ "\u0120SCH",
+ "ioso",
+ "\u0120inaug",
+ "heimer",
+ "\u0120reflecting",
+ "\u0120Ruth",
+ "\u0120Oil",
+ "\u0120trouver",
+ "uep",
+ "..]",
+ "\u0120\u00ec\u0140\u012a\u00eb",
+ "\u0120olha",
+ "\u0120reasonably",
+ "\u0120glitch",
+ "UB",
+ "\u0120Gran",
+ "\u0120adalah",
+ "\u0120lent",
+ "\u00d8\u00b1\u00d8\u00a7",
+ "\u0120traction",
+ "\u0120adjusting",
+ "\u00b4\u00a4",
+ "\u00d0\u00bd\u00d0\u00b8\u00d0\u00b1\u00d1\u0125\u00d0\u00b4\u00d1\u012e",
+ "\u0120\u00d0\u00b4\u00d0\u00be\u00d0\u00bf",
+ "\u0120stretched",
+ "\u0120ort",
+ "\u0120cosine",
+ "viol",
+ "\u0120\u00ec\u0127",
+ "cir",
+ "\u0120bastard",
+ "\u00e4\u00b8\u0129",
+ "\u0120\u00d1\u0127\u00d0\u00be\u00d0\u00b4",
+ "\u0120quier",
+ "\u0120pressures",
+ "\u0120Anh",
+ "\u00e5\u00b9\u00be",
+ "\u0120elles",
+ "\u0120\u00d0\u00b4\u00d1\u0122\u00d1\u0125\u00d0\u00b7",
+ "\u0120\u00d0\u00bc\u00d0\u00be\u00d0\u00b6\u00d0\u00b5\u00d1\u0124\u00d0\u00b5",
+ "\u0120ch\u00e1\u00bb",
+ "\u0120M\u00c3\u00a9",
+ "\u00c3\u00b6k",
+ "\u00e1\u00ba\u00a7u",
+ "\u00ec\u0142\u012a",
+ "zin",
+ "\u0120caution",
+ "iban",
+ "\u0120judging",
+ "\u00d1\u0125\u00d1\u0130\u00d1\u0124",
+ "\u0120baj",
+ "\u0120\u00d0\u00a1\u00d0\u00b5\u00d0\u00b9\u00d1\u0129\u00d0\u00b0\u00d1\u0123",
+ "\u0120Poor",
+ "\u0120Nazi",
+ "\u0120upbeat",
+ "yang",
+ "\u0120weekends",
+ "\u0120Essentially",
+ "\u0120oluyor",
+ "\u0120spatial",
+ "acker",
+ "\u0120seller",
+ "\u0120\u00d7\u0132\u00d7\u0137\u00d7\u00aa",
+ "\u0133\u00d7\u013e",
+ "\u0120vivid",
+ "\u0120Bond",
+ "\u00ea\u00b6\u012e",
+ "iskt",
+ "\u00e3\u0124\u00b5",
+ "\u0120goat",
+ "driver",
+ "\u0120mug",
+ "ictional",
+ "\u0120allt",
+ "\u0120Initi",
+ "\u0120Rand",
+ "\u0120finishes",
+ "\u0120\u00ea\u00b0\u012a",
+ "\u0120vitam",
+ "\u0120teenagers",
+ "\u0120Morris",
+ "\u00ec\u00a4\u0126",
+ "\u0120Ori",
+ "iya",
+ "\u0120my\u00c3\u00b6s",
+ "Step",
+ "\u0120Kre",
+ "\u00e8\u00be\u00a6",
+ "\u0120dinosaur",
+ "\u0120\u00eb\u00aa\u0129",
+ "affe",
+ "\u0120\u00eb\u0132\u00a9\u00eb\u012d\u012a\u00eb\u012d\u00a4",
+ "\u0120zeg",
+ "\u00e5\u012a\u0129",
+ "\u0120Manhattan",
+ "\u0120sujet",
+ "uelle",
+ "stoff",
+ "\u0120d\u00c3\u00bcr",
+ "\u0120submar",
+ "eses",
+ "\u0120aquele",
+ "\u0120nou",
+ "\u0120Faith",
+ "tz",
+ "\u0120\u00d1\u0124\u00d0\u00be\u00d0\u00bc\u00d1\u0125",
+ "aceut",
+ "liers",
+ "\u0120bandwidth",
+ "\u00c6\u00b0\u00e1\u00bb\u013f",
+ "\u0120respective",
+ "\u0120Ave",
+ "\u0120spreadshe",
+ "\u0120Sent",
+ "icamente",
+ "\u0120infra",
+ "\u0120learners",
+ "\u0120\u00e0\u00ae\u012b",
+ "aiah",
+ "renal",
+ "\u0120mustard",
+ "\u0120habt",
+ "\u00e7\u0125",
+ "\u0120Qu\u00c3\u00a9",
+ "\u0120analyzing",
+ "\u00e6\u00af\u0131",
+ "\u0120solic",
+ "\u0120\u00d7\u0136\u00d7\u0137\u00d7\u0132",
+ "\u0120causa",
+ "\u0120welcomed",
+ "\u0120Success",
+ "\u0120facile",
+ "\u0120\u00d0\u0141\u00d0\u00be\u00d1\u0124\u00d0\u00be\u00d0\u00bc\u00d1\u0125",
+ "schein",
+ "\u0120fetch",
+ "\u0120strat",
+ "\u0120\u00d1\u0123\u00d1\u0124\u00d0\u00be\u00d0\u00b8\u00d1\u0124",
+ "\u00ec\u0139\u0132\u00ec\u0126\u013e\u00eb\u012c\u0136",
+ "\u0120\u00d1\u0123\u00d0\u00bf\u00d0\u00be\u00d1\u0123\u00d0\u00be\u00d0\u00b1",
+ "mam",
+ "\u0120ser\u00c3\u0143a",
+ "naments",
+ "writer",
+ "\u0120consulting",
+ "\u00ed\u013a\u0122",
+ "\u0120Berkeley",
+ "eu",
+ "asive",
+ "UU",
+ "\u0120Analyt",
+ "\u0120submission",
+ "\u0120magnificent",
+ "enza",
+ "\u0120econ",
+ "\u0120profiles",
+ "\u0120incar",
+ "Ab",
+ "\u0120Nun",
+ "\u0120hic",
+ "screaming",
+ "\u0120resilient",
+ "\u00e5\u012a\u00a9",
+ "grund",
+ "\u0120concur",
+ "\u0120bereits",
+ "LD",
+ "\u0120nurt",
+ "\u00ec\u012b",
+ "\u0120feast",
+ "\u0120encuent",
+ "\u0120Michel",
+ "\u0120suprem",
+ "\"]",
+ "\u0120feeds",
+ "\u0120Kollegen",
+ "isser",
+ "\u0120Feng",
+ "\u0120Wen",
+ "mun",
+ "\u0120ten\u00c3\u0143a",
+ "\u0120Wrest",
+ "\u0120\u00ec\u013a\u00a4\u00eb\u012c\u013a\u00ec\u013f\u0122",
+ "\u0120stead",
+ "\u0120restoration",
+ "\u0120donated",
+ "\u0120dels",
+ "\u0120census",
+ "\u0120desperately",
+ "worthy",
+ "HE",
+ "\u0120Spa",
+ "\u0120Bryan",
+ "\u0120hj",
+ "\u0120Raw",
+ "\u00ec\u0137\u0126\u00eb",
+ "\u0120Camera",
+ "\u0120zien",
+ "\u0120styl",
+ "\u0120TW",
+ "\u0120Cheese",
+ "borne",
+ "\u0120obl",
+ "\u0120Already",
+ "\u0120unstable",
+ "\u0120flames",
+ "post",
+ "Ha",
+ "romagn",
+ "\u0120\u00ec\u0139\u0126\u00eb\u00a7\u012a",
+ "dest",
+ "\u0120kolej",
+ "\u0120temporarily",
+ "\u0120determining",
+ "\u0120Glass",
+ "\u00d1\u0122\u00d0\u00be\u00d0\u00bd",
+ "olan",
+ "\u0120dominated",
+ "\u00e5\u012e\u0138",
+ "____",
+ "\u0120\u00d9\u0129\u00d8\u00b0\u00d8\u00a7",
+ "\u0120Dana",
+ "\u0120dinheiro",
+ "aqu",
+ "\u00eb\u00af\u00bc",
+ "\u0120\u00c3\u0142s",
+ "\u0120Joey",
+ "\u0120Griff",
+ "\u0120attain",
+ "\u0120transitions",
+ "\u0120Literally",
+ "\u00d0\u00b5\u00d0\u00bd\u00d0\u00b4",
+ "\u0120Haven",
+ "\u0120grabbing",
+ "\u0120crystals",
+ "\u0120Fourth",
+ "\u0120candles",
+ "\u0120\u00d1\u0123\u00d0\u00bb\u00d1\u0125\u00d1\u0129\u00d0\u00b0",
+ "rico",
+ "\u01205000",
+ "etto",
+ "\u0120undo",
+ "\u0120kto",
+ "\u0120divert",
+ "\u0120chir",
+ "\u0120persec",
+ "\u0120hiking",
+ "\u0120announcements",
+ "\u00e7\u0136\u00b1",
+ "\u00d0\u00b7\u00d1\u012d",
+ "\u0120auc",
+ "\u0120systemic",
+ "\u0120RM",
+ "\u00cf\u0125\u00ce\u00b1",
+ "\u0120\u00d0\u0136\u00d0\u00b6",
+ "\u0120yar",
+ "\u0120Ward",
+ "\u0120pissed",
+ "\u0120carn",
+ "\u0120autonomous",
+ "\u00e3\u0127\u0130\u00e3\u0127\u0130",
+ "sover",
+ "\u00e6\u00b2\u0134\u00e9\u012e\u00af",
+ "\u00e5\u00be\u012a\u00e5\u00a5\u00bd",
+ "\u0120reflex",
+ "\u0120gardens",
+ "\u0120dated",
+ "\u00ec\u00b1",
+ "ami\u00c4\u013b",
+ "\u0120continuity",
+ "\u0120citizenship",
+ "\u0120schwer",
+ "\u0120zak",
+ "table",
+ "\u0120\u00d1\u0123\u00d1\u0129",
+ "\u00e8\u00a7\u0123",
+ "\u0120\u00cf\u0125\u00ce\u00b5",
+ "\u0120generates",
+ "\u00ea\u00b5\u00ac\u00eb\u0124\u013a",
+ "\u00c3\u00b6h",
+ "\u00c3\u00b3m",
+ "alam",
+ "\u0120JUDY",
+ "\u0120Bug",
+ "\u0120\u00e3\u0123\u00a6",
+ "\u0120drones",
+ "\u0120\u00c3\u00a1gua",
+ "acaks",
+ "\u00e6\u013c",
+ "\u0120\u00d0\u013c\u00d0\u00be\u00d0\u00bd",
+ "\u00d7\u0138\u00d7\u0136",
+ "\u0120strive",
+ "\u0120Altern",
+ "\u0120nearest",
+ "\u0120proyect",
+ "tera",
+ "\u0120ASHLEY",
+ "\u0120worm",
+ "\u0120replay",
+ "\u0120tara",
+ "\u0120Indians",
+ "\u00e3\u0124\u00b0",
+ "icaid",
+ "\u0120\u00ec\u012a\u013e",
+ "\u0120appealing",
+ "\u0120Wes",
+ "\u0120mentions",
+ "\u0120\u00d0\u00b4\u00d0\u00b5\u00d0\u00bb\u00d0\u00b5",
+ "\u0120kw",
+ "\u0120fragile",
+ "isz",
+ "k\u00c3\u00b3w",
+ "hang",
+ "color",
+ "\u0120presidente",
+ "87",
+ "\u00d0\u00b5\u00d1\u0126",
+ "\u00e7\u012a\u00b8",
+ "\u0120\u00d0\u00b4\u00d0\u00be\u00d0\u00b1\u00d0\u00b0\u00d0\u00b2",
+ "\u0120Nelson",
+ "\u00c3\u00a1fic",
+ "\u0120MICHAEL",
+ "\u0120mechanic",
+ "\u0120metres",
+ "\u0120oczywi\u00c5\u013dcie",
+ "\u0120Cind",
+ "\u0120ogs\u00c3\u00a5",
+ "\u0120landsca",
+ "ACE",
+ "\u0120headlines",
+ "\u0120catalyst",
+ "\u0120Catch",
+ "inkles",
+ "\u0120pills",
+ "ordo",
+ "\u0120immigrant",
+ "\u0120examination",
+ "\u0120accidents",
+ "z\u00c4\u0127d",
+ "\u0120quiere",
+ "\u0120nella",
+ "\u012067",
+ "\u0120passa",
+ "\u0120superfic",
+ "istor",
+ "\u0120nov",
+ "\u00eb\u012d\u00b5",
+ "\u0120mandate",
+ "isons",
+ "\u0120Virtual",
+ "\u0120selber",
+ "\u0120counseling",
+ "\u0120NBA",
+ "\u0120sept",
+ "\u0120believer",
+ "\u0120marvel",
+ "\u0120Integr",
+ "\u0120\u00d0\u00bc\u00d1\u0138",
+ "\u0120orph",
+ "\u0120backward",
+ "\u0120Generation",
+ "\u0120Pict",
+ "\u0120\u00d1\u0124\u00d0\u00be\u00d1\u0124",
+ "\u0120tapi",
+ "prochen",
+ "\u0120hallway",
+ "hte",
+ "\u0120\u00db\u0123\u00db\u0134",
+ "\u0120Zum",
+ "\u00e8\u0122\u0123\u00e5\u00b8\u00ab",
+ "achment",
+ "iquer",
+ "folg",
+ "\u0120Eddie",
+ "\u0120Kil",
+ "\u0120wellness",
+ "stock",
+ "\u00e8\u00bc\u0125",
+ "\u0120ka\u00c3\u00a7",
+ "\u0120terrorism",
+ "\u0120pointer",
+ "Of",
+ "heric",
+ "\u0120Ultimately",
+ "\u0120meses",
+ "\u0120Trade",
+ "\u0120pint",
+ "\u0120tuition",
+ "\u0120disagre",
+ "\u0120\u00ea\u00b2\u012e\u00ec\u0140\u0126",
+ "\u0120manuscript",
+ "\u0120roomm",
+ "\u0120outputs",
+ "\u00d0\u00b5\u00d1\u0128\u00d0\u00b8",
+ "\u0120ries",
+ "\u0120salud",
+ "otzdem",
+ "\u0120masses",
+ "\u0120by\u00c5\u0124a",
+ "\u0120clearing",
+ "\u0120discourse",
+ "atson",
+ "\u0120folded",
+ "\u0120Jar",
+ "\u00d9\u0126\u00d9\u012b",
+ "900",
+ "\u0120\u00d1\u0125\u00d1\u0123\u00d0\u00bf",
+ "\u0120prophecy",
+ "\u0120interfere",
+ "\u00d0\u00b8\u00d1\u0127\u00d0\u00be\u00d0\u00b4",
+ "\u00e0\u00b9\u012e",
+ "\u0120thri",
+ "\u0120\u00d7\u0140\u00d7\u00a9",
+ "\u0120laz\u00c4\u00b1m",
+ "\u01201992",
+ "\u0120futuro",
+ "\u0120locking",
+ "\u0120embargo",
+ "\u0120Neither",
+ "ivamente",
+ "\u0120m\u00c3\u00a5ste",
+ "\u0120mik",
+ "\u0120collector",
+ "\u00d0\u00b5\u00d0\u00ba\u00d0\u00be\u00d1\u0124\u00d0\u00be\u00d1\u0122",
+ "\u0120Gand",
+ "\u0120sentir",
+ "\u0120Might",
+ "\u00e5\u00a1\u0136",
+ "\u0120ganzen",
+ "UC",
+ "\u0120relating",
+ "SD",
+ "\u0120mosquito",
+ "GR",
+ "\u0120hollow",
+ "\u00e2\u013a\u0127",
+ "\u0120Walker",
+ "\u0120affiliate",
+ "\u0120duplicate",
+ "\u00d0\u00bd\u00d0\u00b5\u00d0\u00bc",
+ "\u0120grape",
+ "\u0120Organization",
+ "\u0120synt",
+ "Joe",
+ "\u0120geg",
+ "\u0120revealing",
+ "\u0120Ethan",
+ "outer",
+ "\u0120yay",
+ "\u00e9\u00ab\u0136",
+ "\u00d0\u00bb\u00d0\u00b0\u00d1\u0122",
+ "\u0120reportedly",
+ "\u0120ihrer",
+ "\u0120recognise",
+ "\u0120bumper",
+ "\u0120Randy",
+ "\u0120Venus",
+ "tles",
+ "\u0120appetite",
+ "\u0120glucose",
+ "\u0120chodzi",
+ "\u0120Furthermore",
+ "tir",
+ "\u0120conta",
+ "\u0120intuition",
+ "\u0120altitude",
+ "\u0120chunks",
+ "\u0120Joshua",
+ "\u00c4\u00b1\u00c4\u0141\u00c4\u00b1m",
+ "rylic",
+ "leans",
+ "\u0120\u00ed\u0136\u00bc\u00eb",
+ "LL",
+ "Que",
+ "\u0120gor",
+ "\u0120\u00d0\u00b7\u00d0\u00bd\u00d0\u00b0\u00d1\u0129\u00d0\u00b8\u00d1\u0124",
+ "\u0120poems",
+ "\u0120excel",
+ "\u0120explored",
+ "\u0120popul",
+ "\u0120incluso",
+ "st\u00c3\u00a4",
+ "\u0120Gavin",
+ "alling",
+ "\u0120\u00cf\u0126\u00ce\u00bf\u00ce\u00bd",
+ "\u00e9\u00a9",
+ "arbeit",
+ "\u0120Gas",
+ "\u0120glorious",
+ "rieben",
+ "\u0120spam",
+ "\u0120indoor",
+ "\u0120thrust",
+ "\u0120Ald",
+ "\u0120Prior",
+ "\u0120onboard",
+ "\u00e3\u0123\u0142\u00e3\u0123\u0137\u00e3\u0123\u0126",
+ "oca",
+ "ASH",
+ "\u00a3\u0142",
+ "\u0120Christine",
+ "\u0120drawer",
+ "\u0120noon",
+ "\u0120\u00ec\u0140\u013a\u00eb",
+ "\u0120permanently",
+ "\u00e6\u00b7\u00b1",
+ "\u0120\u00d0\u00bd\u00d0\u00b0\u00d0\u00bf\u00d1\u0122\u00d0\u00b8\u00d0\u00bc\u00d0\u00b5\u00d1\u0122",
+ "\u0120podcasts",
+ "erapeut",
+ "prit",
+ "\u0120stainless",
+ "\u0120\u00da\u00a9\u00db\u0134",
+ "\u0120familia",
+ "\u0120\u00d1\u0122\u00d0\u00b0\u00d0\u00b7\u00d1\u0122",
+ "unto",
+ "\u0120\u00d1\u0123\u00d1\u0124\u00d0\u00be\u00d0\u00bb",
+ "\u0120h\u00c3\u00a4",
+ "\u0120Hai",
+ "\u0120PB",
+ "izon",
+ "\u0120konnte",
+ "\u0120b\u00c3\u00bcy\u00c3\u00bck",
+ "\u0120utilizar",
+ "\u00da\u0128",
+ "\u0120aquesta",
+ "\u0120mixer",
+ "udent",
+ "\u00d0\u00bb\u00d0\u00b5\u00d0\u00ba\u00d1\u0123",
+ "\u00c5\u0124u",
+ "\u0120\u00d1\u0123\u00d0\u00b8\u00d1\u0123\u00d1\u0124\u00d0\u00b5\u00d0\u00bc",
+ "\u0120\u00d0\u00bd\u00d0\u00be\u00d1\u0122\u00d0\u00bc",
+ "\u0120fatal",
+ "\u0120considerations",
+ "\u0120validation",
+ "\u0120oli",
+ "\u0120karde\u00c5\u0141",
+ "\u0120GLORIA",
+ "\u0120pall",
+ "\u00d0\u00b5\u00d1\u0123\u00d1\u0124\u00d0\u00b5",
+ "\u0120rectang",
+ "\u0120medieval",
+ "allahi",
+ "asti",
+ "\u0120Syrian",
+ "\u0120shear",
+ "\u0120debug",
+ "\u0120Mai",
+ "\u0120knocking",
+ "\u0120Lex",
+ "ardan",
+ "rov",
+ "\u0120memorial",
+ "\u00e6\u00b0\u00a3",
+ "ooky",
+ "\u0120stuffed",
+ "\u0120pass\u00c3\u00a9",
+ "\u0120wig",
+ "\u0124\u0142",
+ "\u0120pr\u00c3\u00b3xima",
+ "\u01201991",
+ "\u0120\u00d0\u00bc\u00d0\u00b5\u00d0\u00b6\u00d0\u00b4\u00d1\u0125",
+ "\u0120nuestros",
+ "\u0120Beast",
+ "\u0120smo",
+ "atched",
+ "ologia",
+ "\u0120\u00d0\u00bc\u00d0\u00be\u00d0\u00b4",
+ "\u0120gee",
+ "\u0120conceptual",
+ "\u0120\u00c3\u00b4",
+ "\u0120decreases",
+ "\u0120queries",
+ "\u00d0\u00be\u00d0\u00bb\u00d1\u012e\u00d1\u012a",
+ "\u0120Apart",
+ "\u0120exempl",
+ "\u00e5\u00b1\u00b1",
+ "\u0120fled",
+ "\u0120OFF",
+ "ggak",
+ "\u0120bead",
+ "hir",
+ "lies",
+ "\u0120Clearly",
+ "\u00c4\u00b1lar",
+ "\u0120chess",
+ "\u0120whichever",
+ "\u012096",
+ "\u00e1\u00ba\u00b1",
+ "\u0120respects",
+ "\u0120\u00d0\u00bc\u00d0\u00be\u00d1\u0122",
+ "\u0120organism",
+ "\u0120grandpa",
+ "\u0120Vie",
+ "\u00e8\u00b7\u0141\u00e4\u00bd\u0142",
+ "\u0120flooding",
+ "\u0120upgraded",
+ "\u00d1\u0133\u00d1\u0122",
+ "\u0120cheeks",
+ "\u0120conquer",
+ "\u0120stubborn",
+ "\u0120puzzles",
+ "\u0120auction",
+ "\u0120relying",
+ "\u0120PROF",
+ "\u0120Esper",
+ "\u0120\u00d0\u013e\u00d0\u00a3",
+ "\u0120hype",
+ "\u0120possibil",
+ "\u0120imprison",
+ "\u0120Ern",
+ "\u00ec\u0139\u012a\u00ec\u012c\u00b5\u00eb\u012d\u012a\u00eb\u012d\u00a4",
+ "\u0120envie",
+ "\u0120resurrection",
+ "\u00e4\u00b8\u012f\u00e8\u00a1\u012e",
+ "\u0120sper",
+ "\u0120Venezuela",
+ "som",
+ "\u0120\u00ec\u0140\u0142\u00ea\u00b9",
+ "\u0120nouvelle",
+ "\u0120closes",
+ "\u01201940",
+ "\u0120qua",
+ "\u0120Jared",
+ "\u0120Pir",
+ "\u0120inde",
+ "\u0120scrub",
+ "uku",
+ "\u0120requiring",
+ "\u0120\u00d0\u00b2\u00d0\u00b0\u00d0\u00bc\u00d0\u00b8",
+ "\u0120considerable",
+ "\u00e5\u0132\u013d",
+ "ilia",
+ "\u0120inne",
+ "\u0120meinem",
+ "\u0120hardship",
+ "\u0120traps",
+ "roc",
+ "\u0120\u00ec\u0126\u00a4\u00eb",
+ "\u0120researching",
+ "\u0120Margaret",
+ "\u0120penny",
+ "\u0120b\u00c4\u00b1rak",
+ "\u00d1\u0133\u00d0\u00bb",
+ "\u0120wool",
+ "\u0120rhet",
+ "\u0120flatten",
+ "\u00e7\u0129",
+ "\u00e0\u00b9\u0122\u00e0\u00b8\u00a3",
+ "\u0120pied",
+ "\u0120Chap",
+ "\u0120underm",
+ "\u0120fret",
+ "\u0120crashed",
+ "\u0120Frauen",
+ "\u00d8\u00b0\u00d9\u0129",
+ "ivan",
+ "\u0120literary",
+ "latego",
+ "\u0120sp\u00c3\u00a4ter",
+ "\u0120similarities",
+ "\u00e2\u0128",
+ "\u0120Coron",
+ "\u0120Creek",
+ "\u0120bosses",
+ "\u0120accompanied",
+ "\u0120debates",
+ "\u0120assembled",
+ "\u0120\u00c3\u0123",
+ "\u0120Vai",
+ "\u0120tract",
+ "\u0120simplement",
+ "\u0120Arin",
+ "\u0120vulnerability",
+ "\u0120hormone",
+ "IEL",
+ "OOK",
+ "\u0120relay",
+ "\u0120Andrea",
+ "ril",
+ "\u0120necessity",
+ "aceutical",
+ "\u00d1\u0130\u00d1\u012b",
+ "ousing",
+ "nahmen",
+ "\u0120footprint",
+ "map",
+ "\u0120Tier",
+ "annya",
+ "intend",
+ "\u00e5\u0138\u00ae",
+ "\u00e5\u00a2",
+ "\u0120decorate",
+ "\u0120zombies",
+ "\u0120Hyd",
+ "\u0120Suz",
+ "\u0120campuses",
+ "\u0120Emb",
+ "\u0120throttle",
+ "\u0120admin",
+ "\u0120oportun",
+ "\u0120mirrors",
+ "\u0120identities",
+ "\u0120Clin",
+ "\u0120\u00eb\u00b9\u0126\u00eb",
+ "\u00e1\u00b9\u00a3",
+ "\u0120Ott",
+ "\u0120blues",
+ "\u0120impressions",
+ "-,",
+ "\u0120vague",
+ "afe",
+ "\u0120inferior",
+ "erald",
+ "\u0120medicines",
+ "\u0120pregunta",
+ "osely",
+ "\u0120t\u00c3\u00a9l\u00c3\u00a9",
+ "\u0120Month",
+ "\u0120Leaders",
+ "\u0120Egyptian",
+ "\u0120ration",
+ "kers",
+ "heits",
+ "\u0120recht",
+ "Play",
+ "\u0120eg",
+ "\u0120polls",
+ "\u0120WOODR",
+ "\u0120slots",
+ "jam",
+ "Both",
+ "\u0120Rat",
+ "\u00d1\u0122\u00d0\u00b0\u00d0\u00b6",
+ "\u0120Bright",
+ "\u00e4\u00b8\u0122\u00e5\u00ae\u013c",
+ "\u00e1\u00bb\u0133i",
+ "urious",
+ "\u0120singers",
+ "\u0120login",
+ "\u0120t\u00c3\u00aam",
+ "lation",
+ "\u0120Mum",
+ "\u00c6\u00b0\u00e1\u00bb\u013fng",
+ "\u0120Editor",
+ "\u00e5\u0132\u0133",
+ "\u0120innovations",
+ "have",
+ "\u0120Sek",
+ "\u0120weaker",
+ "\u0120Gob",
+ "After",
+ "\u00b4\u00ec\u00a7\u0122",
+ "\u0120\u00eb\u00ac\u00b8\u00ec\u0142\u013e",
+ "\u00e3\u0125\u00bc\u00e3\u0125\u00bc",
+ "\u0120disadvantage",
+ "\u00e7\u00a2\u00ba",
+ "\u0120gaze",
+ "\u0120Mack",
+ "\u00cf\u0123\u00ce\u00af",
+ "\u0120Kiss",
+ "\u0120Holo",
+ "\u0120Birth",
+ "izi",
+ "bab",
+ "\u00e4\u00bf\u013f",
+ "\u00ec\u012d\u013e\u00ea\u00b3\u0142",
+ "\u00d0\u00b4\u00d0\u00b5\u00d1\u0122\u00d0\u00b6",
+ "\u0120squat",
+ "\u00d0\u00ba\u00d1\u0125\u00d1\u0123",
+ "uni",
+ "\u0120Comme",
+ "\u0120WOODRUFF",
+ "\u0120Championship",
+ "\u0120welche",
+ "\u0120Youth",
+ "zem",
+ "\u0120odpow",
+ "\u0120persistent",
+ "rut",
+ "\u00ec\u0136\u00a9",
+ "\u00ed\u0138\u00a5",
+ "lair",
+ "iku",
+ "\u0120vendor",
+ "\u0120ch\u00c3\u00bang",
+ "\u0120financi",
+ "\u0120overly",
+ "\u00c3\u00a2u",
+ "\u0120gluten",
+ "\u01201800",
+ "\u0120divisions",
+ "\u0120ciudad",
+ "\u0120obed",
+ "\u0120warum",
+ "\u0120eher",
+ "\u0120elim",
+ "\u0120\u00d0\u0134\u00d0\u00be",
+ "\u0120peuvent",
+ "\u0120Wanna",
+ "\u0120attendance",
+ "\u0120assessments",
+ "\u0120Bog",
+ "\u0120imagery",
+ "\u0120collectively",
+ "\u0120informal",
+ "\u0120Schwe",
+ "\u0120deutlich",
+ "\u0120Chel",
+ "\u0120PE",
+ "owed",
+ "\u0120banner",
+ "\u0120shelves",
+ "\u0120Return",
+ "\u00e6\u012d\u00bf",
+ "LAUGHS",
+ "\u0120congratulate",
+ "\u0120Norway",
+ "\u0120dwell",
+ "\u0120Caribbean",
+ "\u0120norms",
+ "\u0120Animal",
+ "\u0120Valentine",
+ "\u0120extending",
+ "\u0120Vou",
+ "orr",
+ "\u0120Cheng",
+ "\u00c2\u00a1",
+ "\u0120\u00d0\u00b4\u00d0\u00be\u00d1\u0122\u00d0\u00be\u00d0\u00b3",
+ "\u0120veg",
+ "\u0120h\u00c3\u00a5",
+ "\u0120Xin",
+ "\u0120\u00ec\u00b9\u00b4\u00eb",
+ "emet",
+ "\u0120hypoth",
+ "\u0120interessante",
+ "rices",
+ "IZ",
+ "\u0120USD",
+ "\u0120runner",
+ "\u0120Bag",
+ "\u0120\u00ea\u00bd",
+ "\u0120come\u00c3\u00a7ar",
+ "\u0120pigs",
+ "\u0120weaknesses",
+ "Ph",
+ "\u0120Viol",
+ "\u00e4\u00b8\u012f\u00e7\u0136\u00a8",
+ "\u0120dragging",
+ "\u0120Aqu\u00c3\u0143",
+ "\u0120CSS",
+ "\u0120millimeters",
+ "\u0120est\u00c3\u00a1s",
+ "\u0120acute",
+ "\u0120dejar",
+ "i\u00c4\u0141",
+ "obra",
+ "Love",
+ "\u0120silk",
+ "****",
+ "\u0120joins",
+ "\u0120prol",
+ "\u0120\u00ea\u00b0\u0132\u00ec\u0124\u00ac\u00ed\u0137\u00a9\u00eb\u012d\u012a\u00eb\u012d\u00a4",
+ "\u00e6\u0136\u00af",
+ "\u00d8\u0143\u00d8\u00af",
+ "aghetti",
+ "\u00c3\u00a4nner",
+ "\u0120strang",
+ "\u0120doubled",
+ "\u0120descriptions",
+ "\u0120stellen",
+ "\u0120parti",
+ "\u00e7\u00ab\u012d",
+ "\u00b2\u0126\u00eb",
+ "\u0120\u00c3\u00b6\u00c4\u0141",
+ "ighing",
+ "\u0120angular",
+ "\u0120natuur",
+ "\u0120Shel",
+ "\u00c6\u00b0\u00c6\u00a1",
+ "\u0120rays",
+ "\u0120seper",
+ "start",
+ "vised",
+ "\u0120rushed",
+ "\u0120internationally",
+ "\u0120nivel",
+ "\u0120boxing",
+ "fallen",
+ "\u00e1\u00bb\u0133c",
+ "\u0120seinen",
+ "plicity",
+ "\u0120carboh",
+ "\u0120Travis",
+ "uso",
+ "\u0120Phase",
+ "\u0120activation",
+ "\u0120opio",
+ "\u00b7\u00a8",
+ "\u0120decreased",
+ "Car",
+ "\u0120bundle",
+ "\u0120expend",
+ "ormal",
+ "\u0120adjacent",
+ "\u0120mee",
+ "\u0120\u00d0\u00be\u00d1\u0122\u00d0\u00b3",
+ "\u0120transcript",
+ "\u0120Language",
+ "GS",
+ "\u00e8\u00a7\u012b",
+ "\u0120seul",
+ "\u00c3\u0142nh",
+ "\u0120nya",
+ "nings",
+ "\u0120\u00ec\u012d\u013e\u00eb",
+ "\u0120\u00eb\u0136\u00b0\u00eb\u013f\u00bc",
+ "\u0120Agr",
+ "\u00c3\u0143d",
+ "\u00e7\u0137\u013b",
+ "\u0120aby",
+ "\u0120Neo",
+ "\u00c4\u00b1yoruz",
+ "\u0120Thinking",
+ "aime",
+ "\u0120vite",
+ "\u0120trav\u00c3\u00a9s",
+ "\u0120\u00d7\u0133\u00d7\u00a2",
+ "\u0120\u00d0\u00bc\u00d0\u00b5\u00d0\u00b4",
+ "Our",
+ "hoot",
+ "\u0120liner",
+ "\u0120Pizza",
+ "\u0120hyg",
+ "flies",
+ "\u0120Continue",
+ "\u0120dental",
+ "\u0120Tib",
+ "\u0120regulate",
+ "lie\u00c3\u0141",
+ "ALK",
+ "\u0120Tae",
+ "\u00ea\u00b8\u00b8",
+ "\u0120Brexit",
+ "\u0120Gut",
+ "\u0120occupation",
+ "\u0120zrobi",
+ "\u00c3\u00a2m",
+ "\u0120whisk",
+ "\u00e4\u00b8\u0138\u00e7\u0137\u012e",
+ "\u0120kanske",
+ "omon",
+ "robe",
+ "\u0120warfare",
+ "\u0120th\u00e1\u00bb\u0125",
+ "\u0120jaki",
+ "\u0120strokes",
+ "\u0120peas",
+ "\u0120Damit",
+ "HAN",
+ "\u0120interference",
+ "\u0120\u00d0\u00bc\u00d0\u00b8\u00d0\u00bd\u00d1\u0125\u00d1\u0124",
+ "NER",
+ "outing",
+ "\u0120textures",
+ "\u0141\u012b",
+ "owi",
+ "\u0120\u00ed\u0137\u013b",
+ "\u0120dens",
+ "\u0120protagonist",
+ "\u00c3\u00a4nn",
+ "\u0120goddess",
+ "\u0120wollte",
+ "ijo",
+ "\u0120Woche",
+ "\u0120VPN",
+ "story",
+ "\u0120kinderg",
+ "\u0120funnel",
+ "\u0120distress",
+ "\u00d0\u00bd\u00d0\u00be\u00d1\u0123\u00d1\u0124\u00d1\u012e\u00d1\u0130",
+ "\u0120noisy",
+ "\u0120\u00d0\u00bf\u00d1\u0122\u00d0\u00be\u00d0\u00b4\u00d0\u00be\u00d0\u00bb\u00d0\u00b6",
+ "\u0120daran",
+ "\u0120enzyme",
+ "\u00d0\u00bb\u00d0\u00be\u00d0\u00b6",
+ "\u0120mute",
+ "\u0120dwar",
+ "\u0120\u00d8\u00a7\u00d8\u00b3",
+ "\u0120kompl",
+ "\u0120merit",
+ "\u0120fosse",
+ "\u0120Drink",
+ "\u0120fora",
+ "\u0120wohl",
+ "\u0120breeze",
+ "\u0120sanit",
+ "\u0120drin",
+ "\u0120\u00ec\u013f\u00b4\u00ea\u00b1\u00b0\u00eb\u012c\u0136",
+ "\u012062",
+ "\u0120\u00ec\u00b0\u00a8\u00eb",
+ "abytes",
+ "\u0120deeds",
+ "\u0120\u00d0\u00b9",
+ "i\u00c3\u00a8me",
+ "iggling",
+ "\u0120\"'",
+ "\u0120\u00d1\u0129\u00d0\u00b0\u00d1\u0123\u00d1\u0124\u00d1\u012e",
+ "\u0120Answer",
+ "\u0120evangel",
+ "\u01201080",
+ "\u0120Visit",
+ "icient",
+ "\u0120reliability",
+ "\u00d1\u0130\u00d1\u0123\u00d1\u012e",
+ "\u0120Earlier",
+ "\u0120fid",
+ "\u00e7\u0143\u012b\u00e4\u00b8\u0122\u00e4\u00b8\u012d",
+ "\u0120sleeves",
+ "iyorsun",
+ "\u0120bib",
+ "\u0120Account",
+ "\u00d1\u0131\u00d0\u00bb\u00d0\u00b8",
+ "ciplinary",
+ "zas",
+ "\u0120\u00d0\u00b1\u00d0\u00b5\u00d1\u0122",
+ "\u0120necklace",
+ "\u0120blender",
+ "\u0120Phillips",
+ "eti",
+ "\u0120Jupiter",
+ "\u0120provoc",
+ "\u0120Years",
+ "entre",
+ "acio",
+ "\u0120k\u00c3\u00bc",
+ "\u0120antenna",
+ "\u0120novels",
+ "\u0120fart",
+ "\u0120Sugar",
+ "\u0120Judy",
+ "\u0120collapsed",
+ "\u00e7\u00b0",
+ "ritis",
+ "\u0120\u00ec\u0125\u0123\u00ed\u013b\u00a9",
+ "\u00d0\u0139\u00d0\u00ab",
+ "\u0120Verf",
+ "ranean",
+ "ereum",
+ "\u0120Target",
+ "\u012088",
+ "\u0120\u00d0\u013a\u00d0\u00b7",
+ "ideo",
+ "\u0120regression",
+ "\u00ec\u00b6\u013e",
+ "\u0120m\u00c3\u00b3wi",
+ "\u0120studios",
+ "iens",
+ "iph",
+ "\u0120frying",
+ "\u0120fascinated",
+ "\u0120Wah",
+ "bucks",
+ "maya",
+ "\u0120Saturn",
+ "\u0120Mommy",
+ "\u0120ratings",
+ "\u0120autumn",
+ "\u00c6\u00b0\u00c6\u00a1ng",
+ "\u0120loser",
+ "\u0120centro",
+ "\u00c3\u00a9rieur",
+ "\u0120Fold",
+ "\u0120supervisor",
+ "\u0120Nobel",
+ "\u0120underest",
+ "obia",
+ "\u0120\u00d0\u00b2\u00d1\u0123\u00d1\u0131",
+ "\u0120verw",
+ "\u0120fuels",
+ "\u0120artifacts",
+ "\u0120\u00eb\u00b6\u013b",
+ "\u0120Autom",
+ "\u00e7\u013c\u0126\u00e6\u013a\u00af",
+ "\u00db\u0136",
+ "\u00d7\u0137\u00d7\u00a1",
+ "\u0120ihnen",
+ "\u012059",
+ "ounding",
+ "\u00d0\u00b5\u00d1\u0122\u00d1\u012d",
+ "inars",
+ "chant",
+ "\u0120addicted",
+ "\u0120explosive",
+ "\u0120dispers",
+ "\u00e2\u0138\u012a",
+ "axis",
+ "ARY",
+ "\u0120lum",
+ "\u0120\u00d1\u0125\u00d1\u0123\u00d0\u00bb",
+ "\u0120\u00d8\u012e",
+ "\u0120rupees",
+ "\u0120Pearl",
+ "camp",
+ "tv",
+ "oya",
+ "\u0120concludes",
+ "\u0120collision",
+ "\u0120buyer",
+ "\u0120playground",
+ "\u0120springs",
+ "\u0120feminine",
+ "\u0120Ras",
+ "\u0120incarcer",
+ "\u00ed\u0139\u013a",
+ "\u0120dialect",
+ "\u0120closure",
+ "\u0120chatting",
+ "\u0120babe",
+ "\u0120spotlight",
+ "\u0120notation",
+ "\u00e8\u00b7\u00af",
+ "Star",
+ "i\u00c3\u00a3o",
+ "\u0120t\u00c3\u00aate",
+ "\u0120tide",
+ "\u0120junto",
+ "\u0120senator",
+ "\u00d0\u00a5",
+ "\u0120excuses",
+ "\u0120blink",
+ "\u0120admission",
+ "\u0120Lily",
+ "\u00d1\u012d\u00d0\u00bc\u00d0\u00b8",
+ "\u0120amigo",
+ "\u0120lust",
+ "\u00eb\u012d\u00ac",
+ "\u0120amino",
+ "\u00e4\u00ba\u012d\u00e6\u0125\u0127",
+ "\u0120consultant",
+ "\u0120Electric",
+ "\u0120\u00eb\u0127\u00b8\u00eb\u0140\u013a",
+ "ujah",
+ "\u0120shooter",
+ "ichten",
+ "\u0120Ukrainian",
+ "\u0120aims",
+ "\u0120Entertain",
+ "\u0120miracles",
+ "\u00e8\u0143\u00b0",
+ "\u0120zeigen",
+ "\u0120lam",
+ "\u0120ress",
+ "\u0120Jill",
+ "ylan",
+ "\u0120rook",
+ "\u0120haya",
+ "\u0120passport",
+ "adata",
+ "\u0120juicy",
+ "conf",
+ "\u00d0\u00bb\u00d0\u00b5\u00d0\u00b9",
+ "\u0120Sz",
+ "\u0120intercept",
+ "\u00e3\u0123\u0124\u00e3\u0124\u012c\u00e3\u0123\u012e\u00e3\u0123\u00a8\u00e3\u0123\u0128\u00e3\u0123\u0136\u00e3\u0123\u0138",
+ "\u0120Teams",
+ "\u0120maken",
+ "irrel",
+ "\u0120LIKE",
+ "\u00e1\u00ba\u0143y",
+ "\u00ea\u00b5\u00b0",
+ "\u0120shortage",
+ "\u0120paradigm",
+ "\u0120papel",
+ "\u0120astero",
+ "\u00e3\u0123\u00be\u00e3\u0123\u0141",
+ "\u0120sollen",
+ "\u0120Mickey",
+ "\u0120Orleans",
+ "\u0120cholesterol",
+ "\u0120goose",
+ "\u00d1\u0128\u00d0\u00b8\u00d1\u0130",
+ "\u00e3\u0123\u0124\u00e3\u0124\u012d",
+ "\u0120FL",
+ "\u0120\u00d0\u00b3\u00d0\u00be\u00d0\u00bb\u00d0\u00be\u00d0\u00b2",
+ "\u0120tribute",
+ "\u0120Gam",
+ "\u0120\u00c3\u00a9videmment",
+ "\u00d1\u0131\u00d1\u0127",
+ "\u00e5\u00ae\u0140",
+ "\u00e7\u0136\u00b0",
+ "\u0120inappropri",
+ "uhan",
+ "\u0120organizational",
+ "ailed",
+ "\u0120endure",
+ "\u012076",
+ "\u0120shotgun",
+ "\u0120livre",
+ "\u0120suited",
+ "\u0120warmth",
+ "\u0120SIM",
+ "\u0120envision",
+ "\u0120degrad",
+ "\u00c3\u00aene",
+ "Laughing",
+ "\u0120Whoever",
+ "\u0120Buddhism",
+ "\u0120sprinkle",
+ "ce\u00c4\u0141iz",
+ "\u0120ruins",
+ "\u0120starch",
+ "\u0120Herz",
+ "\u0120injustice",
+ "\u0120humidity",
+ "\u00d0\u00be\u00d0\u00b6\u00d0\u00b0\u00d0\u00bb\u00d1\u0125\u00d0\u00b9",
+ "\u0120Object",
+ "\u0120Ign",
+ "\u0120Exam",
+ "igers",
+ "\u0120thou",
+ "\u0120Soy",
+ "ivas",
+ "\u0120poles",
+ "math",
+ "\u0120\u00d0\u00b2\u00d0\u00bd\u00d0\u00b8\u00d0\u00bc",
+ "INGING",
+ "edral",
+ "\u0120explor",
+ "\u0120roasted",
+ "\u0120crawl",
+ "\u0120coff",
+ "\u0120anom",
+ "\u0120wij",
+ "\u0120improves",
+ "\u0120treaty",
+ "\u0120discovering",
+ "\u0120statute",
+ "\u0120mercado",
+ "\u0120\u00d1\u0123\u00d0\u00b8\u00d0\u00bb",
+ "\u0120intel",
+ "\u0120Chancellor",
+ "\u0120Medicaid",
+ "ugi",
+ "\u0120verbal",
+ "\u0120d\u00c3\u00b6n",
+ "\u0120scripture",
+ "\u0120iteration",
+ "eks",
+ "\u0120Oxford",
+ "\u0120w\u00c3\u00a4h",
+ "\u0120Vad",
+ "\u0120AK",
+ "\u0120\u00ec\u0137\u0126\u00ec\u013f\u00b4\u00eb",
+ "\u0120iets",
+ "\u0120needles",
+ "\u00d9\u0125\u00d9\u0127",
+ "\u0120pasado",
+ "\u0120albums",
+ "\u0120yea",
+ "etzen",
+ "\u0126\u00eb\u0131\u0126",
+ "\u0120determines",
+ "\u0120thee",
+ "\u0120Playing",
+ "\u00c3\u00a4rt",
+ "\u0120\u00d7\u00a6",
+ "cled",
+ "\u0120downward",
+ "alone",
+ "\u0120solu",
+ "\u0120partition",
+ "\u0120wz",
+ "dd",
+ "\u0120pessoal",
+ "\u00e5\u00aa\u00bd",
+ "\u0120factories",
+ "\u0120bleibt",
+ "\u00e0\u00b8\u00a1\u00e0\u00b8\u00b2",
+ "alsa",
+ "\u0120NFL",
+ "\u0120fuera",
+ "\u0120reserved",
+ "\u0120Earn",
+ "\u0120helt",
+ "\u0120shortcut",
+ "\u0120convincing",
+ "space",
+ "\u0120enforce",
+ "\u0120cores",
+ "\u0120efter",
+ "\u0120recession",
+ "xico",
+ "\u0120proposition",
+ "arians",
+ "ropol",
+ "\u0120\u00eb\u00aa\u00b0\u00eb",
+ "\u0120\u00ce\u013e",
+ "\u0120\u00ec\u013c\u0136\u00ec\u00a6\u013a",
+ "\u0120activist",
+ "\u0120conviction",
+ "\u0120zab",
+ "\u0120canceled",
+ "\u00d1\u0124\u00d0\u00be\u00d1\u0129\u00d0\u00bd\u00d0\u00be",
+ "\u0120\u00ce\u00ae",
+ "\u00e9\u0122\u013b\u00e6\u00a8\u00a3\u00e5\u0143\u0132",
+ "nite",
+ "\u0120fundra",
+ "buzzer",
+ "\u00d0\u00b5\u00d0\u00bb\u00d0\u00be",
+ "ications",
+ "\u0120zona",
+ "\u0120teens",
+ "\u0120methodology",
+ "\u0120\u00ec\u00a4\u0133\u00ec\u013c\u0136",
+ "than",
+ "\u0120Ul",
+ "\u0120Grey",
+ "\u0120hog",
+ "INK",
+ "\u0120Sung",
+ "\u0120Claud",
+ "\u0120CNN",
+ "\u0120delivers",
+ "alin",
+ "\u0120Adobe",
+ "othe",
+ "\u0120Deswegen",
+ "\u00e0\u00b8\u00b3",
+ "\u0120werde",
+ "\u0120grease",
+ "\u0120upgrades",
+ "\u0120Finland",
+ "accept",
+ "\u0120interrog",
+ "bee",
+ "\u0120\u00e3\u0123\u00ab",
+ "\u0120prede",
+ "\u0120Nep",
+ "\u0120Cambridge",
+ "\u0120graphs",
+ "\u0120haunted",
+ "\u00d1\u0123\u00d0\u00b5\u00d0\u00bc",
+ "\u00e6\u00a7",
+ "\u00e5\u0127\u012d",
+ "Some",
+ "\u0120Mall",
+ "\u0120rehearsal",
+ "\u0120Urban",
+ "\u0120Lag",
+ "\u0120nim",
+ "\u00ea\u00b0\u0137",
+ "\u0120positioned",
+ "\u0120avoided",
+ "EMA",
+ "\u0120llegar",
+ "\u0120r\u00c3\u00a1pido",
+ "\u0120gouvern",
+ "\u0120hing",
+ "\u0120dealer",
+ "\u0120reforms",
+ "\u0120fatty",
+ "\u00d0\u00ba\u00d0\u00be\u00d0\u00bb",
+ "\u0120Ace",
+ "\u0120nep",
+ "\u0120\u00ec\u00b2\u0143",
+ "\u0120computation",
+ "\u0120Stream",
+ "bourne",
+ "tur",
+ "Por",
+ "\u0120sleepy",
+ "\u0120banget",
+ "\u00e3\u0123\u0124\u00e3\u0123\u00ae",
+ "\u0120weighs",
+ "\u0120bleiben",
+ "\u0120Gren",
+ "\u0120unions",
+ "\u0120\u00ea\u00b5\u0132",
+ "\u0120aprender",
+ "uitar",
+ "\u0120Jest",
+ "uming",
+ "\u0120Player",
+ "\u0120Extrem",
+ "\u0120integer",
+ "\u00d0\u00b0\u00d1\u0129\u00d0\u00b5",
+ "\u0120concerts",
+ "\u00d7\u0137\u00d7\u013d",
+ "\u0120troch\u00c4\u013b",
+ "\u0120Repe",
+ "\u00e9\u0129\u012f\u00e8\u00a6\u0123",
+ "\u00e0\u00b9\u0124",
+ "\u00c5\u00bcen",
+ "\u0120sounding",
+ "\u0120anonymous",
+ "\u0120exca",
+ "\u0120Iranian",
+ "\u0120energetic",
+ "\u0120wives",
+ "\u0120\u00d1\u0128\u00d0\u00b2\u00d0\u00b5\u00d1\u0124",
+ "\u0120ais",
+ "\u00e3\u0123\u012d\u00e3\u0123\u00aa",
+ "\u0120sudah",
+ "\u0120underwear",
+ "\u0120crunchy",
+ "\u0120Pain",
+ "\u0120ger\u00c3\u00a7ek",
+ "redict",
+ "\u0120misma",
+ "\u00d1\u0138\u00d1\u0124",
+ "\u0120surviving",
+ "\u00ce\u0143\u00cf\u0124",
+ "\u0120participant",
+ "\u0120Hessen",
+ "\u00c3\u00a1rias",
+ "\u0120subway",
+ "ist\u00c3\u00a4",
+ "\u0120coral",
+ "\u0120marijuana",
+ "\u0120Memorial",
+ "\u00d1\u012a\u00d0\u00b8\u00d0\u00b9",
+ "riz",
+ "\u0120satellites",
+ "\u0120lease",
+ "\u0120Cameron",
+ "umph",
+ "\u0120classmates",
+ "\u00c3\u00a4h\u00c3\u00a4n",
+ "\u00d1\u0123\u00d1\u0124\u00d0\u00b2\u00d0\u00b5",
+ "\u0120hue",
+ "\u0135\u00a4\u00ec\u013f\u0126",
+ "\u0120proportional",
+ "\u0120noss",
+ "\u0120laps",
+ "r\u00c3\u00a5",
+ "\u0120bitcoin",
+ "\u00d0\u0139\u00d0\u00ab\u00d0\u013c\u00d0\u0132",
+ "\u0120\u00ec\u00b6\u00a9",
+ "\u0120\u00d9\u0126\u00d9\u0126",
+ "\u0120Mort",
+ "\u0120Esp",
+ "arnos",
+ "\u0120\u00d1\u0123\u00d0\u00ba\u00d0\u00b0\u00d0\u00b7\u00d0\u00b0\u00d0\u00bb",
+ "\u0120\u00c3\u00a4nd",
+ "\u00e5\u0127\u0126",
+ "\u00d7\u013b\u00d7\u013b\u00d7\u013f",
+ "\u0120Geb",
+ "gehen",
+ "Inaudible",
+ "borough",
+ "\u00d1\u0126\u00d1\u0126",
+ "\u0120fellowship",
+ "\u0120Paper",
+ "\u0120curved",
+ "\u0120GEOR",
+ "\u0120calculator",
+ "\u0120Catal",
+ "\u0120v\u00c3\u0142o",
+ "\u0120bypass",
+ "\u00d0\u00bb\u00d0\u00b5\u00d1\u0124",
+ "\u00e0\u00b3",
+ "trans",
+ "rencies",
+ "\u00ec\u00a1\u012e",
+ "igent",
+ "\u0120tasted",
+ "\u0120oceans",
+ "uft",
+ "ervice",
+ "\u0120\u00d0\u013e\u00d0\u00a3\u00d0\u0139\u00d0\u00ab\u00d0\u013c\u00d0\u0132",
+ "\u0120Classic",
+ "\u0120respectively",
+ "~)",
+ "\u00c3\u00aetre",
+ "\u0120Nash",
+ "\u0120zit",
+ "\u0120\u00ec\u013d\u0125",
+ "\u0120\u00eb\u0128\u0134",
+ "quote",
+ "\u0120Uns",
+ "\u0120tac",
+ "\u0120proves",
+ "\u0120Portland",
+ "bly",
+ "\u0120ere",
+ "\u00ec\u00b6\u0136",
+ "\u0120\u00c3\u00a9poca",
+ "\u0120\u00d1\u0124\u00d1\u012d\u00d1\u0123\u00d1\u0131\u00d1\u0129",
+ "76",
+ "\u0120hade",
+ "\u0120Fro",
+ "\u0120pol\u00c3\u0143tica",
+ "tag",
+ "\u0120\u00ed\u0137\u0143",
+ "\u0120sch\u00c3\u00b6",
+ "arett",
+ "\u0120provisions",
+ "\u0120motors",
+ "\u0120imaging",
+ "\u0120dok",
+ "ulously",
+ "\u0120meille",
+ "\u00e7\u0130\u00b0\u00e5\u013e\u00a8",
+ "\u00eb\u0132",
+ "\u0120ISO",
+ "\u0120STEM",
+ "\u0120Bowl",
+ "\u0120towers",
+ "\u0120Ee",
+ "\u0120Performance",
+ "\u0120loin",
+ "cussion",
+ "\u0120coastal",
+ "iale",
+ "compass",
+ "\u0120spells",
+ "\u0120disappointing",
+ "\u0120\u00eb\u00b2\u012a\u00ec\u00a7\u00b8",
+ "EER",
+ "\u0120versatile",
+ "asury",
+ "\u0120enfin",
+ "\u0120downside",
+ "\u0120guiding",
+ "\u0120\u00d8\u00a7\u00d9\u0126\u00d9\u0124",
+ "\u0120ninety",
+ "charged",
+ "\u0120Fans",
+ "\u0120philosophical",
+ "\u0120garn",
+ "\u0120m\u00c3\u00a5nga",
+ "\u0120willingness",
+ "\u0120portions",
+ "aben",
+ "\u0120\u00ef",
+ "\u00c2\u00bf",
+ "raul",
+ "\u0120sprint",
+ "ifen",
+ "\u00c4\u00b1yla",
+ "\u0120\u00d0\u00ba\u00d1\u0125\u00d0\u00bf",
+ "\u00e3\u0123\u0131\u00e3\u0123\u0142\u00e3\u0123\u0137\u00e3\u0123\u0126",
+ "\u0120ensuite",
+ "\u0120Capitol",
+ "\u012063",
+ "\u0120\u00d0\u00b3\u00d0\u00be\u00d0\u00b2\u00d0\u00be\u00d1\u0122\u00d0\u00b8\u00d1\u0124",
+ "\u0120appointments",
+ "\u00e6\u012b\u00be",
+ "omiast",
+ "\u0120careg",
+ "\u0120publisher",
+ "\u0120heraus",
+ "\u0120\u00ce\u00b5\u00ce\u00af",
+ "\u0120VS",
+ "\u00e3\u0123\u013f\u00e3\u0123\u0139\u00e3\u0123\u00a6",
+ "\u00e4\u00b8\u0143\u00e5\u0127\u00b1",
+ "\u0120sacrifices",
+ "third",
+ "\u0120humanitarian",
+ "\u0120\u00eb\u0124\u00b4\u00ec",
+ "imon",
+ "\u0120inequ",
+ "\u0120zob",
+ "\u0120comfortably",
+ "\u0120Dinge",
+ "\u0120cancelled",
+ "\u0120PSAKI",
+ "\u0120Robinson",
+ "\u0120fins",
+ ")?",
+ "\u0120Histor",
+ "\u0120\u00d1\u0129\u00d0\u00b5\u00d0\u00bb\u00d0\u00be\u00d0\u00b2\u00d0\u00b5\u00d0\u00ba\u00d0\u00b0",
+ "\u0120tbsp",
+ "text",
+ "kim",
+ "\u0120updating",
+ "\u0120geld",
+ "feld",
+ "\u0131\u00bc",
+ "\u0120m\u00c3\u00a4",
+ "\u0120caf\u00c3\u00a9",
+ "\u00d6\u0122",
+ "\u0120Sri",
+ "\u0120Region",
+ "\u0120Hahaha",
+ "\u0120finances",
+ "\u0120\u00d8\u00a7\u00d9\u0126\u00d8\u00b4",
+ "\u0120bunk",
+ "ruk",
+ "haft",
+ "\u0120lateral",
+ "\u0120extensions",
+ "\u0120\u00ec\u0137\u0126\u00ec\u013f\u00b4",
+ "\u0120definite",
+ "\u0120Zhao",
+ "\u0120Luis",
+ "sty",
+ "\u0120casos",
+ "\u0120Klim",
+ "\u01201993",
+ "\u0120realization",
+ "\u0120historian",
+ "\u0120cracked",
+ "\u00eb\u0124\u00b4",
+ "\u0120syst\u00c3\u00a8me",
+ "\u0120CIA",
+ "\u0120\u00d1\u0124\u00d0\u00b2\u00d0\u00be",
+ "ospheric",
+ "\u0120flee",
+ "\u0120r\u00e1\u00ba\u00a5t",
+ "\u0120Regardless",
+ "\u0120reluct",
+ "\u0120timely",
+ "\u0120Julian",
+ "GM",
+ "\u00e9\u0134",
+ "adura",
+ "\u00e9\u00a3\u0141",
+ "\u0120dresses",
+ "\u00e7\u0123\u00a3",
+ "\u0120\u00eb\u0136\u0136",
+ "\u0120nominated",
+ "\u0120advocates",
+ "ymph",
+ "\u0120recordings",
+ "\u0120deviation",
+ "\u0120prioritize",
+ "\u0120spiral",
+ "\u0120YOUR",
+ "\u0120transpose",
+ "ampoo",
+ "\u0120\u00ec\u013d\u0132\u00eb\u0140\u013a",
+ "\u0120Vision",
+ "\u0120polite",
+ "\u0120hamb",
+ "\u0120Patient",
+ "\u00e6\u00af\u0136\u00e8\u00bc\u0125",
+ "\u00ed\u0123\u00ac\u00eb",
+ "\u0120sia",
+ "\u0120\u00ea\u00b3\u00b3",
+ "\u0120\u00c5\u00bee",
+ "\u00e8\u00a7\u0122",
+ "\u0120supermarket",
+ "\u00eb\u00b9",
+ "\u0120Sierra",
+ "\u0120grilled",
+ "\u0120Upon",
+ "\u0120absent",
+ "\u0120mec",
+ "\u0120Apollo",
+ "\u0120punk",
+ "\u0120Pa\u00c5\u0126st",
+ "\u0120\u00d1\u0123\u00d0\u00b2\u00d0\u00be\u00d0\u00b9",
+ "\u0120\u00ea\u00b1\u00b0\u00ea\u00b8\u00b0",
+ "Girl",
+ "\u0120skinny",
+ "\u0120Premier",
+ "\u0120territories",
+ "\u0120liability",
+ "\u0120jerk",
+ "ratic",
+ "\u0120dancers",
+ "\u0120\u00d1\u0125\u00d1\u0122\u00d0\u00be\u00d0\u00b2",
+ "\u0120\u00ea\u00b4\u0122\u00eb",
+ "only",
+ "\u0120Stu",
+ "\u0120skeleton",
+ "\u0120\u00eb\u0143\u0132\u00eb",
+ "\u0120\u00d0\u00b7\u00d0\u00b0\u00d0\u00ba\u00d0\u00be\u00d0\u00bd",
+ "\u00c4\u00b1kt",
+ "\u0120MIKE",
+ "\u0120l\u00c3\u00b6",
+ "mie",
+ "\u0120reiter",
+ "\u00e3\u0123\u0135\u00e3\u0124\u012e\u00e3\u0123\u00af",
+ "\u0120Kolleg",
+ "\u0120Adams",
+ "licher",
+ "\u0120\u00c3\u00a7ocuk",
+ "\u00d1\u0131\u00d0\u00b3",
+ "\u0120blush",
+ "\u0120sunshine",
+ "\u0120ez",
+ "\u0120Devil",
+ "\u0120\u00ea\u00b8\u00b8",
+ "\u0120\u00e3\u0123\u012c",
+ "add",
+ "\u0120licensed",
+ "\u0120vinyl",
+ "\u0120Czech",
+ "imag",
+ "\u0120cracking",
+ "\u0120\u00ec\u00ba",
+ "\u0120udah",
+ "\u0120sommes",
+ "\u0120\u00ec\u0138\u00bc\u00ea\u00b5",
+ "wa\u00c4\u0129",
+ "\u0120fres",
+ "\u00e5\u0133\u00bd",
+ "\u0120Walmart",
+ "\u0120\u00d0\u00a2\u00d0\u00b5\u00d0\u00bf\u00d0\u00b5\u00d1\u0122\u00d1\u012e",
+ "atisf",
+ "CI",
+ "lang",
+ "\u0120diffusion",
+ "\u00e7\u0136\u00b7",
+ "\u0120somos",
+ "\u0120Makes",
+ "\u00e6\u012a\u0133\u00e6\u0125\u00b3",
+ "\u0120Ricky",
+ "\u0120mucha",
+ "\u00ed\u0137\u00a8",
+ "\u0120horsepower",
+ "asia",
+ "\u0120fibers",
+ "\u0120erm",
+ "\u00d1\u0123\u00d0\u00ba\u00d0\u00b8\u00d0\u00b5",
+ "\u0120jeste",
+ "\u0120firefight",
+ "\u0120cuisine",
+ "\u0120besonders",
+ "dig",
+ "\u0120\u00ec\u00a2\u0127",
+ "\u0120\u00d1\u0125\u00d0\u00b6",
+ "\u0120tracing",
+ "\u0120certains",
+ "\u0120Apply",
+ "\u00d1\u012d\u00d0\u00b2\u00d0\u00b0\u00d1\u0124\u00d1\u012e",
+ "\u00e7\u012e",
+ "\u0120bru",
+ "\u0120YES",
+ "\u0120Bai",
+ "\u0120Dit",
+ "\u0120Bis",
+ "\u0120unle",
+ "\u00d1\u0123\u00d1\u0124\u00d0\u00b0\u00d1\u0124\u00d0\u00be\u00d1\u0129\u00d0\u00bd\u00d0\u00be",
+ "\u0120Awak",
+ "..\"",
+ "\u0120125",
+ "\u0120rooted",
+ "\u0120cautious",
+ "const",
+ "\u0120orchestra",
+ "\u00e7\u013e\u00bc",
+ "\u0120\u00d0\u00b2\u00d0\u00bd\u00d1\u0125\u00d1\u0124",
+ "\u0120quelqu",
+ "\u0120\u00d0\u00be\u00d1\u0124\u00d0\u00b2\u00d0\u00b5\u00d1\u0124",
+ "\u0120Method",
+ "\u00ec\u00b9\u013e",
+ "\u0120\u00ce\u00bc\u00ce\u00b1\u00cf\u0124",
+ "l\u00c3\u00bc",
+ "\u0120\u00ec\u0137\u0126\u00ea\u00b9\u012e",
+ "\u0120naming",
+ "Char",
+ "\u0120Sicher",
+ "\u0120privileged",
+ "\u0120Fly",
+ "\u0120\u00e3\u0123\u012d",
+ "\u00e1\u00ba\u0143t",
+ "\u0120advances",
+ "\u0120Zelda",
+ "\u0120andra",
+ "\u0120grinding",
+ "\u0120Edition",
+ "pf",
+ "\u0120warriors",
+ "\u0120hedge",
+ "\u0120unseren",
+ "\u0120\u00d1\u0123\u00d1\u0130\u00d0\u00b4\u00d0\u00b0",
+ "eliness",
+ "\u0120personalities",
+ "\u0120f\u00c3\u00b6",
+ "'M",
+ "\u0120\u00d1\u0124\u00d0\u00be\u00d1\u0129\u00d0\u00bd\u00d0\u00be",
+ "\u0120shipped",
+ "\u0120meteor",
+ "\u0120surroundings",
+ "\u0120Fill",
+ "uesta",
+ "\u0120Personal",
+ "\u0120Alle",
+ "ORT",
+ "\u00e4\u00b9\u0127",
+ "\u0120Sche",
+ "VI",
+ "\u0120comparable",
+ "damn",
+ "\u0120ditch",
+ "YAN",
+ "ismus",
+ "\u0120pickup",
+ "\u0120dak",
+ "\u0120EP",
+ "best",
+ "\u0120Sue",
+ "\u00c3\u00a4llt",
+ "\u0120popcorn",
+ "\u0120folding",
+ "home",
+ "\u00d0\u00b8\u00d0\u00b2\u00d0\u00b0\u00d0\u00b5\u00d1\u0124",
+ "\u00e5\u00b7\u00b2\u00e7\u00b6\u0135",
+ "\u0120annot",
+ "chuck",
+ "\u0120fierce",
+ "\u0120damaging",
+ "\u0120flop",
+ "\u0120pasar",
+ "\u0120reef",
+ "\u0120\u00d1\u0123\u00d0\u00b2\u00d0\u00be\u00d0\u00b5\u00d0\u00b9",
+ "\u0120zoo",
+ "overs",
+ "jets",
+ "\u0120pr\u00c3\u00a8s",
+ "\u0120Silicon",
+ "teok",
+ "\u0120Seth",
+ "atamente",
+ "\u0120transmitted",
+ "\u0120replicate",
+ "\u0120slim",
+ "\u0120Cream",
+ "\u00e6\u0126\u0141\u00e3\u0123\u013a",
+ "\u0120sidewalk",
+ "\u00ec\u012a\u013a\u00eb",
+ "\u0120\u00d0\u00b6\u00d0\u00b8\u00d0\u00b7\u00d0\u00bd\u00d1\u012e",
+ "\u0120Monica",
+ "\u00e4\u00be\u0128\u00e4\u00ba\u0128",
+ "\u0120copied",
+ "\u0120Terra",
+ "istent",
+ "\u00e7\u00b3\u00bb",
+ "\u0120\u00d0\u00be\u00d0\u00bd\u00d0\u00be",
+ "\u0120whale",
+ "\u0120WITH",
+ "\u00d0\u00bb\u00d1\u0125\u00d1\u012a",
+ "\u00e5\u00bd\u00b1\u00e7\u012b\u0129",
+ "\u0120Een",
+ "\u0120\u00d1\u0123\u00d0\u00b2\u00d0\u00be\u00d0\u00b8",
+ "\u0120ordin",
+ "\u0120plural",
+ "\u0120spokes",
+ "\u0120dispute",
+ "\u0120sensible",
+ "\u0120preaching",
+ "\u0120kt\u00c3\u00b3rzy",
+ "pted",
+ "avier",
+ "\u0120pistol",
+ "\u0120Tapi",
+ "\u0120\u00c5\u0124",
+ "ffff",
+ "\u0120acrylic",
+ "\u0120ignorance",
+ "\u0120Ziel",
+ "rans",
+ "\u0120welding",
+ "mid",
+ "\u00e6\u012a\u0133\u00e4\u00b8\u012f",
+ "\u0120\u00d0\u00b7\u00d0\u00b0\u00d0\u00bd\u00d0\u00b8\u00d0\u00bc",
+ "\u0120lanes",
+ "\u0120mines",
+ "\u0120moms",
+ "\u00d7\u0137\u00d7\u0139",
+ "\u0120Chamber",
+ "tier",
+ "\u0120modest",
+ "\u0120\u00ec\u0139\u00ac\u00ea\u00b8\u00b0\u00ec\u0126\u013e",
+ "\u0120unas",
+ "\u0120wrench",
+ "handed",
+ "\u0120saturated",
+ "\u0120Fang",
+ "\u0120Commissioner",
+ "\u00e0\u00a4\u00b0",
+ "\u0120\u00d7\u0138",
+ "\u0120Louisiana",
+ "\u0120Mask",
+ "\u0120cubes",
+ "\u00ec\u0136\u00a8",
+ "\u0120vid\u00c3\u00a9os",
+ "\u0120n\u00c3\u00a5gon",
+ "\u0120rider",
+ "\u0120\u00ec\u00b6\u013e",
+ "\u0120s\u00c3\u00b3n",
+ "\u0120Latino",
+ "bank",
+ "\u00ed\u0137\u00b4\u00ec\u00a3\u00bc",
+ "\u0120Brend",
+ "\u0120sexuality",
+ "...,",
+ "\u0120forgetting",
+ "\u0120\u00db\u012e",
+ "\u0120Avengers",
+ "\u0120Bonjour",
+ "cessor",
+ "\u00d0\u00ba\u00d1\u0122\u00d0\u00b0\u00d1\u0139",
+ "cence",
+ "\u0120geograph",
+ "culo",
+ "\u00d0\u00be\u00d1\u0123\u00d1\u0124\u00d1\u012e",
+ "\u0120sweating",
+ "\u00ed\u0125\u0122",
+ "\u0120symmetry",
+ "ts\u00c3\u00a5",
+ "\u0120jan",
+ "\u0120Ferr",
+ "\u00e9\u00a6\u0138",
+ "\u0120ambassador",
+ "zi\u00c4\u013bk",
+ "\u0120musun",
+ "\u0120\u00d1\u0125\u00d1\u0124",
+ "\u0120LG",
+ "issent",
+ "commun",
+ "\u0120cours",
+ "\u0120develops",
+ "\u0120bronze",
+ "\u0120substances",
+ "driven",
+ "\u00ec\u00a3\u00bc\u00ec\u0126\u00b8\u00ec\u013c\u0136",
+ "\u0120aos",
+ "\u00e5\u0126\u0126",
+ "\u0120PROFESS",
+ "half",
+ "\u0120sorted",
+ "\u0120Bomb",
+ "\u00d0\u00bb\u00d0\u00b0\u00d0\u00b3",
+ "\u0120Malaysia",
+ "\u0120Christina",
+ "\u0120teammate",
+ "\u00e8\u0123\u0140",
+ "FT",
+ "\u0120k\u00c4\u00b1",
+ "hearted",
+ "++",
+ "ogenic",
+ "\u0120bells",
+ "\u0120Ouais",
+ "\u0120specialists",
+ "\u00d0\u00b1\u00d1\u012d",
+ "depth",
+ "lasses",
+ "gies",
+ "\u0120Coffee",
+ "\u0120marking",
+ "\u0120foll",
+ "uli",
+ "\u0120adhesive",
+ "\u0120Bot",
+ "\u0120Punkt",
+ "eye",
+ "\u0120Bub",
+ "elong",
+ "\u00e5\u012a\u00b6",
+ "\u0120\u00d0\u00bf\u00d1\u0122\u00d0\u00b8\u00d0\u00ba",
+ "\u0120donor",
+ "84",
+ "\u0120enfor",
+ "\u0120catches",
+ "\u0120bricks",
+ "\u0120knitting",
+ "\u0120Knowing",
+ "oks",
+ "HY",
+ "ride",
+ "\u0120Fantasy",
+ "iman",
+ "\u0120pse",
+ "\u0120\u00ec\u013a\u00a8",
+ "\u0120\u00d0\u00b2\u00d0\u00b4",
+ "\u0120restra",
+ "\u0120evaluated",
+ "\u00d1\u0122\u00d0\u00b5\u00d0\u00b2",
+ "\u0120fortunately",
+ "\u0120chegar",
+ "\u00d8\u00b1\u00d8\u00a8",
+ "\u0120domains",
+ "ibi",
+ "arry",
+ "\u0120shutter",
+ "\u0120ficou",
+ "Mike",
+ "\u0120inclu",
+ "\u0120donors",
+ "\u0120apl",
+ "\u0120Lower",
+ "\u0120imported",
+ "\u0120academy",
+ "\u0120finals",
+ "\u0120disappears",
+ "\u00d9\u012c\u00d8\u00a7",
+ "\u0120administrator",
+ "js",
+ "\u0120cutter",
+ "\u0120ranging",
+ "\u00c3\u00b6rper",
+ "\u0120constraint",
+ "\u0120Table",
+ "\u0120Shan",
+ "vic",
+ "\u0120Fix",
+ "\u0120Swift",
+ "ounces",
+ "\u0120Warum",
+ "\u0120lettuce",
+ "appelle",
+ "\u0120shave",
+ "\u0120b\u00c3\u00a1s",
+ "\u012077",
+ "\u0120Ooo",
+ "ao",
+ "\u0120McM",
+ "\u0120Drew",
+ "\u0120lump",
+ "\u0120lashes",
+ "scheinlich",
+ "Rep",
+ "inis",
+ "\u0120Cette",
+ "\u0120composite",
+ "emetery",
+ "\u0120sorte",
+ "\u0120Financial",
+ "\u00d0\u00be\u00d0\u00bd\u00d0\u00b5",
+ "rones",
+ "\u0120Voy",
+ "\u0120t\u00c3\u00a9c",
+ "\u0142\u00b9",
+ "\u0120Ninja",
+ "\u0120Corin",
+ "\u00d0\u00b5\u00d0\u00bd\u00d0\u00bd\u00d1\u0131",
+ "\u00ec\u013f\u00b4\u00ec\u0139\u012a",
+ "\u0120nich",
+ "\u0120detective",
+ "\u00e2\u0122\u00a6\"",
+ "\u00cf\u0125\u00ce\u00b5",
+ "\u013f\u00bc\u00eb\u0131\u0126",
+ "\u0120\u00eb\u00b3\u0122",
+ "\u0120\u00eb\u00b8\u0136\u00eb",
+ "\u0120prope",
+ "\u0120Wright",
+ "\u0120\u00d7\u0136\u00d7\u00aa",
+ "\u0120Shi",
+ "\u0120\u00e3\u0123\u0141",
+ "\u0120investigations",
+ "\u00e9\u0124\u0126\u00e6\u013a\u00af",
+ "\u0120PowerPoint",
+ "\u0120Chu",
+ "\u0120\u00ec\u013a\u00a4\u00ed",
+ "\u0120\u00ec\u013b\u0126\u00ec\u0142\u0126",
+ "\u0120Fragen",
+ "unning",
+ "\u0120pourrait",
+ "\u0120textbook",
+ "\u00d0\u00bc\u00d1\u012d",
+ "\u0120fahren",
+ "\u0120\u00d1\u0124\u00d0\u00be\u00d1\u0122",
+ "\u0120lakes",
+ "\u00c3\u00bcnde",
+ "Int",
+ "\u0120Metro",
+ "\u0120mansion",
+ "\u0120\u00d0\u00b0\u00d0\u00b1",
+ "\u0120Zhou",
+ "\u0120corridor",
+ "\u0120escol",
+ "\u0120indicating",
+ "ia\u00c5\u0124a",
+ "\u0120mommy",
+ "\u0120archives",
+ "\u0120founders",
+ "engine",
+ "\u0120Dieu",
+ "\u0120sickness",
+ "\u0120\u00eb\u00b3\u00b4\u00eb\u012d\u012a\u00ea\u00b9\u012e",
+ "\u0120arb",
+ "\u0120ned",
+ "\u0120Chop",
+ "\u0120covid",
+ "\u0120slam",
+ "\u0120publications",
+ "DC",
+ "\u0120spends",
+ "\u00e6\u00be",
+ "\u0120refugee",
+ "\u0120dile",
+ "\u0120\u00d7\u0132\u00d7\u0138",
+ "ificar",
+ "\u0120Sach",
+ "Gu",
+ "\u0120reload",
+ "????",
+ "\u0120je\u00c5\u013dli",
+ "\u0120\u00d1\u0123\u00d0\u00be\u00d1\u0123\u00d1\u0124\u00d0\u00be",
+ "\u0120simplicity",
+ "\u0120bullying",
+ "\u0120\u00d0\u00bc\u00d0\u00be\u00d0\u00bb",
+ "\u0120realidad",
+ "\u0120unclear",
+ "appa",
+ "levant",
+ "\u0120ISIS",
+ "\u0120Watson",
+ "\u0120dein",
+ "\u0120Micro",
+ "\u00ed\u0137\u013e\u00eb",
+ "\u00c3\u00bcg",
+ "\u0120devam",
+ "\u0120tweeted",
+ "\u00e5\u00b0\u0130",
+ "\u0120understandable",
+ "atan",
+ "\u0120versa",
+ "\u0120preca",
+ "\u0120v\u00e1\u00bb\u0123",
+ "\u0120Copy",
+ "\u0120Oracle",
+ "\u0120mindfulness",
+ "\u0120discret",
+ "ernen",
+ "\u0120Ple",
+ "Have",
+ "\u0120isolate",
+ "\u0120deu",
+ "\u0120seventy",
+ "\u0120Hills",
+ "\u0120arcade",
+ "\u0120\u00d1\u0123\u00d0\u00bf\u00d0\u00b5\u00d1\u0128\u00d0\u00b8",
+ "\u0120siguiente",
+ "\u0120B\u00c3\u013eNDNIS",
+ "liga",
+ "\u0120\u00d0\u00b2\u00d1\u0123\u00d1\u0124\u00d1\u0122\u00d0\u00b5\u00d1\u0129",
+ "\u00c3\u00b4m",
+ "\u0120tweets",
+ "\u0120schauen",
+ "\u0120critique",
+ "\u0120\u00f0\u0141\u0130\u00b5",
+ "\u0120statt",
+ "\u0120\u00d1\u0123\u00d0\u00b0\u00d0\u00bc\u00d0\u00be\u00d0\u00b5",
+ "\u00c3\u00a2ncia",
+ "\u0120supernatural",
+ "\u0120plugged",
+ "Fl",
+ "yn\u00c4\u00b1",
+ "\u0120Tambi\u00c3\u00a9n",
+ "\u0120encouragement",
+ "\u0120Server",
+ "\u00eb\u0124\u013e",
+ "upa",
+ "\u0120aston",
+ "\u0120hears",
+ "\u00d1\u0122\u00d0\u00b0\u00d1\u0127",
+ "\u0120sche",
+ "\u0120rats",
+ "\u0120recuper",
+ "\u0120unten",
+ "\u0120Fighting",
+ "\u0120academics",
+ "\u00e7\u00a4\u00ba",
+ "\u0120S\u00c3\u00bc",
+ "\u00d1\u0123\u00d0\u00ba\u00d0\u00b8\u00d1\u0127",
+ "\u0120paired",
+ "\u0122\u00ec\u013f\u0126",
+ "\u0120\u00c3\u00a1rea",
+ "\u0120sweetness",
+ "\u00e5\u0131\u012c",
+ "\u0120defer",
+ "\u0120muitas",
+ "\u0120Audio",
+ "\u0120locker",
+ "\u00d9\u012c\u00d8\u00af",
+ "\u0120\u00d1\u0123\u00d1\u0124\u00d0\u00b0\u00d0\u00b2",
+ "\u0120buena",
+ "ANS",
+ "\u0120detector",
+ "avo",
+ "bek",
+ "\u0120\u00ce\u00b1\u00ce\u00bd",
+ "\u00ed\u0130\u00b8",
+ "\u0120dragged",
+ "\u0120\u00d0\u00b4\u00d0\u00be\u00d0\u00bb\u00d0\u00b6\u00d0\u00b5\u00d0\u00bd",
+ "\u00c3\u0138",
+ "\u00d8\u00b1\u00d8\u00a9",
+ "\u00ec\u013f\u00b4\u00ec\u00a7\u0122",
+ "\u0120celle",
+ "cking",
+ "\u0120\u00d8\u00a7\u00d9\u0126\u00d8\u00ac",
+ "\u0120Canvas",
+ "\u0120espa\u00c3\u00b1",
+ "\u0120glimp",
+ "\u0120spreads",
+ "ongo",
+ "\u0120Mason",
+ "\u0120Ing",
+ "\u0120\u00ea\u00b0\u0122\u00eb\u012c\u00a5",
+ "\u00cf\u0126\u00ce\u00b9\u00ce\u00ba",
+ "\u0120secular",
+ "\u0120bater",
+ "\u0120inquiry",
+ "\u0120energies",
+ "\u0120manufactured",
+ "\u0120vegetarian",
+ "\u0120pineapple",
+ "\u00d1\u0131\u00d1\u0124\u00d0\u00b0",
+ "\u0120practitioners",
+ "2000",
+ "\u0120\u00ed\u0137\u00b4\u00ec\u013c\u0136",
+ "\u0120\u00ec\u0139\u00ac\u00eb\u0141\u00ac\u00eb\u00b6\u0126\u00eb\u0135\u00a4",
+ "\u0120\u00eb\u00b6\u012a\u00eb",
+ "\u0120Jefferson",
+ "\u0120Joan",
+ "\u0120tram",
+ "\u00e5\u00ae\u00b9",
+ "chmal",
+ "\u0120Hait",
+ "\u00e1\u00b9\u0129",
+ "\u0120unreal",
+ "\u0120symbolic",
+ "\u0120stealth",
+ "\u0120splash",
+ "\u0120Entertainment",
+ "\u0120metallic",
+ "?\".",
+ "\u00e8\u00b6\u012c",
+ "around",
+ "\u0120despair",
+ "\u0120Nevada",
+ "\u0120Finance",
+ "\u0120krie",
+ "\u0120Lux",
+ "\u0120Smash",
+ "keeping",
+ "\u0120\u00d0\u00b7\u00d0\u00b0\u00d0\u00b3",
+ "\u0120narciss",
+ "\u0120dzisiaj",
+ "\u0120tolerate",
+ "oard",
+ "\u0120linking",
+ "\u0120Economic",
+ "\u0120\u00ec\u00bc",
+ "\u0120morph",
+ "\u0120Nak",
+ "\u0120Baker",
+ "aton",
+ "rings",
+ "\u0120Peng",
+ "\u0120Airport",
+ "\u00e3\u0123\u012d\u00e3\u0123\u00a3\u00e3\u0123\u0141",
+ "\u00ed\u0137\u013a\u00eb\u012d\u00a4",
+ "\u00a7\u0123",
+ "prints",
+ "\u0120hadi",
+ "\u0120empir",
+ "\u0120Lives",
+ "anners",
+ "\u0120\u00d0\u00bd\u00d0\u00b8\u00d0\u00bc",
+ "\u0120PROFESSOR",
+ "\u0120positively",
+ "antom",
+ "\u0120badge",
+ "kelt",
+ "\u0120interfer",
+ "\u0120fulfilling",
+ "\u0120visualization",
+ "\u00e9\u0139\u013e\u00e4\u00bf\u0124",
+ "\u0120Price",
+ "\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd",
+ "\u0120scenery",
+ "\u0120prone",
+ "\u0120wizard",
+ "\u0120banyak",
+ "verb",
+ "sky",
+ "\u0120wished",
+ "\u0120railway",
+ "\u0120\u00c3\u00bczer",
+ "\u0120alguien",
+ "\u0120AW",
+ "\u0120\u00d0\u00ba\u00d0\u00be\u00d0\u00bb\u00d0\u00b8\u00d1\u0129\u00d0\u00b5",
+ "\u0120reacting",
+ "\u0120Buch",
+ "\u00e0\u00b8\u00b6",
+ "\u0120anth",
+ "\u0120sih",
+ "\u0120hust",
+ "\u0120Screen",
+ "ilant",
+ "aho",
+ "\u0120fragrance",
+ "\u0120elevation",
+ "\u0120Mediter",
+ "\u0120\u00eb\u00bf",
+ "\u0120\u00c3\u00a9qu",
+ "\u0120wraps",
+ "\u0120inert",
+ "\u0120recreate",
+ "\u00d0\u00bb\u00d0\u00b0\u00d1\u0124",
+ "\u0120boleh",
+ "\u0120harassment",
+ "unky",
+ "\u0120glimpse",
+ "regierung",
+ "\u0120futur",
+ "\u0120repository",
+ "\u0120engra",
+ "\u0120trafficking",
+ "assis",
+ "\u0120Trek",
+ "\u0120\u00eb\u00b2\u012e",
+ "\u0120\u00eb\u00a7\u012a\u00eb",
+ "\u0120Kab",
+ "aniu",
+ "give",
+ "\u0120dinosaurs",
+ "\u0120feather",
+ "\u0120attitudes",
+ "\u0120plum",
+ "\u0120RS",
+ "\u0120Anfang",
+ "illery",
+ "\u0120\u00ec\u012c\u00a4",
+ "MY",
+ "\u0120trzeba",
+ "\u0120skies",
+ "\u0120Aj",
+ "urable",
+ "CU",
+ "\u0120Shane",
+ "\u0120departure",
+ "\u0120TON",
+ "ieten",
+ "rats",
+ "\u00e6\u00b0\u0139",
+ "isu",
+ "\u0120bord",
+ "\u0120interestingly",
+ "\u00e7\u013b\u00bb",
+ "oughing",
+ "\u0120rushing",
+ "\u0120volatility",
+ "\u0120pyt",
+ "\u0120formats",
+ "\u0120\u00d0\u00b7\u00d0\u00b0\u00d1\u0124",
+ "\u0120\u00ea\u00bc\u0143",
+ "\u0120whatnot",
+ "\u0120comport",
+ "sw",
+ "orean",
+ "\u0120Relax",
+ "\u0120clan",
+ "\u0120AH",
+ "\u0120pew",
+ "\u0120dictionary",
+ "Take",
+ "shirts",
+ "\u0120Hugh",
+ "\u0120\u00d8\u00b9\u00d9\u0126\u00d9\u012c",
+ "\u0120Pic",
+ "\u0120enrolled",
+ "\u0120jednak",
+ "\u0120offerings",
+ "\u0120coraz",
+ "Life",
+ "\u0120!!!",
+ "\u0120cler",
+ "\u0120Videos",
+ "\u0120Rodrig",
+ "\u0120Ident",
+ "\u0120Pos",
+ "\u0120Stage",
+ "\u0120Race",
+ "\u0120enact",
+ "\u00e3\u0123\u0126\u00e3\u0123\u00be\u00e3\u0123\u0139\u00e3\u0123\u0141",
+ "\u0120Gy",
+ "\u0120Hispan",
+ "\u0120defence",
+ "\u0120Campbell",
+ "matic",
+ "\u0120relev",
+ "\u0120peach",
+ "\u0126\u00b8\u00ec\u013c\u0136",
+ "\u0120paradise",
+ "\u0120ceremon",
+ "\u0120annoyed",
+ "\u00e6\u012e\u0129",
+ "lax",
+ "\u0120exploit",
+ "\u0120clause",
+ "eker",
+ "\u0120Bloom",
+ "nant",
+ "ateurs",
+ "\u0120heights",
+ "Even",
+ "\u00d1\u0123\u00d0\u00be\u00d0\u00bd",
+ "\u0120outrage",
+ "\u0120Vietnamese",
+ "\u00e3\u0123\u00af\u00e3\u0123\u00af",
+ "TR",
+ "\u0120eer",
+ "\u0120cannon",
+ "\u0120Comb",
+ "\u0132\u00eb\u00a7\u012e",
+ "\u00e8\u00bb\u012c",
+ "\u0120\u00ea\u00b2\u0125\u00eb\u0131\u0126",
+ "\u0120accomplishments",
+ "\u0120Analytics",
+ "\u0120shaping",
+ "reiben",
+ "\u0120bachelor",
+ "\u0120fingert",
+ "acked",
+ "\u0120pyramid",
+ "\u0120Stewart",
+ "\u00c3\u00a1st",
+ "\u0120survivor",
+ "\u0120duct",
+ "\u0120dealers",
+ "\u00e6\u00b4\u00bb",
+ "\u00d8\u00b9\u00d9\u0127",
+ "\u00d0\u00bb\u00d0\u00b8\u00d0\u00bd",
+ "\u0120ede",
+ "\u00d7\u0137\u00d7\u00a2",
+ "\u0120\u00d9\u0125\u00d8\u00a7\u00d9\u0128",
+ "\u0120\u00cf\u0126\u00ce\u00b9",
+ "\u0120chooses",
+ "\u0120Own",
+ "\u00d0\u00b3\u00d0\u00be\u00d1\u0124\u00d0\u00be\u00d0\u00b2",
+ "hire",
+ "\u00d0\u00b0\u00d0\u00bb\u00d1\u012e\u00d0\u00bd\u00d1\u012d\u00d0\u00b5",
+ "\u0120\u00d0\u013d\u00d1\u0130",
+ "\u0120\u00d0\u00be\u00d1\u0123\u00d1\u0124\u00d0\u00b0\u00d0\u00b2",
+ "tech",
+ "\u0120droit",
+ "\u0120subjective",
+ "enes",
+ "\u0120divis",
+ "avez",
+ "\u0120maneuver",
+ "\u00e0\u00b9\u0126\u00e0\u00b8\u0136",
+ "adece",
+ "\u0120Ens",
+ "acial",
+ "\u0120Protection",
+ "\u0138\u00b4",
+ "\u0120formally",
+ "\u0120wyd",
+ "ingu\u00c3\u00a9m",
+ "\u0120ziem",
+ "\u0120recruiting",
+ "\u00d7\u013b\u00d7\u013c",
+ "nem",
+ "\u0120forbidden",
+ "\u0120Bapt",
+ "\u00d7\u0132\u00d7\u0142\u00d7\u013b",
+ "\u0120subset",
+ "\u0120Magaz",
+ "nement",
+ "\u0120aquela",
+ "ragon",
+ "\u0120committees",
+ "\u0120\u00c3\u00a9taient",
+ "udi",
+ "\u0120Dawn",
+ "\u0120bore",
+ "\u0120composer",
+ "\u0120wi\u00c4\u013bcej",
+ "anga",
+ "\u0120dislike",
+ "\u0120Days",
+ "\u00e5\u0141\u00ba",
+ "\u0120paral",
+ "\u0120mientras",
+ "\u0120heavens",
+ "\u00e3\u0123\u0134",
+ "heid",
+ "\u0120traders",
+ "once",
+ "\u0120mascara",
+ "\u0120\u00cf\u0122\u00cf\u0123\u00ce\u00bf",
+ "\u0120whisper",
+ "\u0120Musk",
+ "\u00e9\u013d\u0128",
+ "\u0120Familie",
+ "Allah",
+ "\u0120Olivia",
+ "\u0120Pros",
+ "\u0120olika",
+ "ilim",
+ "\u0120r\u00c3\u00a9pond",
+ "\u0120Peters",
+ "\u0120\u00e5\u00be\u012a",
+ "\u0120bites",
+ "\u0120vic",
+ "\u0120NY",
+ "emption",
+ "\u0120450",
+ "\u0120visuals",
+ "\u0120lieu",
+ "\u00c3\u00bccken",
+ "\u0120Steel",
+ "\u0120GP",
+ "wait",
+ "\u0120noticeable",
+ "ucha",
+ "\u0120rehabil",
+ "\u0120rejection",
+ "\u0120\u00d1\u0123\u00d0\u00bb\u00d0\u00b5\u00d0\u00b4\u00d1\u0125\u00d1\u0130\u00d1\u012b",
+ "\u0120slider",
+ "\u0120regarded",
+ "\u0120gravit",
+ "\u0120Reserve",
+ "count",
+ "\u0120breeding",
+ "\u0120longe",
+ "aleb",
+ "\u0120knight",
+ "\u0120\u00d0\u00b2\u00d0\u00be\u00d0\u00b9",
+ "\u0120pr\u00c3\u00a9sent",
+ "\u0124\u013a\u00ec\u013c\u0136",
+ "\u0120Specifically",
+ "\u0120poses",
+ "\u0120veure",
+ "okay",
+ "emas",
+ "\u0120\u00e3\u0123\u00a7\u00e3\u0123\u013b",
+ "\u0120maj\u00c4\u0127",
+ "\u0120webinars",
+ "\u0120cannabis",
+ "\u0120damals",
+ "\u0120Northwest",
+ "\u0120pada",
+ "\u0120crowds",
+ "\u0120futures",
+ "\u0120\u00c3\u00a4n",
+ "\u0120civilians",
+ "\u0120Sachen",
+ "\u00e6\u012f",
+ "\u0120traces",
+ "\u0120\u00eb\u00a8\u00b9\u00ea\u00b3\u0142",
+ "QU",
+ "\u00e9\u00a1\u013a\u00e3\u0123\u0126",
+ "\u0120IF",
+ "an\u00c4\u00b1n",
+ "\u00ec\u0124\u00b4",
+ "\u0120biblical",
+ "\u0120Ved",
+ "\u0120storing",
+ "\u00d1\u0122\u00d0\u00b0\u00d0\u00b2\u00d0\u00bb\u00d1\u0131",
+ "\u00e6\u0129\u012b\u00e8\u00a9\u00b2",
+ "\u0120nast",
+ "\u0120d\u00c3\u00b6",
+ "\u00d1\u0122\u00d0\u00be\u00d0\u00bf",
+ "elia",
+ "\u0120sideways",
+ "\u0120Understand",
+ "\u0120Qur",
+ "\u0120perpend",
+ "\u0120Millionen",
+ "\u0120watermelon",
+ "\u0120Divine",
+ "ultur",
+ "abord",
+ "\u0120successes",
+ "\u0120hombre",
+ "\u0120carp",
+ "\u0120suscept",
+ "ungkin",
+ "\u0120kij",
+ "ulus",
+ "\u00d8\u00a7\u00d8\u00ac",
+ "\u0120notch",
+ "\u0120polynomial",
+ "\u00e5\u00b9\u00b2",
+ "\u00e5\u00a9",
+ "\u0120\u00c3\u00banico",
+ "\u0120telescope",
+ "\u0120politique",
+ "kiem",
+ "\u0120\u00ce\u0143\u00ce\u00bd\u00ce\u00b1",
+ "\u0120aggregate",
+ "\u0120Geoff",
+ "\u0120tril",
+ "\u0120GRA",
+ "\u0120subscriber",
+ "imet",
+ "\u0120\u00d0\u00b4\u00d0\u00be\u00d0\u00bb\u00d0\u00bb\u00d0\u00b0\u00d1\u0122",
+ "oping",
+ "\u0120therapeut",
+ "\u0120Cancer",
+ "\u0120parade",
+ "\u0120irrig",
+ "\u00e2\u013b\u00aa\u00e2\u013b\u00aa",
+ "\u0120clearer",
+ "\u0120bog",
+ "\u0120Maur",
+ "\u00e0\u00b8\u00b2\u00e0\u00b8\u0129",
+ "\u0120Shanghai",
+ "achte",
+ "\u0120Kol",
+ "elujah",
+ "\u0120hav",
+ "\u0120Crime",
+ "sek",
+ "\u0120\u00eb\u00a1\u013e",
+ "ienna",
+ "\u0120Gor",
+ "\u00e8\u013d",
+ "\u0120\u00d0\u00bf\u00d0\u00be\u00d1\u0124\u00d1\u0122",
+ "\u0120\u00d0\u00ba\u00d0\u00b0\u00d0\u00b6\u00d0\u00b5\u00d1\u0124\u00d1\u0123\u00d1\u0131",
+ "\u0120Lift",
+ "\u0120Sort",
+ "\u0120Psal",
+ "\u0120ping",
+ "\u0135\u013f",
+ "phis",
+ "\u0120FUCK",
+ "\u0120Syn",
+ "\u0120bamboo",
+ "\u00ac\u00ec\u013a\u0123",
+ "cuts",
+ "\u0120mmm",
+ "\u0120funktioniert",
+ "\u0120_",
+ "\u00c3\u0143cio",
+ "Stop",
+ "\u0120imaginary",
+ "\u0120notamment",
+ "\u0120Initiative",
+ "\u00e3\u0125\u00a5",
+ "\u0120Kurt",
+ "\u0120loosen",
+ "\u0120buscar",
+ "\u00e7\u0123\u00ab",
+ "\u0120zelf",
+ "\u0120props",
+ "\u00e5\u013d\u012b",
+ "\u0120moeten",
+ "\u0120milli",
+ "\u0120halls",
+ "\u0120Match",
+ "\u0120brackets",
+ "\u0120Cou",
+ "\u00e6\u00a6\u0124",
+ "\u0120\u00d0\u013e\u00d0\u00b0\u00d1\u0122",
+ "ISA",
+ "\u0120cigarette",
+ "\u0120competitions",
+ "\u0120MIN",
+ "\u0120beh\u00c3\u00b6",
+ "voor",
+ "\u0120ust",
+ "\u0120Zi",
+ "\u0120Occ",
+ "ulates",
+ "\u0120balloons",
+ "\u0120pronto",
+ "\u0120Miy",
+ "\u0120File",
+ "\u0120\u00d0\u00ba\u00d0\u00bb\u00d0\u00b0\u00d1\u0123\u00d1\u0123",
+ "\u00d0\u00bd\u00d1\u0125\u00d0\u00bb",
+ "\u0120cereal",
+ "\u0120increment",
+ "\u0120refined",
+ "\u00e5\u0131\u00a6\u00e5\u00a4\u0138",
+ "prising",
+ "\u0120RF",
+ "\u0120respectful",
+ "\u0120loot",
+ "asket",
+ "\u0120deixa",
+ "ingle",
+ "\u0120funciona",
+ "\u0120Revel",
+ "\u0120sober",
+ "\u0120performs",
+ "\u0120Gentle",
+ "\u00e3\u0124\u00a8",
+ "\u0120recipient",
+ "\u0120Hause",
+ "\u0120\u00eb\u0125",
+ "From",
+ "\u0120ministers",
+ "\u0120paradox",
+ "\u00e5\u00b0\u00b1\u00e6\u013a\u00af\u00e8\u00aa\u00aa",
+ "\u0120tasting",
+ "\u0120\u00d7\u0136\u00d7\u0139",
+ "\u0120reuse",
+ "\u0120Lane",
+ "\u0120\u00d1\u0123\u00d0\u00be\u00d0\u00b2\u00d0\u00b5\u00d1\u0122\u00d1\u012a",
+ "\u0120remembers",
+ "\u0120feminist",
+ "\u0120commitments",
+ "\u0120projected",
+ "\u0120gaz",
+ "iyoruz",
+ "\u0120obligations",
+ "Ro",
+ "zar",
+ "\u0120chw",
+ "\u0120JAM",
+ "\u0120b\u00c4\u013bd\u00c4\u0127",
+ "aspberry",
+ "\u0120\u00d0\u00bc\u00d0\u00b5\u00d1\u0123\u00d1\u0124\u00d0\u00be",
+ "\u00eb\u00b2\u0137",
+ "\u0120regulated",
+ "\u0120wicht",
+ "\u0120Trevor",
+ "\u0120secondly",
+ "\u0120Ihre",
+ "elsh",
+ "\u0120reporters",
+ "\u00d1\u0124\u00d0\u00be\u00d1\u0122\u00d0\u00b0",
+ "oyo",
+ "GI",
+ "\u0120interconnect",
+ "\u00e9\u0132\u013a",
+ "OSH",
+ "\u00e6\u0143\u00b2",
+ "\u0120brass",
+ "\u0120ignoring",
+ "\u00e4\u00bb\u012c\u00e6\u0139\u00a5",
+ "infect",
+ "\u0120projekt",
+ "oret",
+ "\u00cf\u0126\u00ce\u00b1\u00ce\u00bd",
+ "\u0120\u00d1\u0124\u00d0\u00b8\u00d0\u00bf",
+ "\u0120mutta",
+ "\u0120unboxing",
+ "\u0126\u00b0",
+ "\u00e5\u00a1\u012c",
+ "\u0120advised",
+ "\u0120Denver",
+ "\u0120severely",
+ "\u0120Mhm",
+ "\u0120flipped",
+ "\u0120pien",
+ "\u0120kommun",
+ "\u0120FRE",
+ "\u0120\u00e0\u00ae\u0129\u00e0\u00ae\u00b0",
+ "ainted",
+ "\u0120knives",
+ "\u0120habl",
+ "\u0120geworden",
+ "arettes",
+ "CS",
+ "\u0120\u00d0\u00bc\u00d0\u00b0\u00d0\u00bb\u00d0\u00b5\u00d0\u00bd\u00d1\u012e",
+ "\u0120galax",
+ "\u0120ninete",
+ "\u00ea\u00b1\u00b0\u00eb\u0124\u013a",
+ "\u0120sis",
+ "\u0120advisory",
+ "\u0120drilling",
+ "\u0120Wouldn",
+ "\u00c3\u00bcnf",
+ "gestellt",
+ "\u0120Helen",
+ "\u0120\u00d7\u0140\u00d7\u0132",
+ "apolis",
+ "\u0120rzeczy",
+ "\u0120terra",
+ "\u0120hep",
+ "\u0120alg\u00c3\u00ban",
+ "ikk",
+ "\u0120astronom",
+ "\u0120Starbucks",
+ "k\u00c4\u0127",
+ "\u0120patrol",
+ "\u0120\u00ec\u00bd\u0136",
+ "\u0120gon",
+ "\u0120\u00e3\u0122\u0132",
+ "\u0120sonst",
+ "\u0120encounters",
+ "\u0120retrou",
+ "\u0120sharks",
+ "\u0120dor",
+ "\u0120Rever",
+ "\u0120evapor",
+ "\u0120reservoir",
+ "\u0120alleged",
+ "uler",
+ "\u0120verm",
+ "\u0120commerce",
+ "\u0120fitted",
+ "gem",
+ "\u0120tactical",
+ "\u0120lith",
+ "\u00e9\u012b\u0126\u00e5\u00a1\u0136",
+ "had",
+ "\u00e8\u00ae\u012c",
+ "\u0120carbohyd",
+ "\u0120lengths",
+ "\u00ce\u00b9\u00ce\u00bf",
+ "\u0120demographic",
+ "Rob",
+ "\u0120Skin",
+ "ccoli",
+ "\u0120simplified",
+ "\u0120readily",
+ "\u0120Cum",
+ "adesh",
+ "\u0120D\u00c3\u00a5",
+ "usst",
+ "igne",
+ "eton",
+ "\u0120menor",
+ "qi",
+ "OOM",
+ "\u00e0\u00b8\u0143\u00e0\u00b8\u013b",
+ "\u0120psychiat",
+ "\u0120eighty",
+ "\u0120\u00d0\u00bc\u00d0\u00b8\u00d0\u00bb\u00d0\u00bb\u00d0\u00b8",
+ "\u0120Tob",
+ "edo",
+ "\u00e7\u00b6\u00b2",
+ "\u0120\u00c4\u0133\u00e1\u00ba\u00bfn",
+ "\u0120circuits",
+ "\u0120LAUGH",
+ "icism",
+ "emor",
+ "\u0120regener",
+ "egree",
+ "\u0120bureauc",
+ "\u0120Alber",
+ "\u00e4\u00b9\u012d\u00e5\u00be\u012e",
+ "\u0120Wor",
+ "\u00e5\u00a4\u00ab",
+ "\u0120resin",
+ "\u0120by\u00c5\u0124y",
+ "\u0120IG",
+ "\u00e0\u00af\u012f,",
+ "\u012078",
+ "\u0120weeds",
+ "\u0120Myth",
+ "93",
+ "\u00e6\u00bf",
+ "\u0120\u00eb\u0124\u013a\u00ec\u013b\u0136",
+ "\u00c3\u00a9v",
+ "\u00e1\u00bd",
+ "\u00c3\u00b6ren",
+ "\u00c3\u00a7ar",
+ "\u0120PAUL",
+ "\u0120disadvant",
+ "\u0120positioning",
+ "\u0120cocktail",
+ "\u0120agrees",
+ "nn",
+ "\u0120Sally",
+ "Ms",
+ "\u0120inherent",
+ "\u0120monetary",
+ "\u0120natur",
+ "\u0120Nh",
+ "\u0120Import",
+ "\u0120leben",
+ "\u0120wi",
+ "ussy",
+ "\u0120obes",
+ "\u0120wandering",
+ "\u0120\u00ec\u012d\u0142\u00eb",
+ "\u00c4\u0127da",
+ "etchup",
+ "\u0120disposal",
+ "\u0120JA",
+ "\u0120Cer",
+ "zilla",
+ "\u0120virgin",
+ "\u0120Slide",
+ "andel",
+ "\u0120righteousness",
+ "\u0120\u00ce\u00a3",
+ "\u0120ideia",
+ "\u00e4\u00bd\u0142\u00e5\u00a5\u00bd",
+ "\u00d0\u00b8\u00d1\u0122\u00d0\u00be\u00d0\u00b2\u00d0\u00b0\u00d1\u0124\u00d1\u012e",
+ "\u00d7\u00a8\u00d7\u0132",
+ "Comment",
+ "\u0120prelim",
+ "\u0120Vale",
+ "\u0120\u00ec\u00a7\u0122\u00eb\u0124\u013e",
+ "\u0120Vanc",
+ "OMAN",
+ "\u0120\u00d0\u00bf\u00d1\u0138\u00d0\u00b4",
+ "\u0120yum",
+ "stre",
+ "cem",
+ "\u0120pocz",
+ "\u0120fragment",
+ "\u0120\u00d1\u0123\u00d0\u00bb\u00d1\u0125\u00d1\u0129\u00d0\u00b0\u00d0\u00b5",
+ "\u0120undergo",
+ "\u0120Hank",
+ "ceks",
+ "\u0120FPS",
+ "\u0120ocur",
+ "\u0120deterior",
+ "\u00e6\u00b3\u00a8",
+ "\u0120empresas",
+ "Paul",
+ "\u0120)))",
+ "\u0120\u00d0\u00b2\u00d1\u0122\u00d0\u00b5\u00d0\u00bc\u00d0\u00b5\u00d0\u00bd\u00d0\u00b8",
+ "\u0120scold",
+ "\u00d7\u013b\u00d7\u00a2",
+ "\u0120suspected",
+ "\u0120accessing",
+ "\u0120substit",
+ "\u0120historians",
+ "\u00e4\u00bb\u00bb",
+ "\u0120\u00d0\u00b4\u00d0\u00b5\u00d0\u00bb\u00d0\u00be",
+ "\u0120socied",
+ "rone",
+ "\u0120reden",
+ "\u0120extends",
+ "epherd",
+ "\u0120balcon",
+ "\u00e4\u00b8\u012f\u00e8\u00b5\u00b7",
+ "\u0120Solo",
+ "\u0120politician",
+ "\u00d0\u00be\u00d0\u00bb\u00d1\u012e\u00d0\u00bd\u00d0\u00be",
+ "\u0120irgendw",
+ "\u0120traumatic",
+ "\u0120rapper",
+ "\u0120ROBERT",
+ "Really",
+ "\u00e6\u0123\u00af",
+ "\u0120lineup",
+ "ASE",
+ "\u0120contractor",
+ "\u0120Corporation",
+ "gor",
+ "\u0120Todo",
+ "\u00d1\u0123\u00d1\u0124\u00d1\u0122\u00d0\u00be\u00d0\u00b9",
+ "FBE",
+ "\u0120newsletter",
+ "\u0120ko\u00c5\u0126",
+ "alties",
+ "\u0120\u00d0\u00bf\u00d1\u0122\u00d0\u00b8\u00d1\u0129",
+ "\u0120Heavy",
+ "\u0120swords",
+ "\u0120manipulation",
+ "\u0120funk",
+ "\u0120v\u00c3\u00a5r",
+ "\u0120Taliban",
+ "\u0120\u00eb\u00b0\u00a5",
+ "\u0120acne",
+ "\u00c3\u00bcr\u00c3\u00bc",
+ "\u0120deswegen",
+ "\u0120Dust",
+ "\u0120silic",
+ "\u0120hooks",
+ "\u0120blij",
+ "\u0120petits",
+ "\u0120filme",
+ "\u0120Bereich",
+ "\u0120Said",
+ "\u0120imposed",
+ "\u0120diary",
+ "\u0120\u00d0\u00b3\u00d0\u00be\u00d1\u0122",
+ "\u0120Gates",
+ "\u0120alta",
+ "\u00e5\u00b8\u012e",
+ "\u0120chcia",
+ "pleasant",
+ "\u0120\u00eb\u00b0\u013f",
+ "\u0120mo\u00c5\u00bcemy",
+ "\u0120Austria",
+ "\u0120broker",
+ "\u0120sucked",
+ "\u00e8\u0122\u0125",
+ "\u0120compartment",
+ "\u0120clone",
+ "\u0120\u00d7\u0136\u00d7\u00a2",
+ "\u0120Danke",
+ "\u0120nochmal",
+ "\u00d0\u00b5\u00d0\u00b7\u00d0\u00b4",
+ "\u0120adrenal",
+ "\u0120kleinen",
+ "\u00e3\u0123\u00be\u00e3\u0123\u0139\u00e3\u0124\u0129\u00e3\u0123\u0128",
+ "\u0120subsequently",
+ "\u0120decentral",
+ "\u0120genetics",
+ "\u0120\u00ea\u00b4\u0133",
+ "\u0120monitors",
+ "\u0120Applic",
+ "\u0120Reporter",
+ "wert",
+ "\u0120wiem",
+ "\u0120Movement",
+ "\u0120interviewing",
+ "\u0120hairs",
+ "\u0120pu\u00c3\u00b2",
+ "\u0120Chelsea",
+ "\u0120coher",
+ "\u0120cot",
+ "\u0120zas",
+ "\u0120patches",
+ "\u0120lah",
+ "\u00d1\u0125\u00d0\u00bd\u00d0\u00ba",
+ "\u0120Reagan",
+ "\u0120Marco",
+ "city",
+ "\u0120defender",
+ "\u0120decoration",
+ "iji",
+ "\u0120litter",
+ "\u00d0\u00a8",
+ "\u0120jego",
+ "REW",
+ "\u0120Pik",
+ "\u0120Hee",
+ "\u0120Iv",
+ "\u0120\u00d0\u00b8\u00d0\u00b4\u00d0\u00b5",
+ "\u0120Theater",
+ "\u0120\u00d1\u0129\u00d0\u00b0\u00d1\u0123\u00d1\u0124\u00d0\u00be",
+ "\u0120sweater",
+ "\u0120highlighting",
+ "\u0120ainsi",
+ "\u0120diplomatic",
+ "\u0120Nevertheless",
+ "\u00e5\u00b3",
+ "ASON",
+ "\u0120p\u00c3\u00bablico",
+ "\u0120ferm",
+ "reated",
+ "cod",
+ "\u0120\u00eb\u00ac\u00bc\u00eb",
+ "\u0120mister",
+ "\u0120Vancouver",
+ "\u0120recognizes",
+ "ecd",
+ "\u0120complications",
+ "encial",
+ "\u00e3\u0123\u0139\u00e3\u0123\u0131",
+ "\u0120\u00ea\u00b0\u0122\u00ec\u00a7\u0122",
+ "\u0120Ultimate",
+ "\u0120vaig",
+ "\u0120Merry",
+ "\u00d7\u0137\u00d7\u0134",
+ "\u0120Marcus",
+ "\u00e7\u00b8\u00bd",
+ "owego",
+ "\u0120mente",
+ "Sm",
+ "\u0120aja",
+ "\u0120Tao",
+ "\u0120judicial",
+ "\u0120entrepreneurship",
+ "\u0120\u00d0\u00bd\u00d0\u00b5\u00d0\u00bc\u00d0\u00bd\u00d0\u00be\u00d0\u00b3\u00d0\u00be",
+ "\u0120pis",
+ "\u0120erg",
+ "\u0120christ",
+ "\u0120Curt",
+ "\u0120\u00d1\u0122\u00d0\u00b0\u00d1\u0123\u00d0\u00bf",
+ "\u00ce\u00bb\u00ce\u00b5",
+ "ensch",
+ "\u00c3\u0143re",
+ "\u0120focal",
+ "\u0120Diamond",
+ "av\u00c3\u0143a",
+ "\u0120hanno",
+ "\u0120Squad",
+ "\u0120associations",
+ "\u0120Creative",
+ "\u0120messenger",
+ "\u0120begging",
+ "\u0120decimal",
+ "\u0120d\u00c4\u00b1\u00c5\u0141",
+ "\u0120metadata",
+ "sels",
+ "\u0120\u00c4\u00b0\u00c5\u0141",
+ "\u00e1\u00bb\u00afa",
+ "\u0120difficile",
+ "d\u00c4\u00b1",
+ "\u0120slaughter",
+ "\u0120Verg",
+ "\u0120\u00d7\u0134\u00d7\u013f",
+ "\u00e7\u00b0\u00a1",
+ "\u00e6\u012e\u012b",
+ "\u0120Tea",
+ "asses",
+ "Ok",
+ "\u0120synthes",
+ "otiation",
+ "\u0120painter",
+ "\u0120elbows",
+ "\u0120architectural",
+ "\u0120\u00d1\u0122\u00d0\u00b0\u00d0\u00b4",
+ "\u0120glor",
+ "image",
+ "ampa",
+ "culiar",
+ "\u0142\u00a8",
+ "\u0120teve",
+ "\u0120Stelle",
+ "\u0120Bam",
+ "\u0120\u00ec\u00b4\u012a",
+ "asis",
+ "ipedia",
+ "\u0120GI",
+ "\u0120Active",
+ "\u00e7\u0126\u00b6\u00e5\u0132\u0130",
+ "azi",
+ "\u00e3\u0124\u012e\u00e3\u0123\u00a6",
+ "\u0120Lucky",
+ "\u00ed\u0137\u00a9",
+ "\u0120\u00d0\u00bf\u00d1\u0122\u00d0\u00b8\u00d1\u0127\u00d0\u00be\u00d0\u00b4",
+ "\u0120runway",
+ "\u0120authentication",
+ "\u0120posible",
+ "\u0120supplements",
+ "\u0120surgical",
+ "Gen",
+ "\u0120feasible",
+ "DO",
+ "\u0120outlook",
+ "\u0120intervals",
+ "\u0120anecd",
+ "\u00c3\u0142ng",
+ "\u0120straps",
+ "\u0120Shu",
+ "udd",
+ "issenschaft",
+ "\u0120porte",
+ "\u0120committing",
+ "\u0120alley",
+ "\u0120covenant",
+ "\u0120Pedro",
+ "lessness",
+ "\u0120Solid",
+ "\u0120Molly",
+ "\u0120\u00d0\u00bd\u00d0\u00b5\u00d0\u00ba\u00d0\u00be\u00d1\u0124\u00d0\u00be\u00d1\u0122",
+ "\u0120cooperate",
+ "\u00e5\u012e\u0139",
+ "ollen",
+ "\u0120tuna",
+ "\u0120kindergarten",
+ "\u0120Siz",
+ "\u0120du\u00c5\u00bco",
+ "\u0120MBA",
+ "\u0120GEORGE",
+ "\u0120Fisher",
+ "\u00e5\u00bf\u013a",
+ "\u0120Caesar",
+ "\u0120\u00d0\u00ba\u00d1\u0122\u00d0\u00b0\u00d1\u0123\u00d0\u00b8\u00d0\u00b2",
+ "\u0120Delhi",
+ "zym",
+ "\u0120explicar",
+ "\u00ea\u00b0\u0122\u00ec\u00a7\u0122",
+ "uns",
+ "grow",
+ "\u0120\u00d0\u00bf\u00d1\u0122\u00d0\u00b8\u00d1\u0123",
+ "\u012086",
+ "\u0120stating",
+ "\u0120massa",
+ "chter",
+ "\u0120\u00ec\u00bb\u00ac\u00eb\u0141\u00ac",
+ "\u0120deputy",
+ "SM",
+ "noc",
+ "\u0120geography",
+ "\u0120Enterprise",
+ "\u0120Cant",
+ "\u00c3\u00b6z",
+ "\u0120unpack",
+ "\u0120\u00ed\u013b\u0136\u00eb",
+ "\u0120searches",
+ "\u0120presidency",
+ "\u0120trivial",
+ "\u0120pige",
+ "oubt",
+ "\u00e3\u0124\u013c",
+ "\u00ec\u00bc\u0122\u00ec\u013f\u00b4",
+ "\u0120budgets",
+ "\u0120ub",
+ "\u0120pne",
+ "\u0120Yale",
+ "\u0120\u00c5\u0141\u00c3\u00b6yle",
+ "regular",
+ "\u0120imperfect",
+ "ARA",
+ "\u0120fam\u00c3\u0143lia",
+ "urm",
+ "\u0120Adventure",
+ "\u00e3\u0125\u012c",
+ "cis",
+ "emark",
+ "\u0120nego",
+ "\u0120inappropriate",
+ "\u0120\u00d0\u00bf\u00d1\u0122\u00d0\u00b8\u00d0\u00b7",
+ "\u0120\u00d1\u0122\u00d0\u00be\u00d0\u00bb",
+ "\u0120dreamed",
+ "Bry",
+ "\u0120shuttle",
+ "\u0120pillars",
+ "\u0120bik",
+ "inum",
+ "\u0120\u00d1\u0125\u00d1\u0123",
+ "\u0120Nebr",
+ "\u0120perpendicular",
+ "\u0120booked",
+ "bery",
+ "\u0120vikt",
+ "bear",
+ "esus",
+ "\u0120\u00d0\u00b2\u00d0\u00be\u00d0\u00b7\u00d0\u00bc\u00d0\u00be\u00d0\u00b6\u00d0\u00bd\u00d0\u00be",
+ "\u00a8\u00b9",
+ "\u0120presumably",
+ "\u0120Memphis",
+ "\u0120ambulance",
+ "\u00d7\u0137\u00d7\u0140\u00d7\u00a8",
+ "\u0120thumbnail",
+ "\u0120modification",
+ "\u00e9\u0129\u0131",
+ "\u0120interpreted",
+ "\u0120promo",
+ "\u0120\u00ce\u00ba\u00ce\u00ac",
+ "\u0120\u00ce\u00b5\u00cf\u0122",
+ "\u0120acoustic",
+ "\u0120DB",
+ "\u00e5\u0135\u0130",
+ "\u0120nonetheless",
+ "oule",
+ "\u0120pequ",
+ "\u0120knob",
+ "\u00e3\u0124\u00a3",
+ "\u0120\u00eb\u0131\u012e\u00ec\u0137\u0126",
+ "\u0120purchases",
+ "\u0120\u00c3\u0129\u00c3\u00bcnk\u00c3\u00bc",
+ "\u0120dividing",
+ "perform",
+ "raction",
+ "healthy",
+ "\u0120Title",
+ "\u0120uk",
+ "\u0120cerca",
+ "\u0120arguably",
+ "\u0120fale",
+ "\u00eb\u00b3\u00b5",
+ "\u0120gamers",
+ "\u0120utilizing",
+ "\u0120offended",
+ "\u0120tava",
+ "al\u00c4\u00b1",
+ "\u0120median",
+ "\u0120infectious",
+ "\u0120Annie",
+ "\u0120smartphones",
+ "\u0120parole",
+ "\u00e5\u0138\u013f",
+ "\u0120Epic",
+ "zza",
+ "\u0120unified",
+ "\u0120\u00ea\u00b7\u00b8\u00eb\u0137\u012e",
+ "\u0120curtain",
+ "\u0120\u00c4\u0125",
+ "\u0120sexually",
+ "\u0120unserem",
+ "\u0120Convention",
+ "\u0120allegedly",
+ "Ya",
+ "\u0120Hoo",
+ "enment",
+ "\u00e6\u0122\u00aa",
+ "\u00ed\u013d\u0126",
+ "\u0120gigantic",
+ "\u0120noting",
+ "\u0120rebo",
+ "\u0120Jama",
+ "\u0120Alz",
+ "\u0120borrowed",
+ "\u00ec\u00b9\u00a8",
+ "\u0120peripher",
+ "\u00d0\u00be\u00d1\u0124\u00d0\u00b0",
+ "\u0120GB",
+ "\u0120Gear",
+ "\u0120economically",
+ "\u0120telefon",
+ "\u0120queremos",
+ "\u0120\u00d0\u00b4\u00d0\u00b0\u00d0\u00bb\u00d1\u012e\u00d1\u012a\u00d0\u00b5",
+ "\u0120ras",
+ "\u0120Teach",
+ "icios",
+ "atos",
+ "\u0120pledge",
+ "bau",
+ "\u0120Himself",
+ "Link",
+ "\u0120espero",
+ "\u0120chromos",
+ "\u0120PER",
+ "\u0120erle",
+ "\u0120podium",
+ "\u00c3\u00a7os",
+ "\u0120nieu",
+ "\u0120fen",
+ "\u0120GOD",
+ "\u0120Chocolate",
+ "werk",
+ "\u0120t\u00e1\u00bb\u00ab",
+ "\u0120suppress",
+ "\u00ce\u00bb\u00ce\u00b7",
+ "\u0120240",
+ "\u0120sit\u00c3\u00a4",
+ "\u0120honesty",
+ "\u0120Bio",
+ "\u0120Bard",
+ "\u0120\u00d0\u00be\u00d0\u00b1\u00d1\u012b\u00d0\u00b5\u00d0\u00bc",
+ "\u0120\u00d0\u00bc\u00d1\u0125\u00d0\u00b7",
+ "\u0120marble",
+ "\u0120\u00d1\u0128\u00d0\u00b5\u00d0\u00bd\u00d1\u0124",
+ "\u0120procure",
+ "\u0120rotor",
+ "bern",
+ "\u0120tuh",
+ "\u0120headset",
+ "atem",
+ "\u0120warranty",
+ "\u00e0\u00ae\u00b4",
+ "\u0120filing",
+ "\u00ce\u00b9\u00ce\u00ac",
+ "\u0120comprendre",
+ "\u0120impulse",
+ "\u0120salv",
+ "written",
+ "\u0120institute",
+ "Kim",
+ "\u0120LGBTQ",
+ "ficiente",
+ "His",
+ "\u0120\u00ce\u00b1\u00cf\u0127\u00cf\u0126\u00cf\u012e",
+ "\u0120teenage",
+ "orus",
+ "\u0120\u00d1\u0122\u00d0\u00b0\u00d0\u00b7\u00d0\u00b1",
+ "See",
+ "\u0120Conserv",
+ "\u00e1\u00bb\u0123n",
+ "fulness",
+ "\u0120strawberries",
+ "\u0120Abu",
+ "\u00d0\u00b8\u00d0\u00be\u00d0\u00bd",
+ "\u0120olla",
+ "NOISE",
+ "\u0120Employ",
+ "\u0120wiped",
+ "urger",
+ "\u0120modifications",
+ "\u0120\u00ed\u0137\u013a\u00ec\u00a7\u0122",
+ "\u0120footsteps",
+ "\u0120honors",
+ "\u0120adul",
+ "\u0120flipping",
+ "\u0120HU",
+ "ZY",
+ "\u0120integrating",
+ "\u00d8\u00a8\u00d8\u00b1",
+ "ulla",
+ "\u0120natuurlijk",
+ "\u0120\u00ed\u0139\u012a",
+ "\u0120Ethereum",
+ "\u00d9\u012c\u00d9\u0126",
+ "wed",
+ "\u0120peaks",
+ "\u0120Kes",
+ "\u0120bloom",
+ "\u0120crashing",
+ "\u0120911",
+ "\u0120\u00d0\u00be\u00d1\u0124\u00d0\u00bb\u00d0\u00b8\u00d1\u0129",
+ "\u0120controllers",
+ "\u0120Dod",
+ "\u0120\u00d0\u00b2\u00d0\u00bc\u00d0\u00b5\u00d1\u0123\u00d1\u0124\u00d0\u00b5",
+ "\u0120sortir",
+ "\u00e5\u00a5\u0129",
+ "\u0120Straight",
+ "\u0120Gracias",
+ "\u0120groove",
+ "\u0120togg",
+ "\u0120\u00ec\u012d\u00b6\u00ec\u013f\u0122",
+ "\u00c3\u00a9ro",
+ "\u0120outward",
+ "\u0120WA",
+ "\u0120Rocky",
+ "\u0120scam",
+ "\u0120hayat",
+ "ignty",
+ "\u00e2\u0126",
+ "plings",
+ "\u0120antibiotics",
+ "\u0120\u00e4\u00b8\u0122",
+ "\u0120nevertheless",
+ "jang",
+ "commerce",
+ "\u0120spoiler",
+ "\u0120glove",
+ "\u0120chatter",
+ "\u0120BY",
+ "~?",
+ "\u0120\u00ed\u013a\u00b8",
+ "\u0120demol",
+ "wechsel",
+ "imir",
+ "\u0120raid",
+ "\u00d0\u00b5\u00d1\u0122\u00d1\u0127",
+ "\u00ec\u0140\u0132\u00ea\u00b8\u00b0",
+ "enf",
+ "\u0120commented",
+ "\u0120optimized",
+ "\u0120convicted",
+ "\u0120bats",
+ "\u0120SB",
+ "\u0120Aur",
+ "\u0120Tong",
+ "\u0120implicit",
+ "\u0120Janet",
+ "\u0120reag",
+ "\u00e3\u0123\u00b2",
+ "\u0120Advanced",
+ "\u0120impose",
+ "\u00d7\u00a9\u00d7\u0136",
+ "\u0120schemes",
+ "ougher",
+ "abolic",
+ "\u0120\u00ea\u00b1\u00b0\u00ec\u00a3\u0142",
+ "\u0120slowing",
+ "\u0120wtedy",
+ "\u0120destructive",
+ "\u0120\u00d0\u00be\u00d0\u00bf\u00d1\u0122\u00d0\u00b5\u00d0\u00b4",
+ "\u0120landmark",
+ "\u0120\u00eb\u0131\u012a",
+ "\u0120Walking",
+ "\u00e1\u00ba\u00b9",
+ "\u0120tijd",
+ "\u0120KN",
+ "\u0120Quant",
+ "\u00ec\u013a\u00a4\u00eb",
+ "\u0120\u00d0\u00ba\u00d1\u0122\u00d1\u0125",
+ "\u0120perder",
+ "\u0120nove",
+ "\u00c3\u00a4nde",
+ "\u0120\u00e3\u0123\u0139",
+ "bia",
+ "\u0120custody",
+ "\u0120biod",
+ "\u00e6\u013f\u00b1\u00e8\u00a5\u00bf",
+ "\u0120directing",
+ "...\u00e2\u0122\u012d",
+ "\u0120reloc",
+ "\u0120demande",
+ "\u00e3\u0124\u0135\u00e3\u0123\u0142",
+ "\u0120o\u00c4\u0141lum",
+ "\u0120\u00d0\u00be\u00d0\u00b4\u00d0\u00bd\u00d0\u00b0",
+ "\u0120Milk",
+ "\u00e5\u0131\u00b7",
+ "\u0120Kra",
+ "\u0120Honda",
+ "\u0120pue",
+ "\u0120elekt",
+ "\u0120beginners",
+ "\u0120spear",
+ "\u00c3\u0143nh",
+ "\u0120Luft",
+ "\u0120nig",
+ "\u0120Schools",
+ "\u0120forums",
+ "\u0120Qin",
+ "ppo",
+ "\u0120zag",
+ "\u0120\u00d0\u00ae",
+ "\u0120toothp",
+ "\u0120Style",
+ "\u00ec\u00b4\u012a",
+ "\u0120punct",
+ "\u0120reps",
+ "\u0120Aly",
+ "\u0120amendments",
+ "\u0120\u00c3\u00b6z",
+ "\u0120digits",
+ "urai",
+ "\u0120chaotic",
+ "\u0120Masters",
+ "eon",
+ "\u0120Cash",
+ "\u0120Cuz",
+ "\u0120bedeutet",
+ "\u0120scanning",
+ "\u0120\u00d0\u00b6\u00d0\u00b4",
+ "\u00d0\u00bd\u00d0\u00b5\u00d1\u0124",
+ "\u0120certainty",
+ "jek",
+ "\u0120dijo",
+ "\u0120Climate",
+ "\u0120rinse",
+ "\u0120krij",
+ "veland",
+ "\u0120soundtrack",
+ "\u0120Safe",
+ "\u0120Nova",
+ "94",
+ "\u0120athe",
+ "\u0120Verb",
+ "oler",
+ "\u00ec\u013f\u00b4\u00ec\u00a3\u0142",
+ "\u0120vin",
+ "\u0120respiratory",
+ "\u0120Study",
+ "\u0120CAM",
+ "\u0120avocado",
+ "\u0120Zhen",
+ "\u0120latency",
+ "\u0120feathers",
+ "\u0120contar",
+ "\u0120\u00d0\u00b2\u00d0\u00b5\u00d1\u012b",
+ "\u0120fark",
+ "\u0120blended",
+ "\u0120exploded",
+ "\u0120XX",
+ "\u0120Benim",
+ "\u0120algu\u00c3\u00a9m",
+ "istoire",
+ "\u0120confidential",
+ "\u0120mast",
+ "\u0120\u00ec\u00bf",
+ "geh",
+ "\u0120disrespect",
+ "\u0120Systems",
+ "\u00c6\u00b0a",
+ "Ed",
+ "\u0120wys",
+ "\u0120exotic",
+ "\u0120glowing",
+ "\u00c3\u00b9ng",
+ "ounge",
+ "\u00e8\u0126",
+ "\u00d0\u00b0\u00d0\u00bd\u00d0\u00b8\u00d0\u00b7",
+ "\u0120palav",
+ "\u0120Sword",
+ "\u0120gim",
+ "\u0120Crow",
+ "\u0120potent",
+ "bish",
+ "\u0120abused",
+ "\u0120Jed",
+ "\u0120gambling",
+ "\u0120Spect",
+ "\u0120investigators",
+ "\u00e6\u013b\u013c",
+ "\u0120ratt",
+ "\u0120dob",
+ "\u0120DES",
+ "hog",
+ "\u0120\u00d0\u00be\u00d1\u0124\u00d0\u00ba\u00d1\u0122\u00d1\u012d",
+ "\u00ed\u012e\u0127",
+ "\u0120\u00d0\u00b4\u00d0\u00b5\u00d0\u00bd\u00d1\u012e\u00d0\u00b3\u00d0\u00b8",
+ "\u0120\u00ed\u013a\u00b9",
+ "\u0120\u00eb\u00a8\u00b8\u00eb\u00a6\u00ac",
+ "\u0120saturation",
+ "\u0120inherited",
+ "\u0120Innovation",
+ "\u00ec\u0139\u012a\u00eb\u012f\u013a",
+ "\u0120tangible",
+ "\u0120depri",
+ "hed",
+ "\u0120\u00d0\u00bf\u00d0\u00be\u00d0\u00bc\u00d0\u00be\u00d0\u00b3",
+ "\u0120sliced",
+ "\u00e0\u00a5\u012f",
+ "\u0120th\u00e1\u00ba\u00bf",
+ "\u00c5\u00a5",
+ "68",
+ "\u0120corona",
+ "\u0120gifted",
+ "\u0120soir",
+ "\u0120humility",
+ "\u0120\u00ec\u013f\u00b4\u00ea\u00b1\u00b8",
+ "\u0120flaws",
+ "\u0120\u00d0\u00bf\u00d1\u0122\u00d0\u00b0\u00d0\u00ba\u00d1\u0124\u00d0\u00b8",
+ "\u0120kald",
+ "wa\u00c5\u00bc",
+ "yw",
+ "\u00e3\u0124\u0135\u00e3\u0123\u00a7\u00e3\u0123\u013b",
+ "irteen",
+ "\u0120crochets",
+ "\u00a6\u00ac\u00ea\u00b0\u0122",
+ "\u0120\u00ec\u0142\u0126\u00ec\u0139\u0132",
+ "\u0120dese",
+ "\u00e6\u00a5\u0143",
+ "\u0120\u00d0\u00bc\u00d0\u00b0\u00d0\u00b3",
+ "\u0120dzia\u00c5\u0124",
+ "\u0120l\u00c3\u00a9g",
+ "changing",
+ "\u0120llev",
+ "\u00c5\u0126sk",
+ "\u00e7\u0136\u00bb",
+ "\u01201984",
+ "orns",
+ "\u0120Welsh",
+ "\u0120pharmaceutical",
+ "\u0120pumping",
+ "\u0120Shaw",
+ "punk",
+ "\u0120vault",
+ "\u0120kinetic",
+ "\u0120hurricane",
+ "\u0120Including",
+ "\u00e1\u00bb\u00a9c",
+ "\u0120Grandpa",
+ "anship",
+ "\u00e9\u00a6\u013b\u00e6\u00b8\u00af",
+ "\u0120\u00d0\u00b2\u00d1\u012d\u00d1\u0127\u00d0\u00be\u00d0\u00b4",
+ "\u00d0\u00bd\u00d0\u00be\u00d0\u00b6",
+ "\u013e\u0142",
+ "utta",
+ "\u0120\u00ea\u00b2\u0123\u00eb\u012d\u012a\u00eb\u012d\u00a4",
+ "\u0120baz",
+ "\u0120\u00d0\u00bf\u00d0\u00be\u00d1\u012a",
+ "\u0120peculiar",
+ "zy\u00c4\u0129",
+ "\u0120Ellie",
+ "\u0120learns",
+ "\u0120Krishna",
+ "\u0120consecut",
+ "\u0120empath",
+ "\u0120Din",
+ "\u0120traded",
+ "\u0120Boris",
+ "uggage",
+ "olla",
+ "\u0120\u00d0\u00bd\u00d0\u00b0\u00d0\u00b7\u00d0\u00b2",
+ "\u0120eternity",
+ "\u0120\u00d0\u00b2\u00d0\u00bf",
+ "\u00c3\u00a8mes",
+ "\u0120grapp",
+ "b\u00c3\u00a9",
+ "\u0120\u00d0\u00bf\u00d1\u0122\u00d0\u00b5\u00d0\u00b4\u00d1\u0123\u00d1\u0124\u00d0\u00b0\u00d0\u00b2",
+ "\u0120FC",
+ "\u012f\u00eb\u012d\u012a\u00eb\u012d\u00a4",
+ "even",
+ "\u0120Nebraska",
+ "ortune",
+ "\u0120karena",
+ "\u0120Agent",
+ "\u0120sting",
+ "\u0120PI",
+ "\u0120municipal",
+ "powered",
+ "\u0120consegue",
+ "\u0120Manchester",
+ "\u0120rainy",
+ "\u0120bli",
+ "\u0120kost",
+ "\u0120halten",
+ "\u0120Ahhh",
+ "insula",
+ "erting",
+ "\u0120\u00d8\u00a7\u00d9\u0126\u00d9\u0123",
+ "\u0120relacion",
+ "\u0120komen",
+ "\u0120dome",
+ "\u0120priests",
+ "\u0120Introdu",
+ "rophe",
+ "shore",
+ "velt",
+ "clipse",
+ "\u0120\u00d1\u0122\u00d1\u0125\u00d1\u0123",
+ "\u00d7\u013b\u00d7\u00a1",
+ "\u0120sabemos",
+ "\u0120Holland",
+ "ogi",
+ "anki",
+ "\u0120Mats",
+ "\u0120smoked",
+ "ullie",
+ "\u0120europe",
+ "\u0120\u00d0\u00b4\u00d0\u00b5\u00d0\u00b9\u00d1\u0123\u00d1\u0124\u00d0\u00b2\u00d0\u00b8\u00d1\u0124\u00d0\u00b5\u00d0\u00bb\u00d1\u012e\u00d0\u00bd\u00d0\u00be",
+ "\u0120bardziej",
+ "\u0120transforming",
+ "\u0120Ez",
+ "opath",
+ "\u0120\u00ec\u0138\u00b8\u00eb\u012d\u012a",
+ "\u0120\u00d1\u0123\u00d1\u0124\u00d0\u00b0\u00d0\u00bd",
+ "\u00e1\u00ba\u00b1ng",
+ "\u00e0\u00b8\u00b1\u00e0\u00b9\u012b",
+ "\u0120Ouch",
+ "\u0120clearance",
+ "ustain",
+ "\u0120solidarity",
+ "\u0120proving",
+ "\u0120\u00d0\u013a\u00d0\u00bd",
+ "\u0120\u00d1\u0123\u00d1\u012c",
+ "\u0120prolong",
+ "\u00d0\u00b0\u00d0\u00b4\u00d0\u00bd\u00d0\u00be",
+ "\u0120sos",
+ "\u0120Deal",
+ "\u0120170",
+ "mons",
+ "\u0120\u00d0\u00b7\u00d0\u00b5\u00d0\u00bc",
+ "\u0120logged",
+ "\u0120lifelong",
+ "\u0120sensory",
+ "\u0120behold",
+ "\u0120FAR",
+ "\u00c3\u00a8tement",
+ "\u0120Federation",
+ "\u0120dodge",
+ "\u0120Shir",
+ "\u0120dragons",
+ "\u0120Arctic",
+ "\u00c4\u0127\u00c5\u00bc",
+ "\u00c5\u012f",
+ "\u00c2\u00ba",
+ "\u0120denke",
+ "\u0120podr\u00c3\u0143a",
+ "cole",
+ "\u00d1\u0125\u00d0\u00bb\u00d1\u012e\u00d1\u0124\u00d0\u00b0\u00d1\u0124",
+ "\u0120systematic",
+ "\u00d0\u00b0\u00d0\u00bc\u00d0\u00b0",
+ "chos",
+ "\u0120clinics",
+ "\u0120BS",
+ "\u0120tales",
+ "usions",
+ "\u0120\u00ed\u012a\u00ac",
+ "\u0120preservation",
+ "\u0120lore",
+ "\u0120Protest",
+ "\u00e1\u00bb\u013d",
+ "\u00e5\u00b8\u0124",
+ "\u0120acknowledged",
+ "\u0120Isaiah",
+ "\u0120\u00eb\u0137\u012e\u00eb\u012c\u0136",
+ "\u0120\u00d7\u013a",
+ "\u0120competitor",
+ "\u0120advancing",
+ "zip",
+ "\u0120tenth",
+ "\u0120Laure",
+ "\u0120hints",
+ "\u0120exercising",
+ "\u0140\u013e\u00eb",
+ "\u0120Intelligence",
+ "uated",
+ "OUT",
+ "oped",
+ "\u0120autonomy",
+ "\u0120branding",
+ "\u0120Mediterranean",
+ "\u00d1\u0138\u00d0\u00ba",
+ "\u0120screwdriver",
+ "\u0120supre",
+ "\u0120stap",
+ "\u0120jurisdiction",
+ "\u0120Settings",
+ "\u0120forefront",
+ "\u0120Female",
+ "comfort",
+ "\u0120multiplication",
+ "\u0120Murray",
+ "\u0120bob",
+ "\u0120Tas",
+ "\u0120tahu",
+ "\u0120onun",
+ "etter",
+ "\u0120prophets",
+ "lag",
+ "\u0120revenues",
+ "\u0120pr\u00c3\u00a1",
+ "\u0120uploading",
+ "\u0120machinery",
+ "ascal",
+ "\u0120Est\u00c3\u00a1",
+ "\u0120Goth",
+ "\u0120Bald",
+ "\u0120Saw",
+ "\u0120stripes",
+ "\u00ec\u0142\u0133",
+ "\u0120powin",
+ "\u00e6\u0139\u00a5\u00e6\u013e\u00ac",
+ "\u0120hostile",
+ "\u0120darum",
+ "\u0120prevented",
+ "\u00d0\u00be\u00d0\u00b6\u00d0\u00b0\u00d0\u00bb\u00d1\u0125\u00d0\u00b9\u00d1\u0123\u00d1\u0124\u00d0\u00b0",
+ "\u0120algunas",
+ "\u0120hopeless",
+ "\u0120znaj",
+ "\u0120readings",
+ "\u0120craving",
+ "tat",
+ "\u0120Pig",
+ "\u0120liar",
+ "\u00e7\u012a\u00b1",
+ "\u0120multiplayer",
+ "\u0120dale",
+ "\u0120Course",
+ "\u00ed\u0123\u00bc",
+ "\u0120Kita",
+ "\u0120customs",
+ "\u0120responds",
+ "endra",
+ "\u00e8\u00a6\u0138",
+ "\u0120metro",
+ "\u00d1\u0123\u00d0\u00be\u00d0\u00bb",
+ "\u0120mitigate",
+ "\u0120oppression",
+ "\u0120\u00e6\u012a\u0133\u00e5\u0122\u0133",
+ "quinho",
+ "\u0120ammo",
+ "\u0120enfer",
+ "\u0120pony",
+ "\u0120ounces",
+ "\u00b0\u0136",
+ "\u0120\u00ec\u012a\u013a\u00ea\u00b0\u0122",
+ "\u0120dicho",
+ "\u0120Deb",
+ "\u0120wonders",
+ "\u0120Roose",
+ "\u0120prizes",
+ "\u0120ALEX",
+ "\u0120thankfully",
+ "\u0120tissues",
+ "\u0120\u00d1\u0122\u00d0\u00b0\u00d0\u00b2\u00d0\u00bd\u00d0\u00be",
+ "\u0120Luna",
+ "intelligible",
+ "\u0120\u00ec\u013b\u00b8",
+ "\u00ea\u00b0\u0133",
+ "\u0120Heat",
+ "\u0120\u00d1\u0123\u00d0\u00b8\u00d0\u00b4",
+ "\u0120Qui",
+ "\u0120ions",
+ "\u0120accommodation",
+ "\u00e4\u00be\u00bf",
+ "\u0120Kart",
+ "ienst",
+ "\u0120tarde",
+ "\u0120soaked",
+ "\u0120Casey",
+ "\u0120\u00ec\u00b4\u013f",
+ "\u0120\u00d1\u0122\u00d1\u0125\u00d0\u00b1",
+ "\u0120differenti",
+ "\u0120leftover",
+ "\u0120exchanges",
+ "second",
+ "\u0120firstly",
+ "\u0120builder",
+ "rien",
+ "\u0120dw",
+ "\u0120bouncing",
+ "?<",
+ "olog\u00c3\u0143a",
+ "wealth",
+ "\u0120meditate",
+ "\u0135\u00a4\u00ec\u013f\u013a",
+ "\u0120Craft",
+ "\u00e8\u00a7\u012b\u00e5\u00be\u0139",
+ "\u00e6\u013b\u00ae",
+ "riv",
+ "\u0120Against",
+ "\u0120ceramic",
+ "esp\u00c3\u00a8re",
+ "\u0120competent",
+ "\u0120Hopkins",
+ "\u0120kilos",
+ "\u0120gravel",
+ "\u0120piston",
+ "\u0120friendships",
+ "\u0120escre",
+ "\u0120voz",
+ "\u0120Gesellschaft",
+ "\u0120unterst\u00c3\u00bct",
+ "\u0120muj",
+ "\u0120warnings",
+ "pos",
+ "\u0120Professional",
+ "wszy",
+ "odle",
+ "bands",
+ "\u0120teamwork",
+ "stellung",
+ "\u0120dx",
+ "\u00e5\u012f\u012c",
+ "\u0120attorneys",
+ "\u0120weitere",
+ "\u00e3\u0127\u012d\u00e3\u0127\u012d\u00e3\u0127\u012d",
+ "\u0120Original",
+ "\u00d7\u013b\u00d7\u0139",
+ "\u0120broadcasting",
+ "\u0120\u00d0\u00bf\u00d0\u00b5\u00d1\u0122\u00d0\u00b2\u00d1\u012d\u00d0\u00b9",
+ "uchi",
+ "\u0120heure",
+ "\u0120grabs",
+ "\u0120WOR",
+ "\u0120Plaid",
+ "Min",
+ "\u0120paz",
+ "\u0120Puis",
+ "umu",
+ "itates",
+ "\u0120coats",
+ "\u0120buen",
+ "\u0120heir",
+ "\u0120pneum",
+ "\u00d7\u00a9\u00d7\u00a8",
+ "enser",
+ "\u0120JUDGE",
+ "\u0120blonde",
+ "\u00e1\u00b9\u013d",
+ "\u0120gak",
+ "\u0120s\u00c4\u00b1k",
+ "\u0120quoted",
+ "\u0120equipo",
+ "\u0120wishing",
+ "\u00c3\u0143cia",
+ "\u0120verbs",
+ "\u00e7\u00b5\u0126",
+ "\u0120Canadians",
+ "\u0120governing",
+ "\u0120Evans",
+ "Euro",
+ "\u0120genres",
+ "\u0120unterschied",
+ "\u0120Becky",
+ "\u00b3\u00bc\u00ea\u00b2\u012e\u00ec\u013c\u0136",
+ "\u0120einge",
+ "\u0120Raise",
+ "oland",
+ "\u0120Strateg",
+ "\u0120eres",
+ "\u0120Veterans",
+ "\u0120breakout",
+ "\u0120sant\u00c3\u00a9",
+ "\u0120adel",
+ "\u0120investigated",
+ "\u0120peur",
+ "\u0120agile",
+ "\u0120railroad",
+ "anska",
+ "\u0120\u00d0\u00b5\u00d0\u00b9",
+ "\u0120expos",
+ "atories",
+ "\u0120Content",
+ "\u0120truths",
+ "\u0120Trail",
+ "\u0120gua",
+ "\u0120pores",
+ "\u0120writings",
+ "\u0120Uhr",
+ "\u0120Thats",
+ "\u0120icing",
+ "OC",
+ "\u0120Production",
+ "\u0120carne",
+ "ISS",
+ "\u0120ningu\u00c3\u00a9m",
+ "non",
+ "\u0120vicious",
+ "\u00d7\u0137\u00d7\u0136",
+ "\u0120reconnect",
+ "\u0120centres",
+ "\u0120Kem",
+ "\u0120crease",
+ "\u0120\u00ec\u013f\u00b4\u00eb\u00af\u00b8",
+ "\u00d0\u00b0\u00d0\u00b9\u00d1\u0124\u00d0\u00b5\u00d1\u0123\u00d1\u012e",
+ "\u0120\u00d0\u00b1\u00d0\u00be\u00d1\u0122",
+ "\u0120Hay\u00c4\u00b1r",
+ "\u0120\u00d1\u0123\u00d1\u0125\u00d0\u00b4",
+ "\u0120\u00c3\u00banica",
+ "owa\u00c5\u0124",
+ "\u0120adher",
+ "hua",
+ "ZZ",
+ "\u0120preciso",
+ "\u0120currents",
+ "\u0120seasoned",
+ "\u0120IoT",
+ "\u0120Bishop",
+ "\u00e8\u00a8\u012a",
+ "sted",
+ "\u0120Bernard",
+ "\u00ec\u00a4\u013a",
+ "\u00e6\u00b2\u00bb",
+ "\u0120Glenn",
+ "\u0120kt\u00c3\u00b3rym",
+ "\u00e0\u00b8\u00b7\u00e0\u00b9\u012a",
+ "\u0120astrolog",
+ "\u0120Kot",
+ "\u00e5\u00a4\u013e",
+ "\u0120parfois",
+ "\u0120forwards",
+ "\u0120Wi\u00c4\u013b",
+ "\u0120\u00ce\u013a",
+ "\u0120nano",
+ "\u00e8\u00bb\u012f",
+ "sub",
+ "\u0120Brill",
+ "\u0120grit",
+ "\u0120cited",
+ "gado",
+ "\u0120melts",
+ "\u0120forc\u00c3\u00a9",
+ "\u00e2\u0138\u012a\u00e2\u0138\u012a",
+ "\u0120bajo",
+ "\u0120discretion",
+ "\u00b0\u00b0",
+ "ativity",
+ "\u0120situated",
+ "\u00e3\u0125\u00ab\u00e3\u0124\u00af",
+ "\u00d1\u012b\u00d0\u00b5\u00d0\u00b5",
+ "\u00e5\u013e\u00b0\u00e6\u0138\u00b9",
+ "\u0120\u00d0\u00bf\u00d1\u0122\u00d0\u00b8\u00d0\u00bd\u00d1\u0128\u00d0\u00b8\u00d0\u00bf",
+ "amaz",
+ "\u0120aquarium",
+ "\u0120dissolve",
+ "\u0120Gods",
+ "Super",
+ "\u0120amid",
+ "zk",
+ "\u0120\u00e3\u0123\u0126",
+ "\u00e9\u0142\u0132",
+ "ampf",
+ "\u0120hela",
+ "'!",
+ "\u0120developmental",
+ "\u0120Dise",
+ "\u0120\u00d1\u0122\u00d0\u00b0\u00d0\u00b1\u00d0\u00be\u00d1\u0124\u00d0\u00b0\u00d0\u00b5\u00d1\u0124",
+ "\u0120snapshot",
+ "\u00e5\u00a5\u00bd\u00e5\u00a5\u00bd",
+ "\u00d5\u00b8",
+ "\u0120Yue",
+ "\u0120Hulk",
+ "\u0120Doom",
+ "\u0120Felix",
+ "\u0120r\u00c3\u00a9f",
+ "Male",
+ "\u00e7\u00b7\u012c",
+ "phants",
+ "ENS",
+ "\u0120Mechan",
+ "\u0120Golf",
+ "\u00e5\u0128\u012f\u00e8\u00a6\u012d",
+ "\u0120generosity",
+ "\u00c3\u00a4tze",
+ "\u0120unlocked",
+ "\u0120\u00e3\u0124\u0134",
+ "\u00ed\u0125\u0123",
+ "ocalypse",
+ "Alright",
+ "\u0120\u00ea\u00b0\u013e\u00eb",
+ "\u0120\u00d7\u0132\u00d7\u0133\u00d7\u013e",
+ "\u0120Keeping",
+ "\u0120collaborating",
+ "chief",
+ "\u0120Fernando",
+ "\u0120chefs",
+ "\u0120\u00ed\u0136\u00bc\u00eb\u00b6\u0122",
+ "\u0120skipped",
+ "\u0120personn",
+ "\u0120axe",
+ "chez",
+ "\u0120extraction",
+ "\u0120AV",
+ "\u0120Gibbs",
+ "\u0120\u00ed\u013e",
+ "\u0120s\u00c4\u00b1",
+ "IAM",
+ "View",
+ "\u0120GRANT",
+ "\u0120\u00eb\u00aa\u00b8",
+ "\u0120verification",
+ "\u0120depicted",
+ "\u0120Moz",
+ "oux",
+ "\u0120tul",
+ "\u0120scanner",
+ "\u0120comedian",
+ "\u0120Volks",
+ "\u0120JEFF",
+ "\u00e8\u00a8\u0124\u00e9\u0138\u00b1",
+ "\u00a7\u0126",
+ "\u0120distraction",
+ "r\u00c3\u00a1",
+ "\u0120INTER",
+ "\u0120sincer",
+ "\u0120\u00d7\u0140\u00d7\u00aa",
+ "\u0120\u00d7\u00a9\u00d7\u0142",
+ "\u0120constructive",
+ "arf",
+ "\u0120\u00eb\u012a\u0126\u00eb",
+ "\u0120eco",
+ "ramos",
+ "\u0120renewed",
+ "inement",
+ "\u0120Ub",
+ "\u0120Pepper",
+ "\u00ec\u00a7\u0122\u00ea\u00b0\u0122",
+ "\u0120Darwin",
+ "\u0120merchand",
+ "\u0120v\u00c3\u00a1rias",
+ "\u00c3\u00a8ce",
+ "NG",
+ "\u0120\u00ec\u013e\u0126\u00ed\u0137\u00b4\u00ec\u0126\u013e",
+ "\u0120\u00d0\u00b0\u00d0\u00ba\u00d1\u0124\u00d0\u00b8\u00d0\u00b2",
+ "\u0120Unters",
+ "\u00d8\u00b9\u00d9\u0126",
+ "\u0120intric",
+ "omma",
+ "ieving",
+ "\u0120Caroline",
+ "\u00e5\u0135\u0123",
+ "\u0120PRES",
+ "\u0120performer",
+ "\u0120autour",
+ "\u00e3\u0123\u00be\u00e3\u0123\u013d\u00e3\u0124\u0135",
+ "\u0120utterly",
+ "\u0120synthesis",
+ "\u0120lesbian",
+ "\u0120retrieve",
+ "\u0120maneira",
+ "\u0120impair",
+ "\u0120mentoring",
+ "\u0120Souls",
+ "\u0120GoPro",
+ "\u00d1\u0122\u00d0\u00b0\u00d1\u0124\u00d1\u012e",
+ "\u0120cose",
+ "\u0120SSD",
+ "IRE",
+ "\u0120upfront",
+ "\u0120Aun",
+ "\u0120gamer",
+ "\u0120litt",
+ "\u0120aggression",
+ "\u0120Likewise",
+ "\u0120Betty",
+ "\u0120Dart",
+ "\u0120DLC",
+ "ishment",
+ "\u00ec\u0140\u00a5\u00ec\u013f\u0126",
+ "\u0120\u00e5\u00af\u00b9",
+ "\u00e7\u00bb\u0131",
+ "cream",
+ "\u0120Babylon",
+ "\u0120nug",
+ "brar",
+ "\u0120ayn\u00c4\u00b1",
+ "amily",
+ "bike",
+ "ahahaha",
+ "loyd",
+ "\u0120mira",
+ "\u0120perme",
+ "\u0120Gaming",
+ "\u0120firmware",
+ "Ma",
+ "\u0120assisted",
+ "atics",
+ "\u0120\u00ec\u0137\u0140\u00ec\u013e\u00bc\u00eb\u00a1\u013e",
+ "\u0120Mental",
+ "niejs",
+ "\u0120Iz",
+ "ow\u00c4\u0127",
+ "\u0120tougher",
+ "\u0120deed",
+ "\u00e8\u012d\u00a6",
+ "\u0120stylish",
+ "\u0120Tools",
+ "\u0120Hamp",
+ "\u0120sunscreen",
+ "\u0120articulate",
+ "iye",
+ "\u00d0\u00b8\u00d1\u0126",
+ "\u0120Spread",
+ "\u0120HAVE",
+ "\u0120swirl",
+ "\u0120sponsoring",
+ "\u00e4\u00bb\u012d",
+ "iovascular",
+ "mesi",
+ "\u0120relaxation",
+ "\u0120\u00d1\u0123\u00d0\u00b2\u00d0\u00be\u00d0\u00b8\u00d1\u0127",
+ "\u0120margins",
+ "\u0120sa\u00c4\u0141",
+ "\u0120Pride",
+ "\u0120\u00cf\u0126\u00ce\u00bf\u00cf\u0127\u00cf\u0124",
+ "\u00d0\u00b8\u00d1\u0128\u00d0\u00b8",
+ "enci",
+ "Does",
+ "\u0120corpse",
+ "\u0120endurance",
+ "\u0120\u00ed\u0140\u013a",
+ "\u00ec\u00b9\u00b4",
+ "\u0120haircut",
+ "\u0120interrupted",
+ "\u0120windy",
+ "\u0120Caleb",
+ "\u00cf\u0123\u00cf\u0129",
+ "\u0120Pourquoi",
+ "\u0120holistic",
+ "uclear",
+ "\u0120Whole",
+ "\u00e5\u00a3\u00ab",
+ "Act",
+ "\u0120gallon",
+ "cade",
+ "\u0120Regional",
+ "roads",
+ "\u0120Schne",
+ "\u00c3\u00a1ng",
+ "\u0120\u00d0\u00b8\u00d0\u00b7\u00d0\u00bc\u00d0\u00b5\u00d0\u00bd",
+ "\u00e3\u0124\u012a\u00e3\u0123\u0143",
+ "\u0120menus",
+ "\u0120splitting",
+ "\u0120priced",
+ "\u0120\u00ce\u0135",
+ "\u0120username",
+ "\u0120\u00d0\u0140\u00d1\u0129",
+ "\u0120compressed",
+ "yin",
+ "\u0120guardian",
+ "\u0120goof",
+ "\u0120checklist",
+ "\u0120interchange",
+ "\u0120expedition",
+ "\u0120extern",
+ "\u0120infrared",
+ "engo",
+ "\u0120denying",
+ "\u0120packets",
+ "onent",
+ "BB",
+ "\u0120Incre",
+ "\u0120sini",
+ "\u00c3\u0141er",
+ "\u00c3\u00a8g",
+ "maal",
+ "generation",
+ "\u0120minorities",
+ "\u0120llevar",
+ "\u0120nomination",
+ "\u0120consid",
+ "\u0120\u00d7\u013e\u00d7\u00a2",
+ "mu\u00c5\u0141",
+ "\u0120Esc",
+ "\u0120numerator",
+ "\u0120kaik",
+ "\u0120kt\u00c3\u00b3rych",
+ "iesen",
+ "\u0120v\u00c3\u00aa",
+ "\u0120USS",
+ "\u0120Private",
+ "\u0120\u00d0\u00be\u00d0\u00b4\u00d0\u00bd\u00d0\u00be",
+ "\u0120al\u00c3\u00a9m",
+ "\u00c3\u0143tulo",
+ "\u0120limb",
+ "\u0120forgiven",
+ "\u0120disclosure",
+ "\u00cf\u0126\u00ce\u00af",
+ "\u0120ning\u00c3\u00ban",
+ "\u0120therapeutic",
+ "\u0120negotiating",
+ "\u0120Nike",
+ "enseful",
+ "\u0120incap",
+ "\u0120flagship",
+ "town",
+ "\u00e2\u012a",
+ "\u0120\u00cf\u0122\u00ce\u00bf\u00ce\u00bb",
+ "\u0120wolves",
+ "\u0120violations",
+ "\u0120Arnold",
+ "\u0120intervene",
+ "\u0120heater",
+ "\u0120recursos",
+ "\u0120maid",
+ "\u00ea\u00b2\u00bc",
+ "\u0120\u00d0\u00b4\u00d0\u00b0\u00d0\u00b2\u00d0\u00b0\u00d0\u00b9\u00d1\u0124\u00d0\u00b5",
+ "\u0120Celebr",
+ "\u0120cape",
+ "\u0120Sty",
+ "ainen",
+ "site",
+ "bij",
+ "\u0120\u00d0\u00bf\u00d0\u00be\u00d0\u00bb\u00d1\u012e\u00d0\u00b7",
+ "\u0120framed",
+ "\u0120publishers",
+ "\u0120\u00d1\u0129\u00d1\u0125\u00d1\u0124\u00d1\u012e",
+ "\u0120temptation",
+ "\u0120certeza",
+ "\u0120exempt",
+ "\u00ec\u012c\u00b9",
+ "selling",
+ "\u0120Task",
+ "hoon",
+ "\u0120Coc",
+ "\u0120Parks",
+ "\u0120repetition",
+ "\u0120\u00d1\u0124\u00d1\u0125\u00d0\u00b4\u00d0\u00b0",
+ "\u0120ensl",
+ "\u0120de\u00c4\u0141i\u00c5\u0141",
+ "\u0120Orlando",
+ "\u0120Mainten",
+ "\u00e6\u0143\u00a2",
+ "ocument",
+ "\u0120HC",
+ "\u0120scooter",
+ "\u0120\u00d0\u00bd\u00d0\u00b0\u00d0\u00bf\u00d0\u00b8\u00d1\u0123",
+ "\u0120tighter",
+ "\u0120tease",
+ "\u0120removes",
+ "\u0120kijken",
+ "\u0120\u00d1\u0123\u00d1\u0125\u00d1\u012b\u00d0\u00b5\u00d1\u0123\u00d1\u0124\u00d0\u00b2",
+ "\u0120th\u00c3\u00a9",
+ "\u0120\u00d0\u00b2\u00d1\u012d\u00d0\u00b3\u00d0\u00bb\u00d1\u0131\u00d0\u00b4",
+ "\u0120relieve",
+ "\u0120mit\u00c3\u00a4",
+ "\u0120stationary",
+ "\u00c3\u00b6ff",
+ "pable",
+ "\u0120arter",
+ "\u0120d\u00c3\u00a9f",
+ "rative",
+ "\u0120conect",
+ "\u0120saddle",
+ "\u0120Diane",
+ "\u0120commemor",
+ "fendim",
+ "S\u00c3\u0143",
+ "\u0120\u00ed\u0123\u00b4\u00eb",
+ "\u0120mange",
+ "atte",
+ "\u0120arrogant",
+ "\u0120robotic",
+ "\u0120gi\u00c3\u0142",
+ "\u00e6\u013a\u00af\u00e7\u013c\u0126",
+ "\u0120neighbourhood",
+ "isson",
+ "\u0120\u00d0\u00b4\u00d0\u00b2\u00d0\u00b8\u00d0\u00b6",
+ "\u0120RI",
+ "\u0120Norman",
+ "brand",
+ "amation",
+ "\u0120razor",
+ "\u0120murders",
+ "\u0120\u00d1\u0124\u00d1\u0125",
+ "\u0120wszystkim",
+ "\u0120utilities",
+ "\u0120microscop",
+ "\u00ea\u00bf",
+ "\u0120daqui",
+ "ollar",
+ "\u0120\u00d0\u0136\u00d0\u00b0\u00d0\u00b2\u00d0\u00b0\u00d0\u00b9\u00d1\u0124\u00d0\u00b5",
+ "\u0120ann\u00c3\u00a9e",
+ "\u0120kilometres",
+ "\u0120homosexual",
+ "\u0120architects",
+ "\u00e3\u0123\u00a1\u00e3\u0123\u00af",
+ "\u0120niye",
+ "LER",
+ "\u0120microphones",
+ "\u0120Stunden",
+ "\u0120consecutive",
+ "ienda",
+ "v\u00c3\u00a4nd",
+ "DER",
+ "\u0120lifts",
+ "\u0120Meat",
+ "\u0120savez",
+ "\u00ed\u0138\u012a\u00eb\u012f\u013a",
+ "Men",
+ "\u0120dismant",
+ "\u00ea\u00b1\u00b0\u00eb\u00a5\u00bc",
+ "\u0120insulation",
+ "\u0120scall",
+ "\u0120spooky",
+ "\u0120parc",
+ "\u0120ballet",
+ "\u0120WhatsApp",
+ "\u0120franc",
+ "\u0120deliberate",
+ "\u0120\u00ed\u0127\u012e",
+ "\u0120mars",
+ "\u0120Zur",
+ "Pr",
+ "disciplinary",
+ "\u0120obsession",
+ "\u00d0\u00bc\u00d0\u00b5",
+ "\u0120marching",
+ "\u0120Emergency",
+ "iguous",
+ "\u0120szy",
+ "\u0120Lands",
+ "\u0120boarding",
+ "\u0120\u00d0\u00bf\u00d0\u00be\u00d1\u0129\u00d1\u0124\u00d0\u00b8",
+ "\u0120envy",
+ "\u0120compassionate",
+ "\u0120merci",
+ "\u0120desirable",
+ "dale",
+ "\u0120can\u00c4\u00b1m",
+ "\u0120Antar",
+ "temps",
+ "\u0120configured",
+ "\u0120Compared",
+ "neh",
+ "icating",
+ "\u0120nickel",
+ "\u00d9\u012a\u00d9\u0124",
+ "\u00d9\u0125\u00d9\u012a\u00d9\u0128",
+ "opes",
+ "\u0120formulas",
+ "\u0120\u00d0\u0137\u00d1\u0123\u00d1\u0124\u00d1\u012e",
+ "\u0120pobl",
+ "\u0120PJ",
+ "\u0120Lud",
+ "\u00e4\u00bb\u012c\u00e5\u013d\u0140",
+ "\u0120Brid",
+ "\u0120Hog",
+ "\u0120Bris",
+ "Jen",
+ "\u0120shading",
+ "\u0120Yas",
+ "\u0120disturbed",
+ "\u0120recommending",
+ "\u0120c\u00c3\u00a9",
+ "\u0120HOW",
+ "\u00ec\u0139\u012a\u00ec\u0138\u00b4",
+ "\u0120reversed",
+ "\u0120Interestingly",
+ "ioxid",
+ "\u00e5\u0127\u0143",
+ "\u0120\u00ec\u013a\u00a4\u00ec\u00bc\u0122\u00ec\u013f\u00b4",
+ "\u00e1\u00ba\u00bfu",
+ "xx",
+ "\u0120ouais",
+ "\u0120YouTubers",
+ "\u0120Rosa",
+ "\u0120Haupt",
+ "jadi",
+ "\u0120vlogs",
+ "\u0120cultura",
+ "\u0120Leadership",
+ "\u0120Hep",
+ "\u0120illum",
+ "\u00b4\u00eb\u0131\u013b",
+ "\u0120customized",
+ "\u0120marca",
+ "\u0120quatro",
+ "\u0120\u00d0\u00bd\u00d0\u00b0\u00d0\u00b3",
+ "\u0120SpaceX",
+ "\u0120Eigen",
+ "asting",
+ "\u0120oldu\u00c4\u0141u",
+ "\u0120forts",
+ "\u00e3\u0123\u012b",
+ "riment",
+ "iencia",
+ "\u0120tenir",
+ "roffen",
+ "\u01201979",
+ "\u0120cie",
+ "\u0120\u00eb\u0132\u013a\u00ea\u00b3\u0142",
+ "\u0120escri",
+ "\u00cf\u012e\u00cf\u0124",
+ "\u00ed\u0131\u00ac",
+ "uzzy",
+ "Cong",
+ "\u00ec\u013f\u00b8\u00ec\u013f\u00b4",
+ "Great",
+ "sil",
+ "\u00c3\u00a9ch",
+ "\u00e3\u0123\u00a8\u00e3\u0123\u012d",
+ "\u0120multic",
+ "\u0120Disk",
+ "\u00b2\u0137",
+ "\u0120fazla",
+ "\u0120levant",
+ "\u0120abajo",
+ "urry",
+ "stru",
+ "\u0120\u00eb\u00a8\u00b9\u00eb\u012c\u0136",
+ "\u0120accessory",
+ "\u0120\u00d0\u00b4\u00d0\u00b2\u00d0\u00b8\u00d0\u00b3",
+ "\u0120Rid",
+ "2019",
+ "\u0120downstream",
+ "\u00e6\u0137\u00b8",
+ "\u0120kaz",
+ "utan",
+ "\u0120charcoal",
+ "\u0120afect",
+ "wu",
+ "\u0120contexts",
+ "\u0120feared",
+ "\u0120\u00ec\u0126\u00a4",
+ "\u0120histories",
+ "\u0120fas",
+ "ensible",
+ "\u0120cocoa",
+ "illar",
+ "geons",
+ "\u0120spirituality",
+ "\u0120Pew",
+ "\u0120pharmacy",
+ "\u0120passions",
+ "\u0120bos",
+ "\u0120all\u00c3\u00a1",
+ "\u0120thriving",
+ "\u0120React",
+ "\u0120occupy",
+ "\u0120withdrawal",
+ "\u0120allowance",
+ "\u0120Fraktion",
+ "\u0120buddies",
+ "\u0120idle",
+ "\u0120dissolved",
+ "\u0120prevalent",
+ "\u0120militar",
+ "\u0120sensing",
+ "\u0120pojaw",
+ "\u0120ancora",
+ "\u0120abundant",
+ "\u0120hairst",
+ "\u00e3\u0123\u0124\u00e3\u0124\u012e",
+ "\u0120twee",
+ "\u0120n\u00c3\u00a4chste",
+ "\u0120M\u00c3\u00b6glichkeit",
+ "\u0120hoo",
+ "ufficient",
+ "\u0120fantast",
+ "\u0120edible",
+ "\u0120\u00eb\u0138\u00a8\u00ec\u0138\u00b4\u00ec",
+ "\u00ec\u013d\u0125",
+ "\u0120vein",
+ "ucci",
+ "\u0120devotion",
+ "\u0120concealer",
+ "income",
+ "\u0120recycled",
+ "\u0120\u00ec\u012c\u00a4\u00ed\u0125\u0122",
+ "\u0120pontos",
+ "\u0120dessus",
+ "\u0120v\u00c3\u00a9rit",
+ "\u0120reflections",
+ "\u0120AA",
+ "\u0120takeaway",
+ "bare",
+ "\u0120Contact",
+ "eil",
+ "\u0120Hear",
+ "\u0120mirac",
+ "\u0120Gerilim",
+ "\u0120\u00d1\u0123\u00d0\u00b0\u00d0\u00bc\u00d1\u012d\u00d0\u00b9",
+ "\u0120vivo",
+ "\u0120kilograms",
+ "\u0120Crim",
+ "\u00c3\u00bbt",
+ "78",
+ "\u0120sincerely",
+ "raz",
+ "\u0120\u00eb\u00b3\u00b5",
+ "\u0120arriv",
+ "\u0120conception",
+ "\u0120Persian",
+ "\u0120sj\u00c3\u00a4l",
+ "\u0120starring",
+ "\u0120\u00ec\u0137\u0126\u00eb\u00ac\u00b4",
+ "\u0120Forever",
+ "\u00d0\u00b5\u00d1\u0123\u00d1\u0124\u00d1\u012e",
+ "\u0120veil",
+ "\u0120subtit",
+ "odka",
+ "\u0120\u00d0\u00be\u00d1\u0124\u00d0\u00bd\u00d0\u00be\u00d1\u012a",
+ "\u0120cooks",
+ "\u00d0\u00b5\u00d0\u00bd\u00d1\u0131",
+ "Kay",
+ "\u0120ni\u00c3\u00b1os",
+ "\u0120Phone",
+ "\u0120stitching",
+ "\u0120fingerprint",
+ "\u00e9\u00a2\u013a",
+ "\u00ce\u00bb\u00ce\u00ac",
+ "\u0120dedicate",
+ "\u0120Lob",
+ "\u0120blacks",
+ "\u0120Ble",
+ "bout",
+ "\u0120\u00c4\u0133ang",
+ "\u0120eks",
+ "\u0120squash",
+ "\u0120K\u00c3\u00bc",
+ "odi",
+ "\u0120n\u00c6\u00b0\u00e1\u00bb\u013dc",
+ "\u0120voyage",
+ "\u0120playful",
+ "\u0120\u00d8\u00a5\u00d9\u0126\u00d9\u012b",
+ "anic",
+ "\u0120condemn",
+ "\u0120B\u00c3\u00b6yle",
+ "\u0120Polize",
+ "\u00e3\u0124\u00bf\u00e3\u0125\u00bc",
+ "\u0120ayuda",
+ "\u0120pam",
+ "\u00e0\u00b9\u0126\u00e0\u00b8\u013d",
+ "\u0120Kathy",
+ "\u00d0\u00b5\u00d0\u00b4\u00d0\u00b8\u00d0\u00bd",
+ "\u00d0\u00bd\u00d0\u00be\u00d0\u00b2\u00d0\u00b0",
+ "\u0120brig",
+ "eger",
+ "\u0120eagle",
+ "\u0120visions",
+ "\u0120\u00ed\u0137\u0143\u00ec\u0125\u0123",
+ "\u0120shitty",
+ "\u0120hott",
+ "\u0120Britt",
+ "utors",
+ "ENTE",
+ "\u00e6\u013d\u00b2",
+ "\u0120phon",
+ "\u0120Bing",
+ "\u0120\u00d0\u00bf\u00d0\u00be\u00d0\u00b4\u00d0\u00b4\u00d0\u00b5\u00d1\u0122\u00d0\u00b6",
+ "spring",
+ "\u00e6\u0138\u00af",
+ "etten",
+ "\u0120pilgr",
+ "\u0120ediyor",
+ "\u00d0\u00b5\u00d0\u00bd\u00d1\u0124\u00d1\u012d",
+ "aggio",
+ "\u0120jul",
+ "\u0120comprend",
+ "teil",
+ "\u0120\u00d8\u00b2",
+ "\u0120performers",
+ "\u0120infamous",
+ "\u0120MK",
+ "\u00e7\u00aa",
+ "\u00e6\u00b3\u0123",
+ "otle",
+ "eff",
+ "\u0120Hash",
+ "\u0120coward",
+ "\u0120BRA",
+ "\u0120DD",
+ "\u0120comida",
+ "\u0120plata",
+ "\u0120flap",
+ "\u0120Mehr",
+ "ribution",
+ "\u0120Yemen",
+ "\u0120mysteries",
+ "\u0120\u00c4\u00b0yi",
+ "\u0120stell",
+ "\u0120eyeliner",
+ "\u0120deles",
+ "\u0120nailed",
+ "\u0120illnesses",
+ "\u0120stacks",
+ "\u0120trabajar",
+ "flower",
+ "ciu",
+ "\u0120crude",
+ "\u0120substantially",
+ "\u0120homem",
+ "\u0120nephew",
+ "\u0120stamps",
+ "\u0120carbs",
+ "\u00d1\u012e\u00d1\u0124\u00d0\u00b5",
+ "mooth",
+ "\u0120tunnels",
+ "acie",
+ "\u00e6\u00b3\u00a2",
+ "\u0120Se\u00c3\u00b1",
+ "\u0120Hera",
+ "\u0120\u00ec\u0137\u0126\u00eb\u012d\u012a\u00ec\u0139\u0132\u00ec\u013c\u0136",
+ "\u0120Wyoming",
+ "\u0120HDMI",
+ "\u0120Lis",
+ "uci\u00c3\u00b3n",
+ "\u0120steer",
+ "\u00d0\u00be\u00d1\u0130",
+ "\u00d0\u00b8\u00d1\u0124\u00d0\u00b0",
+ "NT",
+ "\u0120\u00ec\u0138\u00bc\u00ea\u00b5\u00b4",
+ "\u0120palms",
+ "\u0120neon",
+ "\u00d0\u00be\u00d0\u00b2\u00d0\u00b0\u00d0\u00bd\u00d0\u00b8\u00d1\u0131",
+ "\u0120filtering",
+ "\u0120jouer",
+ "\u0120H\u00c3\u00b6",
+ "\u0120\u00d0\u00bd\u00d0\u00b5\u00d1\u0123",
+ "\u00ea\u00b2\u0142\u00ec\u0138\u00b4\u00ec\u013c\u0136",
+ "\u012081",
+ "\u0120storyline",
+ "\u0120przep",
+ "\u0120thanking",
+ "\u0120Boeing",
+ "\u0120softly",
+ "jem",
+ "\u00d0\u00b0\u00d0\u00bb\u00d1\u012e\u00d0\u00bd\u00d1\u012d\u00d1\u0127",
+ "\u0120flashlight",
+ "\u0120\u00d0\u00bf\u00d1\u0125",
+ "\u0120WOMAN",
+ "\u00e1\u00ba\u00afc",
+ "\u00c3\u0143ch",
+ "\u0120luxurious",
+ "\u0120w\u00c3\u00bcn",
+ "\u0120impactful",
+ "\u0120conson",
+ "reu",
+ "irring",
+ "ifter",
+ "\u0120constituents",
+ "\u00e8\u0132\u00bd",
+ "\u012094",
+ "\u0120Tou",
+ "gom",
+ "\u0120\u00ec\u0125\u013f\u00ea\u00b0\u0123\u00ec\u013f\u0126",
+ "\u0120stereotypes",
+ "\u0120mo\u00c5\u00bcli",
+ "\u00e5\u012a\u0128\u00e4\u00ba\u00ab",
+ "\u0124\u00a8",
+ "\u0120pencils",
+ "\u0120\u00d1\u0123\u00d0\u00bb\u00d0\u00be\u00d0\u00b6",
+ "\u0120ihrem",
+ "\u0120Besch",
+ "\u0120Koh",
+ "\u0120Entscheid",
+ "\u0120lek",
+ "\u0120f\u00c3\u00b6rs",
+ "\u0120totalmente",
+ "\u0120lively",
+ "\u0120entropy",
+ "\u0120discern",
+ "\u0120\u00d0\u0139\u00d0\u00bd\u00d0\u00b0",
+ "\u0120dov",
+ "\u0120mythology",
+ "\u00e8\u00a8\u013a\u00e5\u00be\u0139",
+ "apanese",
+ "\u0120approximate",
+ "\u00d0\u00b0\u00d1\u0124\u00d0\u00b8\u00d0\u00b2",
+ "ifiable",
+ "\u0120Seo",
+ "\u00e5\u0122\u0134",
+ "\u00b4\u00ec\u012d\u00ac\u00ed\u0140\u012a",
+ "\u0120\u00ec\u013a\u00b7",
+ "\u0120temporal",
+ "\u0120iT",
+ "\u0120estat",
+ "\u00d0\u00ba\u00d0\u00b8\u00d0\u00bc",
+ "\u0120sprink",
+ "\u0120grund",
+ "\u0120infantry",
+ "\u0120schaffen",
+ "\u00e7\u00b4\u0126",
+ "\u0120ank",
+ "riages",
+ "\u0120Yeon",
+ "\u0120Moroc",
+ "\u0120invasive",
+ "\u0123\u0136",
+ "\u0120parenting",
+ "\u0120Ris",
+ "ibile",
+ "\u0120mods",
+ "\u00e5\u00bd\u00a2",
+ "\u0120\u00d0\u00bf\u00d1\u0122\u00d0\u00be\u00d0\u00b2\u00d0\u00b5\u00d1\u0122",
+ "\u0120Thing",
+ "\u0120Wherever",
+ "\u0120acknowledging",
+ "\u0120pawn",
+ "ummer",
+ "orb",
+ "69",
+ "\u0120retrouve",
+ "\u0120relies",
+ "\u0120Highway",
+ "\u0120awe",
+ "\u00e3\u0123\u00a7\u00e3\u0123\u013b\u00e3\u0123\u012d",
+ "itaire",
+ "\u0120applicant",
+ "\u0120aisle",
+ "worm",
+ "\u0120payload",
+ "\u0120carre",
+ "\u0120Bach",
+ "\u00e6\u0142\u00bc",
+ "\u0120\u00ec\u00b9\u013e\u00ea\u00b5\u00ac\u00eb",
+ "\u00d0\u00bd\u00d0\u00b8\u00d0\u00b5",
+ "\u0120it\u00c3\u0143s",
+ "onnaise",
+ "sol",
+ "\u00e8\u0131\u00af",
+ "algia",
+ "\u0120rocking",
+ "\u0120besten",
+ "rites",
+ "^^",
+ "\u00d0\u00b8\u00d0\u00bd\u00d0\u00be\u00d0\u00b9",
+ "\u0120baixo",
+ "\u0120\u00ea\u00b8\u00b0\u00ec\u0138\u00b5",
+ "\u00d0\u00be\u00d1\u0124\u00d1\u0122\u00d0\u00b8",
+ "sim",
+ "\u0120incarn",
+ "\u00eb\u012d\u00a4\u00ec\u013f\u012e",
+ "\u0120lick",
+ "sided",
+ "\u012071",
+ "forder",
+ "\u0120resonance",
+ "\u0120tegen",
+ "\u0120metaph",
+ "owser",
+ "\u0120\u00d7\u0132\u00d7\u0142\u00d7\u0139\u00d7\u0142\u00d7\u0137",
+ "?\u00e3\u0122\u012f",
+ "\u0120spielen",
+ "\u0120volley",
+ "\u0136\u00ec\u013f\u00b4\u00ed\u0123\u00ac\u00ec\u0139\u0127",
+ "looked",
+ "\u0120sentenced",
+ "\u0120multiplying",
+ "\u0120ideals",
+ "\u0120wahrscheinlich",
+ "\u0120deposits",
+ "bilir",
+ "\u0120effet",
+ "illon",
+ "\u012a\u00eb\u00a7\u012e",
+ "\u0120testimon",
+ "\u0120zawsze",
+ "\u0120\u00d0\u00bf\u00d1\u0122\u00d0\u00be\u00d1\u0128\u00d0\u00b5\u00d1\u0123\u00d1\u0123",
+ "\u0120Lav",
+ "\u00e4\u00b8\u012f\u00e9\u012e\u00af",
+ "\u0120travailler",
+ "\u0120laisse",
+ "\u0120Mountains",
+ "\u0120\u00d1\u0122\u00d0\u00be\u00d0\u00b1",
+ "\u0120examined",
+ "itus",
+ "Was",
+ "\u00d0\u00bb\u00d1\u012d",
+ "\u0120attributed",
+ "\u0120\u00ec\u012c\u00b9",
+ "\u0120Baron",
+ "\u0120gep",
+ "\u0120attent",
+ "\u0120Collection",
+ "\u0120theat",
+ "\u0120Cai",
+ "\u0120wells",
+ "\u0120humano",
+ "\u00e7\u0139\u0127",
+ "\u0120Hast",
+ "\u0120\u00d1\u0127\u00d0\u00be\u00d1\u0124\u00d1\u0131",
+ "czas",
+ "\u0120permits",
+ "\u0120legg",
+ "\u0120epo",
+ "\u0120Fen",
+ "\u0120thi",
+ "\u0120Foi",
+ "\u0120\u00c3\u00a9lect",
+ "\u012083",
+ "\u0120overth",
+ "\u0120\u00e8\u00ac\u013f\u00e8\u00ac\u013f",
+ "\u0120tenant",
+ "\u00e8\u00b2\u00b7",
+ "Next",
+ "\u0120praised",
+ "security",
+ "\u0120Impact",
+ "\u00e4\u00b8\u00ba\u00e4\u00bb\u0122\u00e4\u00b9\u012a",
+ "\u0120vouch",
+ "\u0120neg\u00c3\u00b3",
+ "\u0120unve",
+ "\u0120criticize",
+ "\u0120Kenya",
+ "\u0120tactic",
+ "\u0120logr",
+ "\u0120pois",
+ "\u0120papa",
+ "speaks",
+ "\u00f0\u0141\u0133",
+ "ispers",
+ "\u0120surplus",
+ "\u0120colder",
+ "\u00e5\u012f\u0139",
+ "\u00e5\u0132\u00ac",
+ "plets",
+ "\u0120Vienna",
+ "\u0120Lead",
+ "\u0120aerial",
+ "\u0120Tah",
+ "\u00d0\u00b5\u00d0\u00bd\u00d1\u0124\u00d0\u00be\u00d0\u00b2",
+ "\u0120Greeks",
+ "Cam",
+ "\u0120m\u00c3\u00a1xim",
+ "\u0120kuin",
+ "chio",
+ "\u0120demonstrates",
+ "anos",
+ "\u0120Cert",
+ "\u0120\u00d1\u012f\u00d0\u00bd",
+ "\u0120blogs",
+ "\u0120\u00ec\u0126\u013e\u00ec\u013c\u00b8",
+ "\u0120beams",
+ "\u00d0\u00b8\u00d0\u00ba\u00d0\u00be\u00d0\u00b2",
+ "\u0120prompted",
+ "\u0120frightening",
+ "\u0120Porsche",
+ "\u00e3\u0123\u012a\u00e3\u0123\u00a6",
+ "lar\u00c4\u00b1n\u00c4\u00b1",
+ "\u0120chilling",
+ "isphere",
+ "\u0120flashing",
+ "\u0120Kard",
+ "bread",
+ "\u0120exh",
+ "\u0120tycker",
+ "\u0120ecological",
+ "\u0120Mae",
+ "\u0120\u00d7\u0140\u00d7\u0132\u00d7\u0137\u00d7\u0135",
+ "\u0120\u00eb\u0124\u013a\u00eb\u0131\u0126",
+ "\u00d0\u00bb\u00d0\u00be\u00d0\u00bd",
+ "yss",
+ "\u0120pergunt",
+ "\u0120prix",
+ "izzard",
+ "\u0120cancers",
+ "\u012091",
+ "susp",
+ "\u0120Item",
+ "\u00c5\u0141a",
+ "\u0120pest",
+ "\u0120tak\u00c4\u0127",
+ "\u0120lymph",
+ "\u0120Patri",
+ "fill",
+ "\u0120reconna",
+ "\u0120optimism",
+ "\u0120mimic",
+ "\u0120\u00ec\u00b2\u013e",
+ "\u0120Madame",
+ "ocy",
+ "lining",
+ "\u00e5\u0133\u012c\u00e8\u00a8\u00b4",
+ "erme",
+ "\u0120folders",
+ "\u0120cz\u00c5\u0124",
+ "uchar",
+ "\u0120curso",
+ "\u0120breach",
+ "\u00d0\u00bd\u00d0\u00b8\u00d1\u0124\u00d1\u012e",
+ "\u0120pami\u00c4\u013b",
+ "\u0120elig",
+ "\u0120autop",
+ "Flow",
+ "\u0120programmed",
+ "\u0120Process",
+ "\u0120figur",
+ "\u0120SF",
+ "\u0120Eles",
+ "\u0120programmes",
+ "\u0120dizzy",
+ "\u00ec\u012d\u013e\u00ea\u00b0\u0126",
+ "\u0120\u00d0\u00bb\u00d0\u00b8\u00d0\u00b1\u00d0\u00be",
+ "\u0120sniff",
+ "\u0120Sebastian",
+ "\u0120Hye",
+ "\u01204000",
+ "\u0120permite",
+ "\u00e6\u00a2\u013f",
+ "\u0120\u00d0\u00b7\u00d0\u00b0\u00d1\u012b",
+ "\u0120guit",
+ "\u0120Dais",
+ "\u0120accordance",
+ "\u0120modular",
+ "ogeneous",
+ "\u00e6\u012d\u012f",
+ "\u0120pouquinho",
+ "\u0120artillery",
+ "\u0120lubric",
+ "\u0120volcan",
+ "\u0120NH",
+ "\u00f0\u0141\u00a4",
+ "\u0120dean",
+ "Rh",
+ "\u0120ministre",
+ "\u00e5\u013f\u0132",
+ "\u0120Inv",
+ "\u0120Bulgar",
+ "\u0120Daten",
+ "\u00e8\u0130",
+ "Im",
+ "\u0120originated",
+ "\u0120Nixon",
+ "integr",
+ "\u0120lacks",
+ "\u0120Nacht",
+ "\u00ec\u0138\u00b4\u00eb\u0124\u013a",
+ "camera",
+ "\u0120radish",
+ "kiye",
+ "\u0120anges",
+ "\u0120pr\u00c3\u00a9f",
+ "juk",
+ "\u0120Bee",
+ "\u0120BU",
+ "\u0120\u00d0\u00b2\u00d0\u00be\u00d1\u0123\u00d0\u00bf",
+ "\u0120BT",
+ "\u00c3\u00aames",
+ "\u0120St\u00c3\u00bcck",
+ "\u0120Ink",
+ "\u00e6\u012a\u0138\u00e8\u0122\u0127",
+ "\u0120Sergeant",
+ "\u0120Multip",
+ "\u0120hi\u00c3\u00a7bir",
+ "\u0120\u00d0\u00a1\u00d0\u00b0\u00d0\u00bc",
+ "\u0120D\u00c3\u00a9",
+ "olph",
+ "\u00ec\u0138\u00b8",
+ "\u0120impat",
+ "\u0120\u00ec\u0137\u012c\u00ea\u00b3\u0142",
+ "\u0120\u00d1\u0124\u00d0\u00b0\u00d0\u00ba\u00d0\u00be\u00d0\u00b3\u00d0\u00be",
+ "\u0120\u00d0\u00bd\u00d0\u00b0\u00d0\u00b2\u00d0\u00b5\u00d1\u0122\u00d0\u00bd\u00d0\u00be\u00d0\u00b5",
+ "\u0120unpredictable",
+ "\u0120mend",
+ "\u0120\u00ec\u0139\u0128\u00ec\u0138\u00b4\u00ec\u013c\u0136",
+ "\u0120jakie\u00c5\u013d",
+ "\u0120anni",
+ "\u0120donn\u00c3\u00a9",
+ "\u0120Kirsty",
+ "\u0120rectangular",
+ "\u0120empezar",
+ "\u0120Exchange",
+ "\u00ea\u00b0\u0136",
+ "\u0120\u00c3\u00a9conom",
+ "\u00e3\u0123\u0135\u00e3\u0124\u0135",
+ "elin",
+ "reibt",
+ "\u0120\u00d7\u0136\u00d7\u00a4",
+ "\u0120cemetery",
+ "\u0120espa\u00c3\u00b1ol",
+ "olin",
+ "\u00d0\u00bb\u00d1\u0130\u00d0\u00b4",
+ "\u0120gr\u00c3\u00a2ce",
+ "allen",
+ "\u0120Philos",
+ "\u0120Erst",
+ "\u0120\u00ec\u0125\u012a",
+ "\u0120Vid",
+ "Give",
+ "OH",
+ "\u00ce\u00bc\u00ce\u00bf",
+ "\u0120Pare",
+ "\u0120metabolism",
+ "\u0120maple",
+ "\u0120axle",
+ "\u0120Dy",
+ "\u0120komme",
+ "\u00cf\u0130\u00ce\u00bd",
+ "\u0120greatness",
+ "\u0120verified",
+ "\u0120sp\u00c3\u00a9",
+ "\u0120Fahrenheit",
+ "\u0120Bren",
+ "\u0120Confeder",
+ "\u0120histoire",
+ "\u0120eliminating",
+ "\u0120Adding",
+ "\u0120Abi",
+ "\u00e6\u013f\u0130",
+ "\u0120hospitality",
+ "tim",
+ "\u0120bonito",
+ "\u0120partes",
+ "\u0120\u00d0\u00b4\u00d1\u0122\u00d1\u0125\u00d0\u00b3\u00d0\u00b8\u00d1\u0127",
+ "\u0120Shay",
+ "\u0120Sed",
+ "\u0120regrets",
+ "\u00d1\u0131\u00d0\u00bc\u00d0\u00b8",
+ "\u0120tenants",
+ "\u00e9\u0122\u0141",
+ "\u0120PTS",
+ "\u0120devi",
+ "\u0120Late",
+ "uez",
+ "\u0120s\u00c3\u00b6yl",
+ "\u00e3\u0124\u00bb",
+ "\u0120\u00ec\u0140\u00ac\u00eb\u00b0\u012e",
+ "\u0120toggle",
+ "\u0120masking",
+ "\u00d0\u00b0\u00d0\u00bb\u00d1\u012e\u00d0\u00bd\u00d0\u00be\u00d0\u00b3\u00d0\u00be",
+ "\u0120pers\u00c3\u00b6n",
+ "\u0120american",
+ "fik",
+ "\u0120RGB",
+ "enson",
+ "\u0120KA",
+ "wwww",
+ "\u0120\u00d1\u0122\u00d0\u00b5\u00d0\u00b3",
+ "metics",
+ "\u0120educator",
+ "\u00e3\u0124\u00b7\u00e3\u0125\u00ab\u00e3\u0124\u00af",
+ "park",
+ "\u00d0\u00b5\u00d0\u00bb\u00d1\u012e\u00d0\u00b7\u00d1\u0131",
+ "arus",
+ "\u00d1\u0122\u00d0\u00b5\u00d1\u0124",
+ "\u0120feito",
+ "\u0120choir",
+ "\u0120largo",
+ "\u0120eens",
+ "\u0120watts",
+ "\u0120Single",
+ "\u0120susceptible",
+ "icer",
+ "\u0120\u00d0\u00b2\u00d0\u00ba\u00d0\u00bb\u00d1\u0130\u00d1\u0129",
+ "\u0120pus",
+ "\u00ed\u013b\u013a",
+ "Eng",
+ "\u0120fantas",
+ "\u0120specification",
+ "\u0120confronted",
+ "\u0120Columbus",
+ "\u00d0\u00b8\u00d0\u00b2\u00d0\u00b5\u00d1\u0124",
+ "ar\u00c4\u00b1m",
+ "\u0120caffeine",
+ "munition",
+ "\u0120migrants",
+ "lide",
+ "itations",
+ "\u0120Geme",
+ "\u00e1\u00ba\u00ab",
+ "\u0120planner",
+ "\u0120stimulate",
+ "\u0120aproxim",
+ "ceu",
+ "\u0120Nom",
+ "\u0120vog",
+ "\u0120\u00d1\u0122\u00d0\u00b0\u00d1\u0123\u00d1\u0124",
+ "\u0120ense\u00c3\u00b1",
+ "\u0120sellers",
+ "\u0120guten",
+ "zd",
+ "Cal",
+ "\u0120descript",
+ "\u0120reconciliation",
+ "zinho",
+ "\u00e1\u00b9\u0129a",
+ "\u00e3\u0123\u013a\u00e3\u0124\u0125\u00e3\u0123\u0124",
+ "acyj",
+ "\u0120COL",
+ "saw",
+ "\u0120\u00ed\u013b\u0137\u00ec\u013f\u00b8",
+ "\u0120varit",
+ "\u0120partnering",
+ "\u0120detention",
+ "\u0120bombing",
+ "clapping",
+ "iencies",
+ "ondu",
+ "AME",
+ "\u0120\u00ea\u00b0\u013b\u00ec\u012c\u00b5\u00eb\u012d\u012a\u00eb\u012d\u00a4",
+ "c\u00c3\u0143a",
+ "\u0120\u00d0\u00bf\u00d0\u00be\u00d1\u0123\u00d1\u0124\u00d0\u00be",
+ "\u0120ASMR",
+ "\u0120homepage",
+ "\u0120si\u00c3\u00a8",
+ "antha",
+ "\u0120Poll",
+ "\u0120igen",
+ "cych",
+ "\u0120\u00ea\u00b0\u0133\u00ec\u0140\u0132\u00ea\u00b8\u00b0",
+ "\u0120considerably",
+ "\u00e4\u00bb\u0138\u00e7\u013c\u0126",
+ "\u0120Arist",
+ "\u0120withstand",
+ "\u0120qualitative",
+ "\u0120Kraft",
+ "\u0120\u00d1\u012f\u00d0\u00bb\u00d0\u00b5\u00d0\u00ba\u00d1\u0124",
+ "\u0120Bead",
+ "\u00d0\u00b5\u00d0\u00ba\u00d1\u0124\u00d0\u00b8\u00d0\u00b2",
+ "\u0120crushing",
+ "\u00ec\u00b3\u0132",
+ "\u0120navy",
+ "\u00d9\u012a\u00da\u00ba",
+ "sho",
+ "\u0120oak",
+ "ippers",
+ "\u0120soils",
+ "\u0120pigment",
+ "\u0120evitar",
+ "\u00e3\u0125\u0129",
+ "\u0120fuse",
+ "\u0120Dale",
+ ":\"",
+ "\u0120compl\u00c3\u00a8tement",
+ "\u0120kel",
+ "\u00e0\u00b9\u0128",
+ "\u0120quatre",
+ "\u0120UM",
+ "\u0120\u00eb\u00a7\u0132\u00eb",
+ "\u00e6\u0142\u00b9",
+ "\u00c3\u0143r",
+ "\u0120leisure",
+ "\u0120Housing",
+ "\u0120folds",
+ "estion",
+ "ARS",
+ "\u0120mash",
+ "urpose",
+ "\u0120accumulated",
+ "\u0120Stuff",
+ "\u00e8\u00aa\u0140",
+ "\u0120tapes",
+ "\u0120\u00d1\u0123\u00d0\u00b8\u00d0\u00bb\u00d1\u012e\u00d0\u00bd\u00d0\u00be",
+ "\u0120LOVE",
+ "\u01201982",
+ "\u0120scars",
+ "\u0120capitalist",
+ "\u0120Ned",
+ "\u0120soften",
+ "\u0120notably",
+ "\u0120forc\u00c3\u00a9ment",
+ "\u0120Raum",
+ "\u0120\u00d0\u00bd\u00d0\u00b5\u00d0\u00be\u00d0\u00b1\u00d1\u0127\u00d0\u00be\u00d0\u00b4",
+ "\u0120trademark",
+ "\u0120fertig",
+ "\u0120?!",
+ "\u00e6\u0139\u0142",
+ "\u0120reinforced",
+ "\u0120recharge",
+ "\u0120Putting",
+ "\u0120villains",
+ "\u0120handic",
+ "\u0120advertisement",
+ "\u00d8\u00aa\u00d9\u012c",
+ "\u0120\u00d1\u0123\u00d1\u0125\u00d0\u00bc",
+ "\u0120Riley",
+ "\u00d7\u0137\u00d7\u0133\u00d7",
+ "\u00e4\u00ba\u00ac",
+ "Os",
+ "\u00d8\u00a7\u00d8\u00b2",
+ "Boy",
+ "\u0120squish",
+ "ocket",
+ "\u0120testify",
+ "\u00e6\u00bc\u0136",
+ "\u0120\u00d7\u013e\u00d7\u0140\u00d7",
+ "\u0120\u00d0\u00bc\u00d0\u00b0\u00d1\u0123\u00d1\u0123",
+ "manuel",
+ "\u0120Arkansas",
+ "iffe",
+ "\u0120analysts",
+ "\u0120Deaf",
+ "\u0120j\u00c3\u00b3",
+ "\u0120groceries",
+ "\u0120Wheel",
+ "\u0120\u00d1\u0122\u00d0\u00b8\u00d1\u0123",
+ "\u0120c\u00c3\u00b2n",
+ "\u0120Cob",
+ "\u0120prisons",
+ "\u00c3\u00a8ve",
+ "\u0120Cabinet",
+ "\u0120posed",
+ "\u0120guerre",
+ "\u0120Lloyd",
+ "\u0120clerk",
+ "\u0120crises",
+ "\u0120Sho",
+ "\u0120Ore",
+ "\u0120Football",
+ "\u0120Advis",
+ "\u0120Zheng",
+ "\u00e8\u012f",
+ "\u0120AMY",
+ "\u0120unfor",
+ "\u0120monaster",
+ "\u0120compile",
+ "\u0120immortal",
+ "atable",
+ "\u0120parano",
+ "\u0120tiver",
+ "\u0120Steph",
+ "\u0120Fu\u00c3\u0141",
+ "\u0120discontin",
+ "\u0120ripe",
+ "\u0120hacking",
+ "\u0120siendo",
+ "\u0120seguro",
+ "altres",
+ "\u0120anderes",
+ "\u0120\u00eb\u00a6\u00ac\u00eb",
+ "\u0120exports",
+ "\u00e6\u0143\u00a5",
+ "\u0120tabii",
+ "\u0120\u00ea\u00b8\u00b0\u00eb\u012d\u00a4\u00eb",
+ "\u0120bothering",
+ "\u0120pickle",
+ "\u0120BRIAN",
+ "\u0120altar",
+ "\u0120\u00d0\u00bf\u00d1\u0122\u00d0\u00b8\u00d0\u00b1",
+ "\u0120transferring",
+ "\u0120Vors",
+ "\u0120\u00d9\u0129\u00d9\u012a",
+ "\u0120Za",
+ "\u0120Frances",
+ "\u0120browse",
+ "emit",
+ "\u0120chewing",
+ "\u0120Freddy",
+ "\u0120editors",
+ "\u00c3\u00a4lle",
+ "\u0120\u00ed\u012e\u0122",
+ "\u0120Sque",
+ "\u0120Cultural",
+ "awk",
+ "\u0120Sache",
+ "\u0120Carbon",
+ "\u00e1\u00ba\u00aft",
+ "FL",
+ "\u0120NGO",
+ "pe\u00c5\u0124",
+ "\u0120Sou",
+ "\u0120hvor",
+ "unintelligible",
+ "\u0120\u00eb\u00b2\u0137",
+ "\u0120\u00c2\u00b0",
+ "iin",
+ "\u0120\u00d7\u00a2\u00d7\u013f",
+ "\u0120derri\u00c3\u00a8re",
+ "\u0120czym",
+ "\u0120Apost",
+ "\u0120regarder",
+ "\u0120agrade",
+ "\u0120Candy",
+ "\u0120mare",
+ "\u0120introduces",
+ "birds",
+ "\u0120uniquely",
+ "\u0120muk",
+ "\u0120cooker",
+ "\u0120crews",
+ "\u0120jeito",
+ "ERT",
+ "\u00b6\u0126\u00eb",
+ "nisse",
+ "\u0120ef",
+ "\u0120carte",
+ "\u0120Yak",
+ "\u0120PAT",
+ "\u00d0\u00b8\u00d0\u00bd\u00d0\u00be",
+ "bokki",
+ "\u0120mates",
+ "\u0120distint",
+ "\u0120\u00ec\u00bd\u0136\u00eb\u00a1\u013e\u00eb\u0124\u013a",
+ "\u0120y\u00c4\u00b1l",
+ "\u0120\u00ce\u00ba\u00ce\u00ac\u00ce\u00bd",
+ "\u0120configurations",
+ "enga",
+ "recht",
+ "Happy",
+ "\u00e3\u0124\u0126\u00e3\u0123\u00a3\u00e3\u0123\u00a6",
+ "invest",
+ "\u0120reconstruct",
+ "\u0120\u00d1\u012f\u00d1\u0124\u00d0\u00be\u00d0\u00bc\u00d1\u0125",
+ "\u0120mosque",
+ "raum",
+ "\u0120voyez",
+ "\u0120NBC",
+ "\u0120\u00ec\u0140\u0132\u00ec\u012d\u0142",
+ "\u0120sturdy",
+ "\u0120\u00d0\u00ba\u00d0\u00b0\u00d0\u00bf",
+ "\u0120ansch",
+ "alid",
+ "\u0120masih",
+ "\u0120REP",
+ "\u0120\u00ec\u00bd\u0136\u00eb",
+ "\u0120deduct",
+ "\u0120salir",
+ "wurf",
+ "ilot",
+ "\u0120Mutter",
+ "olds",
+ "\u0120FEMA",
+ "\u0120Bib",
+ "\u0120neighboring",
+ "\u0120bliss",
+ "\u0120\u00ed\u013a\u00bc",
+ "\u00d0\u00bb\u00d0\u00b8\u00d1\u0123\u00d1\u012e",
+ "\u0120\u00d1\u0124\u00d1\u0122\u00d0\u00b5\u00d0\u00b1",
+ "\u0120\u00e5\u00b0\u00b1\u00e6\u013a\u00af",
+ "\u0120grenade",
+ "\u0120egal",
+ "\u0120finely",
+ "\u0120petals",
+ "\u0120keer",
+ "\u0120chyba",
+ "\u0120skipping",
+ "\u0120thirteen",
+ "\u0120gravy",
+ "\u0120SAT",
+ "61",
+ "\u0120\u00d0\u00bd\u00d0\u00be\u00d0\u00b3",
+ "\u0120mins",
+ "ITE",
+ "\u0120sozial",
+ "\u00ed\u0137\u013a\u00eb\u00a9\u00b4\u00ec\u0126\u013e",
+ "ruktur",
+ "\u0120\u00d0\u00b2\u00d0\u00be\u00d0\u00b7\u00d0\u00bc\u00d0\u00be\u00d0\u00b6",
+ "\u0120\u00d0\u00be\u00d0\u00bf\u00d1\u0131\u00d1\u0124\u00d1\u012e",
+ "\u0120arth",
+ "\u0120Cuban",
+ "\u0120treasures",
+ "\u0120fertilizer",
+ "\u0120awakening",
+ "\u0120\u00eb\u00b0\u00b1\u00ec\u012d\u0142",
+ "\u0120rall",
+ "\u0120depict",
+ "\u0120Pablo",
+ "\u0120nineteen",
+ "\u0120watt",
+ "\u0120entirety",
+ "KS",
+ "\u0120Woods",
+ "Sch",
+ "\u0120\u00da\u00a9\u00d9\u012a",
+ "\u0120Dry",
+ "\u00e3\u0123\u0140",
+ "uve",
+ "\u0120reconstruction",
+ "\u0120anatomy",
+ "\u012a\u00eb\u00a5\u00bc",
+ "\u0120baba",
+ "\u0120listener",
+ "\u0120sharpen",
+ "\u0120Peru",
+ "\u0120\u00d0\u00b2\u00d1\u012d\u00d0\u00b7",
+ "\u0120recreation",
+ "\u0120initiate",
+ "\u0120calor",
+ "\u0120Naj",
+ "gee",
+ "\u0120Feels",
+ "\u0120Snapchat",
+ "\u0120Tet",
+ "\u0120Nest",
+ "\u0120Daf",
+ "\u0120Finish",
+ "\u0120\u00d1\u0124\u00d0\u00b0\u00d0\u00ba\u00d0\u00b8\u00d0\u00bc",
+ "\u00c3\u00bac",
+ "izens",
+ "\u0120spins",
+ "\u0120embry",
+ "\u0120passages",
+ "\u0120cient",
+ "\u0120justification",
+ "\u00e4\u00bb\u0138\u00e8\u00aa\u00aa",
+ "\u0120olmaz",
+ "\u0120flooded",
+ "\u0120emoji",
+ "\u0120embracing",
+ "\u0120discard",
+ "\u0120Basic",
+ "agog",
+ "\u0120\u00ec\u013e\u0126\u00ed\u0137\u00b4",
+ "\u0120asylum",
+ "erin",
+ "\u0120fim",
+ "\u0120ninja",
+ "\u0120automate",
+ "\u0120allergic",
+ "\u00c3\u00bf\u00c3\u00bf\u00c3\u00bf\u00c3\u00bf",
+ "amam",
+ "\u0120\u00d0\u00bc\u00d0\u00b0\u00d1\u0122",
+ "\u0120Oi",
+ "\u00c3\u00a4us",
+ "\u0120induct",
+ "\u0120BEN",
+ "\u0120z\u00c5\u0124",
+ "\u0120ka\u00c5\u00bcdy",
+ "\u0120AMP",
+ "n\u00c4\u013d",
+ "Sure",
+ "\u0120quil",
+ "\u0120espec",
+ "rok",
+ "BSCRI",
+ "\u0120liebe",
+ "pus",
+ "achsen",
+ "\u0120cricket",
+ "\u00eb\u012c\u0132",
+ "\u0120Frame",
+ "ekk\u00c3\u00bcr",
+ "arb",
+ "\u0120p\u00c5\u013b",
+ "\u00d0\u00b8\u00d1\u0123\u00d1\u0123",
+ "\u0120zeggen",
+ "\u0120doubles",
+ "\u0120Dre",
+ "test",
+ "insp",
+ "boys",
+ "\u0120m\u00c3\u00a3o",
+ "\u0120Verse",
+ "\u0120muscular",
+ "\u0120MALE",
+ "\u0120dulu",
+ "\u0120occasional",
+ "Lo",
+ "conomic",
+ "\u0120vak",
+ "\u0120remedy",
+ "\u00e5\u00a4\u0142",
+ "\u0120\u00e2\u013b\u00aa\u00e2\u013b\u00aa\u00e2\u013b\u00aa",
+ "vem",
+ "\u0120\u00c3\u00b6nem",
+ "\u0120kar\u00c5\u0141\u00c4\u00b1",
+ "\u0120Sharp",
+ "hur",
+ "\u0120\u00eb\u00b0\u00a9\u00eb\u00b2\u0137",
+ "\u0120grandson",
+ "\u0120aktiv",
+ "\u0120Thrones",
+ "\u0120\u00ec\u0137\u012a\u00ec\u0139\u0132",
+ "\u0120tots",
+ "\u0120subd",
+ "\u0120Paula",
+ "\u0120graves",
+ "\u0120Brent",
+ "\u0120\u00d0\u00bd\u00d0\u00b8\u00d0\u00ba\u00d1\u0124\u00d0\u00be",
+ "\u0120s\u00c3\u00b6z",
+ "\u0120crec",
+ "\u0120Vladimir",
+ "\u00e7\u0138\u00ab",
+ "\u0120\u00d0\u00bf\u00d0\u00be\u00d0\u00b9",
+ "\u0120\"-",
+ "\u0120psy",
+ "atri",
+ "idan",
+ "\u0120a\u00c3\u00ban",
+ "\u0120standardized",
+ "\u00ec\u00b9\u013a\u00eb",
+ "\u0120\u00d0\u00ba\u00d1\u0122\u00d0\u00be\u00d0\u00b2",
+ "\u0120Zhu",
+ "something",
+ "\u0120750",
+ "\u0120mujeres",
+ "\u0120ait",
+ "\u00e9\u0139\u00b4",
+ "agu",
+ "\u0120corrected",
+ "ikka",
+ "eled",
+ "\u0120Career",
+ "owym",
+ "\u0120roommate",
+ "\u0120descendants",
+ "\u0120Napoleon",
+ "\u0120\u00d0\u0136\u00d0\u00be",
+ "\u00ed\u0138\u012a\u00ec\u0138\u00b4\u00ec\u013c\u0136",
+ "\u0120bunun",
+ "\u0120Micha",
+ "\u00e7\u00b7\u013c",
+ "\u0120descob",
+ "PI",
+ "\u0120palabra",
+ "\u0120tracked",
+ "\u0120dependence",
+ "\u0120Barack",
+ "\u00e5\u0123\u0129",
+ "\u0120fertility",
+ "\u0120Southwest",
+ "\u0120incomplete",
+ "\u0120comunic",
+ "\u0120compris",
+ "\u0120Restaur",
+ "\u0120acron",
+ "\u00ce\u00ba\u00ce\u00b1",
+ "\u0120apprentices",
+ "\u0120musst",
+ "\u0120Abr",
+ "\u0120pentru",
+ "\u0120Consort",
+ "\u0120Avec",
+ "\u0120dumplings",
+ "LR",
+ "\u0120wszystkie",
+ "\u0120swamp",
+ "\u00d0\u00bd\u00d0\u00b5\u00d0\u00b2",
+ "uggle",
+ "\u0120watercolor",
+ "\u0120proton",
+ "\u0120Espa\u00c3\u00b1a",
+ "ocking",
+ "\u00d0\u00be\u00d0\u00b2\u00d0\u00b0\u00d0\u00bb",
+ "\u0120takim",
+ "Very",
+ "\u0120dementia",
+ "\u0120\u00c5\u0141eyi",
+ "Jac",
+ "\u0120MacBook",
+ "\u0120Liv",
+ "fficients",
+ "\u0120Hunt",
+ "\u0120overlay",
+ "\u00e6\u0126\u0141\u00e8\u00a6\u00ba",
+ "\u0120Skype",
+ "punkt",
+ "\u0120confined",
+ "\u0120Adrian",
+ "\u00d8\u00b1\u00d9\u0125",
+ "\u0120Jeep",
+ "\u0120enquanto",
+ "\u0120anest",
+ "\u00d0\u00be\u00d1\u0124\u00d0\u00b2\u00d0\u00b5\u00d1\u0124",
+ "\u0120\u00d0\u00bc\u00d0\u00b5\u00d0\u00bd\u00d1\u012e",
+ "\u0120irrigation",
+ "\u00e1\u00bb\u0133n",
+ "\u0120eighteen",
+ "\u0120Pon",
+ "\u0120rescued",
+ "\u01201983",
+ "r\u00c3\u00bc",
+ "jae",
+ "\u0120Jeong",
+ "\u0120amazingly",
+ "\u0120FDP",
+ "\u0120backstage",
+ "cue",
+ "\u0120\u00cf\u0125\u00cf\u0126\u00ce\u00b7\u00ce\u00bd",
+ "\u0120\u00d8\u00a7\u00d9\u0126\u00d8\u00b5",
+ "\u0120livestock",
+ "\u0120Warner",
+ "\u0120majors",
+ "\u00e3\u0125\u0123\u00e3\u0125\u00a3",
+ "\u0120cooperative",
+ "\u0120Brady",
+ "rained",
+ "rieb",
+ "\u0120\u00d7\u0133\u00d7\u0140\u00d7",
+ "\u0120\u00d0\u00b4\u00d0\u00be\u00d0\u00b2\u00d0\u00be\u00d0\u00bb\u00d1\u012e\u00d0\u00bd\u00d0\u00be",
+ "\u0120FE",
+ "\u0120leaked",
+ "\u0120Mercury",
+ "\u0120persuade",
+ "\u0120transformer",
+ "\u0120Norweg",
+ "\u0120\u00ec\u0139\u00ac\u00eb\u0141\u00ac",
+ "\u0120zrobi\u00c4\u0129",
+ "\u0120cardiovascular",
+ "\u0120Crash",
+ "\u0120gossip",
+ "\u00d0\u00b0\u00d1\u0123\u00d1\u0124\u00d1\u012e",
+ "\u0120\u00ec\u00aa\u00bd",
+ "\u0120swept",
+ "\u0120Horn",
+ "\u0120At\u00c3\u00a9",
+ "\u0120bukan",
+ "\u0120Kaw",
+ "KY",
+ "\u0120Stories",
+ "Gary",
+ "\u0120gardening",
+ "\u0120Quickly",
+ "\u0120Falcon",
+ "\u0120ovat",
+ "c\u00c4\u00b1",
+ "\u0120Complet",
+ "\u0120Date",
+ "\u0120\u00d0\u00bf\u00d1\u0122\u00d0\u00b8\u00d0\u00bc",
+ "\u0120l\u00c3\u00a4uft",
+ "\u0120Audrey",
+ "\u0120Went",
+ "\u0120pel\u00c3\u0143cul",
+ "\u0120carriage",
+ "\u0120unacceptable",
+ "nymi",
+ "\u0120\u00d1\u0123\u00d0\u00bb\u00d1\u012d\u00d1\u012a",
+ "\u0120terre",
+ "uellement",
+ "EEEE",
+ "\u0120pharmac",
+ "h\u00c3\u00b5es",
+ "\u0120zich",
+ "\u0120migrate",
+ "\u0120Fry",
+ "\u00c3\u00b1ana",
+ "\u0120Muito",
+ "EOVER",
+ "\u0120fortress",
+ "\u0120Compan",
+ "\u0120JSON",
+ "ordnung",
+ "\u0120warto",
+ "\u0120ungef",
+ "\u00ec\u0127\u0136\u00ec\u0126\u013e",
+ "\u0120\u00d1\u0122\u00d0\u00be\u00d0\u00ba",
+ "\u0120paddle",
+ "Jared",
+ "\u0120submitting",
+ "\u0120latch",
+ "\u0120fug",
+ "\u0120\u00d0\u00ba\u00d0\u00be\u00d1\u0123",
+ "\u0120Ef",
+ "\u0120launches",
+ "\u0120ft",
+ "otechn",
+ "\u0120travelled",
+ "\u00d8\u00a7\u00d9\u0123",
+ "\u00e9\u0123\u0137",
+ "\u0120proch",
+ "\u0120dedim",
+ "83",
+ "\u0120rebound",
+ "\u0120LU",
+ "path",
+ "\u0120\u00d1\u0123\u00d0\u00bf\u00d1\u0122\u00d0\u00b0\u00d0\u00b2",
+ "\u0120\u00c3\u00b6l",
+ "\u0120\u00ed\u0124\u00a4",
+ "\u0120privat",
+ "\u0120tractor",
+ "\u0120Attention",
+ "Ser",
+ "\u0120coses",
+ "\u00c3\u00a1ria",
+ "pal",
+ "\u0120\u00ec\u013f\u0122",
+ "\u0120successor",
+ "\u0120connectors",
+ "\u0120\u00d1\u0125\u00d1\u0123\u00d1\u0124\u00d0\u00b0\u00d0\u00bd\u00d0\u00be\u00d0\u00b2",
+ "\u0120genocide",
+ "\u0120sufficiently",
+ "\u0120Aix\u00c3\u00b2",
+ "\u0120stabilize",
+ "\u0120congest",
+ "\u0120carving",
+ "\u0120zost",
+ "\u0120\u00d0\u00b1\u00d1\u012d\u00d1\u0123\u00d1\u0124\u00d1\u0122\u00d0\u00be",
+ "\u0120shortest",
+ "\u0120livel",
+ "\u012089",
+ "\u00e9\u0123\u012c",
+ "\u0120erk",
+ "\u0120portraits",
+ "\u00e0\u00a5\u0122",
+ "\u00e8\u013a",
+ "boat",
+ "llah",
+ "ANC",
+ "\u0120empirical",
+ "\u0120Echo",
+ "\u0120Nederland",
+ "\u00e8\u00bf\u013b\u00e4\u00b9\u012a",
+ "Net",
+ "\u0120cuidado",
+ "\u0120Roma",
+ "\u0120calf",
+ "\u0120giants",
+ "\u0120Explorer",
+ "\u0120Collect",
+ "alition",
+ "\u0120Destiny",
+ "\u0120ausge",
+ "\u0120Edu",
+ "\u0120Clo",
+ "\u0120earrings",
+ "\u0120Track",
+ "\u0120ROS",
+ "\u0120Belle",
+ "\u00e7\u013b\u00be",
+ "\u0120pueda",
+ "\u0120daytime",
+ "\u0120supplier",
+ "\u0120SV",
+ "\u0120Exhale",
+ "\u0120galera",
+ "course",
+ "\u0120centimeter",
+ "\u0120Bast",
+ "mud",
+ "\u0120sangat",
+ "\u0120Physical",
+ "\u0120privately",
+ "\u0120trata",
+ "lynn",
+ "illi",
+ "\u0120\u00eb\u00a9\u0136\u00ec\u013f\u00b4\u00ed\u0123\u00ac\u00ec\u0139\u0127",
+ "\u0120crystall",
+ "\u0120pods",
+ "\u00e1\u00ba\u00a3n",
+ "inator",
+ "\u0120Records",
+ "\u00e5\u00ae\u013a",
+ "\u00c4\u0141imiz",
+ "issement",
+ "hare",
+ "hadow",
+ "\u0120DK",
+ "\u0120\u00ec\u0137\u012e\u00ea\u00b3\u0142",
+ "\u0120wyn",
+ "\u0120requesting",
+ "\u0120Donna",
+ "\u0120\u00ec\u0139\u00b4\u00ec\u012d\u00ac\u00ed\u0140\u012a",
+ "inea",
+ "\u0120exert",
+ "\u0120Duncan",
+ "\u0120\u00d0\u00b2\u00d0\u00b5\u00d1\u0129",
+ "\u0120Hah",
+ "\u00e0\u00a4\u0124",
+ "\u0120Lif",
+ "\u0120Finding",
+ "\u0120Nov",
+ "\u0120\u00d0\u00b7\u00d0\u00bd\u00d0\u00b0\u00d0\u00ba",
+ "\u0120\u00d0\u00be\u00d1\u0126",
+ "\u0120Qu\u00c3\u00a8",
+ "\u0120quarterback",
+ "\u0120\u00d1\u0126\u00d0\u00b0\u00d0\u00ba",
+ "\u0120bipartisan",
+ "\u00c4\u0141in",
+ "\u0120n\u00c3\u00a9cess",
+ "\u0120referendum",
+ "\u0120compiler",
+ "\u0120probabil",
+ "\u00d0\u00b5\u00d0\u00b4\u00d0\u00b8",
+ "\u0120trader",
+ "\u00e6\u013a\u0135",
+ "\u0120Rum",
+ "geme",
+ "\u0120dio",
+ "\u0120b\u00c4\u013bdziemy",
+ "\u0120\u00cf\u0122\u00ce\u00ac",
+ "\u00ea\u00be\u00b8",
+ "\u00d7\u0137\u00d7\u013a",
+ "\u0120\u00e0\u00a4\u0137",
+ "\u0120\u00d0\u00b1\u00d0\u00bb\u00d0\u00b0\u00d0\u00b3",
+ "\u0120scalp",
+ "\u0120Pause",
+ "\u0120caption",
+ "\u0120endanger",
+ "\u0120enlar",
+ "\u0120rotten",
+ "\u00e3\u0125\u0125\u00e3\u0125\u012a",
+ "\u0120wah",
+ "\u00e8\u0124\u012b",
+ "\u0120dzi",
+ "\u0120Install",
+ "Ay",
+ "\u0120crear",
+ "\u00d0\u00b5\u00d0\u00bd\u00d1\u0124\u00d0\u00b0",
+ "\u0120weighing",
+ "\u0120butterflies",
+ "\u0120Gast",
+ "\u00e4\u00ba\u0137",
+ "horn",
+ "warz",
+ "ICEOVER",
+ "\u0120\u00d0\u00bd\u00d0\u00b0\u00d0\u00b9\u00d1\u0124\u00d0\u00b8",
+ "\u0120coefficients",
+ "\u00e7\u00b0\u00a1\u00e5\u0138\u00ae",
+ "\u0120Spencer",
+ "\u0120Higher",
+ "\u0120cowork",
+ "\u00e5\u00a8\u013a",
+ "\u0120\u00d0\u00ba\u00d0\u00be\u00d1\u0124\u00d0\u00be\u00d1\u0122\u00d0\u00be\u00d0\u00b5",
+ "\u0120monit",
+ "\u0120dysfunction",
+ "\u0120\u00d1\u0123\u00d1\u0124\u00d0\u00b0\u00d0\u00bd\u00d0\u00be\u00d0\u00b2",
+ "\u0120tournaments",
+ "\u0120oyster",
+ "BN",
+ "\u0120trud",
+ "slow",
+ "\u0120Penny",
+ "\u0120Odys",
+ "\u00c3\u00a6r",
+ "\u0120fou",
+ "\u0120enjoyment",
+ "\u00d0\u00b0\u00d1\u0124\u00d1\u012d",
+ "\u0120wygl\u00c4\u0127da",
+ "\u00d0\u00b0\u00d0\u00bb\u00d1\u012e\u00d0\u00bd\u00d0\u00b0\u00d1\u0131",
+ "\u0120Protect",
+ "\u0120moy",
+ "\u0120claw",
+ "\u0120suspicion",
+ "\u0120sacrificed",
+ "\u0120gosto",
+ "Big",
+ "\u0120aggressively",
+ "\u0120vorne",
+ "\u00e3\u0125\u0142",
+ "\u0120blamed",
+ "\u0120Sehr",
+ "\u00d7\u00a4\u00d7\u00a8",
+ "cito",
+ "\u0120seals",
+ "\u0120mujer",
+ "\u0120Weird",
+ "\u0120forens",
+ "\u0120contributes",
+ "estra",
+ "\u0120pog",
+ "LOL",
+ "\u0120hacerlo",
+ "\u00d0\u00be\u00d1\u0124\u00d1\u012e",
+ "fiction",
+ "79",
+ "\u00ce\u00bb\u00ce\u00bf",
+ "\u00e5\u00a4\u00a7\u00e6\u00a6\u0124",
+ "\u00e5\u00a3\u00b0",
+ "\u0120\u00d1\u0124\u00d0\u00be\u00d0\u00b1",
+ "\u0120GS",
+ "\u0120Clara",
+ "itez",
+ "\u0120advocating",
+ "\u0120\u00ed\u0136\u0126\u00eb",
+ "sung",
+ "\u0120vertices",
+ "\u0120navigating",
+ "\u0120europ\u00c3\u00a9",
+ "\u00e7\u013c\u0128",
+ "\u0120slowed",
+ "\u0120foreground",
+ "\u0120Industrial",
+ "\u0120adore",
+ "\u00ec\u012d\u0143",
+ "\u0120cr\u00c3\u00a9er",
+ "\u00e6\u0140\u0139",
+ "chnitt",
+ "\u0120unaware",
+ "\u0120curly",
+ "entar",
+ "\u0120ler",
+ "\u0120prohibited",
+ "\u0120Heroes",
+ "\u0120Reed",
+ "uca",
+ "\u0120smok",
+ "\u0120kunna",
+ "zeitig",
+ "immen",
+ "\u0120Lun",
+ "\u0120\u00d0\u00b0\u00d0\u00b1\u00d1\u0123\u00d0\u00be\u00d0\u00bb\u00d1\u0130\u00d1\u0124",
+ "\u0120degli",
+ "\u0120villagers",
+ "\u0120preset",
+ "zept",
+ "uds",
+ "\u0120emit",
+ "\u00e4\u00bd\u0142\u00e8\u00a6\u0123",
+ "\u0120\u00eb\u012b",
+ "\u00eb\u012c\u0136\u00ec\u00a7\u0122",
+ "\u00d0\u00bd\u00d0\u00b0\u00d0\u00ba\u00d0\u00be",
+ "\u0120os\u00c3\u00b3b",
+ "\u01201969",
+ "\u0120\u00d0\u0132\u00d1\u0122",
+ "\u0120manchmal",
+ "\u0120Brock",
+ "\u0120mantra",
+ "\u0120WIL",
+ "bach",
+ "in\u00c3\u00a4",
+ "elas",
+ "keln",
+ "\u0120disciple",
+ "\u0120qualc",
+ "\u0120dehyd",
+ "\u00ec\u013f\u00b4\u00eb\u013f\u00bc\u00eb\u012c\u0136",
+ "Af",
+ "\u00ec\u0126\u00b1\u00ec\u013f\u00b4",
+ "Ryan",
+ "\u0120puppet",
+ "\u0120\u00d0\u00b4\u00d1\u0122\u00d1\u0125\u00d0\u00b3\u00d0\u00b8\u00d0\u00b5",
+ "\u0120rud",
+ "\u0120pending",
+ "Plus",
+ "\u0120\u00ec\u0137\u012c\u00ec\u013f\u0126",
+ "\u0120b\u00e1\u00bb\u012d",
+ "\u0120Sega",
+ "\u00c3\u00a7e",
+ "\u0120programmer",
+ "bli",
+ "\u0120unl",
+ "\u0120enslaved",
+ "\u0120soci\u00c3\u00a9t\u00c3\u00a9",
+ "\u00c4\u0123h",
+ "\u0120inheritance",
+ "\u0120Bangl",
+ "ermaid",
+ "\u0120practitioner",
+ "\u0120Stalin",
+ "\u0120User",
+ "cible",
+ "\u0120cardiac",
+ "\u0120Koreans",
+ "\u0120dumped",
+ "\u0120\u00d7\u0136\u00d7\u013b\u00d7\u0136",
+ "\u00c3\u00a1is",
+ "\u0120hydraulic",
+ "oubtedly",
+ "\u0120Pit",
+ "\u0120picnic",
+ "\u0120beh\u00c3\u00b6ver",
+ "\u0120\u00d1\u0123\u00d0\u00bc\u00d0\u00be\u00d0\u00b3",
+ "\u0120braking",
+ "\u00e9\u00bb\u0133",
+ "utar",
+ "\u0120\u00ec\u0126\u00b8\u00eb",
+ "ubl",
+ "\u0120\u00c3\u00bcz",
+ "\u0120majesty",
+ "\u0120bers",
+ "utable",
+ "\u0120hotter",
+ "\u00e7\u0127\u00a7",
+ "\u00db\u012e\u00d9\u0128",
+ "\u0120biases",
+ "\u0120subjected",
+ "\u0120naughty",
+ "\u0120circus",
+ "\u00e3\u0123\u0139\u00e3\u0123\u012d",
+ "\u0120Immedi",
+ "\u0120Stefan",
+ "\u0120Triple",
+ "enk",
+ "\u0120wit",
+ "\u0120recycle",
+ "emie",
+ "dated",
+ "\u0120unload",
+ "\u0120popula",
+ "chin",
+ "\u0120yields",
+ "\u0120english",
+ "\u0120Bonnie",
+ "\u0120spiders",
+ "\u00c3\u0123",
+ "\u0120erosion",
+ "\u00e9\u0125\u00a8\u00e5\u012a\u0128",
+ "\u0120NICK",
+ "\u00d0\u00b8\u00d1\u0131\u00d1\u0127",
+ "\u0120impart",
+ "\u0120\u00d0\u00ba\u00d0\u00bd\u00d0\u00b8",
+ "\u0120resolutions",
+ "\u0120lithium",
+ "\u0120convergence",
+ "\u0120Tara",
+ "\u0120\u00d0\u00b4\u00d0\u00b2\u00d0\u00b5",
+ "ths",
+ "\u0120Cindy",
+ "\u00e6\u012a\u0133\u00e8\u00a6\u0123",
+ "\u00e5\u00b9\u00ab",
+ "\u0120DIE",
+ "\u0120assurance",
+ "\u0120\u00d0\u00be\u00d0\u00bf\u00d0\u00b8\u00d1\u0123",
+ "\u0120buckets",
+ "\u0120cues",
+ "\u0120Quiet",
+ "\u0120similarity",
+ "\u0120foundational",
+ "\u0120Minist",
+ "\u00e6\u00bb\u00bf",
+ "\u0120pian",
+ "\u0120centr",
+ "\u0120numb",
+ "\u0120monks",
+ "ujourd",
+ "enzie",
+ "\u0120skateboard",
+ "\u0120dlatego",
+ "\u0120\u00d1\u0123\u00d0\u00be\u00d1\u0124",
+ "\u0120AE",
+ "\u0120masterpiece",
+ "\u0120Solomon",
+ "\u0120Reddit",
+ "\u0120riot",
+ "abl",
+ "\u0120Jazz",
+ "\u0120electromagnetic",
+ "\u0120insecure",
+ "\u0120Compet",
+ "geries",
+ "\u00d0\u00be\u00d0\u00b1\u00d0\u00be\u00d0\u00b4",
+ "\u0142\u00d7\u0137",
+ "\u00f0\u0141\u0134",
+ "\u0120senators",
+ "\u0120Brisbane",
+ "\u0120Alb",
+ "uttering",
+ "\u0120Allow",
+ "zero",
+ "\u0120pai",
+ "\u0120\u00d0\u0132\u00d0\u00bb\u00d0\u00b5\u00d0\u00ba\u00d1\u0123",
+ "\u0120Display",
+ "\u0120Blade",
+ "\u0120Apps",
+ "\u0120p\u00c3\u00a4",
+ "\u0120\u00d0\u00b4\u00d0\u00b5\u00d1\u0123\u00d1\u0131",
+ "\u0120quella",
+ "\u0120Gao",
+ "\u00d0\u00b5\u00d0\u00bd\u00d0\u00bd\u00d1\u012d\u00d1\u0127",
+ "\u0120spoilers",
+ "\u0120gallons",
+ "\u0120\u00d9\u0126\u00d9\u012c",
+ "\u0120Zion",
+ "\u00e6\u013e\u012b\u00e4\u00b8\u0122",
+ "onie",
+ "ragt",
+ "\u0120Chand",
+ "\u0120\u00eb\u00b3\u0133",
+ "\u0120blunt",
+ "\u0120usu",
+ "\u0120Kad",
+ "rakt",
+ "\u0120cinematic",
+ "\u0120ammunition",
+ "rene",
+ "\u0120fourteen",
+ "\u0120Carn",
+ "crit",
+ "\u0120tenure",
+ "vu",
+ "\u0120principalmente",
+ "\u0120alleen",
+ "\u00e9\u0122\u013b\u00e4\u00b8\u0122",
+ "\u0120komplett",
+ "\u0120d\u00c3\u00bcny",
+ "James",
+ "\u0120receptor",
+ "\u0120oneself",
+ "guru",
+ "\u0120merchant",
+ "liness",
+ "\u0120overlooked",
+ "\u0120harmonic",
+ "\u00e9\u0137\u00bf",
+ "ieso",
+ "\u00d7\u0137\u00d7\u0140",
+ "colm",
+ "\u0120\u00d0\u00bf\u00d1\u0122\u00d0\u00be\u00d0\u00b5\u00d0\u00ba\u00d1\u0124",
+ "\u0120Ada",
+ "\u00d8\u00a7\u00d8\u00b3",
+ "Tim",
+ "\u0120recurring",
+ "\u0120proceeds",
+ "\u0120Particularly",
+ "\u0120Download",
+ "etrical",
+ "\u0120matrices",
+ "\u0120proyecto",
+ "ancies",
+ "\u0120Uhm",
+ "\u0120caves",
+ "\u0120\u00ec\u0138\u00b4\u00eb\u0142\u00a4",
+ "\u0120Leaf",
+ "\u0120\u00d0\u00be\u00d0\u00b1\u00d1\u012d\u00d1\u0129",
+ "\u0120\u00ec\u013f\u00b4\u00ec\u013e\u0142",
+ "Europe",
+ "\u0120t\u00c4\u0127",
+ "\u0120puls",
+ "\u0120takiego",
+ "\u00d0\u013f\u00d0\u00b5",
+ "GU",
+ "\u0120fors",
+ "\u00cf\u0123\u00ce\u00b3",
+ "\u0120fotos",
+ "\u0120))",
+ "\u0120\u00eb\u00a9\u00a4\u00eb",
+ "\u0120aquilo",
+ "\u0120Kurd",
+ "\u00ef\u00b8\u0131",
+ "ptic",
+ "\u0120Dort",
+ "\u0120misery",
+ "auso",
+ "\u00e5\u012c\u0141",
+ "chuckling",
+ "\u0120Ridge",
+ "\u0120\u00ed\u0138\u012a\u00ec\u012c\u00b5\u00eb\u012d\u012a\u00eb\u012d\u00a4",
+ "\u0120***",
+ "\u00e5\u00ae\u00a2",
+ "\u0120Hmmm",
+ "\u0120geographic",
+ "\u0120anys",
+ "\u0120talvez",
+ "\u0120skelet",
+ "\u0120signatures",
+ "\u0120liters",
+ "\u0132\u00eb\u00a9\u00b4",
+ "\u0120\u00d1\u0123\u00d0\u00b2\u00d0\u00be\u00d0\u00b5\u00d0\u00b3\u00d0\u00be",
+ "\u0120skiing",
+ "\u0120\u00d0\u013e\u00d0\u00be\u00d1\u0123",
+ "\u0120adopting",
+ "\u0120haft",
+ "\u0120symmetric",
+ "\u0120Liqu",
+ "\u0120thyroid",
+ "\u0120misin",
+ "lude",
+ "\u0120hull",
+ "\u0120XD",
+ "\u0120Gust",
+ "zeich",
+ "\u0120vibrations",
+ "\u0120esemp",
+ "\u0120\u00d0\u00b2\u00d1\u0123\u00d1\u0130",
+ "\u0120Quem",
+ "\u0120\u00c3\u00bcbrig",
+ "\u0120Ske",
+ "\u0120Lynch",
+ "rooms",
+ "artet",
+ "fest",
+ "\u0120fr\u00c3\u00bcher",
+ "\u0120lure",
+ "\u00e4\u00b8\u012f\u00e5\u00a5\u00bd\u00e6\u0126\u0131\u00e6\u0122\u013f",
+ "\u0120\u00ec\u0137\u012e\u00ec\u0137\u0126",
+ "\u0120WIN",
+ "\u0120RYAN",
+ "\u0120\u00d0\u00ba\u00d0\u00be\u00d1\u0124\u00d0\u00be\u00d1\u0122\u00d1\u0125\u00d1\u0130",
+ "\u0120Kash",
+ "\u0120\u00d7\u0136\u00d7\u0140",
+ "\u0120safeg",
+ "\u0120Hallelujah",
+ "\u0120\u00d0\u00b4\u00d0\u00b2\u00d1\u0125\u00d1\u0127",
+ "\u0120staple",
+ "\u0120sediment",
+ "\u0120Acts",
+ "\u0120blaming",
+ "\u0120mainland",
+ "\u0120sporting",
+ "\u0120decorations",
+ "\u0120executing",
+ "\u0120paran",
+ "\u0120Dollar",
+ "\u0120projections",
+ "\u0120commissioned",
+ "\u0120bour",
+ "\u00c3\u00b6m",
+ "\u0120steamed",
+ "\u0120\u00eb\u0143\u013a",
+ "\u0120petrol",
+ "\u0120celular",
+ "\u00e5\u00b8\u00b6",
+ "\u0120Hungary",
+ "\u0120rented",
+ "\u0120\u00d0\u00b2\u00d0\u00b0\u00d1\u0122\u00d0\u00b8",
+ "bbie",
+ "\u0120s\u00c3\u00a9cur",
+ "\u00c3\u00bcll",
+ "\u0120swings",
+ "between",
+ "\u0120\u00d0\u00b8\u00d1\u0124",
+ "estro",
+ "\u0120niemand",
+ "\u0120\u00ec\u0124\u00bc",
+ "\u0120Pardon",
+ "esses",
+ "\u0120MID",
+ "\u0120centralized",
+ "\u0120Alien",
+ "culos",
+ "\u0120crise",
+ "\u00e8\u00a3\u00a1\u00e9\u013f\u00a2",
+ "\u0120classe",
+ "beitet",
+ "i\u00c4\u0141i",
+ "\u0120whales",
+ "\u0120perimeter",
+ "\u0120tying",
+ "\u0120strony",
+ "\u0120likewise",
+ "\u0120Punch",
+ "Da",
+ "\u0120Baptist",
+ "\u0120sorting",
+ "\u0120iv",
+ "\u0120\u00ed\u0137\u00a9",
+ "\u0120rehab",
+ "\u0120eta",
+ "river",
+ "\u0120sai",
+ "\u00e3\u0123\u0126\u00e3\u0123\u0141\u00e3\u0123\u0142",
+ "odus",
+ "\u00e3\u0123\u012c\u00e9\u00a1\u013a\u00e3\u0123\u0126\u00e3\u0123\u0139\u00e3\u0123\u00be\u00e3\u0123\u013b",
+ "\u0120essayer",
+ "\u0120turtles",
+ "\u0120Hazrat",
+ "\u0120fabrics",
+ "\u0120cavity",
+ "\u0120poniewa\u00c5\u00bc",
+ "\u0120schlecht",
+ "\u0120salsa",
+ "\u00c5\u0141ekk\u00c3\u00bcr",
+ "\u0120seating",
+ "\u0120economists",
+ "\u0120mang",
+ "\u0120seguinte",
+ "\u0120rang",
+ "\u0120ratios",
+ "\u0120constell",
+ "\u0120longtemps",
+ "uating",
+ "\u0120spoiled",
+ "\u0120recipients",
+ "\u0120sniper",
+ "\u00e4\u00b9\u012d\u00e5\u012b\u012f",
+ "\u00ec\u012c\u00b5\u00eb\u012d\u012a\u00ea\u00b9\u012e",
+ "\u0120wp",
+ "\u0120LINKE",
+ "\u0120flare",
+ "\u0120Adri",
+ "\u00c3\u00b1as",
+ "\u0120backl",
+ "m\u00c3\u00a4\u00c3\u0141",
+ "\u0120Bend",
+ "\u0120workloads",
+ "\u0120\u00d1\u0123\u00d1\u0125\u00d0\u00bf",
+ "\u01201975",
+ "\u00d0\u00b8\u00d0\u00bc\u00d1\u0123\u00d1\u0131",
+ "\u00d0\u00b0\u00d0\u00bd\u00d0\u00b5",
+ "\u0120\u00d0\u00bc\u00d0\u00be\u00d0\u00bd",
+ "\u0120aspirations",
+ "\u0120Aer",
+ "\u0120\u00d0\u00b3\u00d0\u00be\u00d0\u00b2\u00d0\u00be\u00d1\u0122\u00d0\u00b8\u00d1\u0124\u00d1\u012e",
+ "\u0120Qian",
+ "\u00e5\u00a6\u012a",
+ "\u0120compromised",
+ "\u0120yolk",
+ "\u00d0\u00bb\u00d0\u00b0\u00d1\u0123\u00d1\u0124",
+ "\u0120hemen",
+ "rove",
+ "dens",
+ "\u0120\u00d0\u00ba\u00d0\u00be\u00d0\u00bc\u00d0\u00bc\u00d0\u00b5\u00d0\u00bd\u00d1\u0124",
+ "\u0120---",
+ "\u0120fluores",
+ "\u00d0\u00bd\u00d0\u00be\u00d1\u0123",
+ "\u0120Liverpool",
+ "\u0120\u00d1\u0123\u00d0\u00be\u00d0\u00b1\u00d0\u00be\u00d0\u00b9",
+ "\u0120Zwe",
+ "\u0120lumin",
+ "\u0120OG",
+ "\u00e1\u00b8",
+ "holm",
+ "profits",
+ "SN",
+ "\u0120proportions",
+ "\u0120mica",
+ "\u0120Boh",
+ "\u0120Atlas",
+ "\u0120unsure",
+ "\u0120touring",
+ "\u0120nied",
+ "\u0120t\u00c4\u013b",
+ "\u0120imperative",
+ "\u0120demek",
+ "\u0120Sheriff",
+ "rance",
+ "\u0120homeland",
+ "\u0120Hail",
+ "\u0120Ganz",
+ "ymm",
+ "Mon",
+ "\u00e5\u0128\u00b7",
+ "vida",
+ "\u0120desarroll",
+ "\u00e6\u012c\u0122",
+ "\u0120intriguing",
+ "\u0120Hugo",
+ "\u0120\u00e3\u0124\u0124",
+ "\u00e9\u00ac",
+ "\u00d0\u00b0\u00d1\u0128",
+ "\u0120Wi\u00c4\u013bc",
+ "atted",
+ "\u0120\u00ec\u0137\u0126\u00eb\u012d\u012a\u00ea\u00b3\u0142",
+ "\u0120Vari",
+ "\u00c3\u00a1d",
+ "\u0120surreal",
+ "\u0120disparities",
+ "\u0120m\u00c3\u00b3",
+ "ullen",
+ "\u0120\u00ec\u0140\u012a\u00eb\u012d\u00a4\u00ea\u00b3\u0142",
+ "\u0120\u00d0\u00bf\u00d0\u00be\u00d0\u00b6\u00d0\u00b0\u00d0\u00bb\u00d1\u0125\u00d0\u00b9\u00d1\u0123\u00d1\u0124\u00d0\u00b0",
+ "\u0120mains",
+ "\u0120eject",
+ "\u0120methane",
+ "\u0120marginalized",
+ "\u0120chilli",
+ "r\u00c3\u00a8s",
+ "\u0120yem",
+ "\u00e4\u00bd\u0142\u00e6\u013a\u00af",
+ "\u0120Chun",
+ "\u0120debts",
+ "\u0120downloading",
+ "\u0120Athens",
+ "isierung",
+ "ryn",
+ "\u0120tekn",
+ "\u0120Quindi",
+ "\u00e9\u013e\u0122",
+ "\u0120taraf",
+ "\u0120h\u00c3\u00a9",
+ "\u0120consciously",
+ "\u0120fixes",
+ "uckle",
+ "may\u00c4\u00b1n",
+ "\u0120frei",
+ "\u0120spa",
+ "\u0120\u00ec\u00a7\u0126\u00ed\u0138\u012b",
+ "\u0120\u00d8\u00a7\u00d9\u0126\u00d8\u00b0",
+ "\u0120\u00d1\u0125\u00d0\u00ba",
+ "lett",
+ "\u0120olmu\u00c5\u0141",
+ "\u0120cheesy",
+ "\u00e0\u00b8\u00b2\u00e0\u00b8\u0123",
+ "naire",
+ "\u0120widen",
+ "\u0120lien",
+ "\u0120escaping",
+ "iggs",
+ "\u0120Blick",
+ "c\u00c4\u0127",
+ "\u0120\u00ec\u0126\u013e\u00eb",
+ "\u0120\u00d7\u0136\u00d7\u00a1",
+ "\u0120\u00d0\u00b2\u00d0\u00bf\u00d0\u00b5\u00d1\u0122",
+ "ophone",
+ "iell",
+ "\u0120SUBSCRI",
+ "\u0120lions",
+ "\u0120\u00ea\u00b7\u00b8\u00ea\u00b2\u0125",
+ "\u0120inspires",
+ "\u0120guarantees",
+ "\u0120come\u00c3\u00a7a",
+ "\u0120Growing",
+ "\u0120neglig",
+ "\u0120Frankf",
+ "\u0120gegeben",
+ "\u0120\u00c4\u0133\u00e1\u00ba\u00a7u",
+ "\u0120endlich",
+ "\u0120\u00ec\u012f\u00a8",
+ "\u0120TT",
+ "\u0120Lith",
+ "\u00cf\u0122\u00ce\u00b1",
+ "astern",
+ "\u0120Azer",
+ "\u0120lunar",
+ "hic",
+ "\u0120\u00d0\u00bd\u00d0\u00b0\u00d1\u0122\u00d0\u00be\u00d0\u00b4",
+ "\u0120nenhum",
+ "\u00e8\u00b7\u0133",
+ "\u0120Salvador",
+ "\u0120Progress",
+ "\u0120privileges",
+ "\u0120\u00eb\u0131\u013b\u00ec\u0137\u012a",
+ "\u0120antagon",
+ "\u0120Impf",
+ "\u0120descub",
+ "\u0120Lei",
+ "\u0120\u00ec\u0125\u012a\u00eb\u00a1\u013e",
+ "\u00d1\u0129\u00d0\u00b5",
+ "\u0120d\u00c3\u00b3lares",
+ "\u0120Meghan",
+ "\u0120Wire",
+ "too",
+ "aying",
+ "usc",
+ "\u0120tud",
+ "\u0120appeals",
+ "educ",
+ "\u0120pane",
+ "\u0120ji",
+ "\u0120decks",
+ "\u0120Alter",
+ "\u0120\u00e5\u00b0\u00b1",
+ "\u00ec\u0126\u00a4",
+ "\u00e5\u012a\u0128\u00e9\u0132\u013a",
+ "\u0120productions",
+ "\u0120WILLIAM",
+ "\u0120implied",
+ "\u0120fulfillment",
+ "\u0120Aah",
+ "\u0120saja",
+ "xus",
+ "\u0120\u00ce\u013c\u00ce\u00b1\u00ce\u00b9",
+ "\u00c3\u0142s",
+ "ucch",
+ "\u00d0\u00be\u00d0\u00ba\u00d0\u00be",
+ "\u0120Discord",
+ "\u0120SY",
+ "jsk",
+ "\u0120Wallace",
+ "unction",
+ "Daniel",
+ "\u0120k\u00c3\u00b6t",
+ "ijah",
+ "\u0120marche",
+ "\u0120disgr",
+ "\u0120mungkin",
+ "\u0120alma",
+ "\u00b3\u00b5",
+ "\u0120extensively",
+ "\u0120Floren",
+ "\u0120Allison",
+ "\u00e3\u0124\u00b1",
+ "\u00d9\u012c\u00d9\u0127",
+ "\u0120juven",
+ "\u0120Renaissance",
+ "\u0120fundraising",
+ "\u0120Chaos",
+ "\u0120paraly",
+ "\u0120narrator",
+ "\u0120ecosystems",
+ "Ash",
+ "\u0120mitigation",
+ "\u0120Aujourd",
+ "\u0120Idee",
+ "!,",
+ "\u0120\u00c2\u00bd",
+ "\u0120landlord",
+ "\u0120defects",
+ "\u0120acre",
+ "ulsive",
+ "\u0120algae",
+ "pek",
+ "\u0120emba",
+ "\u0120Roc",
+ "\u00e9\u013d\u00a2",
+ "ksom",
+ "\u00c3\u00a4che",
+ "\u0120leuk",
+ "\u0120leveraging",
+ "\u0120\u00ea\u00b7\u00b8\u00eb\u0142\u0129\u00ec\u00a7\u0122",
+ "\u0120Palm",
+ "\u0120\u00c3\u00a4ven",
+ "\u0120lis",
+ "\u0120Insp",
+ "\u0120Rita",
+ "\u0120Abb",
+ "ithm",
+ "\u0120supervision",
+ "\u0120revisit",
+ "\u0120pi\u00c4\u013b",
+ "\u0120euh",
+ "\u0120fades",
+ "\u0120motto",
+ "\u00e5\u012f\u00a1",
+ "\u00d0\u00b5\u00d0\u00b7\u00d0\u00b6",
+ "\u0120Shim",
+ "\u0120relevance",
+ "\u0120oo",
+ "\u0120ostat",
+ "nica",
+ "\u0120choix",
+ "\u0120Faculty",
+ "\u0120\u00ec\u00a4\u0133\u00ec\u0139\u0132",
+ "\u0120Above",
+ "\u0120\u00d0\u00bd\u00d0\u00b5\u00d0\u00b1\u00d0\u00be\u00d0\u00bb\u00d1\u012e\u00d1\u012a",
+ "\u0120sequencing",
+ "\u0120nutrient",
+ "\u0120conquered",
+ "\u0120digestive",
+ "\u0120backdrop",
+ "\u0120Lori",
+ "ailable",
+ "Game",
+ "\u0120neglected",
+ "omorph",
+ "illah",
+ "\u0120kne",
+ "\u0120siit\u00c3\u00a4",
+ "\u0120workspace",
+ "\u0120Venice",
+ "\u0120Kne",
+ "\u00d1\u012b\u00d0\u00be",
+ "\u0127\u0122",
+ "\u0120Hass",
+ "\u0120vita",
+ "\u013f\u00bc\u00eb\u00a9\u00b4",
+ "\u0120lays",
+ "\u00c3\u00aancias",
+ "\u00c3\u00a9rica",
+ "\u0120Ll",
+ "\u00e6\u00b1\u0124",
+ "\u0120Coca",
+ "\u0120WHY",
+ "\u00e8\u012a\u0140",
+ "\u0120routing",
+ "\u0120permissions",
+ "\u0120dings",
+ "prend",
+ "program",
+ "\u0120crocod",
+ "bral",
+ "AAAAAAAA",
+ "agit",
+ "\u0120N\u00c3\u00a4",
+ "\u0120gekommen",
+ "atten",
+ "\u0120referenced",
+ "\u0120pairing",
+ "\u0120Partner",
+ "\u0120Coronavirus",
+ "\u00d1\u0138\u00d1\u0123",
+ "\u00e8\u00bd\u012b",
+ "\u0120\u00d7\u0136\u00d7\u0135",
+ "\u0120espec\u00c3\u0143fic",
+ "arsi",
+ "quelle",
+ "\u0120spontaneous",
+ "\u00e7\u0128\u00b1",
+ "\u0120\u00ea\u00b2\u0125\u00ec\u013f\u0126",
+ "\u0120\u00d0\u0141\u00d0\u00be\u00d1\u0123\u00d0\u00bb\u00d0\u00b5",
+ "\u0120\u00d8\u00a7\u00d9\u0126\u00d8\u00af",
+ "\u0120Shout",
+ "\u0120\u00d0\u00bd\u00d0\u00b0\u00d0\u00bb",
+ "\u0120disguise",
+ "\u0120Jord",
+ "\u0120wee",
+ "\u0120miejsc",
+ "\u0120serum",
+ "\u0120plaisir",
+ "\u0120credible",
+ "\u0120b\u00c3\u00a5",
+ "\u0120AJ",
+ "mares",
+ "\u0120rods",
+ "\u0120eran",
+ "\u00e3\u0123\u00be\u00e3\u0123\u0124",
+ "\u0120p\u00c3\u00a4\u00c3\u00a4",
+ "\u0120UA",
+ "\u0120Unknown",
+ "\u0120\u00d9\u0126\u00d9\u0127",
+ "\u0120Rabbi",
+ "\u0120laat",
+ "\u0120hairstyle",
+ "\u0120\u00d8\u00ba",
+ "\u00e9\u0123\u012d",
+ "\u0120cach",
+ "\u0120Writing",
+ "\u00d0\u00be\u00d1\u0129\u00d0\u00ba\u00d0\u00b8",
+ "abad",
+ "\u0120straighten",
+ "--\"",
+ "wife",
+ "\u0120hottest",
+ "\u0120punya",
+ "\u0120Fashion",
+ "griff",
+ "\u0120QR",
+ "otch",
+ "\u0120\u00d0\u013e\u00d0\u00be\u00d0\u00b6\u00d0\u00b5\u00d1\u0124",
+ "Cloud",
+ "\u0120Strike",
+ "\u0120Hein",
+ "\u0120\u00e7\u013e\u0141\u00e7\u013c\u0126",
+ "\u0120lei",
+ "\u0120Flow",
+ "wegs",
+ "\u0120habr",
+ "\u00e5\u012b\u013d\u00e5\u012b\u013d",
+ "nahme",
+ "\u00cc\u0123",
+ "\u0120pleasing",
+ "opping",
+ "\u0120\u00ea\u00b5\u00ac\u00eb\u0131\u0127",
+ "\u0120dran",
+ "\u0120bangs",
+ "\u012079",
+ "\u0120sket",
+ "\u0120caval",
+ "\u0120Macron",
+ "\u0120weighted",
+ "\u0120muted",
+ "\u0120nuestras",
+ "EEP",
+ "\u0120mathematic",
+ "\u0120MRI",
+ "agus",
+ "\u0120therapies",
+ "\u00ce\u00b8\u00ce\u00b5",
+ "\u0120unpl",
+ "\u0120commencer",
+ "full",
+ "\u0120towels",
+ "\u0120prue",
+ "\u0120licenses",
+ "\u00d7\u013d\u00d7\u0137\u00d7\u013e",
+ "\u0120\u00d0\u0141\u00d0\u00be\u00d1\u0129\u00d0\u00b5\u00d0\u00bc\u00d1\u0125",
+ "\u0120pointless",
+ "Bye",
+ "\u0120eligibility",
+ "\u0120scrape",
+ "\u0120abusive",
+ "\u0120Mant",
+ "\u0120jeunes",
+ "tal",
+ "\u0120Princip",
+ "\u0120Orthodox",
+ "\u0120melod",
+ "\u0120\u00d0\u00bc\u00d0\u00b0\u00d1\u0124\u00d0\u00b5\u00d1\u0122\u00d0\u00b8",
+ "\u0120prosecutor",
+ "\u0120opioid",
+ "\u0120\u00d1\u0125\u00d0\u00b2\u00d0\u00b5\u00d1\u0122",
+ "\u0120Been",
+ "\u0120\u00ec\u0142\u0133\u00ec\u00a2\u0127",
+ "\u0120dynasty",
+ "\u0120ajuda",
+ "\u0120entreg",
+ "\u0120weighed",
+ "\u0120eure",
+ "\u0120Bem",
+ "\u0120abnormal",
+ "82",
+ "\u0120JR",
+ "\u0120Akt",
+ "\u0120Bri",
+ "\u00c3\u00bat",
+ "\u0120stagn",
+ "!*",
+ "\u0120wegen",
+ "\u0120leaking",
+ "\u0120Words",
+ "\u0120Mau",
+ "\u0120vue",
+ "\u0120Liam",
+ "\u00d0\u00b0\u00d0\u00bd\u00d0\u00b8\u00d0\u00b5\u00d0\u00bc",
+ "\u0120clinicians",
+ "\u0120Pump",
+ "\u0120f\u00c3\u00b6rst",
+ "?...",
+ "\u0120automotive",
+ "\u0120Owen",
+ "zusagen",
+ "\u0120Hundred",
+ "\u0120decentralized",
+ "\u0120bulbs",
+ "\u0120\u00d7\u013e\u00d7\u013d",
+ "\u0120provinces",
+ "\u0120Milan",
+ "81",
+ "kas",
+ "\u0120\u00eb\u0135\u00a3",
+ "\u0120for\u00c3\u00a7a",
+ "\u0120rightly",
+ "\u00e5\u00b3\u00b6",
+ "r\u00c4\u0127",
+ "\u0120venues",
+ "\u0120wai",
+ "\u0120predicting",
+ "\u0120WiFi",
+ "\u0120\u00ea\u00b6\u0123\u00ea\u00b8\u012a",
+ "\u00d8\u00b1\u00d9\u012a",
+ "\u0120\u00d7\u0136\u00d7\u0138",
+ "century",
+ "\u0120gradual",
+ "\u0120Probleme",
+ "\u0120\u00ec\u0139\u0127",
+ "\u0120coping",
+ "\u0120Brus",
+ "\u0120peanuts",
+ "irtschaft",
+ "\u0120\u00d0\u00b7\u00d0\u00b0\u00d0\u00bb",
+ "\u0120Troy",
+ "\u0120sperm",
+ "\u0120Mitar",
+ "\u0120T\u00c3\u00bcrkiye",
+ "grand",
+ "\u00a6\u0143",
+ "\u0120\u00d7\u0140\u00d7\u00a1",
+ "\u0120pans",
+ "\u0120Knowledge",
+ "berly",
+ "\u0120\u00d0\u0137\u00d0\u00b3\u00d0\u00be",
+ "\u0120danced",
+ "\u0120Frost",
+ "\u0120Burg",
+ "\u0120biting",
+ "\u00ec\u0142\u0137\u00ec\u013f\u0126",
+ "meal",
+ "\u0120heroic",
+ "\u0120motherboard",
+ "\u0120Licht",
+ "\u00e3\u0123\u00a3\u00e3\u0123",
+ "llan",
+ "\u00d0\u00b0\u00d0\u00b9\u00d0\u00bd",
+ "\u0120\u00d1\u0122\u00d1\u0131\u00d0\u00b4",
+ "\u0120\u00e0\u00b9\u0122\u00e0\u00b8",
+ "onen",
+ "irie",
+ "Art",
+ "rang",
+ "\u00ce\u00bd\u00ce\u00b7",
+ "\u0120newborn",
+ "\u0120amis",
+ "\u0120\u00d8\u00a7\u00d9\u012a\u00d8\u00b1",
+ "\u0120sophom",
+ "\u0120Careful",
+ "\u0120prospects",
+ "ensen",
+ "\u0120thrill",
+ "\u0120Vi\u00e1\u00bb\u0129t",
+ "Adam",
+ "rition",
+ "entric",
+ "uden",
+ "\u0120certificates",
+ "\u0120ashes",
+ "\u00e8\u00aa\u00bf",
+ "playing",
+ "\u0120sadece",
+ "\u0120ost",
+ "\u0120airplanes",
+ "\u00d1\u0122\u00d0\u00be\u00d0\u00ba",
+ "oner",
+ "\u0120magnesium",
+ "\u0120goddamn",
+ "\u01201972",
+ "\u0120Schule",
+ "\u0120temat",
+ "\u0120partout",
+ "\u00e0\u00af\u0124",
+ "\u0120inve",
+ "\u0120Scientists",
+ "\u0120Hudson",
+ "winning",
+ "ceksin",
+ "\u0120congressional",
+ "oru",
+ "\u0120ropes",
+ "\u00d0\u00b2\u00d0\u00b5\u00d0\u00b4",
+ "\u0120madre",
+ "\u0120ferry",
+ "\u0120Cohen",
+ "\u0120Pred",
+ "\u0120vagy",
+ "\u0120\u00d0\u00b1\u00d0\u00b5\u00d1\u0123\u00d0\u00bf",
+ "\u0120multim",
+ "\u0120drainage",
+ "\u0120simulator",
+ "giggles",
+ "\u0120Stadium",
+ "\u00d0\u00be\u00d0\u00b1\u00d1\u012b",
+ "\u0120notices",
+ "\u0120crawling",
+ "\u0120groupe",
+ "\u00e5\u0131\u00b8",
+ "\u0120kto\u00c5\u013d",
+ "\u0120Yoga",
+ "\u0120medida",
+ "\u0120\u00d1\u0127\u00d0\u00b2\u00d0\u00b0\u00d1\u0124",
+ "\u0120Lite",
+ "\u0120rav",
+ "orama",
+ "\u0120discord",
+ "\u0120DIRE",
+ "\u0120teh",
+ "\u0120Nurs",
+ "\u00e7\u00b2\u012b",
+ "\u0120pitched",
+ "\u0120barking",
+ "\u0120Coke",
+ "wiad",
+ "\u0120populated",
+ "\u00e9\u013b\u00a4",
+ "pelled",
+ "\u0120\u00d0\u00b1\u00d0\u00be\u00d0\u00b3",
+ "\u0120pewno",
+ "\u0120Cube",
+ "\u0120recruited",
+ "\u00e9\u0122\u013b\u00e7\u00a8\u00ae",
+ "\u0120Cara",
+ "\u00c4\u00b1\u00c4\u0141\u00c4\u00b1n\u00c4\u00b1",
+ "imated",
+ "\u0120\u00d1\u012a\u00d0\u00ba\u00d0\u00be\u00d0\u00bb",
+ "icional",
+ "\u0120\u00d0\u00bf\u00d1\u0122\u00d0\u00be\u00d1\u0126",
+ "\u0120contamination",
+ "\u0120\u00c3\u00baltimos",
+ "\u0120fearful",
+ "\u0120elephants",
+ "usi",
+ "\u0120iTunes",
+ "\u0120Swami",
+ "\u00ea\u00bc",
+ "\u0120\u00ec\u0126\u00a4\u00eb\u00aa\u0127",
+ "\u0120Richards",
+ "\u0120magnets",
+ "\u0120Richtung",
+ "\u0120Legion",
+ "\u00e8\u0131\u013e",
+ "\u0120kitty",
+ "\u0120kissed",
+ "\u0120watering",
+ "\u0120cono",
+ "\u0120Palestine",
+ "idir",
+ "\u0120maze",
+ "\u0120fluids",
+ "\u0120Producer",
+ "\u0120Krsna",
+ "\u00e5\u00a5\u00bd\u00e5\u0137\u00a6",
+ "laf",
+ "\u0120\u00d7\u0132\u00d7\u0137",
+ "\u0120miesz",
+ "\u0120Xing",
+ "ointed",
+ "sein",
+ "\u0120Fuk",
+ "\u0120Depression",
+ "\u0120Duty",
+ "\u0120Panther",
+ "\u0120sund",
+ "\u0120refere",
+ "\u0120exclusion",
+ "\u0120naval",
+ "\u0120Winston",
+ "\u0120slogan",
+ "\u0120hypothetical",
+ "\u0120elevate",
+ "\u00eb\u0142\u00b9",
+ "\u0120cabe\u00c3\u00a7a",
+ "\u0120Gesund",
+ "meter",
+ "\u0120\u00ec\u0137\u0126\u00eb\u012d\u012a\u00eb\u00a9\u00b4",
+ "\u0120cloudy",
+ "\u00e2\u0122\u00a6?",
+ "\u0120Schritt",
+ "\u0120JS",
+ "\u00ec\u012f",
+ "\u0120Springs",
+ "\u0120Batter",
+ "\u00b7\u00b0",
+ "\u0120tailor",
+ "\u0120PTSD",
+ "\u0120Gent",
+ "\u0120ba\u00c4\u0141",
+ "\u0120spatula",
+ "\u0120cray",
+ "\u0120Legisl",
+ "\u0120s\u00c3\u00ba",
+ "\u0120leve",
+ "\u00e0\u00b8\u00b2\u00e0\u00b8\u00a1",
+ "\u0120erad",
+ "\u0120dong",
+ "\u0120derm",
+ "\u0120Banks",
+ "icho",
+ "\u00e5\u0127\u012a\u00e7\u0136\u0141",
+ "\u0120Franz",
+ "ravel",
+ "\u00e9\u0123\u0136",
+ "\u00d0\u00be\u00d0\u00bb\u00d0\u00be",
+ "\u0120flute",
+ "\u0120Ek",
+ "\u0120joyful",
+ "\u0120chased",
+ "\u0120Large",
+ "Over",
+ "\u0120entrepreneurial",
+ "\u0120considers",
+ "\u00d1\u0125\u00d0\u00b5\u00d0\u00bc",
+ "opa",
+ "\u0120dormir",
+ "\u0120Elementary",
+ "\u0120przypad",
+ "\u00d1\u0125\u00d1\u0123\u00d0\u00ba\u00d0\u00b0",
+ "\u0120\u00d0\u00be\u00d1\u0129\u00d0\u00b5\u00d1\u0122",
+ "ugene",
+ "\u0120tenido",
+ "\u0120lugares",
+ "\u00eb\u00a5",
+ "\u0120\u00d1\u0129\u00d0\u00b0\u00d1\u0123\u00d1\u0124",
+ "\u0120sao",
+ "\u0120braid",
+ "\u0120Vere",
+ "\u0120Reich",
+ "\u0120Poss",
+ "\u0120inan",
+ "wand",
+ "ref",
+ "\u0120montrer",
+ "\u01201981",
+ "\u00e7\u0137\u00aa",
+ "as\u00c4\u00b1nda",
+ "\u0120chrome",
+ "\u0120Trinity",
+ "\u0120exploitation",
+ "\u0120Sense",
+ "\u0120CMS",
+ "\u0120Noble",
+ "\u0120\u00ec\u0126\u0142\u00ed\u0125\u013f",
+ "\u0120swelling",
+ "electronic",
+ "]?",
+ "\u0120brushing",
+ "\u0120liquidity",
+ "\u0120Hook",
+ "\u0120Connor",
+ "\u0120Alum",
+ "\u0120gucken",
+ "suite",
+ "\u0120wiele",
+ "\u0120barrels",
+ "\u0120Regel",
+ "\u0120Ment",
+ "\u0120Trip",
+ "\u0120Brush",
+ "\u0120Erik",
+ "urate",
+ "\u00c9\u013br",
+ "\u0120Cyr",
+ "ouble",
+ "\u0120Becca",
+ "\u0120passwords",
+ "\u00c5\u00b1",
+ "borg",
+ "\u0120vendo",
+ "\u0120Claus",
+ "\u0120Faz",
+ "indest",
+ "\u0120deceased",
+ "\u0120comparisons",
+ "\u0120LCD",
+ "\u0120Pork",
+ "\u0120eventual",
+ "\u0120patreon",
+ "\u0120inability",
+ "\u0120extinction",
+ "\u0120\u00ec\u00a2\u012d\u00ec\u0137\u0126\u00ed\u0137\u013a\u00eb\u012c\u0136",
+ "\u0120\u00d1\u0123\u00d0\u00be\u00d1\u0123",
+ "aju",
+ "\u0120\u00d7\u0133\u00d7\u0132\u00d7",
+ "\u0120sofort",
+ "\u0120destined",
+ "\u0120Rin",
+ "\u0120mouths",
+ "\u0120Nat\u00c3\u00bcrlich",
+ "\u0120preserving",
+ "\u0120limp",
+ "\u00e9\u00bb\u00a8",
+ "ocused",
+ "\u00d0\u00b8\u00d0\u00bd\u00d0\u00b3",
+ "\u0120exposing",
+ "\u0120\u00ce\u00be",
+ "\u00eb\u012f",
+ "laugh",
+ "\u0120hiss",
+ "\u00e3\u0123\u0142\u00e3\u0123\u012d\u00e3\u0124\u012b",
+ "\u0120indie",
+ "\u0120detal",
+ "\u00d1\u0122\u00d0\u00b0\u00d0\u00b2\u00d1\u0123\u00d1\u0124\u00d0\u00b2",
+ "\u0120tr\u00c3\u00aan",
+ "\u00e6\u0137\u00b0",
+ "\u0120ogni",
+ "\u0120simplemente",
+ "\u01201978",
+ "\u0120goo",
+ "\u01201967",
+ "\u0120genug",
+ "h\u00c3\u00b6",
+ "\u0120hist\u00c3\u00b3",
+ "\u00e5\u00ae\u0141",
+ "\u0120lobster",
+ "cendo",
+ "\u0120teil",
+ "\u0120allevi",
+ "0000",
+ "OLD",
+ "\u0120pesos",
+ "\u0120bonuses",
+ "\u0120ami",
+ "\u0120revival",
+ "\u0120Horse",
+ "\u0120sack",
+ "Talk",
+ "\u0120mulher",
+ "\u0120\u00d0\u00bf\u00d0\u00be\u00d1\u0123\u00d1\u0124\u00d0\u00be\u00d1\u0131\u00d0\u00bd",
+ "\u0120Hood",
+ "Huh",
+ "\u0120\u00eb\u00b6\u0123",
+ "\u0120hyung",
+ "\u0120Meeting",
+ "\u0120importa",
+ "\u0120\u00ec\u00b0\u00be\u00ec\u0137\u0126",
+ "\u0120Vern",
+ "\u0120stripped",
+ "\u0120refuses",
+ "\u0120qualifications",
+ "opl",
+ "\u0122\u00eb\u0131\u0126",
+ "ix\u00c3\u0143",
+ "\u0120diab",
+ "itime",
+ "flows",
+ "\u0120inac",
+ "\u0120Gong",
+ "\u0120meaningless",
+ "\u0120courageous",
+ "\u0120microbi",
+ "azy",
+ "hist",
+ "\u0120volunteering",
+ "VIE",
+ "\u0120violated",
+ "\u0120sympathy",
+ "\u0120Edit",
+ "\u00e5\u00a5\u00bd\u00e5\u0125\u0131",
+ "electric",
+ "product",
+ "\u0120pandemia",
+ "\u0120geometric",
+ "\u0120Convers",
+ "gre",
+ "\u0120glut",
+ "isted",
+ "\u0120\u00d8\u00a7\u00d9\u0126\u00d9\u0125",
+ "\u0120Chain",
+ "\u0120Present",
+ "\u0120Yin",
+ "\u0120\u00d1\u0123\u00d0\u00be\u00d0\u00b3",
+ "\u0120Vlog",
+ "\u0120\u00ec\u0138\u00b4\u00eb\u00a8\u00b8",
+ "\u0120donn",
+ "\u0120hitch",
+ "ucking",
+ "\u00e3\u0123\u012c\u00e3\u0123\u0126",
+ "wald",
+ "risk",
+ "\u0120hari",
+ "\u0120Kens",
+ "\u0120Idol",
+ "\u0120\u00d0\u00b2\u00d0\u00bd\u00d0\u00b8\u00d0\u00bc\u00d0\u00b0\u00d0\u00bd\u00d0\u00b8\u00d0\u00b5",
+ "\u0120todd",
+ "\u0120smashed",
+ "\u0120invari",
+ "\u0120\u00d0\u00ba\u00d0\u00be\u00d0\u00bd\u00d1\u0124\u00d1\u0122",
+ "\u0120autistic",
+ "\u00ec\u0140\u00a5\u00eb\u012d\u013a",
+ "Res",
+ "\u00d0\u00b4\u00d1\u012d",
+ "chau",
+ "\u0120selv",
+ "\u0120h\u00c3\u00a4tten",
+ "\u00e0\u00a4\u00bf",
+ "\u0120expects",
+ "\u00cf\u0123\u00ce\u00b7",
+ "\u0120a\u00c3\u00a7\u00c4\u00b1k",
+ "\u0120HTTP",
+ "le\u00c5\u0141",
+ "\u0120sweeping",
+ "\u0120Beta",
+ "\u0120counterparts",
+ "abile",
+ "\u0120Sims",
+ "Cs",
+ "\u0120repar",
+ "squ",
+ "\u0120provincial",
+ "\u0120shareholders",
+ "\u0120runter",
+ "\u0120gedacht",
+ "\u0120Teen",
+ "\u0120grands",
+ "\u00e7\u0136\u00a2",
+ "agles",
+ "\u0120rocky",
+ "vens",
+ "\u0120rivals",
+ "unal",
+ "\u0120reacts",
+ "\u00eb\u00a9",
+ "\u0120mercury",
+ "\u0120Luigi",
+ "\u0120\u00d0\u00be\u00d0\u00b3",
+ "\u0120JUST",
+ "\u0120lod",
+ "\u0120cortex",
+ "wig",
+ "\u0120lakh",
+ "\u00ec\u00a4\u0133\u00ec\u0139\u0132",
+ "\u0120Vic",
+ "\u0120Mund",
+ "\u0120mapped",
+ "\u0120Dell",
+ "\u0120Druck",
+ "\u0120lifes",
+ "\u00d0\u00b0\u00d0\u00bb\u00d1\u012e\u00d0\u00bd\u00d0\u00be\u00d0\u00b5",
+ "ividual",
+ "ad\u00c4\u00b1m",
+ "\u0120atrav",
+ "\u0120Flug",
+ "\u0120Klein",
+ "\u00ea\u00b1\u00b0\u00ec\u0137\u00bc",
+ "\u00e0\u00b8\u00ab\u00e0\u00b8\u013b",
+ "\u0120appli",
+ "\u00e0\u00ae\u00be?",
+ "\u00c3\u00bcyorum",
+ "\u0120\u00d0\u00b8\u00d0\u00bd\u00d1\u0124\u00d0\u00b5\u00d1\u0122\u00d0\u00b5\u00d1\u0123\u00d0\u00bd\u00d0\u00be",
+ "\u0120disinfect",
+ ">-",
+ "\u0120champagne",
+ "\u0120kla",
+ "opers",
+ "Trans",
+ "\u0120Desert",
+ "\u0120cultivate",
+ "\u0120Fucking",
+ "idelity",
+ "\u0120\u00d1\u0124\u00d0\u00b0\u00d0\u00bd",
+ "\u0120incub",
+ "\u0120temu",
+ "\u0120learner",
+ "founder",
+ "\u0120Syl",
+ "\u00e3\u0124\u0122",
+ "\u0120fato",
+ "zier",
+ "\u0120\u00ec\u0139\u0128\u00ec\u013f\u00b4",
+ "\u0120\u00ec\u012a\u00a8",
+ "\u0120psycho",
+ "\u0120\u00d1\u0124\u00d0\u00b5\u00d0\u00bb\u00d0\u00b5\u00d1\u0126",
+ "\u0120regarde",
+ "\u0120representations",
+ "\u0120litigation",
+ "\u0120spann",
+ "ults",
+ "bior",
+ "\u00e8\u00a6\u012d\u00e3\u0123\u00a6",
+ "\u00e4\u00b8\u012f\u00e5\u00a4\u013c",
+ "\u0120Survey",
+ "\u0120LEDs",
+ "\u0120tr\u00c3\u00a4",
+ "\u0120l\u00c3\u00aan",
+ "\u0120antioxid",
+ "\u00d0\u00b5\u00d1\u0122\u00d0\u00be\u00d0\u00bc",
+ "\u0120induction",
+ "\u0120fooled",
+ "\u00c3\u00a4tzlich",
+ "\u0120\u00d0\u00b3\u00d0\u00be\u00d0\u00b2\u00d0\u00be\u00d1\u0122\u00d1\u0131\u00d1\u0124",
+ "\u0120Fact",
+ "umbai",
+ "\u0120wiggle",
+ "NOUN",
+ "\u0120d\u00c3\u00a9velopp",
+ "\u0120Claro",
+ "\u0120\u00ec\u00b8",
+ "\u00eb\u00ac",
+ "\u00e3\u0123\u00aa\u00e3\u0124\u0135\u00e3\u0123\u0142",
+ "\u0120accumulate",
+ "\u0120maintains",
+ "\u00eb\u0126",
+ "\u0120Fighter",
+ "\u00ed\u0128\u0142",
+ "\u0120matin",
+ "\u0120coupon",
+ "\u0120stunt",
+ "\u0120debuted",
+ "\u00e5\u00be\u0127\u00e3\u0123\u00a3\u00e3\u0123\u00a6",
+ "\u0120prag",
+ "\u00d0\u00b8\u00d0\u00b2\u00d0\u00b0\u00d0\u00b5\u00d0\u00bc",
+ "73",
+ "\u0120expres",
+ "\u0120\u00ec\u013a\u00a4\u00eb\u00b9\u0142",
+ "\u0120\u00d0\u00bf\u00d0\u00b5\u00d1\u0122\u00d1\u0123\u00d0\u00be\u00d0\u00bd",
+ "\u0120calculus",
+ "\u0120abrupt",
+ "\u0120Inspector",
+ "ourt",
+ "\u00e6\u0138\u013b",
+ "\u00c5\u00baniej",
+ "intense",
+ "Ba",
+ "\u0120lounge",
+ "\u0120asthma",
+ "\u0120Hi\u00c3\u00a7",
+ "\u00aa\u00bb",
+ "\u0120editorial",
+ "\u0120seize",
+ "\u0120k\u00c4\u00b1r",
+ "\u0120mouve",
+ "\u0120tierra",
+ "\u0120testosterone",
+ "\u0120rh",
+ "\u0120Kingston",
+ "ELLE",
+ "\u0120Representative",
+ "\u01201974",
+ "\u0120iba",
+ "Ts",
+ "\u0120sorta",
+ "\u0120(?)",
+ "\u0120\u00d8\u00aa\u00d9\u012a",
+ "\u0120\u00eb\u0124\u00b4\u00eb\u0142\u00a4",
+ "\u0120bekommt",
+ "\u0120spiritually",
+ "\u0120distorted",
+ "Mad",
+ "\u0120reim",
+ "\u00c3\u00a1nh",
+ "\u0120Ottoman",
+ "\u0120Relig",
+ "\u0120Els",
+ "\u0120retained",
+ "\u0120Laughs",
+ "\u00e6\u0122\u00bb",
+ "\u0120SAS",
+ "\u0120\u00d0\u00ba\u00d0\u00be\u00d0\u00bb\u00d0\u00b8\u00d1\u0129\u00d0\u00b5\u00d1\u0123\u00d1\u0124\u00d0\u00b2\u00d0\u00be",
+ "\u00d7\u0137\u00d7\u00aa\u00d7\u00a8",
+ "\u0120innovate",
+ "\u0120kork",
+ "\u0120\u00d1\u0122\u00d0\u00b0\u00d1\u0123\u00d1\u0123\u00d0\u00ba\u00d0\u00b0\u00d0\u00b7\u00d1\u012d\u00d0\u00b2",
+ "ondere",
+ "ivi",
+ "aye",
+ "ounty",
+ "\u0120\u00d0\u00bf\u00d0\u00be\u00d0\u00bb\u00d1\u0125\u00d1\u0129\u00d0\u00b0\u00d0\u00b5\u00d1\u0124\u00d1\u0123\u00d1\u0131",
+ "\u0120buns",
+ "\u00e5\u0127\u00ab",
+ "\u0120y\u00c3\u00bczden",
+ "\u0120surgeries",
+ "\u00d8\u00a3\u00d9\u0128",
+ "\u0120bankruptcy",
+ "welt",
+ "\u0120siamo",
+ "\u0120darkest",
+ "\u0120Hann",
+ "gga",
+ "\u0120formas",
+ "\u0120Dj",
+ "named",
+ "\u0120shields",
+ "ueller",
+ "\u0120Few",
+ "\u0120lace",
+ "\u0120furious",
+ "\u0120YU",
+ "\u0120societal",
+ "\u0120judgement",
+ "\u0120Dos",
+ "\u0120jab",
+ "laws",
+ "\u0120reinvent",
+ "\u0120Katherine",
+ "\u0120Choi",
+ "adows",
+ "\u0120rans",
+ "oden",
+ "\u0120Midwest",
+ "n\u00c4\u00b1n",
+ "\u0120deport",
+ "\u0120Dip",
+ "\u00e7\u00b4\u0127",
+ "\u0120atenci\u00c3\u00b3n",
+ "\u0120Courtney",
+ "ividad",
+ "\u0120\u00da\u00a9\u00db\u0123",
+ "\u0120efficacy",
+ "\u0120Brooks",
+ "\u0120referral",
+ "\u0120\u00d0\u00ba\u00d0\u00be\u00d0\u00bd\u00d1\u0128",
+ "\u0120malicious",
+ "\u0120kir",
+ "\u0120Goddess",
+ "\u0120funky",
+ "\u0120interim",
+ "\u0120K\u00c3\u00b6rper",
+ "\u0120\u00ec\u0138\u00bc\u00eb\u00a7",
+ "kur",
+ "\u0120\u00d0\u00ba\u00d0\u00bb\u00d0\u00b8",
+ "\u0120trucs",
+ "gesetz",
+ "\u0120zug",
+ "\u0120Gl\u00c3\u00bcck",
+ "\u0120Minute",
+ "\u0120prestigious",
+ "\u0120niez",
+ "\u0120concentrations",
+ "\u00d0\u00bb\u00d0\u00b0\u00d1\u0123\u00d1\u0124\u00d0\u00b8",
+ "\u0120Sis",
+ "\u0120Vitamin",
+ "kov",
+ "\u0120PBS",
+ "\u0120\u00d0\u00bd\u00d0\u00b5\u00d0\u00b5",
+ "\u0120retailers",
+ "\u0120conventions",
+ "\u0120Samantha",
+ "\u0120proudly",
+ "Jordan",
+ "\u0120JASON",
+ "atk",
+ "\u0120triste",
+ "\u0120st\u00c3\u00a4r",
+ "\u0120reiterate",
+ "\u0120posterior",
+ "\u01201973",
+ "\u0120Pine",
+ "\u0120Juliet",
+ "\u0120pedir",
+ "kil",
+ "\u0120overlapping",
+ "\u0120exclude",
+ "\u0120econ\u00c3\u00b3m",
+ "\u0120accepts",
+ "\u0120Ster",
+ "\u00e6\u00b1\u00ba",
+ "\u0120\u00ec\u013c\u00b4\u00eb\u0131\u013b",
+ "estab",
+ "\u0120tug",
+ "arg",
+ "\u0120livro",
+ "\u00d8\u00a7\u00d8\u00b5",
+ "\u0120seams",
+ "\u0120buraya",
+ "\u0120ello",
+ "\u0120TM",
+ "\u0120Paw",
+ "\u0120Index",
+ "Exc",
+ "\u0120inspirational",
+ "\u0120dunk",
+ "\u00e8\u00b0\u0123",
+ "akter",
+ "\u0120conditioner",
+ "\u0120Salut",
+ "\u00c5\u0124ec",
+ "\u0120\u00ec\u012b\u00bd",
+ "\u0120\u00d1\u0125\u00d0\u00b7\u00d0\u00bd\u00d0\u00b0",
+ "\u0120Romeo",
+ "fruit",
+ "\u0120YO",
+ "\u0120ch\u00e1\u00bb\u012b",
+ "\u00d0\u00b1\u00d1\u0125",
+ "bons",
+ "\u0120reproductive",
+ "\u0120orada",
+ "\u0120\u00ed\u013c\u00a8",
+ "\u0120tentar",
+ "\u0120ma\u00c3\u00b1ana",
+ "\u00e3\u0124\u00ac",
+ "\u0120solvent",
+ "Jessica",
+ "\u0120Legal",
+ "\u0120tua",
+ "\u0120sic",
+ "\u0120EQ",
+ "aukee",
+ "\u00ec\u012d\u013e\u00eb\u012d\u00a4",
+ "\u0120\u00c5\u0140u",
+ "\u0120adhere",
+ "\u0120Tul",
+ "\u0120\u00e0\u00ae\u0128",
+ "\u0120textbooks",
+ "\u0120Fifth",
+ "\u0120experi",
+ "\u0120chic",
+ "\u0120heap",
+ "inely",
+ "atra",
+ "Two",
+ "\u0120helemaal",
+ "\u0120fren",
+ "\u00e6\u0130\u00a8",
+ "\u0120bisher",
+ "\u00d8\u00a7\u00d8\u00b4",
+ "\u0120\u00ec\u0126\u0142\u00ec\u0125\u013f",
+ "\u0120Tages",
+ "\u0120s\u00e1\u00bb\u00b1",
+ "\u0120bullied",
+ "\u00d8\u00a4",
+ "\u0120benefited",
+ "\u0120Previously",
+ "\u0120\u00d1\u012f\u00d1\u0126\u00d1\u0126",
+ "\u00d9\u012f",
+ "\u0120senate",
+ "\u0120Morm",
+ "ijke",
+ "\u0120Flu",
+ "\u0120incorporating",
+ "jack",
+ "\u0120\u00d0\u00bf\u00d0\u00b8\u00d1\u0124",
+ "\u0120imply",
+ "\u0120hacks",
+ "\u0120RICH",
+ "\u0120\u00d0\u00ba\u00d0\u00b2\u00d0\u00b0\u00d1\u0122",
+ "\u0120\u00d0\u00bf\u00d1\u0122\u00d0\u00b5\u00d0\u00ba\u00d1\u0122\u00d0\u00b0\u00d1\u0123",
+ "\u0120dependency",
+ "\u0120\u00ec\u013c\u00a9",
+ "\u0120\u00ec\u00b1\u0127",
+ "\u0120w\u00c3\u00a4hrend",
+ "\u0120sulla",
+ "\u0120Pittsburgh",
+ "\u0120esempio",
+ "\u00bc\u00eb\u00a1\u013e",
+ "prot",
+ "\u0120Rosen",
+ "\u0120Independence",
+ "\u0120parsley",
+ "iegen",
+ "\u0120haw",
+ "\u0120aquell",
+ "\u0120CAP",
+ "\u0120\u00d1\u0122\u00d0\u00b0\u00d0\u00b1\u00d0\u00be\u00d1\u0124\u00d0\u00b0\u00d1\u0124\u00d1\u012e",
+ "\u0120Cliff",
+ "ionar",
+ "\u0120securing",
+ "\u00e6\u012a\u0133\u00e5\u0122\u0133\u00e7\u013c\u0126",
+ "\u00ce\u00bd\u00ce\u00b5",
+ "\u0120utilis",
+ "\u0120coule",
+ "\u0120Ping",
+ "\u0120trek",
+ "\u0120fak",
+ "\u0120enorme",
+ "\u0120\u00ec\u012d\u00ab",
+ "\u00e8\u00ae\u00a9",
+ "\u0120doubling",
+ "\u0120\u00d0\u00bd\u00d1\u0122\u00d0\u00b0\u00d0\u00b2\u00d0\u00b8\u00d1\u0124\u00d1\u0123\u00d1\u0131",
+ "\u0120hed",
+ "hoven",
+ "\u0120Standing",
+ "\u0120m\u00c3\u0143n",
+ "\u0120Jimin",
+ "\u0120monarch",
+ "\u0120coke",
+ "\u0120mr",
+ "\u0120clic",
+ "\u00c3\u012f",
+ "\u0120impeachment",
+ "\u0120durability",
+ "\u0120varios",
+ "\u0120commercials",
+ "\u0120greetings",
+ "\u0120Ri",
+ "\u0120Appreci",
+ "\u00ec\u0140\u012a\u00eb\u012c\u0136",
+ "\u0120r\u00c3\u00a9sult",
+ "\u00c3\u00a9rt",
+ "\u0120salute",
+ "\u0120poderia",
+ "\u0120sunrise",
+ "veck",
+ "\u0120reluctant",
+ "\u0120commissioner",
+ "\u00e5\u00bf\u00b5",
+ "\u00c3\u00a2te",
+ "\u0120Kenny",
+ "\u0120Siri",
+ "\u00e3\u0125\u0125\u00e3\u0125\u0139",
+ "\u0120\u00eb\u012c\u013a",
+ "\u0120EE",
+ "\u0120unch",
+ "\u00d0\u00ba\u00d0\u00be\u00d0\u00bd",
+ "\u0120\u00d8\u00a7\u00d9\u0126\u00d8\u00a5",
+ "\u0120belts",
+ "\u0120hass",
+ "\u0120\u00d0\u00bc\u00d0\u00be\u00d1\u0131",
+ "\u0120displaced",
+ "\u0120abra",
+ "\u00ce\u0143\u00ce\u00bb",
+ "\u0120scratches",
+ "\u0120comet",
+ "\u0120authorization",
+ "\u0120LLC",
+ "\u0120produk",
+ "\u0120rehabilitation",
+ "\u00e5\u0140",
+ "\u00d1\u0138\u00d1\u0129",
+ "uding",
+ "olit",
+ "\u0120105",
+ "\u0120expands",
+ "\u0120altri",
+ "\u0120Komment",
+ "\u0120anf",
+ "Pl",
+ "\u0120Mana",
+ "fed",
+ "\u0120bri",
+ "\u0120ora",
+ "Gs",
+ "\u0120Gur",
+ "uckland",
+ "\u0120junction",
+ "\u0120ironic",
+ "\u0120Feed",
+ "\u0120prakt",
+ "\u0120Hammer",
+ "\u012e\u00eb\u0131\u0126",
+ "\u0120Tracy",
+ "\u00e7\u00b5\u00b1",
+ "\u0120Aside",
+ "\u00d0\u00bd\u00d0\u00b5\u00d0\u00b3\u00d0\u00be",
+ "\u0120\u00d0\u00b8\u00d1\u0123\u00d0\u00bf\u00d0\u00be\u00d0\u00bb\u00d1\u012e\u00d0\u00b7\u00d0\u00be\u00d0\u00b2\u00d0\u00b0\u00d1\u0124\u00d1\u012e",
+ "\u0120zaj",
+ "\u0120equitable",
+ "\u0120curb",
+ "\u0120\u00e3\u0123\u0135\u00e3\u0124\u012e",
+ "\u0120derivatives",
+ "\u0120puppies",
+ "\u0120Kenneth",
+ "\u0120Compl",
+ "igram",
+ "\u0120Garcia",
+ ")\"",
+ "\u0120Harbor",
+ "estial",
+ "\u0120\u00e4\u00be\u0128",
+ "\u0120ers",
+ "\u00e6\u00b9",
+ "\u0120unwanted",
+ "\u0120belang",
+ "\u00d0\u00b0\u00d0\u00b3\u00d0\u00be",
+ "emb",
+ "dos",
+ "\u0120\u00ec\u013b\u013e\u00eb",
+ "\u0120Budget",
+ "\u0120battling",
+ "\u00d8\u0143\u00d8\u00aa",
+ "kok",
+ "\u00d0\u00bd\u00d0\u00b0\u00d1\u0129\u00d0\u00b0\u00d0\u00bb\u00d0\u00b0",
+ "\u0120plag",
+ "\u0120cantidad",
+ "\u0120grupos",
+ "\u0120plugins",
+ "lerini",
+ "\u0120\u00d0\u00b8\u00d0\u00bc\u00d0\u00b5\u00d0\u00b5\u00d1\u0124",
+ "\u0120sozusagen",
+ "olics",
+ "\u0120pueblo",
+ "\u0120reminis",
+ "r\u00c3\u00a4n",
+ "\u0120Morrison",
+ "\u0120linha",
+ "\u0120breaths",
+ "\u0120Taste",
+ "\u0120enfrent",
+ "\u0120Docker",
+ "\u0120\u00d0\u00b4\u00d0\u00b5\u00d0\u00bd",
+ "\u0120ethnicity",
+ "\u0120wob",
+ "\u0120suffers",
+ "\u0120transitioning",
+ "\u0120Range",
+ "\u00c4\u013bdzy",
+ "\u0120\u00d0\u00ba\u00d0\u00b0\u00d1\u0124",
+ "\u0120syner",
+ "\u0120donut",
+ "\u0120probabilities",
+ "\u0120Omar",
+ "Which",
+ "uish",
+ "isin",
+ "\u0120demos",
+ "\u0120\u00ec\u0142\u0122\u00ea\u00b8\u00b0",
+ "\u0120\u00eb\u013a\u0133\u00ea\u00b0\u013b",
+ "\u0120\u00d0\u00b5\u00d0\u00b4\u00d0\u00b8\u00d0\u00bd",
+ "\u0120cerve",
+ "\u0120joka",
+ "IAN",
+ "\u0120kilometer",
+ "\u0120horizontally",
+ "\u0120Bhag",
+ "\u0120->",
+ "\u0120Monitor",
+ "\u0120knowledgeable",
+ "\u0120fav",
+ "\u0120pinned",
+ "\u0120eBay",
+ "icker",
+ "\u0120\u00ec\u0140\u0142\u00ea\u00b9\u0132\u00eb\u00a7\u012e",
+ "\u0120Xiaomi",
+ "\u0120capit",
+ "\u0120np",
+ "\u01201965",
+ "hoe",
+ "\u0120nok",
+ "\u0120Sage",
+ "\u0120\u00d0\u00bd\u00d0\u00b5\u00d0\u00bb\u00d1\u012e\u00d0\u00b7\u00d1\u0131",
+ "\u0120Tow",
+ "gam",
+ "\u0120dicen",
+ "\u0120SUBSCRIBE",
+ "\u0120reboot",
+ "\u0120paj",
+ "\u0120\u00eb\u00b3\u00b4\u00ec\u0139\u00ac\u00eb",
+ "\u0120thicken",
+ "\u0120Reality",
+ "id\u00c3\u00a4n",
+ "Na",
+ "\u0120\u00ea\u00b2\u0125\u00ec\u013f\u0122",
+ "!!)",
+ "\u0120routines",
+ "\u0120\u00d0\u00be\u00d0\u00b4\u00d0\u00bd\u00d0\u00be\u00d0\u00b3\u00d0\u00be",
+ "\u0120exting",
+ "\u0120\u00ec\u00a6\u013f",
+ "\u0120sulfur",
+ "\u0120carve",
+ "\u0120asteroid",
+ "\u0120Warrior",
+ "\u0120photographers",
+ "\u0120pell",
+ "\u0120crossover",
+ "\u00e6\u012a\u0133\u00e7\u0141\u00a5\u00e9\u0123\u0135",
+ "\u0120hacemos",
+ "\u0120Nej",
+ "\u0120settling",
+ "\u0120irm",
+ "\u0120Books",
+ "ient\u00c3\u00b4t",
+ "\u0120espacio",
+ "\u0120Scholars",
+ "\u0120doomed",
+ "\u0120IRS",
+ "wohl",
+ "\u0120segue",
+ "\u0120\u00eb\u012a\u0126\u00ea\u00b0\u0122",
+ "\u0120pratic",
+ "BT",
+ "\u0120Considering",
+ "\u0120Buffalo",
+ "\u0120trainings",
+ "\u0120gebru",
+ "\u0120Gleich",
+ "\u0120pirates",
+ "\u0120envelop",
+ "\u0120reopen",
+ "imat",
+ "\u0120tee",
+ "\u0120sued",
+ "feh",
+ "\u0120\u00d7\u0136\u00d7\u00a7",
+ "\u0120diets",
+ "\u0120juntos",
+ "asto",
+ "\u0120misunderstood",
+ "\u0120ruim",
+ "\u0120classify",
+ "\u0120\u00d0\u00bf\u00d1\u0122\u00d0\u00be\u00d0\u00b4\u00d1\u0125\u00d0\u00ba",
+ "\u0120inse",
+ "\u0120illustrated",
+ "\u0120corrosion",
+ "\u0120accred",
+ "\u0120Auntie",
+ "\u0120\u00d0\u00bf\u00d1\u0122\u00d0\u00b8\u00d0\u00b2\u00d0\u00b5\u00d1\u0124",
+ "\u0120LIVE",
+ "\u0120rek",
+ "\u0120receipt",
+ "\u00e5\u012a\u00b0\u00e5\u00ba\u0137",
+ "\u0120Barbie",
+ "\u0120Snake",
+ "turn",
+ "Jeff",
+ "\u00e3\u0123\u012c\u00e3\u0123\u012c",
+ "\u0137\u0126",
+ "VOICEOVER",
+ "coll",
+ "\u0120runners",
+ "\u00ec\u0142\u013e\u00eb",
+ "osos",
+ "moon",
+ "\u0120keynote",
+ "\u0120Instit",
+ "SPEAK",
+ "\u0120plugs",
+ "\u0120curv",
+ "\u0120Yuri",
+ "\u0120Theres",
+ "\u0120Ps",
+ "\u0120\u00ce\u00bc\u00cf\u0122\u00ce\u00bf",
+ "\u0120converter",
+ "\u0120refine",
+ "\u0120badass",
+ "\u0120\u00ce\u00bf\u00ce\u00b9",
+ "\u0120regen",
+ "azzi",
+ "\u00d9\u012c\u00d9\u0123",
+ "\u0120seized",
+ "\u0120i\u00c3\u00a7er",
+ "ilee",
+ "\u0120upstream",
+ "\u0120buds",
+ "\u0120pim",
+ "\u0120\u00ed\u0137\u013a\u00eb\u00a3\u00a8",
+ "\u0120alluded",
+ "\u0120themed",
+ "\u0120consisting",
+ "\u0120bons",
+ "unuz",
+ "\u0120\u00d0\u00bf\u00d1\u0122\u00d0\u00be\u00d0\u00b2\u00d0\u00be\u00d0\u00b4",
+ "\u0120Lovely",
+ "\u00e0\u00a5\u012d",
+ "\u0120parach",
+ "\u0120Staats",
+ "\u00e9\u013c\u012c",
+ "\u0120selective",
+ "\u0120fase",
+ "\u0120Georget",
+ "\u0120cocaine",
+ "\u0120reproduction",
+ "\u0120Lara",
+ "\u0120LD",
+ "\u0120gh",
+ "Jon",
+ "\u0120l\u00c3\u00a5",
+ "\u0120\u00eb\u0133\u0132\u00eb",
+ "\u0120typed",
+ "\u0120Bana",
+ "\u00eb\u0135\u013e\u00eb",
+ "\u0120savory",
+ "\u0120Zomb",
+ "standen",
+ "\u0120pedestrian",
+ "\u0120diff\u00c3\u00a9rents",
+ "\u0120\u00ec\u012d\u00b8",
+ "\u00e8\u012b\u00af",
+ "\u0120complained",
+ "\u00e7\u00a6\u0131",
+ "\u0120\u00d0\u013c\u00d1\u0124\u00d0\u00be",
+ "\u0120\u00d7\u013e\u00d7\u00a4",
+ "ali\u00c5\u013dmy",
+ "\u0120mortar",
+ "\u0120verdict",
+ "\u0120suficiente",
+ "\u0120Million",
+ "mittel",
+ "inals",
+ "\u0120\u00d8\u00a7\u00d9\u0126\u00d8\u00ae",
+ "\u00d0\u00b0\u00d1\u0130\u00d1\u0123\u00d1\u012e",
+ "\u0120mi\u00c4\u013bdzy",
+ "\u0120Ole",
+ "\u0120invert",
+ "czy\u00c4\u0129",
+ "\u00d0\u00be\u00d0\u00b7\u00d0\u00bc\u00d0\u00be\u00d0\u00b6\u00d0\u00bd\u00d0\u00be",
+ "starter",
+ "\u0120auditor",
+ "\u0120Scout",
+ "chien",
+ "\u0120Sverige",
+ "uffled",
+ "\u0120zehn",
+ "\u0120Auckland",
+ "\u0120argent",
+ "\u01201976",
+ "\u0120Hoe",
+ "\u0120bothers",
+ "\u0120socialist",
+ "\u0120pliers",
+ "\u0120emergen",
+ "\u0120XP",
+ "\u00d0\u00b5\u00d1\u0122\u00d0\u00be\u00d0\u00b2",
+ "More",
+ "\u0120Levi",
+ "\u0120Anders",
+ "ibilidad",
+ "\u0120Parents",
+ "\u0120induced",
+ "\u00ec\u0138\u00b4\u00ec\u00a4",
+ "\u0120balances",
+ "\u0120\u00d0\u00b2\u00d1\u012d\u00d1\u012a",
+ "\u0120submarine",
+ "Start",
+ "\u0120dries",
+ "\u0120volver",
+ "\u0120ticking",
+ "cott",
+ "\u0120faj",
+ "pr\u00c3\u00a9s",
+ "\u0120Sabb",
+ "\u0120\u00d0\u00b7\u00d0\u00b0\u00d1\u0129",
+ "\u0120\u00d0\u00bf\u00d0\u00be\u00d0\u00ba\u00d1\u0125\u00d0\u00bf",
+ "\u0120baptized",
+ "\u0120Brilliant",
+ "\u0120\u00d0\u0133\u00d0\u00be\u00d0\u00b3",
+ "\u0120mots",
+ "bits",
+ "\u0120lattice",
+ "\u00e6\u012a\u0133\u00e8\u00b7\u0141\u00e4\u00bd\u0142",
+ "\u0120coriander",
+ "\u0120residency",
+ "ync",
+ "\u0120pierwszy",
+ "\u0120Knock",
+ "\u0120Zap",
+ "\u0120\u00d0\u0137\u00d0\u00b2",
+ "\u00ea\u00b2\u00ac",
+ "\u00e5\u00b0\u0131\u00e5\u00bf\u0125",
+ "\u0120uneven",
+ "\u0120Jas",
+ "odor",
+ "\u00e7\u00bf\u0134",
+ "74",
+ "\u0120Site",
+ "\u0120aconteceu",
+ "ympt",
+ "\u0120trilogy",
+ "\u0120lantern",
+ "\u0120Zucker",
+ "vari",
+ "welling",
+ "\u0120Potato",
+ "gomery",
+ "\u0120reacted",
+ "\u0120Chron",
+ "\u0120jede",
+ "beeld",
+ "\u0120twent",
+ "\u0120lact",
+ "\u00e6\u00a8\u0124",
+ "\u0120r\u00c3\u00a9se",
+ "\u0120relent",
+ "\u0120furnace",
+ "\u0120widget",
+ "\u0120earthquakes",
+ "\u0120Adjust",
+ "ilit",
+ "\u0120\u00d8\u00a3\u00d9\u012a",
+ "\u0120hearings",
+ "\u0120defendant",
+ "irsiniz",
+ "\u0120bask",
+ "cja",
+ "\u013e\u00a8",
+ "\u0120rifles",
+ "\u0120instal",
+ "\u0120Forgive",
+ "pical",
+ "\u0120\u00d0\u0140\u00d1\u0129\u00d0\u00b5\u00d0\u00bd\u00d1\u012e",
+ "\u0120petites",
+ "\u0120hp",
+ "\u0120renowned",
+ "\u0120Inn",
+ "\u0120\u00ec\u00a3\u00bc\u00ec\u0126\u00b8\u00ec\u013c\u0136",
+ "\u0120emphasized",
+ "\u00e9\u0139\u00ae\u00e9\u00a2\u013a",
+ "\u0120\u00ec\u0140\u012a\u00ec\u00a3\u0142",
+ "\u0120\u00ea\u00b2\u0125\u00ec\u013e\u00bc\u00eb\u00a1\u013e",
+ "\u00e3\u0124\u0128",
+ "\u00c5\u0135",
+ "gili",
+ "Dave",
+ "\u0120exhausting",
+ "\u00c5\u0124ug",
+ "\u0120schema",
+ "\u00ce\u00bc\u00ce\u00ac",
+ "cycl",
+ "\u0120autant",
+ "\u0120parcel",
+ "\u0120materia",
+ "\u0120Berry",
+ "\u0120\u00d1\u0123\u00d0\u00b0\u00d0\u00bc\u00d0\u00b8",
+ "\u0120extracted",
+ "\u0120Saying",
+ "ismatic",
+ "\u0120\u00d0\u00bf\u00d0\u00be\u00d0\u00bf\u00d1\u0122\u00d0\u00be\u00d0\u00b1",
+ "\u0120neuron",
+ "graph",
+ "\u013e\u00eb\u00a9\u00b4",
+ "\u0120enclosure",
+ "\u0120Johann",
+ "\u0120aftermath",
+ "\u00d1\u0124\u00d0\u00be\u00d0\u00b1",
+ "\u0120u\u00c5\u00bcy",
+ "\u0120samp",
+ "360",
+ "\u0120Mei",
+ "\u0120taco",
+ "\u0120receptors",
+ "\u0120punches",
+ "\u0120Hoje",
+ "\u0120\u00d9\u0129\u00d9\u0128\u00d8\u00a7",
+ "=\"#",
+ "\u0120Angular",
+ "\u0120musique",
+ "\u0120rol",
+ "\u0120\u00c3\u00b1",
+ "sterreich",
+ "\u0120clam",
+ "\u0120Treasury",
+ "chemical",
+ "\u0120apar",
+ "\u0120append",
+ "\u0120forbid",
+ "\u0120Hamburg",
+ "\u00d0\u00b0\u00d0\u00ba\u00d0\u00be\u00d0\u00b2",
+ "\u0120\u00ea\u00b8\u012a",
+ "ilda",
+ "\u0120preparations",
+ "\u0120mog\u00c4\u0127",
+ "\u0120camino",
+ "Eric",
+ "\u0120Blind",
+ "\u00e8\u012a\u0129",
+ "\u00e5\u00b9\u00b4\u00e7\u013c\u0126",
+ "\u0120Discovery",
+ "\u00ec\u00b8\u0142",
+ "\u00e7\u012a\u00b6",
+ "\u0120interpreter",
+ "\u0120bred",
+ "\u0120Psalm",
+ "\u0120defended",
+ "\u00ec\u012b\u00ac",
+ "\u0120Erfahr",
+ "\u0120Peach",
+ "\u0120moons",
+ "\u0120Ost",
+ "\u0120sp\u00c3\u00a9cial",
+ "\u0120arriver",
+ "\u0120Wis",
+ "uci",
+ "\u0120robotics",
+ "IVE",
+ "\u0120siege",
+ "arla",
+ "\u0120separates",
+ "\u0120TC",
+ "\u00ed\u0131\u00b0",
+ "quisite",
+ "\u0120parentheses",
+ "\u00d0\u00b8\u00d0\u00ba\u00d0\u00b5",
+ "\u00e7\u00ab\u013b",
+ "\u0120trous",
+ "\u00e5\u00bb\u00ba",
+ "\u0120\u00d1\u0123\u00d0\u00b8\u00d0\u00bb\u00d1\u012e",
+ "\u0120beers",
+ "\u0120\u00d0\u00bf\u00d0\u00bb\u00d0\u00b0\u00d1\u0124",
+ "\u00e3\u0123\u013b\u00e3\u0123\u0136\u00e3\u0123\u0126",
+ "\u0120sola",
+ "\u0120d\u00c3\u00a8s",
+ "mingham",
+ "ikte",
+ "\u0120oops",
+ "\u0120twitch",
+ "\u00e5\u00b0\u0129",
+ "\u00cf\u012a",
+ "\u0120Shouldn",
+ "uvre",
+ "\u0120leer",
+ "criptions",
+ "\u0120eyeshadow",
+ "\u0120Guo",
+ "\u0120Powell",
+ "\u0120supuesto",
+ "\u0120ana",
+ "rals",
+ "\u0120Montreal",
+ "\u0120surfing",
+ "\u0120\u00d0\u0141\u00d0\u00b5\u00d1\u0122\u00d0\u00b2",
+ "\u00d7\u0140\u00d7\u0137",
+ "\u0120milliseconds",
+ "\u0120suburbs",
+ "\u0120planeta",
+ "\u00d1\u0125\u00d1\u012a\u00d0\u00ba\u00d0\u00b0",
+ "hrlich",
+ "\u0120HY",
+ "\u0120\u00d8\u00b3\u00db\u0134",
+ "\u0120MM",
+ "\u0120Eff",
+ "\u00e5\u0131\u00af\u00e6\u0126\u013d",
+ "\u0120HS",
+ "anson",
+ "\u0120\u00ec\u00a7\u0123\u00ec\u0142\u0133",
+ "\u0120suo",
+ "\u0120deploying",
+ "\u0120kunt",
+ "tering",
+ "\u0120erect",
+ "\u00ec\u0140\u00a5\u00ec\u013f\u00b4",
+ "\u0120\u00ec\u013f\u012e\u00ec\u012d\u013f",
+ "\u0120specimen",
+ "!...",
+ "\u00e6\u012a\u0133\u00e8\u00aa\u00aa",
+ "\u0120ligne",
+ "\u0120konst",
+ "adequ",
+ "\u0120\u00ec\u0125\u0123\u00ed\u0125\u013e",
+ "\u0120accessed",
+ "\u0120Pole",
+ "kill",
+ "\u0120\u00eb\u00b2\u0126\u00eb",
+ "\u0120authenticity",
+ "\u0120appelle",
+ "ulle",
+ "\u0120revision",
+ "\u0120goats",
+ "\u00d0\u00b3\u00d0\u00bb\u00d0\u00b8",
+ "\u0120pau",
+ "\u0120Ranger",
+ "\u0120Imag",
+ "author",
+ "\u0120eve",
+ "\u0120Messenger",
+ "\u0120nay",
+ "\u0120wholes",
+ "\u00c3\u00a4tte",
+ "\u0120onwards",
+ "\u0120Depois",
+ "\u0120\u00ed\u0133\u013e\u00ed\u013a\u0126",
+ "\u0120SARS",
+ "\u0120wszystkich",
+ "\u0120destru",
+ "umbing",
+ "\u0120compatibility",
+ "\u0120misinformation",
+ "odore",
+ "\u0120Favor",
+ "eko",
+ "\u0131\u012e",
+ "waukee",
+ "\u0120Teaching",
+ "\u0120KO",
+ "\u0120betting",
+ "\u0120quests",
+ "\u0120vivre",
+ "\u0120\u00d0\u00bc\u00d1\u0125\u00d0\u00b7\u00d1\u012d",
+ "\u0120saga",
+ "\u0120swell",
+ "\u0120gehe",
+ "\u00e6\u0122\u0130\u00e9\u00ba\u00bc\u00e6\u00a8\u00a3",
+ "\u0120\u00d0\u00be\u00d1\u0122\u00d0\u00b3\u00d0\u00b0\u00d0\u00bd\u00d0\u00b8\u00d0\u00b7",
+ "\u0120gide",
+ "\u0120Gross",
+ "\u0120dalej",
+ "\u0120claws",
+ "\u00e1\u00bb\u013bc",
+ "\u0120prejudice",
+ "\u0120insign",
+ "ihood",
+ "\u0120pled",
+ "\u0120d\u00c3\u00b3nde",
+ "\u0120Political",
+ "\u0120premises",
+ "undert",
+ "\u00d8\u00b9\u00d8\u00aa",
+ "onnen",
+ "\u0120espa\u00c3\u00a7o",
+ "\u0120f\u00c3\u00a9",
+ "\u0120Harrison",
+ "\u0120Census",
+ "\u0120cardio",
+ "\u0120diy",
+ "\u0120milieu",
+ "\u0120journ\u00c3\u00a9e",
+ "\u0120Release",
+ "NIE",
+ "\u0120Muk",
+ "id\u00c3\u00a9e",
+ "\u00e1\u00bb\u012fi",
+ "\u0120i\u00c3\u00a7inde",
+ "\u0140\u013b",
+ "\u0120resonate",
+ "\u0120moles",
+ "\u0120Flying",
+ "\u0120Gloria",
+ "\u0120Pastor",
+ "\u0120Arena",
+ "\u00e5\u00a5\u00bd\u00e4\u00b8\u012f\u00e5\u00a5\u00bd",
+ "NON",
+ "\u00d0\u00be\u00d0\u00bb\u00d0\u00be\u00d0\u00b2",
+ "\u0120all\u00c3\u0143",
+ "omat",
+ "\u00ec\u0138\u00b4\u00eb\u0131\u0126",
+ "\u0120caracter\u00c3\u0143st",
+ "\u0120declining",
+ "\u00d1\u0138\u00d1\u0131",
+ "anco",
+ "\u0120Inform",
+ "\u0120bargain",
+ "\u0120bushes",
+ "\u0120Naturally",
+ "\u0120rechts",
+ "\u0120Tensor",
+ "\u0120Patricia",
+ "\u0120principio",
+ "\u0120Mumbai",
+ "\u0120womb",
+ "\u0120nostra",
+ "\u0120dilemma",
+ "\u0120irgendwann",
+ "\u01201964",
+ "\u0120energ\u00c3\u0143a",
+ "\u0120\u00d0\u00bd\u00d0\u00b0\u00d1\u0122",
+ "\u0120segregation",
+ "\u0120Athlet",
+ "\u0120\u00c2\u00bb,",
+ "\u0120yeni",
+ "\u0120Seit",
+ "\u0120venom",
+ "\u0120dakika",
+ "\u0120\u00eb\u0131\u012e\u00eb",
+ "\u0120\u00c3\u012bl",
+ "\u0120fus",
+ "\u0120Mog",
+ "\u00a6\u00bd\u00eb\u012d\u012a\u00eb\u012d\u00a4",
+ "\u0120remar",
+ "\u0120Teddy",
+ "\u0120breasts",
+ "icans",
+ "\u00e6\u0136\u00b6\u00e7\u013e\u012d",
+ "kap",
+ "\u0120h\u00c6\u00a1n",
+ "\u0120JP",
+ "\u00e3\u0125\u00b3\u00e3\u0124\u00bf",
+ "\u0120resurrect",
+ "\u0120\u00ec\u013f\u00b8\u00eb",
+ "herical",
+ "\u0120fotograf",
+ "\u0120Jos\u00c3\u00a9",
+ "\u0120livelihood",
+ "\u0120bibli",
+ "teri",
+ "\u0120vorstellen",
+ "\u0120AAA",
+ "\u0120assessing",
+ "YA",
+ "\u0120splend",
+ "\u0120excav",
+ "\u0120baptism",
+ "yll",
+ "wow",
+ "Mac",
+ "\u0120plastics",
+ "teokbokki",
+ "\u0120int\u00c3\u00a9ressant",
+ "\u0120commanded",
+ "\u0120famously",
+ "\u0120\u00d0\u013a\u00d0\u00bb\u00d0\u00b8",
+ "\u0120Manuel",
+ "\u0120southwest",
+ "\u0120deformation",
+ "\u00c3\u0143culo",
+ "\u0120\u00d0\u00bd\u00d0\u00b0\u00d1\u0127\u00d0\u00be\u00d0\u00b4\u00d0\u00b8\u00d1\u0124\u00d1\u0123\u00d1\u0131",
+ "\u0120Patter",
+ "degree",
+ "\u0120cz\u00c4\u013bsto",
+ "\"-",
+ "\u0120\u00ec\u0127\u012d",
+ "\u0120manger",
+ "\u0120Trustee",
+ "\u0122\u00eb\u00a6\u00ac",
+ "\u0120puntos",
+ "ivable",
+ "\u0120volatile",
+ "\u0120\u00eb\u012c\u0132",
+ "\u0120instability",
+ "\u0120ciel",
+ "ci\u00c4\u0127",
+ "\u0120purity",
+ "\u00d0\u00bd\u00d0\u00be\u00d1\u0123\u00d1\u0124",
+ "Sil",
+ "edar",
+ "\u00e5\u013b\u00a8",
+ "NOUNCER",
+ "\u0120spelled",
+ "GER",
+ "\u0120sanctuary",
+ "\u0120accelerating",
+ "\u0120scout",
+ "\u0120\u00d0\u00bf\u00d1\u0122\u00d0\u00b5\u00d0\u00b2",
+ "fahren",
+ "\u00e3\u0123\u0135\u00e3\u0123\u00a1\u00e3\u0124\u012b",
+ "\u0120\u00eb\u0124\u013a\u00ec\u013a\u00a8",
+ "\u0120pocz\u00c4\u0127t",
+ "\u0120Meu",
+ "kaar",
+ "\u00b3\u00b4\u00ea\u00b3\u0142",
+ "akra",
+ "Down",
+ "\u0120\u00c3\u0126r",
+ "\u0120Elite",
+ "\u0120allons",
+ "\u0120mayonnaise",
+ "\u0120Sustain",
+ "prisingly",
+ "\u0120supervis",
+ "\u0120\u00ea\u00b7\u00b8\u00eb\u0142\u0129\u00ec\u00a3\u0142",
+ "\u0120unemployed",
+ "\u0120freshly",
+ "\u0120\u00d7\u0140\u00d7\u00a2",
+ "\u0120Dh",
+ "\u0120tackling",
+ "\u0120ogr",
+ "\u0120\u00ec\u00b4\u012a\u00eb",
+ "\u00e3\u0124\u012a\u00e3\u0124\u012f",
+ "\u0120loft",
+ "arah",
+ "\u0120Airl",
+ "\u0120Dir",
+ "\u0120\u00d0\u013e\u00d0\u00be\u00d0\u00b6\u00d0\u00bd\u00d0\u00be",
+ "\u0120booking",
+ "\u0120CRA",
+ "\u0120https",
+ "\u0120choke",
+ "\u0120gown",
+ "\u0120noite",
+ "\u0120zac",
+ "istol",
+ "\u0120secre",
+ "\u0120resembles",
+ "\u0120cuad",
+ "\u00ec\u0124\u00ac\u00ea\u00b0\u0122",
+ "show",
+ "\u0120blanc",
+ "\u0120agu",
+ "\u0120Print",
+ "asted",
+ "\u0120Weather",
+ "ipl",
+ "\u0120obscure",
+ "\u0120conte",
+ "oughs",
+ ");",
+ "\u0120Dame",
+ "\u00e4\u00b8\u0122\u00e7\u013d\u00b4",
+ "\u0120clarification",
+ "\u0120intimacy",
+ "\u0120uphold",
+ "\u0120Mirror",
+ "\u0120wagon",
+ "xide",
+ "\u0120clog",
+ "apper",
+ "\u0120Immediately",
+ "\u00c3\u00bade",
+ "\u0120touchdown",
+ "\u0120rooft",
+ "\u00d0\u00b0\u00d1\u012a\u00d0\u00b0",
+ "\u0120\u00c3\u00a7\u00c4\u00b1kt",
+ "\u0120laisser",
+ "\u0120Unreal",
+ "ensitive",
+ "\u0120123",
+ "\u0120plaster",
+ "\u0120ducks",
+ "\u0120etme",
+ "\u0120bishop",
+ "brevi",
+ "\u0120bic",
+ "\u00e4\u00b8\u012d\u00e5\u0130\u00bb",
+ "\u0120runtime",
+ "\u0120ambitions",
+ "\u00d0\u00bc\u00d0\u00b0\u00d1\u0124",
+ "\u0120Wein",
+ "\u0120Mari",
+ "\u0120\u00ed\u012c\u00b8\u00eb",
+ "\u0120resolver",
+ "\u0120ng\u00c3\u0142y",
+ "\u0120Rise",
+ "\u00e3\u0124\u012a\u00e3\u0123\u0128\u00e3\u0123\u00ab",
+ "\u0120Crus",
+ "\u0120merchandise",
+ "\u0120eli",
+ "\u0120statewide",
+ "\u0120owl",
+ "\u00e9\u0123\u0142",
+ "\u00e6\u0136\u00b9",
+ "\u0120twisting",
+ "\u0120contaminated",
+ "\u0120Commerce",
+ "hythm",
+ "\u0120\u00c3\u012a",
+ "\u0120\u00ec\u012d\u00a4\u00eb",
+ "\u0120musste",
+ "uir",
+ "\u0120sums",
+ "\u0120Somewhere",
+ "\u00e3\u0125\u0130",
+ "\u0120kami",
+ "\u0120aired",
+ "\u0120ANDREW",
+ "\u0120\u00ea\u00ba",
+ "\u0120viendo",
+ "\u0120antibody",
+ "\u0120absolument",
+ "\u0120protesters",
+ "\u0120Qu\u00c3\u00a9bec",
+ "stadt",
+ "Shaun",
+ "\u0120chambers",
+ "\u0120Wear",
+ "\u0120Effects",
+ "\u0120hazards",
+ "\u0120nei",
+ "\u0120coraz\u00c3\u00b3n",
+ "\u0120\u00e1\u00bc",
+ "\u0120SG",
+ "\u0136\u00a9",
+ "\u0120\u00ec\u0139\u0143\u00ec\u012d\u013e",
+ "\u0120comfy",
+ "\u0120Cody",
+ "\u0120pensando",
+ "\u0120ganska",
+ "\u0120Across",
+ "\u00c3\u00b6llig",
+ "abyte",
+ "\u0120wedge",
+ "\u0120kalian",
+ "\u0120sigue",
+ "endes",
+ "\u0120Gro\u00c3\u0141",
+ "\u0120utiliser",
+ "\u0120flown",
+ "\u00d0\u00b0\u00d0\u00bd\u00d0\u00b8\u00d1\u0130",
+ "\u0120levar",
+ "restrial",
+ "\u0120illustrations",
+ "\u0120asl\u00c4\u00b1nda",
+ "BLEEP",
+ "\u0120\u00d0\u00b4\u00d0\u00be\u00d1\u0123\u00d1\u0124",
+ "\u0120turret",
+ "\u0120suitcase",
+ "zi\u00c4\u013bki",
+ "\u0120sketches",
+ "\u0120acred",
+ "\u0120Rei",
+ "\u0120tsun",
+ "\u0120Sag",
+ "\u0120thirds",
+ "\u0120KIRBY",
+ "rai",
+ "\u0120humanos",
+ "\u0120recommends",
+ "\u0120extraordinarily",
+ "\u0120commencement",
+ "KN",
+ "opez",
+ "\u0120\u00d7\u0133\u00d7\u00a9",
+ "\u0120lethal",
+ "\u0120Estamos",
+ "\u0120inspector",
+ "\u0120Seok",
+ "eun",
+ "\u0120offshore",
+ "\u0120gettin",
+ "years",
+ "\u0120Silence",
+ "\u0120Natur",
+ "upun",
+ "\u0120trzy",
+ "\u0120noget",
+ "\u0120hamburger",
+ "\u0120Praise",
+ "\u00c3\u00a9nd",
+ "\u01201971",
+ "ylie",
+ "krit",
+ "\u0120\u00ec\u0125\u013f\u00ea\u00b0\u0123\u00ec\u013f\u00b4",
+ "\u00e7\u013c\u00ae",
+ "\u0120momentos",
+ "\u0120est\u00c3\u00a9",
+ "\u0120dissemin",
+ "\u0120gigs",
+ "\u0120desaf",
+ "\u0120avis",
+ "\u0120Zoo",
+ "\u0120\u00ec\u0137\u012c\u00ec\u013f\u0122",
+ "h\u00c3\u00a4ng",
+ "\u00e5\u0131\u00a5",
+ "hake",
+ "\u0120Bism",
+ "\u0120rethink",
+ "\u0120Malcolm",
+ "\u0120identifies",
+ "lower",
+ "ixel",
+ "\u0120tv\u00c3\u00a5",
+ "ked",
+ "ierz",
+ "\u0120\u00c3\u00b6ffentlich",
+ "\u0120proclaim",
+ "soon",
+ "lol",
+ "\u0120loi",
+ "\u0120bitten",
+ "rollo",
+ "\u0120sermon",
+ "\u0120esqu",
+ "\u0120jackets",
+ "\u0120gr\u00c3\u00a1fic",
+ "\u0120\u00d0\u00bf\u00d0\u00be\u00d0\u00ba\u00d0\u00b0\u00d0\u00b7\u00d1\u012d\u00d0\u00b2",
+ "\u0120cabeza",
+ "chodzi",
+ "\u0120pelvis",
+ "\u0120nostalgia",
+ "\u0120brew",
+ "\u0120shortcuts",
+ "\u0120Adem\u00c3\u00a1s",
+ "\u0120superficial",
+ "\u00e5\u0127\u00a9\u00e5\u0122\u012d",
+ "\u0120boca",
+ "\u0120\u00e6\u012a\u0133\u00e6\u013a\u00af",
+ "imentos",
+ "\u00e5\u013d\u0142\u00e4\u00b8\u00ba",
+ "\u0120sprouts",
+ "\u00e9\u00a3\u013d",
+ "\u0120Jonas",
+ "\u0120Florence",
+ "static",
+ "daughter",
+ "*)",
+ "\u00c5\u0124by",
+ "fashion",
+ "\u0120Ginger",
+ "\u0120\u00eb\u00a7\u00a4\u00eb",
+ "\u0120hustle",
+ "utos",
+ "\u0120\u00d1\u0124\u00d1\u0131\u00d0\u00b6",
+ "\u0120L\u00c3\u00b6s",
+ "\u00d7\u00a9\u00d7\u013b\u00d7\u013f",
+ "anych",
+ "tuber",
+ "\u0120tidy",
+ "\u0120frontal",
+ "\u0120whiskey",
+ "\u0120humid",
+ "\u0120\u00ce\u0141",
+ "\u0120ridge",
+ "\u0120marin",
+ "\u0120bient\u00c3\u00b4t",
+ "\u0120Carrie",
+ "chw",
+ "\u0120tahun",
+ "\u0120Ergeb",
+ "FR",
+ "\u0120\u00ec\u0142\u0137\u00eb\u00b6\u0122",
+ "\u0120Soldier",
+ "\u0120enlightenment",
+ "\u0120examining",
+ "\u0120Notre",
+ "\u0120eram",
+ "\u0120Sunny",
+ "\u0120layered",
+ "\u0120Dazu",
+ "rades",
+ "\u00e5\u00a5\u00bd\u00e5\u0132\u0125",
+ "\u0120\u00d0\u00bd\u00d0\u00b0\u00d1\u012a\u00d0\u00b5\u00d0\u00b9",
+ "\u0120timber",
+ "\u0120manners",
+ "\u0120Birmingham",
+ "\u0120miniature",
+ "ometers",
+ "\u0120filler",
+ "\u0120Rip",
+ "\u0120Komb",
+ "owner",
+ "\u00ec\u00bf",
+ "idian",
+ "\u0120dem\u00c3\u00a1s",
+ "\u0120\u00d9\u012a\u00d8\u00aa",
+ "\u0120precautions",
+ "\u0120governo",
+ "zelf",
+ "\u0120Complete",
+ "\u00e5\u00b8\u0125",
+ "\u0120Phantom",
+ "\u00e3\u0123\u00be\u00e3\u0123\u013c",
+ "\u0120\u00d0\u00bd\u00d0\u00b5\u00d0\u00b7",
+ "\u0120\u00d0\u00ba\u00d0\u00b0\u00d1\u0122\u00d1\u0124",
+ "\u0120Antwort",
+ "\u0120Pfizer",
+ "\u0120Franco",
+ "\u0120w\u00c5\u0124",
+ "\u0120frig",
+ "esper",
+ "\u0120kale",
+ "\u0120filmmaker",
+ "\u0120kurt",
+ "\u0120invalid",
+ "\u00e5\u00b1\u0122",
+ "arella",
+ "\u00c4\u0125ng",
+ "ramento",
+ "\u0120nutritional",
+ "\u0120dictators",
+ "\u0120afin",
+ "\u0120fuzzy",
+ "\u0120Gina",
+ "\u00c3\u00b3t",
+ "\u0120Extremadura",
+ "\u0120demonstrations",
+ "\u0120Montgomery",
+ "\u00ed\u0137\u00b4\u00ec\u0126\u00a4",
+ "\u0120Gandhi",
+ "\u00e3\u0125\u013f",
+ "\u00e7\u00bd\u00ae",
+ "\u0120reunion",
+ "\u0120jaki\u00c5\u013d",
+ "\u0120Zug",
+ "OUGH",
+ "lifting",
+ "\u0120\u00e0\u00b2",
+ "\u00e1\u00b9\u013d\u00e1\u00b9\u00a3",
+ "eb",
+ "\u0120WOW",
+ "\u0120Shiva",
+ "ometry",
+ "\u0120wildly",
+ "\u0120tended",
+ "\u0120megap",
+ "\u00ec\u00b2\u013a",
+ "\u0120nause",
+ "\u0120gerek",
+ "\u00e3\u0125\u012d",
+ "\u0120Marcel",
+ "\u0120neste",
+ "\u00d8\u00ae\u00d8\u00b1",
+ "\u0120feh",
+ "\u00e5\u0128\u0127",
+ "suspenseful",
+ "\u0120Wrestle",
+ "\u0120Palestinians",
+ "\u0120GORD",
+ "iyet",
+ "\u0120\u00d1\u0122\u00d0\u00b0\u00d0\u00b4\u00d0\u00b8",
+ "\u0120versuchen",
+ "\u0120transistor",
+ "\u0120\u00d0\u0141\u00d1\u0122\u00d0\u00be\u00d1\u0123\u00d1\u0124\u00d0\u00be",
+ "\u0120\u00d0\u00bf\u00d0\u00be\u00d0\u00bd\u00d1\u0122\u00d0\u00b0\u00d0\u00b2",
+ "\u0120rhyme",
+ "\u0120Vermont",
+ "platz",
+ "\u00e8\u00ae\u00b0",
+ "\u0120\u00c4\u00b0\u00c5\u0141te",
+ "\u0120Hag",
+ "\u0120\u00d0\u013a\u00d0\u00bc",
+ "\u0120\u00d1\u0122\u00d0\u00b0\u00d1\u0123\u00d1\u0123\u00d0\u00ba\u00d0\u00b0\u00d0\u00b7",
+ "\u0120metros",
+ "\u0120Infinity",
+ "wolf",
+ "ibal",
+ "ftig",
+ "\u0120\u00da\u0128",
+ "\u0120\u00ed\u013a\u00b9\u00ec\u012d\u013e",
+ "\u0120oggi",
+ "\u0120disposit",
+ "\u0120\u00d0\u00bf\u00d1\u0122\u00d0\u00b8\u00d0\u00bb",
+ "\u0120\u00d0\u00b2\u00d1\u012d\u00d0\u00bf\u00d0\u00be\u00d0\u00bb",
+ "\u0120th\u00c3\u00b4i",
+ "\u0120KENN",
+ "\u0120handing",
+ "actus",
+ "\u0120tacos",
+ "\u0120formerly",
+ "\u0120Corinthians",
+ "\u00e3\u0123\u00ab\u00e3\u0123\u00af",
+ "\u00d1\u0128\u00d1\u0138\u00d1\u0139",
+ "\u0120padre",
+ "\u0120congregation",
+ "\u00e6\u0133",
+ "fert",
+ "\u0120subir",
+ "aiser",
+ "qua",
+ "araoh",
+ "\u0120Curry",
+ "\u0120\u00ec\u0137\u012c\u00eb\u012c\u0136",
+ "\u00d0\u00b5\u00d0\u00bb\u00d1\u0130",
+ "\u0120fuss",
+ "\u0120booty",
+ "\u0120lows",
+ "\u0120hommes",
+ "\u0120MH",
+ "\u0120Disneyland",
+ "went",
+ "\u0120residue",
+ "\u0120beeping",
+ "\u00e8\u00bc\u0137",
+ "\u00c3\u00a4tta",
+ "\u0120mould",
+ "\u0120Projekt",
+ "stalk",
+ "\u0120artifact",
+ "\u0120Antrag",
+ "\u0120AMD",
+ "\u0120Crypt",
+ "\u0120\u00eb\u00a9\u0136",
+ "\u0120Felipe",
+ "\u0120COB",
+ "elu",
+ "\u0120selfies",
+ "\u0120Santi",
+ "chutz",
+ "\u0120\u00d0\u00a3\u00d0\u00ba\u00d1\u0122\u00d0\u00b0\u00d1\u0139",
+ "gesamt",
+ "\u0120flock",
+ "jaz",
+ "plain",
+ "\u0120wrinkles",
+ "\u0120reais",
+ "\u0120paljon",
+ "\u0120empowerment",
+ "\u0120attendees",
+ "ppa",
+ "\u0120neden",
+ "\u00d0\u00be\u00d0\u00bd\u00d1\u012d",
+ "\u0120timeframe",
+ "\u0120Cherry",
+ "\u0120id\u00c3\u00a9e",
+ "\u0120gag",
+ "\u0120donkey",
+ "\u0120\u00c3\u00b4ng",
+ "\u0120Hare",
+ "\u00e9\u013c\u013d",
+ "\u0120Kara",
+ "\u0120acompan",
+ "places",
+ "imientos",
+ "\u0120Hamm",
+ "\u00d0\u00b1\u00d0\u00b8",
+ "uben",
+ "iliyor",
+ "\u0120thirst",
+ "\u0120kry",
+ "\u0120Georgetown",
+ "\u00d7\u0142\u00d7\u0136",
+ "\u0120orch",
+ "\u0120heartbeat",
+ "\u0120transformations",
+ "estones",
+ "\u0120KH",
+ "\u0120cartoons",
+ "\u0120anci",
+ "\u0120worthless",
+ "\u0120tailored",
+ "pu",
+ "Americans",
+ "\u0120piles",
+ "\u0120Monkey",
+ "\u0120basin",
+ "\u0120Temper",
+ "\u0120Paint",
+ "\u0120punching",
+ "\u0120baik",
+ "\u0120Oakland",
+ "vre",
+ "\u00c5\u0141allah",
+ "ydd",
+ "\u0120casually",
+ "odu",
+ "\u0120coded",
+ "\u0120Norwegian",
+ "\u0120Vince",
+ "\u0120premature",
+ "\u0120Promise",
+ "\u00d0\u00b5\u00d0\u00ba\u00d1\u0123\u00d1\u0124",
+ "\u0120devastated",
+ "\u0120Premium",
+ "\u0120Param",
+ "\u0120\u00c3\u0138yle",
+ "umuz",
+ "PO",
+ "rators",
+ "\u0120lamps",
+ "\u0120territorial",
+ "\u0120backbone",
+ "listed",
+ "DY",
+ "\u0120\u00d8\u00a7\u00d9\u0126\u00d8\u00b1",
+ "\u0120pursued",
+ "\u0120Commons",
+ "\u0120\u00ea\u00b3\u00a1",
+ "locks",
+ "edor",
+ "\u0120conceived",
+ "gere",
+ "\u0120disappearing",
+ "\u0120Sull",
+ "\u0120\u00ec\u0139\u00b0\u00eb",
+ "\u0120hoffe",
+ "\u0120detox",
+ "\u00ed\u0136\u012e",
+ "\u0120retir",
+ "\u0120\u00eb\u0123\u013f\u00eb\u0124",
+ "\u0120pergunta",
+ "\u0120BOY",
+ "\u00e7\u00b2\u00be",
+ "\u0120penn",
+ "\u00e6\u013f\u00a5\u00e4\u00ba\u0128",
+ "h\u00c3\u00a9s",
+ "hon",
+ "\u0120catastrophic",
+ "\u0120aust",
+ "\u0120torso",
+ "\u0120\u00ec\u0138\u00b4\u00eb\u012c\u0132",
+ "\u0120\u00ec\u0124\u00ac\u00eb\u0140\u012e\u00eb\u0135\u00a4\u00ec\u013f\u00b4",
+ "\u0120marvelous",
+ "\u0120Harley",
+ "achine",
+ "\u0120ti\u00e1\u00ba\u00bf",
+ "itto",
+ "\u0120I\u00c3\u0143m",
+ "ylon",
+ "\u0120shutdown",
+ ".''",
+ "\u0120apologies",
+ "\u0120Communication",
+ "\u0120\u00d0\u00b3\u00d0\u00be\u00d0\u00b2\u00d0\u00be\u00d1\u0122\u00d1\u0130",
+ "\u00e3\u0123\u0124\u00e3\u0125\u00bc",
+ "\u00e2\u0126\u00a2",
+ "\u00c3\u0143veis",
+ "acun",
+ "\u0120retaining",
+ "\u0120contradiction",
+ "\u0120ADAM",
+ "COM",
+ "Bryan",
+ "\u0120Monsieur",
+ "\u0120adapting",
+ "\u00d0\u00a8\u00d0\u0132",
+ "\u0120Scr",
+ "\u00c3\u00a4ndert",
+ "\u0120plaus",
+ "\u00e4\u00bb\u012c\u00e5\u00a4\u00a9\u00e7\u013c\u0126",
+ "\u0120onset",
+ "\u0120assistants",
+ "\u0120valves",
+ "\u0120scatter",
+ "\u0120Rust",
+ "awia",
+ "\u0120readiness",
+ "\u0120pais",
+ "\u0120bible",
+ "\u0120ambiente",
+ "\u0120\u00d0\u00b0\u00d0\u00bc\u00d0\u00b5\u00d1\u0122\u00d0\u00b8\u00d0\u00ba",
+ "\u0120uncond",
+ "\u0120kalk",
+ "\u00e5\u012c\u00a8",
+ "\u0120moc",
+ "unn",
+ "\u0120actu",
+ "\u0120humming",
+ "issimo",
+ "\u0120Patrol",
+ "gow",
+ "\u00e3\u0125\u00a4",
+ "\u0120THEY",
+ "\u0120Boden",
+ "\u0120Bie",
+ "\u0120reel",
+ "\u0120\u00d1\u0125\u00d1\u0123\u00d0\u00bb\u00d0\u00be\u00d0\u00b2",
+ "\u0120endeavor",
+ "\u0120Period",
+ "ustomed",
+ "mals",
+ "alon",
+ "Box",
+ "\u0120\u00cf\u0125\u00ce\u00b1\u00cf\u0124",
+ "\u0120omdat",
+ "\u0120altre",
+ "\u0120Heh",
+ "kad",
+ "\u0120protector",
+ "\u0120dominance",
+ "odynamic",
+ "\u0120communicated",
+ "k\u00c3\u00b6",
+ "\u0120predecessor",
+ "\u0120Luk",
+ "\u0120Flower",
+ "\u0120\u00e3\u0123\u00a9",
+ "poque",
+ "\u00d1\u0124\u00d0\u00b8\u00d1\u0122\u00d0\u00be\u00d0\u00b2",
+ "\u0120retrospect",
+ "\u0120decisive",
+ "\u0120exempel",
+ "{\\",
+ "\u0120R\u00c3\u00bcck",
+ "rite",
+ "\u0120Zeus",
+ "\u0120calorie",
+ "\u0120attractions",
+ "\u0120Hinter",
+ "\u0120uhm",
+ "\u0120\u00ed\u012e\u0132",
+ "\u0120rulers",
+ "\u0120discouraged",
+ "\u0120acontecer",
+ "\u0120accents",
+ "\u0120Optim",
+ "\u0120Alg",
+ "kids",
+ "2021",
+ "\u0120Lindsay",
+ "\u0120filmmakers",
+ "prowad",
+ "\u0120terug",
+ "\u00eb\u012d\u00b4",
+ "\u0120Sommer",
+ "2018",
+ "\u0120borrowing",
+ "\u0120Transfer",
+ "\u00d0\u00bd\u00d0\u00be\u00d0\u00bf",
+ "arias",
+ "\u0120headphone",
+ "\u00ec\u00bc\u013e",
+ "\u0120translating",
+ "\u0120aufge",
+ "\u00e0\u00ae\u00aa\u00e0\u00ae\u0141",
+ "weis",
+ "avant",
+ "paid",
+ "baby",
+ "\u0120toughest",
+ "\u0120repeats",
+ "\u0120Teresa",
+ "Lord",
+ "\u0120acabar",
+ "\u0120Ride",
+ "dir",
+ "\u0120leng",
+ "\u0120dwa",
+ "\u0120headaches",
+ "\u0120n\u00e1\u00bb\u00afa",
+ "\u0120\u00d0\u00bd\u00d0\u00b0\u00d1\u0123\u00d1\u0124\u00d0\u00be\u00d1\u0131\u00d1\u012b",
+ "\u0120boils",
+ "\u0120longing",
+ "rias",
+ "\u00c3\u00b3rio",
+ "\u0120Paradise",
+ "\u0120Se\u00c3\u00b1or",
+ "erdem",
+ "\u0120reinst",
+ "\u0120salaries",
+ "\u0120insecurity",
+ "\u00c5\u0124o\u00c5\u013dci",
+ "\u0120\u00d0\u00b0\u00d0\u00b1\u00d1\u0123\u00d0\u00be\u00d0\u00bb\u00d1\u0130\u00d1\u0124\u00d0\u00bd\u00d0\u00be",
+ "inken",
+ "\u0120Eddy",
+ "udos",
+ "\u0120dummy",
+ "\u00d0\u013c\u00d0\u00b0\u00d0\u00ba",
+ "six",
+ "\u0120inbox",
+ "\u00e1\u00ba\u00a9",
+ "People",
+ "\u00e1\u00bb\u0135ng",
+ "\u0120organizers",
+ "find",
+ "\u0120\u00c3\u00bcl",
+ "\u0120COM",
+ "\u00c5\u00bca",
+ "weile",
+ "Commentary",
+ "\u00ed\u012c\u00b8\u00eb\u00a5\u00bc",
+ "\u0120Mittel",
+ "kus",
+ "\u00e8\u013d\u012d",
+ "\u00e0\u00a4\u00a8",
+ "iral",
+ "\u0120garment",
+ "\u00ce\u00b9\u00ce\u00ba\u00ce\u00ac",
+ "\u0120stool",
+ "payers",
+ "\u0120shimmer",
+ "\u0120Ollie",
+ "\u0120Je\u00c5\u00bceli",
+ "\u00e8\u00bf\u013a\u00e6\u013e\u012b",
+ "\u01201977",
+ "\u0120jeux",
+ "\u0120extinct",
+ "\u0120Transportation",
+ "\u0120Maker",
+ "\u0120john",
+ "\u0120richest",
+ "\u0120traumat",
+ "\u0120liegen",
+ "\u00b4\u00eb\u00a5\u00bc",
+ "\u00e8\u00bf\u013b\u00e9\u0129\u012e",
+ "\u0120unrest",
+ "\u0120Straw",
+ "\u00e6\u012d\u013e\u00e6\u012d\u013e",
+ "\u0120coma",
+ "\u0120Kristen",
+ "\u0120\u00d0\u013c\u00d0\u00be\u00d0\u00bd\u00d0\u00b5\u00d1\u0129\u00d0\u00bd\u00d0\u00be",
+ "\u0120Bryce",
+ "\u0120\u00d1\u0131\u00d0\u00ba\u00d1\u0138",
+ "\u0120pearls",
+ "\u0120\u00d0\u00bf\u00d0\u00be\u00d0\u00bd\u00d0\u00b8\u00d0\u00bc\u00d0\u00b0\u00d1\u0130",
+ "\u0120additions",
+ "\u0120asympt",
+ "\u0120\u00d0\u00bc\u00d0\u00b5\u00d0\u00bd\u00d1\u012e\u00d1\u012a\u00d0\u00b5",
+ "\u0120scans",
+ "Child",
+ "\u0120Hide",
+ "\u00d0\u00ba\u00d1\u0125\u00d1\u0130",
+ "etas",
+ "\u0120dank",
+ "\u0120pleas",
+ "\u0120essays",
+ "\u0120jets",
+ "\u00e5\u0127\u0134",
+ "\u0120\u00d0\u00b2\u00d0\u00b5\u00d0\u00b4",
+ "\u0120positives",
+ "hof",
+ "-)",
+ "zzo",
+ "\u0120starters",
+ "\u0120smiled",
+ "\u01201944",
+ "quiera",
+ "\u0120rok",
+ "\u0120puesto",
+ "Nico",
+ "\u0120simulations",
+ "\u0120\u00e0\u00b6",
+ "\u0120intrigued",
+ "\u0120Overwatch",
+ "\u00e5\u0138\u0124",
+ "sigh",
+ "bai",
+ "\u0120\u00eb\u00a7\u0132\u00ea\u00b3\u0142",
+ "id\u00c3\u00a9",
+ "\u0120crabs",
+ "\u00e1\u00ba\u0143p",
+ "\u0120Iraqi",
+ "\u00ec\u013f\u00b4\u00eb\u00a5\u00bc",
+ "\u00d1\u0124\u00d1\u0131",
+ "\u0120Sophia",
+ "\u0120DNS",
+ "\u0120\u00c3\u00b6nemli",
+ "\u0120Luo",
+ "\u013f\u00a4",
+ "\u0120Counsel",
+ "ligen",
+ "\u00d0\u00b0\u00d0\u00bd\u00d1\u012e\u00d1\u012a\u00d0\u00b5",
+ "\u0120trumpet",
+ "\u0120dapat",
+ "\u0120JM",
+ "\u0120EVERY",
+ "\u0120\u00e5\u00b0\u012f\u00e4\u00b8\u012f\u00e5\u00b0\u012f",
+ "\u00e5\u00a4\u00a2",
+ "\u0120Layer",
+ "\u0120c\u00c3\u00b4",
+ "\u00d0\u00bd\u00d0\u00b0\u00d0\u00bb",
+ "\u0120Joo",
+ "\u0120Hack",
+ "\u0120sunt",
+ "\u0120Leonard",
+ "\u0120Firebase",
+ "\u00c3\u00a4nger",
+ "\u0120exploding",
+ "voy",
+ "\u0120\u00ec\u00a6\u0132",
+ "\u0120\u00d1\u0123\u00d0\u00b5\u00d1\u0122\u00d1\u012e",
+ "\u0120severity",
+ "\u0120bestimm",
+ "\u00e7\u00b5\u0132\u00e6\u0140\u013e",
+ "\u0120tiring",
+ "\u0120procurement",
+ "\u0120diplomacy",
+ "\u0120decorative",
+ "\u0120\u00d9\u012c\u00d8\u00a7",
+ "\u0120penetration",
+ "\u00d5\u00ab",
+ "\u0120outright",
+ "ENE",
+ "\u0120Uni",
+ "odles",
+ "\u0120zeros",
+ "\u0120delightful",
+ "jm",
+ "\u0120dopo",
+ "\u00e6\u00b2\u00a1\u00e4\u00ba\u012d",
+ "\u0120positivity",
+ "\u0120VISTA",
+ "\u0120Resource",
+ "\u00ed\u0125\u0122\u00eb",
+ "\u00d1\u012a\u00d0\u00b8\u00d0\u00b5",
+ "Carl",
+ "\u0120piping",
+ "\u0120chopping",
+ "\u0120Ganze",
+ "\u00c3\u00bcss",
+ "\u0120Ao",
+ "\u0120shattered",
+ "\u0120Detective",
+ "\u0120undoubtedly",
+ "\u0120halluc",
+ "\u0120ench",
+ "\u00d1\u012d\u00d1\u0129\u00d0\u00bd\u00d0\u00be",
+ "\u00d1\u0125\u00d0\u00bb\u00d1\u0131\u00d1\u0122",
+ "isesti",
+ "\u0120pedals",
+ "\u0120durum",
+ "\u00a4\u00ed\u0136",
+ "laimer",
+ "\u0120propre",
+ "Cu",
+ "\u0120translator",
+ "\u0120ca\u00c5\u0124",
+ "\u0120\u00ea\u00b7\u00b8\u00ea\u00b1\u00b8",
+ "\u0120ca\u00c5\u0124y",
+ "UA",
+ "\u0120revised",
+ "\u0120\u00d0\u00bf\u00d0\u00be\u00d0\u00b4\u00d0\u00be\u00d0\u00b1",
+ "\u0120Article",
+ "\u0120Haiti",
+ "\u0120\u00c3\u0135",
+ "\u0120Ctrl",
+ "\u0120rozm",
+ "lait",
+ "\u0120letzte",
+ "ispering",
+ "display",
+ "\u0120aluminium",
+ "\u0120palabras",
+ "\u0120conocer",
+ "\u0120zitten",
+ "\u0120dirig",
+ "\u00e5\u0131\u00aa\u00e6\u013e\u012b",
+ "\u0120brainstorm",
+ "\u0120wifi",
+ "\u0120Particip",
+ "\u0120viewpoint",
+ "\u0120Quan",
+ "\u0120hierarch",
+ "Welcome",
+ "\u00e5\u00af\u00be",
+ "\u0120offen",
+ "\u0120Recovery",
+ "gano",
+ "Would",
+ "\u0120repro",
+ "\u0120perceptions",
+ "\u0120demasi",
+ "\u0120Bangladesh",
+ "\u0120Incredible",
+ "\u0120letzt",
+ "\u0120behaving",
+ "\u0120astonishing",
+ "\u0120\u00e2\u0128",
+ "\u0120\u00eb\u0124\u00a8\u00ec\u0140\u0132",
+ "\u00e8\u00b5\u00b0\u00e4\u00ba\u0128",
+ "\u00e3\u0125\u0136",
+ "\u0120GORDON",
+ "CAR",
+ "?!\"",
+ "\u0120Prest",
+ "\u0120\u00eb\u00a7\u0140\u00ec\u0137\u0126\u00ec\u013c\u0136",
+ "\u0120tand",
+ "\u0120lash",
+ "\u00e7\u012c",
+ "ificant",
+ "\u0120intoler",
+ "\u0120\u00d0\u00b3\u00d0\u00b5\u00d1\u0122\u00d0\u00be",
+ "\u0120teu",
+ "aso",
+ "\u0120\u00d1\u0123\u00d0\u00be\u00d0\u00b2\u00d0\u00b5\u00d1\u0124",
+ "\u0120travelers",
+ "\u0120Synd",
+ "\u0120\u00d0\u00b2\u00d0\u00b5\u00d1\u0122\u00d1\u0123",
+ "Fonda",
+ "ad\u00c4\u00b1",
+ "\u0120transcription",
+ "\u0120titanium",
+ "\u0120twists",
+ "\u0120gearbox",
+ "ensation",
+ "fat",
+ "Coll",
+ "\u0120Commonwealth",
+ "zon",
+ "\u0120Polizei",
+ "\u0120APPLAUSE",
+ "fry",
+ "\u0120Juda",
+ "esteem",
+ "\u0120sock",
+ "\u0120Jugend",
+ "\u0120\u00d0\u00ba\u00d1\u0123\u00d1\u0124\u00d0\u00b0\u00d1\u0124\u00d0\u00b8",
+ "\u0120Dro",
+ "\u0120prochaine",
+ "\u00e3\u0125\u00bc\u00e3\u0125\u00ab",
+ "\u0120liksom",
+ "\u0120Energie",
+ "\u0120Marina",
+ "\u0120230",
+ "\u0120\u00ea\u00b0\u0122\u00ec\u0126\u013e",
+ "umping",
+ "\u0120lone",
+ "\u00e7\u00b4\u013c",
+ "\u0120fonts",
+ "\u0120businessman",
+ "\u0120ply",
+ "\u0120doe",
+ "grid",
+ "\u0120Milwaukee",
+ "\u0120Eden",
+ "!\".",
+ "\u0120\u00db\u012e\u00db\u0123",
+ "ogens",
+ "\u0120teaser",
+ "\u0120qui\u00c3\u00a9n",
+ "\u0120incentiv",
+ "govern",
+ "\u0120childcare",
+ "\u0120sneakers",
+ "\u0120imprisoned",
+ "\u00c2\u00ae",
+ "\u00d0\u00b8\u00d1\u0124\u00d0\u00b5\u00d1\u0123\u00d1\u012e",
+ "anbul",
+ "\u0120regain",
+ "\u0120tranquil",
+ "Redner",
+ "\u00e9\u013d\u00a8",
+ "IFA",
+ "\u0120ideological",
+ "\u0120mayor\u00c3\u0143a",
+ "\u0120bureau",
+ "eterm",
+ "\u0120DID",
+ "\u00ec\u012c\u00b7",
+ "\u0120waving",
+ "\u0120beb",
+ "\u0120\u00c3\u00a1r",
+ "\u0120\u00d0\u00ba\u00d0\u00b2",
+ "\u0120envoy",
+ "anut",
+ "\u00d0\u00b8\u00d0\u00ba\u00d1\u0125",
+ "\u0120Environment",
+ "\u0120Assass",
+ "\u00e3\u0124\u0135\u00e3\u0123\u00a7",
+ "\u0120Bread",
+ "\u0120\u00d0\u00a2\u00d1\u0125\u00d1\u0124",
+ "\u0120staircase",
+ "\u0120Disease",
+ "\u0120aucun",
+ "\u0120\u00eb\u012d\u012a",
+ "\u0120confrontation",
+ "\u01201941",
+ "\u0120irony",
+ "\u0120worsh",
+ "\u00e3\u0124\u012e\u00e3\u0124\u012d",
+ "\u0120fick",
+ "\u0120Naomi",
+ "\u0120backside",
+ "ieux",
+ "Kap",
+ "\u0120vedere",
+ "\u0120lengthy",
+ "\u0120breaker",
+ "\u0120Rolle",
+ "\u0120predator",
+ "\u0120nossos",
+ "\u0120advertise",
+ "\u00e8\u00b3\u0129",
+ "\u00d1\u0122\u00d0\u00be\u00d0\u00b4\u00d0\u00b5",
+ "Rednerwechsel",
+ "reten",
+ "\u0120collectors",
+ "\u00c4\u00b1\u00c4\u0141\u00c4\u00b1m\u00c4\u00b1z",
+ "\u0120trig",
+ "\u0120axes",
+ "inters",
+ "\u0120penalties",
+ "\u0120Osman",
+ "\u0120Jenna",
+ "\u0120flakes",
+ "\u0120trainers",
+ "\u0120stunned",
+ "\u0120Scroll",
+ "\u0120Pip",
+ "\u0120\u00d0\u00bd\u00d0\u00b0\u00d1\u0123\u00d1\u0124",
+ "\u0120nh\u00c3\u0142",
+ "\u0120Smack",
+ "\u00e1\u00ba\u00abn",
+ "ratos",
+ "\u0120\u00d1\u0122\u00d0\u00b0\u00d0\u00b1\u00d0\u00be\u00d1\u0124\u00d1\u012d",
+ "\u0120ucz",
+ "\u0120Lemon",
+ "\u0120Sind",
+ "\u0120psychic",
+ "\u0120Abg",
+ "\u0120mammals",
+ "\u0120immersive",
+ "\u0120bots",
+ "\u0120verschiedene",
+ "\u0120geral",
+ "\u0120follower",
+ "\u0120\u00e4\u00bb\u0138",
+ "\u0120seguridad",
+ "\u0120immersed",
+ "feito",
+ "cross",
+ "\u0120\u00c3\u00b6ld",
+ "\u00ed\u0125\u0126",
+ "\u0120\u00e3\u0123\u0135\u00e3\u0123\u00ae",
+ "\u0120\u00d7\u0136\u00d7\u013b\u00d7\u0132",
+ "\u0120Jian",
+ "\u0120biliyor",
+ "area",
+ "\u0120kaf",
+ "\u0120godt",
+ "\u00e7\u013d\u00b8\u00e4\u00bf\u00a1",
+ "\u0120\u00eb\u00b0\u00a9\u00ec\u0128\u00a1",
+ "\u0120detriment",
+ "\u00e6\u00a5\u013c",
+ "\u00d1\u0138\u00d0\u00bb",
+ "\u0120\u00c4\u0133\u00c3\u00a2u",
+ "\u0120chloride",
+ "\u00c3\u00b8re",
+ "lei",
+ "\u0120monte",
+ "\u0120diff\u00c3\u00a9rentes",
+ "\u00e0\u00af\u0123.",
+ "\u0120caregivers",
+ "\u0120inadequ",
+ "\u0120farewell",
+ "\u0120\u00d1\u0124\u00d0\u00b8\u00d0\u00bf\u00d0\u00b0",
+ "ontec",
+ "\u0120Eph",
+ "HHH",
+ "\u0120Todos",
+ "\u0120\u00d0\u00a1\u00d0\u00a8\u00d0\u0132",
+ "\u0120trov",
+ "\u0120lige",
+ "\u0120c\u00c3\u00b4ng",
+ "\u0120Civ",
+ "\u0120capaz",
+ "\u0120Vallahi",
+ "\u0120queste",
+ "\u0120replica",
+ "\u00d8\u00b3\u00d8\u00a8",
+ "zna",
+ "\u0120\u00d1\u0123\u00d0\u00bb\u00d1\u0125\u00d0\u00b6",
+ "\u0120PT",
+ "wave",
+ "ieni",
+ "\u0120relied",
+ "develop",
+ "\u0120deme",
+ "\u0120Aman",
+ "\u0120[...]",
+ "\u0120compliments",
+ "uais",
+ "\u0120\u00ed\u012e\u00a8",
+ "\u0120smelling",
+ "\u0120dadurch",
+ "\u00d9\u012a\u00d8\u00aa",
+ "\u0120oranges",
+ "\u0120\u00d0\u00bb\u00d0\u00b0\u00d0\u00b9",
+ "\u0120stabilization",
+ "\u00e5\u0122\u012f",
+ "\u00e3\u0124\u012e\u00e3\u0123\u0141",
+ "\u00e6\u00a5\u00bd",
+ "\u0120appliances",
+ "\u0120hm",
+ "\u0125\u0132\u00eb\u00a9\u00b4",
+ "odynamics",
+ "\u0120ci\u00c4\u013b",
+ "\u0120Cott",
+ "MON",
+ "\u0120Mang",
+ "\u00e6\u0136\u00af\u00e6\u012e\u0123",
+ "\u0120allerdings",
+ "\u00ce\u00b9\u00ce\u00ba\u00ce\u00ae",
+ "shots",
+ "\u0120ts",
+ "\u0120G\u00c3\u00b6r",
+ "\u0120CHAR",
+ "\u0120:(",
+ "\u0120wrath",
+ "\u0120fique",
+ "\u0120f\u00c3\u00bchren",
+ "\u0120testament",
+ "\u0120^^",
+ "\u00e1\u00b9\u013d\u00e1\u00b9\u00a3\u00e1\u00b9\u0129a",
+ "ALD",
+ "\u0120texto",
+ "\u0120Dogs",
+ "\u0120sib",
+ "\u0120pathetic",
+ "ocks",
+ "\u0120radically",
+ "\u0120MORE",
+ "\u0120JAMES",
+ "\u0120ingl",
+ "\u0120Technical",
+ "\u0120porch",
+ "\u0120UT",
+ "\u0120\u00d0\u00be\u00d0\u00b1\u00d1\u0131\u00d0\u00b7\u00d0\u00b0\u00d1\u0124\u00d0\u00b5\u00d0\u00bb\u00d1\u012e\u00d0\u00bd\u00d0\u00be",
+ "\u0120renewal",
+ "\u0120aesthetics",
+ "ikum",
+ "\u0120beverage",
+ "dern",
+ "\u0120predictive",
+ "\u0120chuy",
+ "\u0120Regarding",
+ "\u0120Forward",
+ "\u0120\u00d9\u012a\u00d9\u0126",
+ "\u0120contextual",
+ "\u0120dwarf",
+ "\u0120prehe",
+ "\u0120governed",
+ "\u0127\u0126",
+ "\u0120trabalhar",
+ "\u0120neg\u00c3\u00b3cio",
+ "\u0120\u00d0\u00b1\u00d0\u00be\u00d0\u00bb\u00d1\u012e\u00d1\u012a\u00d0\u00be\u00d0\u00b9",
+ "\u00d0\u00b5\u00d1\u0129\u00d0\u00b0\u00d1\u0124",
+ "\u0120\u00d0\u00b4\u00d1\u0125\u00d1\u0127",
+ "\u0120floods",
+ "\u0120bowling",
+ "\u0120OB",
+ "\u0120H\u00c3\u00a4r",
+ "\u0120grading",
+ "\u00ec\u00a3\u00bc\u00eb\u012c\u0136",
+ "\u0120gars",
+ "dling",
+ "\u0120rak",
+ "\u00eb\u012a",
+ "creat",
+ "\u0120\u00d1\u012b\u00d0\u00b5",
+ "\u0120neighbours",
+ "food",
+ "Query",
+ "\u0120heroin",
+ "iceps",
+ "\u0120Kinda",
+ "NET",
+ "\u0120mari",
+ "\u0120imitate",
+ "\u0120achter",
+ "\u0120settlements",
+ "rare",
+ "cciones",
+ "\u0120\u00eb\u0135\u013e",
+ "\u0120fik",
+ "itung",
+ "\u0120\u00d0\u00bc\u00d0\u00b0\u00d0\u00ba\u00d1\u0123\u00d0\u00b8\u00d0\u00bc",
+ "\u0120elf",
+ "\u0120dalla",
+ "\u0120Polsce",
+ "\u0120Pul",
+ "\u00d0\u00a7\u00d1\u0124\u00d0\u00be",
+ "\u0120Morgen",
+ "\u00d8\u0143\u00d9\u0127",
+ "\u0120supremacy",
+ "\u0120kys",
+ "\u0120Hurricane",
+ "\u0120GTA",
+ "\u0120Feh",
+ "\u0120finalmente",
+ "mund",
+ "\u0120Krie",
+ "\u00c3\u00a9poque",
+ "\u0120Tucker",
+ "ITT",
+ "\u0120lur",
+ "\u0120dipping",
+ "\u00c3\u00a4v",
+ "\u0120eerste",
+ "\u0120Flint",
+ "bildung",
+ "\u00e0\u00b8\u00b9\u00e0\u00b9\u012b",
+ "\u0120toim",
+ "\u0120pracy",
+ "\u0120transforms",
+ "\u0120speeding",
+ "\u0120presenter",
+ "\u0120fellows",
+ "filled",
+ "ieza",
+ "\u0120advising",
+ "\u0120Interview",
+ "\u00d0\u00b8\u00d0\u00b3\u00d1\u0122",
+ "wehr",
+ "\u0120Dante",
+ "pture",
+ "\u012a\u00eb\u00ac\u00b8",
+ "\u00af\u00b8\u00eb",
+ "\u0132\u0132",
+ "\u0120Counter",
+ "\u0120crist",
+ "\u0120\u00ec\u00a7\u013e",
+ "\u0120jeune",
+ "\u0120\u00d1\u0123\u00d1\u0124\u00d1\u0122\u00d0\u00b0\u00d1\u012a",
+ "\u0120mie\u00c4\u0129",
+ "\u0120tutor",
+ "\u0120masala",
+ "\u0120powdered",
+ "\u0120nau",
+ "\u0120Frederick",
+ "\u0120billing",
+ "\u0120Eisen",
+ "\u0120\u00d0\u00b4\u00d0\u00be\u00d0\u00b1\u00d1\u0122",
+ "\u0120mest",
+ "\u00e6\u00bd",
+ "\u0120snipp",
+ "\u0120mono",
+ "\u0120Alo",
+ "\u0120Mercy",
+ "\u00c3\u00a9rience",
+ "\u0120casualties",
+ "\u0120ANNOUNCER",
+ "\u00e4\u00bb\u0130",
+ "\u0120tocar",
+ "\u0120bacterial",
+ "Ho",
+ "\u0120streak",
+ "\u0120JENN",
+ "\u0120plast",
+ "\u00d1\u0123\u00d0\u00bb\u00d0\u00b5\u00d0\u00b4",
+ "\u0120reapp",
+ "\u0120paycheck",
+ "\u0120miners",
+ "habt",
+ "\u0120Jap",
+ "\u00d0\u00bd\u00d1\u0125\u00d1\u0124",
+ "\u0120redemption",
+ "\u0120quir",
+ "hnlich",
+ "\u0120accumulation",
+ "\u0120shove",
+ "\u0120adrenaline",
+ "Make",
+ "\u0120Hern",
+ "ossing",
+ "\u0120Vil",
+ "ubby",
+ "hertz",
+ "breaks",
+ "\u0120spur",
+ "\u0120Daha",
+ "USTIN",
+ "\u0120continuer",
+ "\u0120Saul",
+ "\u00e3\u0123\u00ae\u00e3\u0123\u00af",
+ "\u0120\u00ed\u0131\u0143",
+ "\u0120\u00eb\u0132\u013a\u00eb\u00a9\u00b4",
+ "\u0120\u00eb\u00a7\u0132\u00ec\u0136\u0122",
+ "\u0120\u00d0\u00be\u00d0\u00b6",
+ "\u0120suspects",
+ "\u0120laquelle",
+ "\u0120Muchas",
+ "\u0120v\u00c3\u00b6llig",
+ "ulen",
+ "\u0120impres",
+ "\u0120lobb",
+ "enee",
+ "\u0120\u00d0\u00bd\u00d0\u00b0\u00d0\u00b6",
+ "Ta",
+ "\u0120r\u00c3\u00a9alit\u00c3\u00a9",
+ "\u0120Rex",
+ "\u0120harvesting",
+ "\u0120estr",
+ "\u00e6\u00b6",
+ "ospace",
+ "OSS",
+ "\u0120disturbance",
+ "assic",
+ "\u0120Isab",
+ "\u0120d\u00c3\u00a9couv",
+ "\u0120Hampshire",
+ "\u0120ornament",
+ "\u0120lu\u00c3\u00b4n",
+ "\u0120UW",
+ "\u0120j\u00c4\u0127",
+ "\u00e9\u0124\u00a3\u00e4\u00b9\u012a",
+ "\u0120respecto",
+ "\u0120comunidad",
+ "\u0120comigo",
+ "agna",
+ "\u0120intrinsic",
+ "\u0120Alumni",
+ "\u0120sesleri",
+ "\u0120estimation",
+ "\u00e2\u0122\u0136\u00e2\u0122\u0136",
+ "\u0120produit",
+ "\u00e3\u0122\u0124\u00e3\u0122\u012f",
+ "\u0120\u00d0\u00b2\u00d1\u0122",
+ "\u0120whirl",
+ "\u0120acces",
+ "\u00c3\u00a7u",
+ "\u0120variability",
+ "\u0120vodka",
+ "itsu",
+ "\u0120internships",
+ "\u0120allocate",
+ "RR",
+ "\u00ed\u013d\u012a",
+ "\u0120instructional",
+ "tant",
+ "\u0120\u00e0\u00ae\u0127\u00e0\u00ae\u00a4",
+ "\u0120invites",
+ "\u0120hak",
+ "\u0120scares",
+ "\u0120eclipse",
+ "\u00d0\u00bf\u00d0\u00be\u00d0\u00b2",
+ "\u00d0\u00ba\u00d0\u00be\u00d0\u00bb\u00d1\u012e",
+ "ativas",
+ "\u0120stabbed",
+ "\u0120DOM",
+ "\u00e4\u00b8\u012f\u00e5\u012a\u00b0",
+ "roots",
+ "\u0120Picture",
+ "\u00ed\u013a\u00bc",
+ "\u0120CHA",
+ "iec",
+ "\u00c4\u00b1\u00c4\u00b1",
+ "hanol",
+ "\u0120misunderstand",
+ "Ray",
+ "\u0120roadmap",
+ "ocumented",
+ "izione",
+ "\u0120Olive",
+ "rift",
+ "\u0120\u00d7\u0136\u00d7\u0142",
+ "\u00e6\u00af\u012f",
+ "lest",
+ ";;",
+ "\u0120EA",
+ "\u00e9\u013e\u0122\u00e8\u00a6\u0123",
+ "\u00d0\u00be\u00d0\u00b4\u00d1\u0125",
+ "\u0120hobbies",
+ "\u0120burial",
+ "\u00e3\u0123\u00ab\u00e3\u0123\u00a1\u00e3\u0123\u00af",
+ "\u00d0\u00a4",
+ "lege",
+ "\u0120HJ",
+ "\u0120objection",
+ "\u0120\u00e3\u0123\u0143",
+ "ctory",
+ "\u0120incremental",
+ "\u0120gymn",
+ "\u0120epidemi",
+ "\u00d1\u0123\u00d1\u012d\u00d0\u00bb",
+ "\u00c3\u0133",
+ "\u0120advancement",
+ "\u0120parch",
+ "News",
+ "\u0120ayr",
+ "\u00d0\u00bb\u00d0\u00b0\u00d0\u00bc",
+ "\u0120\u00d7\u013e\u00d7\u00a9",
+ "\u0120diploma",
+ "\u00e3\u0123\u00a1\u00e3\u0124\u0125\u00e3\u0124\u0135",
+ "\u0120robbed",
+ "Only",
+ "\u0120incur",
+ "\u0120chanting",
+ "\u0120\u00ed\u0137\u00b4\u00eb\u0131\u0126",
+ "\u0120riches",
+ "\u0120Carmen",
+ "\u0120nostro",
+ "\u00ce\u00bb\u00ce\u0143",
+ "\u0120Powder",
+ "\u00e0\u00b9\u0122\u00e0\u00b8\u00ab",
+ "\u0120\u00ec\u0140\u012a\u00ec\u013e\u00bc\u00eb\u00a9\u00b4",
+ "\u0120ger\u00c3\u00a7ekten",
+ "\u0120Pikachu",
+ "\u00d0\u00b5\u00d0\u00bc\u00d0\u00be\u00d0\u00bd",
+ "OLL",
+ "\u0120planetary",
+ "\u0120slows",
+ "\u0120clockwise",
+ "alion",
+ "\u0120\u00ec\u012e",
+ "\u0120vern",
+ "\u0120homme",
+ "\u0120endpoint",
+ "\u0120innocence",
+ "\u0120elementos",
+ "\u0120sophomore",
+ "\u0120notions",
+ "\u0120Couldn",
+ "pur",
+ "\u0120zat",
+ "\u0120obsess",
+ "\u0120motivo",
+ "\u0120Kub",
+ "\u0120Drug",
+ "Ant",
+ "\u0120Players",
+ "\u0120Humans",
+ "\u0120melee",
+ "\u0120Wildlife",
+ "\u0120VP",
+ "\u0120volcanic",
+ "\u0120comin",
+ "\u0120Guang",
+ "\u0120\u00cf\u0126\u00ce\u00b9\u00cf\u0124",
+ "\u0120\u00d0\u00be\u00d1\u0123\u00d0\u00be\u00d0\u00b1\u00d0\u00b5\u00d0\u00bd\u00d0\u00bd\u00d0\u00be",
+ "\u0120Size",
+ "Listen",
+ "\u0120Aaa",
+ "appro",
+ "\u0120barbar",
+ "\u0120Parkinson",
+ "\u00d0\u00bd\u00d1\u0131\u00d1\u0124\u00d1\u012e",
+ "\u00e5\u012f\u00b0",
+ "\u0120underestimate",
+ "\u0120substitution",
+ "\u0120cosmetic",
+ "\u00e4\u00b8\u012d\u00e6\u00ac\u00a1",
+ "\u0120willen",
+ "\u0120beide",
+ "anni",
+ "\u0120conditioned",
+ "\u0120Debbie",
+ "\u0120isto",
+ "\u0120Edwards",
+ "\u00ec\u013d\u012e\u00ec\u013c\u0136",
+ "\u0120\u00d1\u0124\u00d0\u00be\u00d0\u00b2",
+ "\u0120abbrevi",
+ "\u0120M\u00c3\u00bcn",
+ "\u0120Princ",
+ "\u0120Liang",
+ "\u0120stink",
+ "\u0120radioactive",
+ "\u00e3\u0123\u0128\u00e3\u0124\u0131",
+ "\u0120acontec",
+ "\u0120uncon",
+ "\u0120Turbo",
+ "\u00e3\u0123\u0132",
+ "\u0120kisses",
+ "\u00e6\u013a\u00af\u00e4\u00bb\u0122\u00e9\u00ba\u00bc",
+ "\u00d0\u00b5\u00d1\u0124\u00d1\u0122\u00d0\u00be\u00d0\u00b2",
+ "\u0120frontier",
+ "\u0120Spy",
+ "\u0120Belarus",
+ "\u0120CBS",
+ "\u00e1\u00bb\u0139",
+ "amoto",
+ "\u00ed\u0137\u013e\u00eb\u012f\u00b0",
+ "\u0120\u00d1\u0123\u00d1\u0124\u00d1\u0122\u00d0\u00be",
+ "\u0120Enfin",
+ "\u0120breadth",
+ "\u00e9\u013a\u00b2",
+ "\u0120Cafe",
+ "\u0120Daf\u00c3\u00bcr",
+ "\u0120Bour",
+ "aras",
+ "\u0120blueprint",
+ "an\u00c4\u00b1",
+ "\u0120constants",
+ "\u0120attacker",
+ "\u0120Formula",
+ "za\u00c4\u0129",
+ "\u0120sowie",
+ "\u0120eyebrow",
+ "obook",
+ "\u0120setzen",
+ "\u00e7\u00ac\u00ac\u00e4\u00b8\u012b",
+ "onsider",
+ "awning",
+ "\u0120s\u00c3\u00b6yleye",
+ "\u0120invaded",
+ "\u0120pronouns",
+ "\u0120dobry",
+ "Si",
+ "\u0120\u00d0\u00a5\u00d0\u00be\u00d1\u0124",
+ "\u0120volleyball",
+ "\u0120lament",
+ "isches",
+ "arme",
+ "api",
+ "\u0120Wiki",
+ "\u00d0\u00bb\u00d0\u00b8\u00d1\u012a",
+ "\u0120kasih",
+ "\u0120pess",
+ "\u0120\u00d1\u0126\u00d0\u00be\u00d1\u0124",
+ "\u0120Sul",
+ "\u00e5\u00be\u00b7",
+ "\u0120pseudo",
+ "\u0120memo",
+ "\u0120\u00ec\u0139\u00b0\u00ec\u012c\u00b5",
+ "\u0120\u00d0\u00b4\u00d0\u00be\u00d0\u00bb\u00d0\u00bb\u00d0\u00b0\u00d1\u0122\u00d0\u00be\u00d0\u00b2",
+ "\u0120\u00d0\u00bf\u00d0\u00b5\u00d1\u0122\u00d0\u00b5\u00d0\u00bc",
+ "\u0120Reach",
+ "miral",
+ "alted",
+ "\u0120statut",
+ "reading",
+ "\u0120s\u00c3\u00b6yled",
+ "\u0120Lindsey",
+ "\u0120Ahmad",
+ "\u00eb\u00b6\u0122\u00eb",
+ "\u0120\u00d0\u00a1\u00d0\u00b5\u00d0\u00b3\u00d0\u00be\u00d0\u00b4\u00d0\u00bd\u00d1\u0131",
+ "\u0120przygot",
+ "\u0120hyster",
+ "URE",
+ "\u0120Neigh",
+ "Reporter",
+ "\u0120Bunu",
+ "\u0120Treaty",
+ "\u0120Rank",
+ "\u0120Fame",
+ "inished",
+ "\u0120geared",
+ "\u0120compose",
+ "odia",
+ "\u0120Lon",
+ "\u0120jeste\u00c5\u013dmy",
+ "\u0120DIRECTOR",
+ "\u0120elkaar",
+ "\u0120Viel",
+ "\u00d7\u0132\u00d7\u00a9",
+ "ynthia",
+ "\u00e4\u00b8\u00a6",
+ "\u0120m\u00c3\u00a8re",
+ "\u0120Tomato",
+ "\u0120exatamente",
+ "ni\u00c4\u013b",
+ "\u0120Frei",
+ "\u0120Dif",
+ "\u0120openings",
+ "\u0120graphical",
+ "\u0120\u00d1\u0125\u00d0\u00b4\u00d0\u00be\u00d0\u00b1",
+ "\u0120\u00d0\u00b2\u00d1\u0123\u00d0\u00bf",
+ "\u0120Weekly",
+ "\u00d0\u00b5\u00d0\u00b2\u00d0\u00b0",
+ "\u0120hangs",
+ "\u0120unsafe",
+ "\u0120emblem",
+ "\u0120Kolleginnen",
+ "alay",
+ "\u0120ksi",
+ "\u0120hides",
+ "\u0120olmay",
+ "\u0120entste",
+ "\u0120arthritis",
+ "\u00c3\u0141erdem",
+ "\u0120binnen",
+ "\u0120listens",
+ "\u0120Hess",
+ "\u00e5\u0128\u012f\u00e4\u00be\u0128",
+ "\u0120Louise",
+ "lden",
+ "\u00d0\u00b5\u00d0\u00bd\u00d1\u0123",
+ "\u0120Version",
+ "\u0120Agriculture",
+ "\u00ec\u012c\u00a4\u00eb\u00a5\u00bc",
+ "\u00d0\u00bc\u00d0\u00b0\u00d0\u00bd",
+ "\u00eb\u0126\u00a4\u00ec\u013c\u0136",
+ "\u0120wines",
+ "\u0120INF",
+ "rul",
+ "\u0120JK",
+ "\u00c4\u00b1yorlar",
+ "shield",
+ "reath",
+ "\u0120terus",
+ "\u0120Lum",
+ "\u0120anticipation",
+ "\u0120accustomed",
+ "\u0120Mina",
+ "\u0120wield",
+ "io\u00c3\u00a8",
+ "mera",
+ "\u0120countdown",
+ "\u0120cling",
+ "\u0120commend",
+ "\u0120faktiskt",
+ "\u0120defenses",
+ "\u0120cockpit",
+ "\u0120\u00d0\u00ba\u00d0\u00be\u00d0\u00bc\u00d0\u00b0\u00d0\u00bd\u00d0\u00b4",
+ "\u0120dishwas",
+ "\u0120Thanos",
+ "\u0120kidneys",
+ "\u0120sehe",
+ "\u0120microbes",
+ "\u0120cuff",
+ "\u0120\u00d0\u00b2\u00d1\u012d\u00d1\u0123\u00d0\u00be\u00d0\u00ba",
+ "\u0120Spicy",
+ "\u00e7\u0143\u012b\u00e7\u0143\u012b",
+ "\u00e0\u00ae\u00b5\u00e0\u00ae\u00b0",
+ "culus",
+ "orc",
+ "\u00e7\u00be\u0127",
+ "ixes",
+ "\u0120Credit",
+ "\u0120raj",
+ "\u0120bringt",
+ "\u0120Niss",
+ "\u0120grim",
+ "\u0120SOL",
+ "\u0120tenim",
+ "\u0120Sudan",
+ "\u0120Spart",
+ "\u0120promotes",
+ "\u0120Nossa",
+ "\u0120\u00d1\u0123\u00d0\u00be\u00d1\u0123\u00d1\u0124\u00d0\u00be\u00d1\u0131\u00d0\u00bd\u00d0\u00b8",
+ "\u0120\u00ec\u00b0\u00a9",
+ "\u0120uncont",
+ "\u0120Liberal",
+ "\u0120\u00d0\u00a2\u00d0\u00be\u00d0\u00bb\u00d1\u012e\u00d0\u00ba\u00d0\u00be",
+ "\u0120Viele",
+ "\u0120kt\u00c3\u00b3rej",
+ "\u0120****",
+ "Max",
+ "\u0120\u00d0\u00a7\u00d1\u0124\u00d0\u00be\u00d0\u00b1\u00d1\u012d",
+ "350",
+ "\u0120\u00ed\u013a\u00bc\u00ec\u0140\u0132",
+ "\u0120\u00eb\u00b6\u0126\u00eb\u0135\u00a4\u00ec\u013f\u00b4",
+ "\u0120warp",
+ "\u0120tenga",
+ "\u0120sympathetic",
+ "\u0120bizi",
+ "\u0120Zack",
+ "iedo",
+ "\u0120\u00eb\u012b\u00b4\u00ec",
+ "piel",
+ "\u0120\u00d1\u0124\u00d0\u00be\u00d0\u00bb",
+ "\u0120scaled",
+ "\u0120PETER",
+ "\u0120COMM",
+ "\u0120Came",
+ "\u0120catastrophe",
+ "\u0120sweaty",
+ "igration",
+ "\u0120stuffing",
+ "\u0120\u00cf\u0122\u00ce\u00bf\u00ce\u00bb\u00cf\u012f",
+ "\u0120Driver",
+ "zyst",
+ "Tech",
+ "\u0120assessed",
+ "\u0120Surface",
+ "\u00c4\u00b1r\u00c4\u00b1m",
+ "sur",
+ "lerweile",
+ "\u0120\u00d0\u00b4\u00d0\u00be\u00d0\u00b3",
+ "\u0120shutting",
+ "\u0120fractions",
+ "\u0120\u00d1\u0123\u00d0\u00be\u00d0\u00bb",
+ "everyone",
+ "\u0120ern",
+ "\u0120\u00d0\u013f\u00d0\u00be\u00d0\u00b2",
+ "\u0120defenders",
+ "\u0120versucht",
+ "\u00e3\u0125\u00b3\u00e3\u0125\u0122",
+ "\u0120polity",
+ "\u0120\u00d0\u0141\u00d0\u00be\u00d0\u00bd",
+ "verst\u00c3\u00a4nd",
+ "\u0120browsers",
+ "\u0120transformative",
+ "\u0120dictate",
+ "\u0120LEGO",
+ "\u0120ninguna",
+ "\u00ea\u00b4\u0133",
+ "\u0120pizz",
+ "\u0120Harold",
+ "\u0120Lopez",
+ "\u00da\u00be\u00db\u012e",
+ "an\u00c4\u00b1z",
+ "atchet",
+ "\u00d9\u012c\u00d8\u00aa",
+ "\u0120lernen",
+ "\u0120\u00ea\u00b7\u0122\u00ec\u0139\u00ac",
+ "\u0120housed",
+ "\u0120cleanse",
+ "\u0120WAT",
+ "laration",
+ "\u0120bytes",
+ "\u0120tucked",
+ "\u0120faults",
+ "\u00d0\u00b4\u00d0\u00be",
+ "FX",
+ "\u0120\u00ec\u0138\u00bc\u00eb\u00a7\u012a\u00eb\u0124\u013a",
+ "\u0120deform",
+ "\u0120contracting",
+ "\u0120TIME",
+ "irse",
+ "\u0120neben",
+ "\u0120cerc",
+ "\u0120Armstrong",
+ "\u0120tester",
+ "\u0120parfait",
+ "\u0120jealousy",
+ "\u0120toxins",
+ "\u0120disbel",
+ "\u00d1\u0125\u00d1\u0122\u00d1\u012d",
+ "impression",
+ "\u0120prostate",
+ "\u0120firewall",
+ "\u0120classics",
+ "\u00d0\u00b5\u00d1\u0129\u00d1\u012e",
+ "\u0120socialism",
+ "\u0120gracious",
+ "\u0120\u00d1\u0123\u00d0\u00bd\u00d0\u00be\u00d0\u00b2\u00d0\u00b0",
+ "\u0120\u00d0\u00b4\u00d0\u00bd\u00d1\u0131",
+ "\u0120burner",
+ "\u0120Minor",
+ "\u0120\u00ec\u013c\u00b0\u00eb\u00a6\u00ac\u00eb",
+ "\u0120jedes",
+ "\u0120continuum",
+ "\u0120hots",
+ "\u0120occurrence",
+ "\u0120administered",
+ "\u0120\u00d0\u00b7\u00d0\u00b0\u00d0\u00bc\u00d0\u00b5\u00d1\u0124",
+ "\u0120hesitation",
+ "\u0120drills",
+ "erca",
+ "\u0120\u00d0\u00b2\u00d1\u0124\u00d0\u00be\u00d1\u0122\u00d0\u00be\u00d0\u00b9",
+ "\u0120steadily",
+ "\u0120insanlar",
+ "\u0120ihan",
+ "\u00ed\u0133",
+ "\u0120helper",
+ "\u0120Senin",
+ "\u00e5\u0123\u013e",
+ "\u00d0\u00be\u00d0\u00b2\u00d0\u00b0\u00d0\u00bd\u00d0\u00b8\u00d0\u00b5",
+ "\u0120ERIC",
+ "bla",
+ "\u0120Academic",
+ "\u0120humanities",
+ "black",
+ "umpy",
+ "ortex",
+ "\u0120\u00ec\u0142\u012a\u00eb",
+ "\u0120\u00d8\u00a5\u00d9\u0128",
+ "\u0120disclose",
+ "\u0120Elijah",
+ "\u0120\u00ce\u00bb\u00ce\u0143",
+ "\u0120Quer",
+ "\u00d8\u00a8\u00d9\u0126",
+ "\u00e3\u0124\u00a1",
+ "Tell",
+ "arle",
+ "\u00d1\u0138\u00d1\u0122",
+ "\u0120augmented",
+ "\u0120\u00eb\u00b9\u0126\u00ec\u012c\u00b7",
+ "\u0120android",
+ "\u00e0\u00a4\u00a4",
+ "arma",
+ "\u0120szer",
+ "geord",
+ "\u0120geek",
+ "\u0120yeux",
+ "\u0120pong",
+ "\u0120\u00e3\u0123\u013f\u00e3\u0123\u0128",
+ "\u0120tortured",
+ "\u0120Bath",
+ "zig",
+ "asonable",
+ "\u0120nets",
+ "\u0120baru",
+ "\u0120Flat",
+ "\u0120Vater",
+ "\u0120Terror",
+ "\u0120Avo",
+ "\u0120ceremonies",
+ "roe",
+ "\u00d9\u0123\u00d8\u00b3",
+ "Ops",
+ "\u0120hyvin",
+ "\u0120apresent",
+ "olor",
+ "\u0120\u00d0\u00b8\u00d0\u00b3\u00d1\u0122\u00d1\u012d",
+ "orton",
+ "\u0120\u00ea\u00b7\u00b8\u00eb\u0140\u00ac",
+ "\u0120lookin",
+ "\u0120TY",
+ "\u0120Mint",
+ "Add",
+ "\u0120mite",
+ "\u0120Smoke",
+ "\u0120nota",
+ "\u0120moss",
+ "\u0120Abend",
+ "\u0120\u00ec\u00bb\u00a8",
+ "\u0120exaggerated",
+ "fires",
+ "\u0120redist",
+ "ffiti",
+ "\u0120openness",
+ "\u00ea\u00b0\u0132\u00ec\u013f\u00b4",
+ "endeu",
+ "\u00d0\u00b5\u00d0\u00bd\u00d0\u00bd\u00d0\u00be\u00d0\u00b9",
+ "Watch",
+ "\u0120avatar",
+ "\u0120Pey",
+ "urun",
+ "\u0120senza",
+ "\u0120\u00ec\u00a7\u0122\u00ec\u0139\u0143",
+ "\u0120Natomiast",
+ "\u0120emergence",
+ "rays",
+ "\u0120crafted",
+ "gary",
+ "\u00e3\u0123\u0142\u00e3\u0123\u0133",
+ "\u00c3\u00bcng",
+ "-\"",
+ "\u0120hacked",
+ "\u0120stray",
+ "encie",
+ "emo",
+ "\u0120comen",
+ "\u0120K\u00c4\u00b1z",
+ "\u0120Jasmine",
+ "\u0120Hindi",
+ "manas",
+ "\u0120infinitely",
+ "emon",
+ "\u00ec\u013f\u00b8\u00eb\u012f\u00b0\u00ec\u013c\u0136",
+ "jak",
+ "\u0120roaring",
+ "\u00c3\u00a9rique",
+ "sweise",
+ "\u0120Rolex",
+ "\u00e5\u0142\u00b1\u00e5\u00b0\u0130",
+ "\u0120Stuart",
+ "bnb",
+ "\u0120diagnose",
+ "\u0120coherent",
+ "\u0120MJ",
+ "\u00e6\u00ba\u0138\u00e5\u0124\u013b",
+ "\u0120pike",
+ "lav",
+ "\u0120orchestral",
+ "\u00d0\u00b0\u00d1\u0123\u00d1\u0124\u00d0\u00b8",
+ "\u0120terminar",
+ "\u0120gatherings",
+ "\u0120compliant",
+ "\u0120upgrading",
+ "\u0120regulator",
+ "\u0120lan\u00c3\u00a7",
+ "\u00e9\u0122\u00a3",
+ "\u0120merchants",
+ "tawa",
+ "\u0120monitored",
+ "\u0120rendre",
+ "\u00e4\u00b8\u00a4",
+ "\u0120unterwegs",
+ "anguard",
+ "gard",
+ "\u0120Below",
+ "duino",
+ "\u0120\u00d0\u00a6\u00d0\u00b5",
+ "\u0120impedance",
+ "\u00ec\u013e\u00a1",
+ "\u00e4\u00bb\u00bd",
+ "\u0120aktuell",
+ "\u0120Vatic",
+ "\u00e5\u0143\u00a9",
+ "\u0120stewards",
+ "\u0120brightest",
+ "\u0120kenn",
+ "\u0120kau",
+ "\u0120Matrix",
+ "\u0120Bark",
+ "\u0120\u00f0\u0141\u0133",
+ "\u0120taper",
+ "\u0120casino",
+ "\u00d7\u00a8\u00d7\u0136",
+ "ysical",
+ "\u0120builders",
+ "\u0120cz\u00c5\u0124owie",
+ "\u0120Nepal",
+ "\u0120!\"",
+ "\u0120terme",
+ "\u0120innych",
+ "\u0120maths",
+ "\u0120drafted",
+ "\u0120Balk",
+ "\u0120hesitant",
+ "\u0120voltar",
+ "\u0120revive",
+ "\u0120\u00d1\u0126\u00d0\u00b8\u00d0\u00bb\u00d1\u012e\u00d0\u00bc\u00d0\u00b0",
+ "\u0120assassin",
+ "\u0120Solutions",
+ "\u0120duel",
+ "\u0120bearings",
+ "\u00e0\u00b8\u0126\u00e0\u00b8\u00b0",
+ "\u0120rookie",
+ "ikat",
+ "\u0120biscuits",
+ "\u0120cords",
+ "\u00d1\u0125\u00d0\u00b2\u00d0\u00b0\u00d1\u0124\u00d0\u00b8",
+ "ARIN",
+ "\u0120progressing",
+ "\u0120Gir",
+ "\u0120penetrate",
+ "\u0120Storage",
+ "eight",
+ "\u0120\u00d1\u0124\u00d1\u0122\u00d1\u0125",
+ "\u0120don\u00c3\u0143t",
+ "\u0120sizin",
+ "\u0120outdated",
+ "\u0120\u00d0\u00bd\u00d0\u00b0\u00d1\u012a\u00d0\u00b8",
+ "\u0120affir",
+ "\u0120spoons",
+ "\u0120oni",
+ "\u0120flank",
+ "\u0120Gol",
+ "h\u00c3\u00a3",
+ "\u0120p\u00c3\u00a9ri",
+ "\u0120honorable",
+ "\u0120Breathe",
+ "scenes",
+ "\u0120obviamente",
+ "\u00d0\u00b8\u00d0\u00ba\u00d1\u0123",
+ "\u0120\u00d7\u00a9\u00d7\u0140\u00d7",
+ "\u0120smoothie",
+ "\u0140\u012a\u00eb",
+ "\u0120dime",
+ "\u0120\u00ed\u0138\u012a\u00ec\u0138\u00b4\u00ec\u013c\u0136",
+ "\u0120appel",
+ "\u0120Catholics",
+ "\u0120singles",
+ "\u0120laten",
+ "\u0120\u00c3\u00a7\u00c3\u00bcnk\u00c3\u00bc",
+ "\u0120Vader",
+ "\u00e6\u0131\u013d",
+ "\u0120vard\u00c4\u00b1",
+ "\u0120Istanbul",
+ "gr\u00c3\u00a9",
+ "\u0120Elsa",
+ "\u00c3\u00abl",
+ "\u0120invece",
+ "\u0120crane",
+ "\u0120obe",
+ "\u0120Shark",
+ "\u0120smack",
+ "\u0120restoring",
+ ".\\",
+ "\u0120\u00eb\u00b9\u0142\u00eb",
+ "\u0120faded",
+ "umbers",
+ "Singing",
+ "\u0120depressing",
+ "thest",
+ "\u0120Wahr",
+ "\u0120multitude",
+ "\u00d1\u0122\u00d0\u00b0\u00d0\u00b2\u00d1\u0123\u00d1\u0124\u00d0\u00b2\u00d1\u0125\u00d0\u00b9\u00d1\u0124\u00d0\u00b5",
+ "rijk",
+ "eka",
+ "\u0120completes",
+ "\u0120Wells",
+ "\u0120roy",
+ "\u0120Pray",
+ "\u0120Kalau",
+ "izin",
+ "ia\u00c5\u0124em",
+ "\u0120locom",
+ "\u0120Nashville",
+ "\u0120Pentagon",
+ "\u00eb\u00af\u00b8",
+ "\u0120NEW",
+ "\u00c4\u0127\u00c4\u0129",
+ "\u00c3\u0143ss",
+ "\u0120marrying",
+ "\u0120feud",
+ "\u00ed\u013b\u0137",
+ "\u00e6\u0122\u00a5",
+ ")!",
+ "\u0120Operations",
+ "\u00d1\u0125\u00d1\u0136",
+ "\u0120moje",
+ "\u0120instructed",
+ "\u0120\u00eb\u012a\u0126\u00ea\u00b5\u00ac",
+ "\u0120\u00d7\u0136\u00d7\u0134",
+ "\u0120\u00d0\u00bf\u00d0\u00be\u00d0\u00bc\u00d0\u00be\u00d1\u012b\u00d1\u012e\u00d1\u0130",
+ "\u0120sabia",
+ "\u00ec\u0137\u013a\u00ec\u0138\u00b4\u00ec\u013c\u0136",
+ "plane",
+ "pri",
+ "\u0120\u00d0\u00bf\u00d0\u00be\u00d0\u00bb\u00d0\u00bd\u00d0\u00be\u00d1\u0123\u00d1\u0124\u00d1\u012e\u00d1\u0130",
+ "\u0120Kitty",
+ "\u0120pr\u00c3\u00b3prio",
+ "edere",
+ "\u0120interesante",
+ "\u0120\u00d0\u00b4\u00d0\u00b5",
+ "\u0120condensed",
+ "\u0120avent",
+ "TOR",
+ "\u0120greasy",
+ "ARK",
+ "orta",
+ "AJ",
+ "\u0120disreg",
+ "\u0120corrections",
+ "\u0120stero",
+ "\u0120influenza",
+ "\u0120desses",
+ "\u0120ballots",
+ "\u0120meget",
+ "\u0120mafia",
+ "\u0120b\u00c3\u00b6l",
+ "nost",
+ "\u0120\u00d1\u0123\u00d1\u0124\u00d0\u00b0\u00d1\u0124\u00d1\u012e",
+ "\u0120responder",
+ "\u0120hinten",
+ "grav",
+ "\u00e0\u00b8\u0143\u00e0\u00b8\u00b0",
+ "ynchron",
+ "\u0120viens",
+ "\u0120samo",
+ "\u0120dt",
+ "pannt",
+ "\u0120\u00c5\u013dwiat",
+ "\u0120\u00d0\u00b7\u00d0\u00b0\u00d0\u00bf\u00d0\u00b8\u00d1\u0123",
+ "\u0120merged",
+ "\u0120kep",
+ "\u0120misleading",
+ "\u0120digamos",
+ "\u0120ammon",
+ "\u00e8\u00be\u013d",
+ "chet",
+ "\u0120\u00ea\u00b0\u0122\u00ec\u0142\u00b8",
+ "\u0120uni",
+ "\u0120\u00eb\u0132\u013a\u00eb\u012c\u0136\u00eb\u012f\u00b0",
+ "\u0120\u00d0\u00bd\u00d0\u00b0\u00d0\u00bf\u00d1\u0122\u00d0\u00b0\u00d0\u00b2",
+ "\u0120\u00d0\u00ba\u00d0\u00be\u00d1\u0124\u00d0\u00be\u00d1\u0122\u00d0\u00be\u00d0\u00b3\u00d0\u00be",
+ "\u0120animate",
+ "\u00d7\u0137\u00d7\u0132\u00d7",
+ "\u00d0\u00b5\u00d1\u0122\u00d0\u00b2",
+ "\u0120minced",
+ "\u0120kaum",
+ "\u00e3\u0123\u0124\u00e3\u0123\u0123",
+ "\u00cf\u0122\u00ce\u00b5",
+ "\u00d0\u00bb\u00d0\u00b5\u00d0\u00b3",
+ "existing",
+ "\u0120plataform",
+ "\u0120KRIS",
+ "\u00ec\u013d\u0142",
+ "\u0120Familien",
+ "\u0120Libya",
+ "\u0120biodiversity",
+ "\u0120idiots",
+ "irdi",
+ "\u0120szyb",
+ "\u0120Rolling",
+ "\u00c3\u00bccht",
+ "\u0120\u00d1\u0125\u00d0\u00b4\u00d0\u00b8\u00d0\u00b2",
+ "\u00d1\u0123\u00d1\u0125\u00d0\u00b4",
+ "\u0120realizar",
+ "\u0120canned",
+ "\u0120\u00d1\u0122\u00d0\u00b0\u00d0\u00bd",
+ "\u0120metabolic",
+ "\u0120Beef",
+ "\u0120kilka",
+ "\u00d0\u00bb\u00d1\u0130\u00d1\u0123",
+ "\u0120registry",
+ "\u00d0\u00bc\u00d0\u00be\u00d1\u0124\u00d1\u0122\u00d0\u00b8\u00d1\u0124\u00d0\u00b5",
+ "\u0120viel\u00c3\u00a4",
+ "\u0120odc",
+ "\u0120condemned",
+ "\u00e6\u00a9\u012d",
+ "fal",
+ "\u0120Dil",
+ "wo\u00c5\u013dci",
+ "Aw",
+ "\u0120statistically",
+ "\u0120sogen",
+ "\u0120BETH",
+ "\u0120shaving",
+ "\u00e5\u00b9\u00b8",
+ "ocal",
+ "\u0120Funny",
+ "\u0120peacefully",
+ "\u0120addictive",
+ "\u0120Insert",
+ "lauf",
+ "\u0120experiencia",
+ "\u00e9\u00a6\u0138\u00e5\u0127\u012a",
+ "\u00d0\u00b8\u00d1\u0124\u00d0\u00b5\u00d0\u00bb\u00d1\u0131",
+ "\u00c3\u0143gen",
+ "\u00c3\u00a1gina",
+ "\u0120abdomen",
+ "\u00ed\u0137\u013e\u00eb\u012d\u00a4",
+ "icus",
+ "imana",
+ "\u00ec\u012f\u00a8",
+ "arching",
+ "\u0120konkret",
+ "\u00ec\u0137\u013a\u00eb",
+ "\u00d0\u00b5\u00d0\u00ba\u00d0\u00b0",
+ "oufl",
+ "ivel",
+ "\u0120nude",
+ "\u00c3\u00a8tres",
+ "\u0120monsieur",
+ "\u0120clash",
+ "\u0120therapists",
+ "\u0120cubed",
+ "\u0120retrouver",
+ "\u0120waveform",
+ "\u0120potem",
+ "\u0120Former",
+ "isi\u00c3\u00b3n",
+ "\u00e5\u00ba\u013e",
+ "\u0120\u00d7\u0132\u00d7\u013f",
+ "undos",
+ "\u0120Meinung",
+ "\u00d8\u00b5\u00d9\u0126",
+ "\u0120Jude",
+ "\u0120n\u00c3\u00a5r",
+ "\u0120Leonardo",
+ "\u0120Cristo",
+ "\u0120GOT",
+ "\u00d1\u0123\u00d1\u0124\u00d1\u0122\u00d1\u0125\u00d0\u00ba",
+ "LAN",
+ "\u0120g\u00c3\u00a5ng",
+ "\u0120d\u00c3\u00a9b",
+ "\u0120Frankfurt",
+ "\u0120crappy",
+ "\u0120lil",
+ "ann\u00c3\u00a9e",
+ "\u0120\u00d0\u00bc\u00d0\u00b5\u00d1\u0123\u00d1\u0124\u00d0\u00b5",
+ "RET",
+ "\u0120Ner",
+ "\u0120COSTA",
+ "\u0120jedem",
+ "\u0120curtains",
+ "\u0120iterations",
+ "\u0120unav",
+ "\u0120plaque",
+ "orum",
+ "\u0120\u00ce\u00b6",
+ "\u0120n\u00c3\u00bameros",
+ "\u0120desap",
+ "\u00b2\u00bd",
+ "\u0120compiled",
+ "\u0120refle",
+ "\u0120rankings",
+ "\u0120repaired",
+ "\u0120\u00d0\u013f\u00d0\u00b0\u00d0\u00bf\u00d1\u0122",
+ "\u0120downloads",
+ "\u0120armour",
+ "\u0120\u00d7\u013b\u00d7\u0137\u00d7\u00aa\u00d7\u00a8",
+ "\u0120longevity",
+ "\u0120TONER",
+ "\u0120\u00d0\u00ba\u00d0\u00be\u00d0\u00bc\u00d0\u00bc\u00d0\u00b5\u00d0\u00bd\u00d1\u0124\u00d0\u00b0\u00d1\u0122",
+ "\u0120czego",
+ "\u0120notify",
+ "\u0120airports",
+ "\u0120enduring",
+ "lette",
+ "\u0120apparat",
+ "\u0120habil",
+ "\u00e1\u00bb\u0129c",
+ "nad",
+ "ICO",
+ "\u0120Brah",
+ "\u0120seg\u00c3\u00ban",
+ "\u0120governors",
+ "kaha",
+ "\u0120Schluss",
+ "\u0120odpowied",
+ "irting",
+ "\u0120rempl",
+ "\u0120Aboriginal",
+ "identally",
+ "\u0120enhancing",
+ "licting",
+ "\u0120Hawaiian",
+ "\u0120striving",
+ "\u0120Niet",
+ "\u0120znaczy",
+ "\u0120obedience",
+ "\u0120n\u00c3\u00a5got",
+ "\u0120expired",
+ "\u01201918",
+ "presented",
+ "\u0120prowad",
+ "\u0120Terr",
+ "\u0120Princeton",
+ "\u0120morgen",
+ "\u0120attracting",
+ "\u0120Sigma",
+ "igner",
+ "\u0120Rechts",
+ "\u0120Peki",
+ "\u0120methy",
+ "\u0120hamm",
+ "\u0120direito",
+ "\u0120delegation",
+ "\u00d0\u00b8\u00d0\u00b2\u00d0\u00b0\u00d1\u0130\u00d1\u0124",
+ "\u0120gin",
+ "Young",
+ "\u0120dependencies",
+ "\u0120Bradley",
+ "buds",
+ "\u0120fis",
+ "\u0120pytanie",
+ "\u0120interconnected",
+ "\u0120embaixo",
+ "\u0120Sas",
+ "\u0120ruh",
+ "\u0120Sicht",
+ "Sur",
+ "\u0120superb",
+ "\u0120Sabbath",
+ "\u0120Danger",
+ "kol",
+ "\u0120hou",
+ "supp",
+ "\u0120Nacional",
+ "\u0120succession",
+ "\u0120v\u00c3\u00a1",
+ "\u0120Ma\u00c3\u0141nahmen",
+ "\u0120Jessie",
+ "\u0120Idaho",
+ "forest",
+ "\u0127\u013a",
+ "\u0120\u00d7\u0140\u00d7\u0135",
+ "\u0120\u00d8\u00a3\u00d9\u012c",
+ "\u0120sweetheart",
+ "\u0120neatly",
+ "\u0120Evangel",
+ "\u00ea\u00b3\u00a1",
+ "\u0120Suite",
+ "\u00c3\u00bablica",
+ "\u0120\u00d1\u0125\u00d0\u00bb\u00d0\u00b8",
+ "\u0120Announcer",
+ "ligh",
+ "\u0120sensations",
+ "\u0120shelters",
+ "\u0120hart",
+ "\u0120squeezing",
+ "\u0120Rivers",
+ "\u0120Cooking",
+ "\u00ec\u00b1\u0127",
+ "personal",
+ "\u0120manos",
+ "\u00d1\u0133\u00d1\u0124\u00d1\u0123\u00d1\u0131",
+ "wij",
+ "\u0120gogg",
+ "\u0120Milli",
+ "\u0120FP",
+ "\u00c3\u00bcnst",
+ "\u0120LS",
+ "\u0120spraying",
+ "\u0120faux",
+ "\u0120autograph",
+ "ologic",
+ "\u0120torment",
+ "\u0120encrypted",
+ "\u00e1\u00bb\u0127",
+ "\u0120estre",
+ "\u00e7\u00b9\u00bc",
+ "\u00e0\u00b1",
+ "\u0120stumbled",
+ "\u0120aider",
+ "\u0120saben",
+ "xter",
+ "\u0120Cities",
+ "\u0120T\u00c3\u00bcrk",
+ "\u00eb\u012d\u00a5",
+ "chine",
+ "\u0120topping",
+ "\u0120poisoned",
+ "\u0120Romania",
+ "\u00d7\u0135\u00d7\u013b",
+ "\u0122\u00eb\u00a1\u013e",
+ "\u0120\u00d0\u00bf\u00d0\u00be\u00d1\u0122\u00d1\u0131\u00d0\u00b4",
+ "\u0120chirping",
+ "\u0120\u00ec\u013b\u0126\u00eb",
+ "\u00d7\u0133\u00d7\u00a2",
+ "\u0120cuanto",
+ "\u0120donating",
+ "\u0120Regent",
+ "\u0120Beruf",
+ "\u0120distracting",
+ "\u0120stamina",
+ "\u0120Darren",
+ "\u0120\u00ec\u00b6\u0137",
+ "lists",
+ "dal",
+ "chuss",
+ "\u0120economist",
+ "\u00e3\u0123\u012a\u00e3\u0125\u00bc",
+ "orgt",
+ "\u0120istiyorum",
+ "\u00e8\u00bf\u013d",
+ "\u0120Surprise",
+ "\u0120Hao",
+ "\u0120\u00ec\u00b5\u013e\u00ea\u00b3\u0142",
+ "\u0120GW",
+ "\u0120Inner",
+ "\u0120quieren",
+ "\u0120minded",
+ "\u0120supercomputer",
+ "\u0120diagrams",
+ "\u00ed\u012c\u013e\u00eb",
+ "\u00ea\u00b2\u0142\u00ec\u0138\u00b4",
+ "\u0120\u00d0\u00be\u00d0\u00b1\u00d1\u012c\u00d1\u0131\u00d1\u0123",
+ "\u0120estaban",
+ "\u0120destroys",
+ "\u0120Breaking",
+ "\u0120kar\u00c4\u00b1\u00c5\u0141",
+ "\u0120rebuilding",
+ "\u013e\u00eb\u012e\u0122",
+ "\u00d0\u00bb\u00d0\u00b8\u00d0\u00b2\u00d0\u00be",
+ "\u0120Sauce",
+ "\u0120Fusion",
+ "\u00d7\u0137\u00d7\u0140\u00d7",
+ "\u0120Quinn",
+ "\u0120gauche",
+ "\u0120\u00d9\u012a\u00d8\u00a3",
+ "\u0120\u00c8",
+ "\u00e7\u0135\u013e",
+ "\u0120techno",
+ "\u0120dispatch",
+ "\u0120a\u00c5\u0141k",
+ "\u0120einzel",
+ "\u0120Gmail",
+ "\u00e7\u0140",
+ "\u0120\u00ea\u00b0\u013e\u00ec\u013f\u00b8",
+ "\u0120\u00d1\u0123\u00d0\u00b5\u00d0\u00bc\u00d1\u012e",
+ "\u0120journeys",
+ "\u0120iht",
+ "\u0120fibre",
+ "\u0120dramas",
+ "ouched",
+ "\u0120rename",
+ "\u0120\u00d0\u00be\u00d0\u00bf\u00d0\u00b5\u00d1\u0122",
+ "\u0120poo",
+ "\u0120Dru",
+ "\u0120\u00d0\u00b8\u00d1\u0124\u00d0\u00be\u00d0\u00b3",
+ "\u0120zast",
+ "\u0120coz",
+ "\u0120zucch",
+ "\u0120obtaining",
+ "\u0120commute",
+ "\u0120submer",
+ "\u0120Vish",
+ "\u0120Rabb",
+ "ogg",
+ "\u0120hut",
+ "\u00ed\u0138\u012a\u00ec\u0138\u00b4",
+ "\u00e6\u00af\u0136\u00e5\u00a6\u0124",
+ "eremi",
+ "\u0120\u00ce\u00bc\u00ce\u00b1",
+ "\u0120diskut",
+ "\u0120\u00d0\u00b1\u00d1\u0125\u00d0\u00ba",
+ "\u0120impaired",
+ "depend",
+ "\u0120\u00d9\u012a\u00d8\u00a7",
+ "\u0120\u00d1\u0122\u00d1\u0125\u00d0\u00ba",
+ "\u0120\u00d0\u00b1\u00d0\u00b0\u00d1\u0122",
+ "\u0120oxidation",
+ "\u0120situa\u00c3\u00a7\u00c3\u00a3o",
+ "\u00c9\u013bn",
+ "u\u00c3\u00a7\u00c3\u00a3o",
+ "\u0120sagte",
+ "\u0120SER",
+ "\u0120Cake",
+ "\u0120turmeric",
+ "\u0120Kak",
+ "bung",
+ "\u0120K\u00e1\u00b9\u013d\u00e1\u00b9\u00a3\u00e1\u00b9\u0129a",
+ "\u0120poisoning",
+ "\u0120slipping",
+ "\u0120Says",
+ "\u00e5\u00b0\u00b1\u00e5\u0131\u00af\u00e4\u00bb\u00a5",
+ "\u00c3\u00b2ng",
+ "\u00e7\u0141\u00b3",
+ "\u00c2\u00ab",
+ "\u0120Claudia",
+ "\u0120Character",
+ "\u00d0\u00bd\u00d0\u00b8\u00d1\u0128",
+ "coat",
+ "\u0120progressed",
+ "\u0120Fergus",
+ "\u0120\u00ec\u013a\u00a4\u00eb\u012c",
+ "\u0120oat",
+ "ordable",
+ "\u0120Ley",
+ "\u0120Heraus",
+ "\u0120resultados",
+ "\u0120Kayla",
+ "\u0120riff",
+ "\u0120chegou",
+ "\u0120xi",
+ "\u0120spacious",
+ "\u0120recognised",
+ "\u0120ech",
+ "\u0120Tie",
+ "\u0120launcher",
+ "Jim",
+ "\u0120suppression",
+ "\u0120Impossible",
+ "\u0120guitars",
+ "\u0120Fourier",
+ "\u00d0\u00b8\u00d1\u0129\u00d0\u00b5\u00d1\u0123\u00d0\u00ba\u00d0\u00b8\u00d0\u00b9",
+ "\u0120Therap",
+ "\u0120Kaf",
+ "centered",
+ "\u0120\u00d1\u0123\u00d0\u00be\u00d0\u00be\u00d1\u0124\u00d0\u00b2\u00d0\u00b5\u00d1\u0124",
+ "\u0120klim",
+ "\u0120carbohydrates",
+ "ignant",
+ "\u0120Astron",
+ "\u0120emple",
+ "\u0120drastic",
+ "\u0120\u00d0\u00bc\u00d0\u00b8\u00d1\u0122\u00d0\u00b5",
+ "\u00d0\u00b2\u00d0\u00b8\u00d0\u00bd",
+ "uw",
+ "\u0120prettier",
+ "\u0120donuts",
+ "\u0120Athena",
+ "\u0120dissert",
+ "\u0120plante",
+ "\u0120uranium",
+ "\u00ec\u013f\u012e\u00eb",
+ "ar\u00c3\u00a9",
+ "\u0120rzecz",
+ "\u0120displaying",
+ "\u00e6\u012a\u00b2",
+ "\u0120sarc",
+ "r\u00c3\u00a3o",
+ "\u0120tampoco",
+ "\u0120philosophers",
+ "\u0120Recht",
+ "\u00e6\u0135\u013c",
+ "\u0120comentarios",
+ "yse",
+ "\u0120\u00ec\u013e\u00a4",
+ "\u0120mise",
+ "\u0120Gin",
+ "\u0120\u00d0\u00bd\u00d0\u00be\u00d0\u00bc",
+ "\u0120FROM",
+ "liner",
+ "atif",
+ "\u0120spo\u00c5\u0124ec",
+ "xa",
+ "\u0120\u00d1\u0124\u00d1\u0122\u00d1\u0125\u00d0\u00b4",
+ "\u0120wag",
+ "\u00ea\u00b8\u00b0\u00ec\u0139\u0132",
+ "\u0120MG",
+ "\u0120offspring",
+ "\u0120Understanding",
+ "\u00e5\u0131\u00aa\u00e6\u013a\u00af",
+ "ORA",
+ "\u0120whirring",
+ "\u0120surrend",
+ "\u0120poker",
+ "\u0120monuments",
+ "\u0120\u00e2\u013b\u00a9",
+ "\u0120organised",
+ "\u0120Sozial",
+ "\u0120Factory",
+ "\u00d1\u0127\u00d0\u00b0",
+ "\u0120resemble",
+ "\u00d0\u00b7\u00d0\u00b4",
+ "\u0120explosions",
+ "\u0120payroll",
+ "\u0120omn",
+ "\u0120Jorge",
+ "\u00ce\u00b9\u00cf\u0125",
+ "\u0120fracture",
+ "\u0120persecution",
+ "\u0120demais",
+ "ECH",
+ ",)",
+ "\u0120criar",
+ "\u0120JOSH",
+ "\u0120demographics",
+ "\u01201600",
+ "\u0120currencies",
+ "\u0120Tips",
+ "\u0120\u00e9\u0122\u013b\u00e5\u0122\u012d",
+ "\u0120Refer",
+ "\u0120Dancing",
+ "\u0120inconsistent",
+ "\u0120deh",
+ "\u0120immens",
+ "\u0120meist",
+ "\u0120impatient",
+ "\u0120behaves",
+ "\u00e6\u013f\u00be",
+ "\u0120\u00eb\u0124\u00b4\u00ec\u013c\u00a9",
+ "\u0120backstory",
+ "\u0120agreeing",
+ "\u0120\u00c5\u0123",
+ "ihin",
+ "\u0120temperatura",
+ "\u0120Background",
+ "\u0120nutzen",
+ "\u0120\u00eb\u0127\u00b9",
+ "\u0120M\u00c3\u00a4nner",
+ "\u0120collaborations",
+ "\u0120Kos",
+ "\u00e9\u0123\u0130\u00e5\u0130\u00bb",
+ "\u0120nightmares",
+ "\u00eb\u0135\u00b1",
+ "\u0120Queensland",
+ "\u0120associates",
+ "\u0120Kok",
+ "\u0120factorial",
+ "\u0120Hyung",
+ "\u0120\u00ea\u00b7\u00b8\u00eb\u012d\u00a4\u00ec\u013f\u012e",
+ "\u0120filho",
+ "\u0120el\u00c3\u00a9t",
+ "\u0120\u00ed\u0138\u012b\u00eb\u00b3\u00b5",
+ "\u00b0\u00b1",
+ "\u0120gefunden",
+ "\u0120semicondu",
+ "\u0120counselors",
+ "\u0120Upper",
+ "\u0120Aub",
+ "ickers",
+ "Ver",
+ "\u0120northwest",
+ "\u0120Maintenant",
+ "\u0120Lakes",
+ "\u00d0\u00b0\u00d1\u0131\u00d0\u00b2",
+ "int\u00c3\u00a9",
+ "\u00ec\u00b0\u00bd",
+ "\u0120\u00d0\u00b3\u00d0\u00b0\u00d0\u00b7",
+ "\u0120giorn",
+ "\u0120digitally",
+ "\u0120Circuit",
+ "\u00ec\u00bc\u0122",
+ "\u00e3\u0124\u012c\u00e3\u0123\u00be\u00e3\u0123\u0139\u00e3\u0123\u0141",
+ "\u0120cheerful",
+ "\u0120Peterson",
+ "\u0120Danish",
+ "ativos",
+ "\u0120liken",
+ "\u0120harbor",
+ "\u00d0\u00b0\u00d0\u00bb\u00d0\u00b8\u00d1\u0123\u00d1\u0124",
+ "xe",
+ "\u0120curls",
+ "\u0120Rhod",
+ "End",
+ "\u0120ET",
+ "\u0120acquaint",
+ "\u0120Kelvin",
+ "\u0120trif",
+ "\u0120Away",
+ "\u00ec\u0140\u0132\u00eb\u012c\u0136",
+ "vs",
+ "\u0120p\u00c3\u00a1gina",
+ "\u0120inlet",
+ "\u0120Santos",
+ "\u0120\u00ec\u013c\u00b0\u00ec\u013b\u0122",
+ "\u0120yap\u00c4\u00b1yorsun",
+ "theme",
+ "\u0120souff",
+ "\u0120injected",
+ "\u0120p\u00c3\u00b3\u00c5\u00baniej",
+ "iverso",
+ "amped",
+ "\u0120daher",
+ "\u0120dagger",
+ "\u0120\u00d0\u00bb\u00d1\u0130\u00d0\u00b1\u00d0\u00b8\u00d0\u00bc",
+ "\u0120tummy",
+ "\u0120enlightened",
+ "cents",
+ "\u0120Dah",
+ "\u0120cuest",
+ "\u00e4\u00be\u0128\u00e8\u00aa\u00aa",
+ "ILY",
+ "\u0120\u00d7\u0133\u00d7\u00a8",
+ "\u0120banging",
+ "\u0120Emil",
+ "\u0120Cler",
+ "\u0120Border",
+ "\u00d0\u00b8\u00d0\u00b6\u00d1\u0125",
+ "\u0120presenters",
+ "\u0120STUD",
+ "coins",
+ "\u0120\u00ed\u013b\u012f",
+ "\u0120perks",
+ "\u0120parap",
+ "\u0120certaines",
+ "\u0120Lore",
+ "\u00c3\u00b6st",
+ "\u0120MARTIN",
+ "\u0120bios",
+ "\u0120whereby",
+ "verts",
+ "\u0120Miranda",
+ "\u0120stip",
+ "\u00e6\u00be\u00a4",
+ "andez",
+ "\u00d7\u013d\u00d7\u013e",
+ "ujin",
+ "\u0120\u00ea\u00be",
+ "\u0120allergies",
+ "plate",
+ "\u0120yap\u00c4\u00b1l",
+ "\u0120undertake",
+ "\u0120\u00eb\u0124\u013a\u00ea\u00b0\u0122",
+ "Part",
+ "\u0120k\u00c4\u00b1z\u00c4\u00b1m",
+ "hguru",
+ "\u00e3\u0123\u0124\u00e3\u0123\u00a8",
+ "\u0120Johns",
+ "\u0120eyelashes",
+ "\u0120drained",
+ "\u0120st\u00c3\u00a5r",
+ "\u00e3\u0123\u0124\u00e3\u0124\u012c\u00e3\u0123\u00be\u00e3\u0123\u013b",
+ "\u0120Jade",
+ "\u0120calend",
+ "film",
+ "\u0120mesa",
+ "\u0120ludzie",
+ "\u0120attracts",
+ "\u0120juices",
+ "\u0120\u00d0\u00ba\u00d0\u00b8\u00d0\u00bb",
+ "\u0120nieuwe",
+ "\u0120mencion",
+ "\u0120ignition",
+ "\u0120bladder",
+ "andaag",
+ "\u0120Extension",
+ "\u00ed\u0124\u00a8",
+ "feed",
+ "\u0120\u00d9\u012a\u00d9\u0129",
+ "\u0120spun",
+ "\u0120t\u00c3\u00a4t",
+ "\u00d0\u00be\u00d1\u0122\u00d0\u00be\u00d1\u0124",
+ "tyard",
+ "ronics",
+ "\u0120Huge",
+ "\u00d1\u0125\u00d0\u00b6\u00d0\u00b4",
+ "string",
+ "\u0120unjust",
+ "\u0120prawn",
+ "\u0120frosting",
+ "\u0120disappearance",
+ "iosa",
+ "\u0120cardi",
+ "\u0120Priest",
+ "\u0120cient\u00c3\u0143fic",
+ "\u00e5\u0135\u00aa\u00e8\u00a3\u00a1",
+ "\u0120\u00d0\u0134\u00d0\u00b0\u00d1\u0123",
+ "\u0120\u00eb\u00b6\u0122\u00ed\u0125\u0123",
+ "\u0120thieves",
+ "\u0120physique",
+ "\u0120Eugene",
+ "\u0120\u00d0\u00b1\u00d0\u00bb\u00d0\u00b8\u00d0\u00b7",
+ "\u0120monopoly",
+ "\u0120biography",
+ "\u0120ho\u00c5\u0141",
+ "\u0120t\u00c3\u00b6",
+ "mac",
+ "\u0120shocks",
+ "\u00ec\u0126\u00b8\u00eb",
+ "hit",
+ "\u0120snug",
+ "\u0120incl",
+ "\u0120dedic",
+ "\u0120ultras",
+ "\u0120\u00d0\u00b8\u00d0\u00b7\u00d0\u00b2\u00d0\u00b5\u00d1\u0123\u00d1\u0124",
+ "\u0120utilization",
+ "\u0120\u00d1\u0123\u00d0\u00be\u00d0\u00b2\u00d0\u00b5\u00d1\u0122\u00d1\u012a\u00d0\u00b5\u00d0\u00bd\u00d0\u00bd\u00d0\u00be",
+ "\u0120servi",
+ "stag",
+ "180",
+ "\u0120sewer",
+ "\u0120Choice",
+ "\u0120discharged",
+ "\u0120JD",
+ "\u00d0\u00be\u00d0\u00bb\u00d0\u00b5\u00d1\u0124",
+ "\u0120\u00d0\u00ba\u00d0\u00b2\u00d0\u00b0\u00d1\u0122\u00d1\u0124\u00d0\u00b8",
+ "\u0120telescop",
+ "\u0120Je\u00c5\u013dli",
+ "\u0120Nana",
+ "cale",
+ "\u0120\u00d1\u0124\u00d0\u00be\u00d0\u00bd",
+ "mmm",
+ "\u00e4\u00ba\u0128\u00e5\u0132\u00a7",
+ "\u0120gehabt",
+ "\u00eb\u0124\u0142",
+ "\u00e6\u012c\u0137",
+ "\u00e0\u00b8\u013b\u00e0\u00b8\u013b",
+ "\u0120ether",
+ "\u0120zen",
+ "\u0120researched",
+ "\u0120Czyli",
+ "\u00e5\u00ae\u012e\u00e5\u0127\u00a8",
+ "workers",
+ "\u0120\u00ea\u00b2\u00bd\u00ec\u00b0\u00b0",
+ "\u0120sheriff",
+ "allo",
+ "\u0120tipos",
+ "\u0120prosecution",
+ "\u0120frogs",
+ "\u0120falt",
+ "jd",
+ "\u0120\u00ed\u012e\u0136",
+ "\u0120filtered",
+ "\u0120Oft",
+ "\u0120\u00ec\u012f",
+ "\u0120disfr",
+ "\u0120Mustang",
+ "\u0120woah",
+ "\u0120REALLY",
+ "\u0120\u00d0\u00bc\u00d0\u00be\u00d0\u00b3\u00d0\u00bb\u00d0\u00b8",
+ "\u0120entrada",
+ "\u0120\u00d0\u00b8\u00d0\u00b3\u00d1\u0122\u00d0\u00b0",
+ "\u0120mixes",
+ "\u0120\u00d0\u00b0\u00d0\u00b2\u00d1\u0124\u00d0\u00be\u00d0\u00bc\u00d0\u00be\u00d0\u00b1",
+ "\u00d0\u013b",
+ "\u0120shin",
+ "\u0120paranormal",
+ "\u0120someplace",
+ "\u0120dishon",
+ "etaan",
+ "\u0120fuerte",
+ "\u00d9\u00b9",
+ "\u0120doom",
+ "\u00ec\u012a\u013e",
+ "\u0120existential",
+ "\u0120buld",
+ "\u0120SDK",
+ "\u0120\u00d0\u00bf\u00d1\u0122\u00d0\u00b0\u00d0\u00b2\u00d0\u00b4\u00d0\u00b0",
+ "\u0120turnover",
+ "\u0120\u00ec\u0139\u00ac\u00ea\u00b8\u00b0\u00ec\u0139\u0132",
+ "\u0120\u00e0\u00a4\u00b9",
+ "\u0120modeled",
+ "\u0120bug\u00c3\u00bcn",
+ "\u0120experimentation",
+ "\u0120mornings",
+ "\u0120medo",
+ "Stevie",
+ "\u0120playable",
+ "\u0120airlines",
+ "gments",
+ "\u0120\u00ea\u00b8\u00b0\u00eb\u00b6\u0126",
+ "\u0120Tomb",
+ "\u0120MVP",
+ "AUDIENCE",
+ "\u0120checkout",
+ "\u0120passt",
+ "\u0120beispiel",
+ "\u0120Links",
+ "heavy",
+ "\u0120questionable",
+ "\u0120\u00ec\u0135\u00b0\u00eb",
+ "\u0120sill",
+ "\u0120manipulated",
+ "\u0120Loren",
+ "\u0120\u00ec\u013e\u00bc",
+ "\u0120verge",
+ "\u00c3\u00a1k",
+ "IES",
+ "\u0120sabot",
+ "\u0120Customer",
+ "ale\u00c5\u00bcy",
+ "\u0120nominee",
+ "\u0120Gad",
+ "\u0120nouvelles",
+ "\u0120SPE",
+ "istling",
+ "\u0120oval",
+ "\u00d0\u00be\u00d0\u00b1\u00d1\u0122\u00d0\u00b0\u00d0\u00b6",
+ "ifty",
+ "\u00e9\u0129\u0130",
+ "\u0120bezel",
+ "yet",
+ "\u0120freight",
+ "\u0120Han\u00c4\u00b1m",
+ "r\u00c3\u0143a",
+ "\u0120zoning",
+ "\u0120indem",
+ "\u0120B\u00c3\u00bc",
+ "\u0120feminism",
+ "\u0120voix",
+ "\u0120oficial",
+ "\u0120diyorum",
+ "\u00bb\u0132",
+ "\u0120arose",
+ "\u0120parar",
+ "\u00ec\u013f\u00b8\u00ec\u00a7\u0122",
+ "\u0120Martine",
+ "\u0120Lect",
+ "\u0120rester",
+ "\u0120drowning",
+ "uya",
+ "cida",
+ "\u0120Ariel",
+ "\u012002",
+ "\u0120\u00d7\u0136\u00d7\u0136",
+ "\u00e7\u00b4\u0142",
+ "\u0120Wert",
+ "\u00d0\u00a2\u00d1\u012d",
+ "\u0120widow",
+ "\u0120parchment",
+ "\u0120cottage",
+ "\u0120XL",
+ "\u0120Slack",
+ "\u0120NES",
+ "\u0120robe",
+ "\u0120gimm",
+ "\u0120caminho",
+ "\u0120Harper",
+ "\u0120citrus",
+ "\u0120firefighters",
+ "\u0120dopamine",
+ "elets",
+ "\u0120democrat",
+ "\u00ec\u0142\u013e\u00eb\u00a1\u013e",
+ "\u0120playback",
+ "oj",
+ "\u0120\u00d0\u00bf\u00d1\u0122\u00d0\u00be\u00d0\u00ba",
+ "\u0120Sullivan",
+ "semble",
+ "\u0120Worth",
+ "\u0120Mustafa",
+ "\u00e0\u00b8\u00b2\u00e0\u00b8\u00a3",
+ "\u0120mets",
+ "\u00e9\u0138\u0122",
+ "\u00d0\u00bb\u00d0\u00be\u00d1\u0123\u00d1\u012e",
+ "\u0120inertia",
+ "\u0120uniforms",
+ "\u00e8\u00b6\u00b3",
+ "\u00c3\u00a9rio",
+ "\u00d7\u0137\u00d7\u00a8\u00d7\u0136",
+ "\u00c3\u00a9nt",
+ "\u0120\u00e0\u00ae\u0134",
+ "\u0120\u00d1\u0123\u00d0\u00b0\u00d0\u00bc\u00d1\u012d\u00d1\u0127",
+ "\u0120voulais",
+ "\u0120Zimmer",
+ "\u00ea\u00b2\u0142\u00eb",
+ "\u0120\u00d0\u00bd\u00d0\u00be\u00d1\u0123",
+ "encias",
+ "\u0120relaci\u00c3\u00b3n",
+ "\u0120\u00ea\u00b1\u00b8\u00eb",
+ "\u0120faction",
+ "\u0120gosp",
+ "\u00d0\u00bf\u00d0\u00be\u00d0\u00bb\u00d0\u00be\u00d0\u00b6",
+ "nap",
+ "hak",
+ "\u0120proceedings",
+ "\u0120\u00ec\u0128\u0136",
+ "\u00ec\u0137\u0126\u00eb\u012d\u012a",
+ "\u0120\u00ec\u0140\u0132\u00ea\u00b8\u00b0",
+ "\u0120werd",
+ "\u0120sof",
+ "\u0120schlim",
+ "\u0120flavored",
+ "\u0120quadratic",
+ "\u0120Boot",
+ "\u0120publicity",
+ "\u0120Caro",
+ "\u0120?\"",
+ "\u00d0\u00bd\u00d0\u00b8\u00d1\u0128\u00d0\u00b0",
+ "mania",
+ "\u0120SUR",
+ "\u0120BUR",
+ "lance",
+ "\u00c3\u00a9tica",
+ "\u0120zobaczy",
+ "\u0120trio",
+ "sama",
+ "\u0120ta\u00c5\u0141",
+ "\u0120asymm",
+ "resser",
+ "\u0120\u00d8\u00aa\u00d8\u00b9",
+ "\u0120\u00d0\u00bf\u00d0\u00b5\u00d1\u0123",
+ "\u0120beginnings",
+ "lad\u00c4\u00b1m",
+ "\u0120\u00d0\u00b1\u00d1\u012d\u00d1\u0123\u00d1\u0124\u00d1\u0122",
+ "\u0120moo",
+ "\u0120Geneva",
+ "\u0120\u00e5\u013e\u00a8",
+ "erus",
+ "borah",
+ "\u0120refusing",
+ "bull",
+ "\u0120Waiting",
+ "\u0120Individual",
+ "\u0120anonym",
+ "imens",
+ "\u0120medidas",
+ "\u0120fragrant",
+ "\u0120directement",
+ "\u0120\u00ec\u0137\u0126\u00eb\u00a7\u012a",
+ "uria",
+ "\u0120spherical",
+ "\u0120abge",
+ "\u0120Victorian",
+ "\u0120spectacle",
+ "\u0120Rodriguez",
+ "\u0120ocup",
+ "\u0120N\u00c3\u00a4r",
+ "marks",
+ "ngulo",
+ "\u0120Luci",
+ "\u0120shouted",
+ "\u0120regulators",
+ "\u00c4\u0141ini",
+ "\u0120disent",
+ "\u0120\u00d1\u0122\u00d1\u012d\u00d0\u00bd",
+ "\u00eb\u0124\u00a8",
+ "\u0120\u00ec\u0124\u00b4\u00eb",
+ "\u0120probl\u00c3\u00a8mes",
+ "\u0120Finger",
+ "assemble",
+ "\u0120pear",
+ "\u0120droite",
+ "\u0120Everywhere",
+ "tam",
+ "\u00d0\u00be\u00d1\u0124\u00d0\u00b8\u00d0\u00b2",
+ "\u00d0\u00b2\u00d0\u00be\u00d0\u00b9",
+ "ordinate",
+ "\u0120Lak",
+ "\u0120m\u00e1\u00bb\u013di",
+ "\u0120Television",
+ "\u0120exponentially",
+ "avas",
+ "\u0120blev",
+ "\u0120MT",
+ "\u00e4\u00bf\u00ba",
+ "Connell",
+ "\u0120\u00ea\u00b5\u0143\u00eb\u00af\u00bc",
+ "\u0120\u00d1\u0123\u00d0\u00b2\u00d0\u00be\u00d0\u00b8\u00d0\u00bc",
+ "\u0120acha",
+ "\u0120Dynasty",
+ "Jin",
+ "\u0120tore",
+ "\u0120flor",
+ "\u0120\u00d0\u00bc\u00d0\u00bd\u00d0\u00be\u00d0\u00b3\u00d0\u00b8\u00d0\u00b5",
+ "\u00e6\u00b2\u0134\u00e4\u00ba\u012d",
+ "owan",
+ "bah",
+ "\u0120\u00ec\u00a3\u0126",
+ "\u0120Cela",
+ "\u0120\u00ec\u00b5\u013e\u00ea\u00b7\u00bc",
+ "\u0120permettre",
+ "\u0120abras",
+ "\u0120verstehen",
+ "\u0120escort",
+ "\u0120Them",
+ "\u00c3\u00a4rke",
+ "porter",
+ "\u0120kahkaha",
+ "\u0120hect",
+ "\u0120dau",
+ "wah",
+ "olve",
+ "\u0120Ages",
+ "schaft",
+ "\u0120Stell",
+ "nelle",
+ "\u0120Ensuite",
+ "\u0120\u00d0\u0134\u00d1\u0123\u00d0\u00b5\u00d0\u00bc",
+ "\u0120cr\u00c3\u00a9d",
+ "\u0120PP",
+ "lords",
+ "grunting",
+ "\u0120contraction",
+ "Got",
+ "\u0120acquiring",
+ "\u0120sopr",
+ "\u0120poisonous",
+ "RNA",
+ "\u0120anar",
+ "\u0120Hof",
+ "')",
+ "\u0120remarkably",
+ "\u0120internacional",
+ "\u00c3\u00bccke",
+ "inqu",
+ "\u0120duy",
+ "\u0120beasts",
+ "\u0120LAN",
+ "\u0120precedent",
+ "\u0120RPM",
+ "\u00e5\u0133\u00a8",
+ "\u0120selon",
+ "\u0120morte",
+ "\u0120come\u00c3\u00a7ou",
+ "\u00d1\u0131\u00d0\u00bb\u00d0\u00b0",
+ "\u0120interpreting",
+ "\u0120Burke",
+ "\u00d1\u0124\u00d1\u0122\u00d0\u00b0",
+ "\u0120\u00ec\u013f\u00b4\u00eb\u0141\u00ac",
+ "\u0120pessim",
+ "\u0120Nok",
+ "\u00ed\u012e\u013f",
+ "Female",
+ "\u0120\u00ec\u012d\u00a4\u00ed",
+ "\u013b\u0122",
+ "\u0120stimulation",
+ "\u0120slick",
+ "\u0120\u00ea\u00b0\u0122\u00eb\u012c\u0136",
+ "\u0120\u00d0\u00ba\u00d0\u00b0\u00d0\u00b7",
+ "\u0120HBO",
+ "\u0120papier",
+ "\u0120k\u00c3\u00b6nnten",
+ "\u00d1\u0125\u00d0\u00b1\u00d0\u00bb\u00d0\u00b8",
+ "\u0120Constant",
+ "SPEAKING",
+ "\u0120kt\u00c3\u00b3r\u00c4\u0127",
+ "\u0120cosmetics",
+ "\u0120Trend",
+ "\u0120robbery",
+ "\u0120titt",
+ "\u0120gjort",
+ "\u0120dietary",
+ "\u0142\u012e",
+ "\u0120Kirby",
+ "\u0120\u00d0\u00bf\u00d1\u0122\u00d0\u00b8\u00d0\u00bc\u00d0\u00b5\u00d1\u0122\u00d0\u00bd\u00d0\u00be",
+ "\u0120qualification",
+ "\u0120\u00ec\u0137\u012b",
+ "\u0120cabinets",
+ "\u0120http",
+ "\u0120Erica",
+ "\u00e7\u00be\u00a9",
+ "\u0120disadvantages",
+ "\u0120chattering",
+ "yz",
+ "feit",
+ "\u0120guild",
+ "\u0120ETF",
+ "\u0120Dragons",
+ "\u0120HERE",
+ "venth",
+ "\u00d9\u0126\u00d8\u00a7\u00d9\u0127",
+ "\u0120march\u00c3\u00a9",
+ "Dam",
+ "\u0120photon",
+ "\u0120estable",
+ "Mag",
+ "\u0120olhar",
+ "\u0120coupling",
+ "\u0120Hilfe",
+ "\u0120Wizard",
+ "\u0120\u00d0\u00bc\u00d0\u00b0\u00d0\u00bb\u00d0\u00be",
+ "help",
+ "\u0120l\u00c3\u0143nea",
+ "\u0120\u00ec\u00ab",
+ "\u0120standalone",
+ "\u0120morale",
+ "\u0120zweite",
+ "\u00e3\u0124\u012a\u00e3\u0124\u012f\u00e3\u0123\u0139\u00e3\u0123\u0131",
+ "\u00c3\u00a4hrt",
+ "\u0120dotted",
+ "\u0120dripping",
+ "\u0120Flag",
+ "\u00e9\u013f\u0134",
+ "rocket",
+ "rategy",
+ "irim",
+ "\u0120\u00ed\u0137\u013a\u00eb\u00a9\u00b4\u00ec\u0126\u013e",
+ "\u0120sogenan",
+ "\u0120Uno",
+ "\u0120Schutz",
+ "\u0120estilo",
+ "\u0120Subs",
+ "\u0120Daisy",
+ "\u00d0\u013f\u00d0\u00b5\u00d1\u0124",
+ "'...",
+ "\u0120platinum",
+ "\u0120birl",
+ "\u0120Sovi",
+ "\u0120violate",
+ "\u00d1\u0125\u00d0\u00b5\u00d1\u0124\u00d1\u0123\u00d1\u0131",
+ "rill",
+ "\u0120traz",
+ "\u0120snip",
+ "\u0120cumpl",
+ "\u00e0\u00b8\u0143\u00e0\u00b8\u0123",
+ "\u0120cuk",
+ "\u00e9\u0127\u0134",
+ "\u0120Parlament",
+ "\u0120hypert",
+ "\u0120pulp",
+ "\u0120tongues",
+ "atto",
+ "\u0120busca",
+ "ihn",
+ "ERO",
+ "\u0120\u00d9\u012c\u00d8\u00b9",
+ "\u0120varias",
+ "\u0120Marian",
+ "\u0120bounded",
+ "\u0120pitching",
+ "\u0120deficiency",
+ "\u0120Blessed",
+ "\u0120Exerc",
+ "uchs",
+ "\u0120nh\u00c6\u00b0ng",
+ "\u00e6\u013e\u00ac\u00e5\u00bd\u0135",
+ "\u0120raped",
+ "hales",
+ "\u0120mala",
+ "pic",
+ "\u0120401",
+ "\u00c5\u013dniej",
+ "arina",
+ "\u00eb\u0135\u00a4\u00ec\u013f\u0126",
+ "otti",
+ "\u0120\u00d0\u00b4\u00d0\u00be\u00d0\u00bb\u00d0\u00b3\u00d0\u00be",
+ "\u0120tracker",
+ "\u0120Shelby",
+ "\u0120vanished",
+ "\u0120bakery",
+ "Kap\u00c4\u00b1",
+ "Jesus",
+ "\u0120KR",
+ "JO",
+ "\u0127\u00b8",
+ "\u0120discs",
+ "\u00ec\u0126\u00af",
+ "\u00ec\u00a7\u0122\u00eb",
+ "\u00d7\u013b\u00d7\u00a6",
+ "emary",
+ "Kendra",
+ "\u0120y\u00c3\u00bck",
+ "\u00c3\u00bcckt",
+ "\u0120vaz",
+ "\u0120kup",
+ "aktu",
+ "\u0120\u00d1\u0123\u00d0\u00bf\u00d0\u00b0\u00d1\u0123\u00d0\u00b8\u00d0\u00b1\u00d0\u00be",
+ "\u0120aik",
+ "\u0120nursery",
+ "\u0120endangered",
+ "\u00c3\u00aamement",
+ "ematics",
+ "\u0120responders",
+ "\u0120Representatives",
+ "\u0120sculptures",
+ "igkeiten",
+ "\u0120depl",
+ "\u0120interpretations",
+ "\u0120deadlines",
+ "\u01201942",
+ "\u00c3\u0139",
+ "\u0120sugars",
+ "emu",
+ "lively",
+ "\u0120recreational",
+ "\u0120distort",
+ "\u0120underscore",
+ "\u0120unquote",
+ "\u0120safest",
+ "\u0120swollen",
+ "\u0120analyses",
+ "\u0120commenc\u00c3\u00a9",
+ "\u00e5\u00a6\u00b9",
+ "andin",
+ "\u0120\u00d0\u00a5\u00d0\u00be\u00d1\u0122\u00d0\u00be\u00d1\u012a\u00d0\u00be",
+ "\u0120diarr",
+ "\u00e3\u0123\u00be\u00e3\u0123\u0123",
+ "ziest",
+ "\u0120toothbrush",
+ "\u00e9\u0142\u00bb\u00e9\u0123\u0135",
+ "uations",
+ "\u0120cade",
+ "\u0120backlash",
+ "hind",
+ "\u0120risque",
+ "zess",
+ "\u0120\u00ec\u013f\u00b4\u00ec\u0137\u00bc\u00ea\u00b8\u00b0",
+ "\u0120esperar",
+ "\u0120translations",
+ "ioned",
+ "groans",
+ "\u0120\u00d0\u00bf\u00d1\u0125\u00d1\u0124",
+ "\u0120genetically",
+ "\u00e9\u0122\u0142",
+ "\u0120happiest",
+ "\u0120werk",
+ "atoon",
+ "\u0120musi",
+ "\u0120fun\u00c3\u00a7\u00c3\u00a3o",
+ "\u0120\u00ec\u0140\u0127\u00eb\u012d\u012a\u00eb\u012d\u00a4",
+ "\u0120\u00d1\u0122\u00d0\u00b0\u00d0\u00b9",
+ "\u0120bevor",
+ "BLANK",
+ "\u0120repentance",
+ "Put",
+ "\u0120potrzeb",
+ "\u0120sala",
+ "\u0120campa",
+ "WER",
+ "\u0120dec\u00c3\u0143a",
+ "\u0120s\u00c3\u00a9curit\u00c3\u00a9",
+ "\u0120Appreciate",
+ "\u00d1\u0129\u00d0\u00b8",
+ "\u0120Random",
+ "\u00eb\u00b3\u0126",
+ "kah",
+ "\u0120m\u00c3\u00b6j",
+ "\u0120s\u00c3\u00a4ger",
+ "\u0120\u00d7\u013b\u00d7\u013d\u00d7\u0137\u00d7\u013e",
+ "\u0120190",
+ "xtures",
+ "Eu",
+ "\u0120g\u00c3\u00a4",
+ "\u0120\u00d7\u0133\u00d7\u00aa",
+ "\u0120Croat",
+ "apo",
+ "PLE",
+ "\u0120persistence",
+ "\u00e5\u012c\u00a9",
+ "\u0120blends",
+ "\u0120treffen",
+ "\u0120Santiago",
+ "ydia",
+ "aldo",
+ "\u0120TensorFlow",
+ "\u0120Dual",
+ "\u00e3\u0125\u013e",
+ "\u0120chiff",
+ "\u00ec\u0139\u00b4",
+ "\u0120contracted",
+ "\u0120segreg",
+ "\u0120Fairy",
+ "\u0120wisely",
+ "\u0120vulnerabilities",
+ "\u0120handheld",
+ "\u0120gadgets",
+ "\u0120bo\u00c5\u0141",
+ "\u0120Popular",
+ "\u0120curvature",
+ "\u00eb\u00ac\u00b8",
+ "\u0120MARY",
+ "\u00ec\u013f\u00b4\u00ec\u012c",
+ "\u0120formulation",
+ "\u0120celery",
+ "\u0120blurry",
+ "\u0120TS",
+ "alez",
+ "\u0120ws",
+ "\u0120programm",
+ "\u0120Stack",
+ "\u0120JIM",
+ "\u00d0\u00be\u00d0\u00b2\u00d0\u00b0\u00d0\u00bb\u00d0\u00b8",
+ "\u00c4\u00b1ll",
+ "\u0120p\u00c3\u00a8re",
+ "\u0120Kanye",
+ "\u0120Delaware",
+ "\u0120\u00e3\u0123\u0142",
+ "\u0120daunting",
+ "\u0120\u00d0\u00b1\u00d0\u00b5\u00d1\u0123",
+ "\u0120Stupid",
+ "big",
+ "fficial",
+ "\u0120precipitation",
+ "\u0120plung",
+ "\u00e1\u00bb\u00a5c",
+ "burse",
+ "\u0120darle",
+ "\u0120cripp",
+ "\u0120pioneer",
+ "\u0120disput",
+ "\u0120sean",
+ "\u00e3\u0123\u0135\u00e3\u0124\u0135\u00e3\u0123\u00aa",
+ "\u0120resistor",
+ "\u0120allein",
+ "ipples",
+ "arel",
+ "\u0120endors",
+ "zust",
+ "\u0120\u00d1\u0122\u00d0\u00b5\u00d0\u00b1\u00d1\u0131\u00d1\u0124\u00d0\u00b0",
+ "eded",
+ "\u0120\u00ec\u00b9\u00b4\u00eb\u00a9\u0136\u00eb",
+ "\u0120lleva",
+ "\u0120kennt",
+ "\u0120\u00d0\u00b1\u00d0\u00b0\u00d0\u00bb",
+ "\u0120Document",
+ "\u0120Knights",
+ "\u0120buckle",
+ "\u0120\u00ec\u012b\u00ac",
+ "\u0120alk",
+ "\u0120Everyday",
+ "atters",
+ "\u0120toilets",
+ "\u0120jugar",
+ "\u0120\u00ec\u0140\u012a\u00ec\u00a7\u0122",
+ "\u0120genauso",
+ "\u0120Landesregierung",
+ "\u00e3\u0123\u00a3\u00e3\u0123\u00b1",
+ "ije",
+ "\u0120trailers",
+ "\u0120Tigers",
+ "\u0120gitti",
+ "\u0120forgiving",
+ "\u0120concurrent",
+ "\u0120Vu",
+ "\u0120\u00ed\u012c\u00b9\u00ed\u0140\u012a",
+ "\u0120BROWN",
+ "ounded",
+ "\";",
+ "\u0120tremb",
+ "\u0120tiet",
+ "\u0120\u00d1\u0122\u00d0\u00b5\u00d0\u00b6\u00d0\u00b8\u00d0\u00bc",
+ "\u0120nutshell",
+ "\u00d0\u00b5\u00d0\u00bb\u00d0\u00b8\u00d1\u0129",
+ "\u0120losers",
+ "ricting",
+ "\u0120redeem",
+ "defined",
+ "Nice",
+ "\u0120broadband",
+ "KO",
+ "\u0120teasing",
+ "\u0120partisan",
+ "\u00c4\u00b1ma",
+ "\u0120\u00ec\u0140\u00ac\u00eb\u00af\u00b8",
+ "\u0120Journey",
+ "\u0120slopes",
+ "uning",
+ "grunts",
+ "\u0120t\u00c3\u00a4ll",
+ "\u0120uncovered",
+ "\u0120my\u00c5\u013dl\u00c4\u013b",
+ "\u0120Esther",
+ "\u00e4\u00ba\u0130",
+ "\u0120Healthy",
+ "\u0120\u00eb\u00b0\u0133",
+ "r\u00c3\u00a9e",
+ "\u0120polarization",
+ "\u0120flav",
+ "\u0120cambiar",
+ "\u0120yr",
+ "\u0120Ranch",
+ "\u0120splits",
+ "\u0120trouv\u00c3\u00a9",
+ "\u00e5\u013e\u012d\u00e5\u00ae\u00b6",
+ "\u0120recorder",
+ "\u0120d\u00c3\u00a9part",
+ "\u00d9\u012a\u00d8\u00a8",
+ "\u0120Kry",
+ "\u0120interessant",
+ "\u0120ederim",
+ "\u00c5\u013dwiad",
+ "ilateral",
+ "wright",
+ "\u0120pourra",
+ "\u00c3\u00aater",
+ "\u0120camel",
+ "\u00e1\u0140",
+ "\u0120rapidement",
+ "\u0120mej",
+ "\u0120stiffness",
+ "ADAS",
+ "\u0120differs",
+ "\u0120alot",
+ "\u0120Sig",
+ "\u00d1\u0131\u00d1\u0124\u00d0\u00b5\u00d0\u00bb\u00d1\u012e",
+ "\u0120abstraction",
+ "\u00e5\u013e\u013a",
+ "\u0120keiner",
+ "grupp",
+ "\u0120Sherlock",
+ "\u00ed\u013a\u0136",
+ "\u0120cite",
+ "\u0120overflow",
+ "\u0120t\u00e1\u00ba\u00a1i",
+ "\u00c3\u00bacar",
+ "bula",
+ "\u0120conjunto",
+ "\u0120CI",
+ "\u0120moderator",
+ "\u0120indirectly",
+ "\u0120alleine",
+ "\u00e2\u0124",
+ "\u00d1\u012a\u00d0\u00b8\u00d0\u00b1",
+ "\u0120\u00d0\u00b1\u00d0\u00b0\u00d0\u00b1",
+ "\u0120danach",
+ "\u01201939",
+ "\u0120promet",
+ "\u0120destinations",
+ "\u0120Illust",
+ "\u00ce\u00b9\u00ce\u00ba\u00cf\u012e",
+ "\u0120sabes",
+ "\u0120heh",
+ "\u0120Gesetzent",
+ "\u0120Miz",
+ "\u00d0\u00b5\u00d0\u00bd\u00d0\u00ba\u00d0\u00be",
+ "\u0120Mys",
+ "\u00d0\u00ac",
+ "\u0120Judaism",
+ "\u0120mustache",
+ "\u0120stimmt",
+ "\u0120Gaza",
+ "\u0120volte",
+ "\u0120nuo",
+ "\u0120m\u00c3\u00b3n",
+ "\u0120Comput",
+ "\u00e0\u00b8\u00b9\u00e0\u00b9\u012a",
+ "\u0120Radi",
+ "\u0120exceptionally",
+ "\u0120assumes",
+ "\u00e9\u0138\u012d\u00e5\u00bf\u0125",
+ "\u00e3\u0123\u012a\u00e3\u0123\u00b0",
+ "inform",
+ "\u0120shrine",
+ "\u00e6\u0135\u012c",
+ "\u0120implication",
+ "\u0120Fitz",
+ "\u00e6\u00b2\u0134\u00e9\u0139\u013e\u00e4\u00bf\u0124",
+ "!.",
+ "\u0120lt",
+ "\u0120alloy",
+ "\u0120ethic",
+ "\u0120monastery",
+ "\u00ec\u012d\u013e\u00ec\u00a3\u0142",
+ "ica\u00c3\u00a7\u00c3\u00a3o",
+ "\u0120coordinating",
+ "\u0120Moto",
+ "\u0120overlook",
+ "\u0120chois",
+ "\u0120antibiotic",
+ "\u0120Minne",
+ "\u0120BJ",
+ "\u0120Apa",
+ "orian",
+ "\u0120spilled",
+ "Jam",
+ "\u0120husbands",
+ "\u0120creations",
+ "\u0120a\u00c3\u00b1",
+ "\u00c3\u00bcssel",
+ "\u0120\u00ec\u013f\u00b4\u00ec\u013c\u00a9",
+ "\u0120analyse",
+ "rose",
+ "\u0120punched",
+ "\u0120presque",
+ "\u0120astronomy",
+ "\u0120schwierig",
+ "\u0120Ebola",
+ "\u0120cis",
+ "\u0120acet",
+ "\u0120FX",
+ "endre",
+ "\u0120\u00ec\u013f\u012e\u00ec\u0137\u0127",
+ "\u0120webpage",
+ "\u0120freaked",
+ "\u0120latte",
+ "\u0120\u00ec\u00bf\u0142",
+ "\u0120\u00eb\u00a8\u00b8\u00eb",
+ "Never",
+ "Gra",
+ "\u00ed\u013b\u0136\u00eb\u00a5\u00bc",
+ "eyed",
+ "\u0120\u00eb\u00b0\u013e\u00eb\u013f\u00bc",
+ "\u0120espera",
+ "\u0120aparece",
+ "ra\u00c3\u00a7\u00c3\u00a3o",
+ "\u0120disruptive",
+ "\u0120Joint",
+ "urous",
+ "reas",
+ "\u0120quer\u00c3\u0143a",
+ "\u0120distributions",
+ "\u0120exponent",
+ "\u00ec\u00b9\u013a\u00eb\u00a5\u00bc",
+ "\u0120dl",
+ "zhou",
+ "\u0120Hearing",
+ "\u00e5\u00b7\u00ae\u00e4\u00b8\u012f\u00e5\u00a4\u013c",
+ "\u0120Craw",
+ "\u0120floats",
+ "ounced",
+ "Lab",
+ "World",
+ "\u0120burdens",
+ "\u0120authoritarian",
+ "\u0120Bolt",
+ "\u0120\u00d0\u00be\u00d0\u00b4\u00d0\u00bd\u00d1\u0125",
+ "\u0120pigeon",
+ "\u0120distractions",
+ "\u0120Herausforder",
+ "\u0120zest",
+ "esc",
+ "\u0120shakes",
+ "atas",
+ "\u0120\u00d9\u0127\u00d8\u00b4",
+ "holes",
+ "\u0120thinkers",
+ "alta",
+ "\u0120arche",
+ "\u0120Suk",
+ "anha",
+ "\u0120tempting",
+ "\u0120youtuber",
+ "\u0120v\u00c3\u00ac",
+ "\u0120dzia\u00c5\u0124a",
+ "\u0120Vatican",
+ "Park",
+ "\u0120supers",
+ "\u0120Nikki",
+ "\u00eb\u012c\u0132\u00eb",
+ "orang",
+ "ramient",
+ "\u00e9\u00ac\u00bc",
+ "\u0120\u00ea\u00b0\u0138\u00ea\u00b3\u0142",
+ "\u0120desserts",
+ "\u0120avere",
+ "\u0120Gregory",
+ "\u0120\u00eb\u0135\u00a4\u00ec\u0138\u00b4\u00ec\u013a",
+ "\u0120costing",
+ "\u0120Clinic",
+ "\u0120rebels",
+ "\u0120Mob",
+ "\u0120bunlar",
+ "\u0120Yours",
+ "ertime",
+ "\u0120retali",
+ "mara",
+ "atus",
+ "alles",
+ "\u0120\u00d0\u00b4\u00d1\u0122",
+ "\u0120\u00d0\u00b4\u00d0\u00b8\u00d1\u0123",
+ "\u0120discounts",
+ "\u0120GUY",
+ "\u0120\u00d0\u00ba\u00d0\u00b0\u00d0\u00ba\u00d0\u00be\u00d0\u00b5",
+ "\u0120Experiment",
+ "rement",
+ "\u0120Xiang",
+ "\u0120bate",
+ "WE",
+ "\u0120specialize",
+ "\u0120deity",
+ "\u0120Loki",
+ "mag",
+ "\u0120Nit",
+ "West",
+ "\u0120maternal",
+ "\u0120quis",
+ "\u00e5\u0141\u00ba\u00e6\u013e\u00ac",
+ "broken",
+ "\u0120lasers",
+ "\u0120hakk",
+ "\u0120Angels",
+ "\u0120mastery",
+ "antis",
+ "Tiffany",
+ "eee",
+ "\u00e7\u0133",
+ "orem",
+ "\u0120inacc",
+ "\u0120jurisdictions",
+ "\u0120Kardash",
+ "\u00e6\u013e\u00ba",
+ "Il",
+ "\u0120Sinn",
+ "\u00e5\u012d\u0137\u00e7\u0136\u00bb",
+ "\u0120athletics",
+ "c\u00c4\u013b",
+ "\u0120loosely",
+ "\u0120dieta",
+ "Ag",
+ "\u0120??",
+ "\u0120\u00eb\u012e\u0122\u00ed\u0133\u013e",
+ "\u0120superv",
+ "\u0120nutrit",
+ "\u0120drifting",
+ "\u0120\u00ec\u0126\u0142\u00ec\u0125\u013f\u00eb\u012d\u013a",
+ "\u0120\u00d0\u00bf\u00d0\u00be\u00d0\u00bd\u00d1\u0131\u00d0\u00bb",
+ "\u0120Victory",
+ "\u00d9\u0126\u00d8\u00a9",
+ "\u00d7\u0137\u00d7\u0142\u00d7\u0136",
+ "\u0120\u00d0\u00bf\u00d0\u00b8\u00d1\u012a",
+ "\u0120shaved",
+ "\u0120mesure",
+ "onden",
+ "\u00d9\u0125\u00d8\u00b1",
+ "\u0120exile",
+ "\u0120Desde",
+ "\u0120Pinterest",
+ "\u0120attachments",
+ "\u0120hombres",
+ "\u0120fines",
+ "\u0120\u00ec\u0126\u00b8\u00ec\u0125\u0123",
+ "\u0120sleeps",
+ "\u0120Taco",
+ "\u0120IRA",
+ "rios",
+ "\u0120oll",
+ "etes",
+ "\u0120unut",
+ "fashioned",
+ "\u0120treball",
+ "\u0120Nearly",
+ "\u0120\u00d1\u0122\u00d0\u00b5\u00d0\u00b0\u00d0\u00bb\u00d1\u012e\u00d0\u00bd\u00d0\u00be",
+ "\u0120chil",
+ "\u00e9\u0122\u00b1",
+ "\u00c4\u0141a",
+ "\u0120MEL",
+ "roscop",
+ "\u0120CG",
+ "\u0120venge",
+ "\u0120dishwasher",
+ "algic",
+ "\u0120modifier",
+ "\u0120embassy",
+ "timer",
+ "emics",
+ "\u0120intricate",
+ "\u0120evet",
+ "\u0120\u00eb\u012e\u0122\u00eb\u00b0\u0137",
+ "\u0120isot",
+ "\u0120\u00d0\u00bd\u00d0\u00b0\u00d1\u0125\u00d1\u0129",
+ "\u0120Quiz",
+ "reso",
+ "\u00ce\u00b4\u00cf\u0130",
+ "\u0120yelled",
+ "\u0120feder",
+ "ELLER",
+ "\u0120exceeded",
+ "onas",
+ "icano",
+ "\u0120\u00d0\u00b6\u00d0\u00b8\u00d0\u00b2\u00d0\u00be\u00d1\u0124",
+ "\u0120Mao",
+ "\u0120Kazuto",
+ "\u0120\u00e3\u0127\u012d\u00e3\u0127\u012d\u00e3\u0127\u012d\u00e3\u0127\u012d",
+ "\u0120frontline",
+ "\u0120Hungarian",
+ "\u0120\u00c3\u00bcberall",
+ "awat",
+ "\u0120grips",
+ "i\u00c3\u00a7\u00c3\u00b5es",
+ "arnya",
+ "\u0120\u00cd\u00a1",
+ "\u0120seid",
+ "\u0120anak",
+ "\u0120acabou",
+ "\u00ed\u0137\u0133",
+ "\u0120notorious",
+ "\u0120Godzilla",
+ "\u0120overcoming",
+ "\u0120Pend",
+ "\u0120olabilir",
+ "\u00c3\u00bclme",
+ "\u0120erhalten",
+ "\u00e3\u0124\u012b\u00e3\u0123\u0126",
+ "\u00ea\u00b7\u00b9",
+ "\u0120Meter",
+ "\u0120staan",
+ "Ol",
+ "\u0120chats",
+ "\u0120Buenos",
+ "\u00c3\u0143ve",
+ "aluable",
+ "\u0120strategically",
+ "\u0120comprised",
+ "\u0120\u00d0\u00bf\u00d0\u00b5\u00d1\u0122\u00d1\u0123\u00d0\u00be\u00d0\u00bd\u00d0\u00b0\u00d0\u00b6",
+ "\u0120wann",
+ "\u0120Cen",
+ "\u00d0\u00bd\u00d0\u00b8\u00d1\u0124\u00d0\u00b5",
+ "\u0141\u0123",
+ "\u0120\u00d1\u0124\u00d0\u00be\u00d0\u00b1\u00d0\u00be\u00d0\u00b9",
+ "iad",
+ "\u0120karde\u00c5\u0141im",
+ "\u0120Congressman",
+ "reaming",
+ "homme",
+ "\u0120communaut",
+ "\u0120alcoholic",
+ "\u0120pickled",
+ "\u0120acord",
+ "position",
+ "eg\u00c3\u00b3l",
+ "\u0120troubling",
+ "\u0120Marcheg",
+ "\u0120zumindest",
+ "\u0120seamlessly",
+ "\u0120olun",
+ "\u0120TVs",
+ "\u0120\u00d0\u00bf\u00d1\u0122\u00d0\u00b0\u00d0\u00ba\u00d1\u0124\u00d0\u00b8\u00d1\u0129\u00d0\u00b5\u00d1\u0123\u00d0\u00ba\u00d0\u00b8",
+ "\u0120backend",
+ "\u00e3\u0123\u0135\u00e3\u0124\u0135\u00e3\u0123\u00ab\u00e3\u0123\u00a1\u00e3\u0123\u00af",
+ "idable",
+ "\u0120gadget",
+ "\u0120fa\u00c3\u00a7o",
+ "\u0120Marchegiani",
+ "\u0120\u00eb\u00b0\u00a4",
+ "\u0120accidental",
+ "\u0120LP",
+ "\u0120eldest",
+ "\u0120Admiral",
+ "\u0120n\u00c4\u0125m",
+ "lever",
+ "\u0120pastel",
+ "\u0120fondo",
+ "Connie",
+ "\u0120tercer",
+ "\u0120pact",
+ "\u0120Monte",
+ "\u0120meats",
+ "\u0120SMS",
+ "\u0120Australians",
+ "\u00e7\u00bc",
+ "Rhett",
+ "\u0120exactement",
+ "\u0120\u00eb\u00b9\u00bc",
+ "\u0120MOD",
+ "\u00e7\u00a1",
+ "\u0120Rapt",
+ "\u0120Noch",
+ "\u0120abort",
+ "\u0120Naval",
+ "\u0120Fuji",
+ "INTER",
+ "\u0120\u00d0\u00bd\u00d0\u00be\u00d0\u00b2\u00d1\u012d\u00d0\u00b9",
+ "\u0120miejsce",
+ "\u0120ICU",
+ "\u0120Graduate",
+ "\u0120Glen",
+ "ardi",
+ "\u0120\u00c8\u013a",
+ "\u0120solder",
+ "\u0120professions",
+ "\u0120orthog",
+ "omn",
+ "introdu",
+ "\u0120Denise",
+ "\u00ec\u0140\u0132\u00eb\u00a5\u00bc",
+ "\u0120correspondence",
+ "AMA",
+ "\u0120inflict",
+ "\u0120fand",
+ "\u0120G\u00c3\u00bc",
+ "\u0120\u00d1\u0129\u00d0\u00b5\u00d1\u0124",
+ "\u0120traced",
+ "\u0120patents",
+ "\u0120ambush",
+ "\u0120lotta",
+ "ffer",
+ "\u0120Wagner",
+ "\u0120imperson",
+ "\u0120extr\u00c3\u00aamement",
+ "\u00d9\u0124\u00d8\u00aa",
+ "conduct",
+ "Att",
+ "\u0120Mueller",
+ "\u0120Alicia",
+ "\u0120cyc",
+ "\u0120hacker",
+ "\u0120tys",
+ "\u0120hail",
+ "\u0120\u00d0\u00b7\u00d0\u00b0\u00d1\u0131\u00d0\u00b2",
+ "\u0120passo",
+ "\u0120\u00ec\u00b6\u0136\u00ea\u00b0\u0122",
+ "\u0120\u00ce\u012a",
+ "\u0120packaged",
+ "\u0120Cynthia",
+ "heet",
+ "\u00e4\u00b8\u0143\u00e5\u013d\u00bd",
+ "\u0120Nissan",
+ "\u0120Questo",
+ "\u00e9\u00a8",
+ "did",
+ "\u0120\u00ce\u00bc\u00ce\u00b9\u00ce\u00b1",
+ "\u0120Ellis",
+ "\u0120Analysis",
+ "cemos",
+ "\u0120aseg",
+ "\u0120Myster",
+ "\u0120Cao",
+ "\u0120tuv",
+ "\u0120Industry",
+ "\u00ec\u00a3\u00bc\u00ea\u00b3\u0142",
+ "otal",
+ "\u0120peque\u00c3\u00b1o",
+ "bras",
+ "\u0120comprehend",
+ "\u0120Simpson",
+ "\u00d1\u0123\u00d1\u0124\u00d0\u00b2\u00d0\u00b8\u00d0\u00b5",
+ "ocracy",
+ "\u00d0\u00b8\u00d1\u0129\u00d0\u00b5\u00d1\u0123\u00d0\u00ba\u00d0\u00b8",
+ "\u0120Mush",
+ "\u0120Laurie",
+ "\u0120triangular",
+ "\u0120Presents",
+ "\u0120Kunden",
+ "\u00e7\u00b4\u00b9",
+ "\u00e6\u0143\u00a6",
+ "\u0120Iss",
+ "\u0120Deck",
+ "\u00e1\u00bb\u0125n",
+ "\u0120Darkness",
+ "\u0120inflammatory",
+ "eremiah",
+ "\u0120warmed",
+ "veyard",
+ "\u0120Memory",
+ "etty",
+ "\u0120taxpayers",
+ "\u00e0\u00b8\u0135",
+ "\u00d8\u00a1",
+ "\u0120practise",
+ "\u00eb\u012d\u00ac\u00eb",
+ "\u0120drilled",
+ "m\u00c3\u00bc\u00c5\u0141",
+ "logo",
+ "\u0120Fach",
+ "\u00a4\u00eb\u00a1\u013e",
+ "\u0120\u00c3\u00bcbrigens",
+ "\u0120konnten",
+ "\u0120normalmente",
+ "\u0120argues",
+ "ilingual",
+ "\u00b0\u00eb\u00a5\u00bc",
+ "egal",
+ "\u0120travaill",
+ "ovy",
+ "\u00d0\u00b0\u00d1\u0124\u00d0\u00be",
+ "\u0120ruth",
+ "\u0120Lights",
+ "\u0120consisted",
+ "\u00d7\u0133\u00d7\u00a8\u00d7\u013b\u00d7\u013f",
+ "\u0120stereotype",
+ "\u0120payer",
+ "\u0120Ree",
+ "\u0120Airbnb",
+ "\u0120drowned",
+ "\u0120Zoe",
+ "\u0120canopy",
+ "\u0120barr",
+ "\u0120\u00d0\u00bd\u00d0\u00be\u00d1\u0129",
+ "\u0120pagan",
+ "\u0120jars",
+ "\u0120r\u00c3\u00aa",
+ "erver",
+ "\u00e6\u012a\u00bf",
+ "ieben",
+ "\u0120espect",
+ "\u0120Fi",
+ "\u0120unwilling",
+ "\u0120technician",
+ "\u00e1\u00ba\u00b7t",
+ "member",
+ "\u0120Canal",
+ "\u00d8\u00b3\u00d9\u0127",
+ "\u0120lieber",
+ "\u0120inference",
+ "\u0120honoring",
+ "\u00e5\u0133\u00b5",
+ "\u0120Campaign",
+ "\u0120lineage",
+ "\u0120Stress",
+ "\u0120victories",
+ "\u0120deja",
+ "\u00d7\u00a3",
+ "\u00c3\u00aates",
+ "blick",
+ "\u0120\u00d0\u00bc\u00d0\u00b5\u00d0\u00bd\u00d0\u00b5\u00d0\u00b5",
+ "oths",
+ "\u0120Couple",
+ "Jason",
+ "\u0120Nicolas",
+ "\u00d0\u00b5\u00d0\u00ba\u00d1\u0123",
+ "lib",
+ "\u0120herramient",
+ "\u0120\u00d7\u0132\u00d7\u0137\u00d7\u0140\u00d7\u00a8",
+ "\u0120\u00d0\u00b2\u00d0\u00b8\u00d0\u00b4\u00d0\u00b8\u00d0\u00bc",
+ "millimeter",
+ "\u0120silhouette",
+ "\u0120driveway",
+ "\u0120cherish",
+ "\u00e3\u0127\u0142\u00e3\u0127\u0142",
+ "\u0120ransom",
+ "\u0120interdisciplinary",
+ "\u0120Portal",
+ "\u0120trag",
+ "thood",
+ "\u0120tedious",
+ "\u0120glossy",
+ "\u0120pr\u00c3\u00a9par",
+ "\u0120Cay",
+ "\u0120Took",
+ "\u0120Bottom",
+ "\u0120zig",
+ "\u00e5\u00ab",
+ "\u00e5\u012f\u00b1",
+ "represented",
+ "\u00e0\u00b9\u0122\u00e0\u00b8\u00a5\u00e0\u00b8\u00a2",
+ "\u0120desarrollo",
+ "\u00ec\u0126\u013e\u00eb",
+ "\u0120viscos",
+ "\u0120milligram",
+ "\u0120Gund",
+ "\u0120ferment",
+ "drum",
+ "\u0120drawers",
+ "Laugh",
+ "\u0120pelos",
+ "\u0120pavement",
+ "\u0120memoir",
+ "avait",
+ "\u01202050",
+ "\u00a4\u00eb\u00a5\u00bc",
+ "\u0120raz\u00c3\u00b3n",
+ "\u0120flourish",
+ "\u0120stern",
+ "\u00e4\u00b8\u012a",
+ "\u0120Chung",
+ "\u0120serpent",
+ "\u0120Gentlemen",
+ "\u00e7\u013e\u0141\u00e7\u013c\u0126\u00e5\u00be\u012a",
+ "kook",
+ "\u0120lut",
+ "importe",
+ "parent",
+ "\u0120wsz",
+ "\u0120scree",
+ "\u0120Mitarbeiter",
+ "\u00e5\u00b7\u00b4",
+ "mut",
+ "\u0120\u00ec\u0138\u013a\u00ea\u00b8\u00b0\u00eb\u00a5\u00bc",
+ "\u0120semble",
+ "\u0120OW",
+ "\u0120investigator",
+ "\u0120Cheryl",
+ "\u0120Gerald",
+ "\u0120prere",
+ "\u0120compares",
+ "nyt",
+ "\u0120diferen\u00c3\u00a7a",
+ "?-",
+ "\u0120qu\u00c3\u00a1",
+ "\u00d7\u00a8\u00d7\u013b",
+ "Sen",
+ "\u0120heps",
+ "\u0120gratuit",
+ "\u0120consort",
+ "\u0120STOP",
+ "\u0120Protestant",
+ "\u0120electrode",
+ "\u00e2\u0139",
+ "\u0120securely",
+ "\u00d0\u00b8\u00d1\u0129\u00d0\u00b5\u00d1\u0123\u00d0\u00ba\u00d0\u00be\u00d0\u00b9",
+ "\u0120t\u00c3\u00a4\u00c3\u00a4",
+ "\u0120registers",
+ "\u0120Heavenly",
+ "ogly",
+ "iss\u00c3\u00a4",
+ "\u0120Physics",
+ "\u0120Merkel",
+ "\u0120r\u00c3\u00a9v",
+ "\u00e9\u013b\u00a2",
+ "\u0120erased",
+ "\u0120Sacramento",
+ "\u0120coffin",
+ "\u0120exacer",
+ "\u0120lanz",
+ "\u0120poets",
+ "ulif",
+ "\u0120\u00ec\u00b9\u013a\u00eb",
+ "\u0120Nerd",
+ "\u0120NCT",
+ "\u0120Hour",
+ "nehmer",
+ "\u0140\u013a\u00eb\u0131\u0126",
+ "\u0120Princi",
+ "Sw",
+ "mies",
+ "armed",
+ "\u0120Beatles",
+ "\u0120propagation",
+ "\u0120exchanged",
+ "\u0120cumulative",
+ "\u0120\u00ec\u00a7\u0133\u00ec\u0139\u0132",
+ "\u0120defeating",
+ "\u00e6\u012c\u00b1",
+ "bels",
+ "\u0120wes",
+ "\u0120Odyssey",
+ "\u00e4\u00bd\u0142\u00e6\u0125\u00b3",
+ "avior",
+ "\u0120\u00ec\u013e\u0126\u00ec\u0139\u0132",
+ "\u0120brit",
+ "\u0120hijo",
+ "DAY",
+ "\u0120\u00d8\u00a7\u00d9\u0126\u00d8\u00aa\u00d9\u012c",
+ "\u0120\u00d0\u00a1\u00d0\u00b5\u00d1\u0122\u00d0\u00b3",
+ "\u00d1\u0125\u00d0\u00ba\u00d0\u00b0",
+ "edsi\u00c4\u013b",
+ "\u0120impos",
+ "\u0120ellas",
+ "\u0120firearms",
+ "\u0120NR",
+ "\u0120\u00d7\u0133\u00d7\u0132",
+ "\u0120\u00d0\u0141\u00d0\u00be\u00d0\u00ba\u00d0\u00b0",
+ "awi",
+ "\u0120\u00ec\u0126\u00b1\u00ea\u00b3\u00b5",
+ "\u0120pupils",
+ "\u0120Tack",
+ "\u0120frase",
+ "\u0120Ship",
+ "\u0120stad",
+ "\u00e4\u00b8\u013e",
+ "\u0120Greater",
+ "unun",
+ "immung",
+ "grown",
+ "\u0120NXT",
+ "\u0120Americas",
+ "fox",
+ "\u0120manten",
+ "\u00e9\u0142\u0132\u00e5\u0124\u013b",
+ "\u0120\u00d1\u0123\u00d0\u00be\u00d0\u00ba",
+ "\u0120rikt",
+ "lectric",
+ "deep",
+ "\u0120\u00d0\u00b7\u00d0\u00bd\u00d0\u00b0\u00d0\u00b5\u00d1\u012a\u00d1\u012e",
+ "\u0120benut",
+ "\u0120Infrast",
+ "\u0120Emir",
+ "\u0120\u00d0\u00be\u00d1\u0124\u00d0\u00bf\u00d1\u0122\u00d0\u00b0\u00d0\u00b2",
+ "\u0120Kimchi",
+ "\u0120Finnish",
+ "\u00b4\u00ec\u0142\u0123",
+ "inaire",
+ "\u0120oike",
+ "\u00e6\u00b8\u0127\u00e6\u00a5\u013c",
+ "\u0120hostage",
+ "\u0120Button",
+ "\u00d9\u0124\u00d9\u012c",
+ "eking",
+ "\u0120Kazakh",
+ "\u0120comforting",
+ "\u0120sog",
+ "\u0120greeted",
+ "guitar",
+ "payer",
+ "\u0120relational",
+ "\u0120construir",
+ "\u00e7\u012b\u00b9\u00e5\u012a\u00a5",
+ "opian",
+ "\u0120Volume",
+ "ieth",
+ "\u00d1\u0123\u00d1\u0124\u00d0\u00b2\u00d0\u00be\u00d0\u00bc",
+ "urrection",
+ "li\u00c5\u013dmy",
+ "\u0120hemisphere",
+ "\u0120Bean",
+ "IGN",
+ "\u0120k\u00c3\u00b6t\u00c3\u00bc",
+ "\u0120Fallout",
+ "\u0120brace",
+ "\u00e7\u00b9\u00bc\u00e7\u00ba\u012e",
+ "\u00cf\u0122\u00ce\u00ac",
+ "\u0120HAS",
+ "\u0120g\u00c3\u00a9",
+ "\u0120characterize",
+ "\u00e1\u00ba\u00b7c",
+ "\u0120Milky",
+ "\u0120tumors",
+ "\u0120nuit",
+ "\u0120Gaz",
+ "\u0120\u00ec\u0140\u012a\u00eb\u012d\u00a4\u00eb\u012c\u0136",
+ "\u0120\u00d0\u00b3\u00d0\u00b0\u00d1\u0122",
+ "essment",
+ "\u0120Abe",
+ "\u0120\u00eb\u00bd\u0133",
+ "\u0120Einsatz",
+ "JIN",
+ "j\u00c3\u00a4",
+ "Cry",
+ "\u0120Promised",
+ "\u0120\u00d1\u0123\u00d0\u00b5\u00d1\u0122\u00d0\u00b4",
+ "okus",
+ "\u0120scalable",
+ "\u0120\u00d0\u00bf\u00d0\u00be\u00d1\u0123\u00d0\u00bc\u00d0\u00be\u00d1\u0124\u00d1\u0122\u00d0\u00b5\u00d1\u0124\u00d1\u012e",
+ "\u00c3\u00bccklich",
+ "\u0120realism",
+ "\u0120mayo",
+ "\u0120juvenile",
+ "\u0120headlights",
+ "\u0120g\u00c3\u00b6r\u00c3\u00bc\u00c5\u0141",
+ "\u0120Reform",
+ "\u0120halves",
+ "czne",
+ "\u0120breakup",
+ "\u00c5\u00bcej",
+ "\u0120r\u00c3\u00a4tt",
+ "Day",
+ "\u0120\u00ec\u013f\u00bc\u00eb\u00b3\u00b8",
+ "\u0120muerte",
+ "\u0120tunes",
+ "\u0120Smile",
+ "record",
+ "\u0120recherche",
+ "atisfied",
+ "\u0120pozi",
+ "\u0120celebrations",
+ "isexual",
+ "\u0120ROB",
+ "thirds",
+ "\u0120Fortune",
+ "\u0120\u00d1\u0124\u00d0\u00be\u00d0\u00b9",
+ "\u0120branded",
+ "loo",
+ "\u0120dud",
+ "\u0120randomized",
+ "\u0120combin",
+ "\u00e4\u00b8\u0122\u00e4\u00ba\u013d",
+ "ieran",
+ "czenia",
+ "\u012f\u00e3\u0125\u00ab",
+ "\u0120curator",
+ "\u0120artery",
+ "\u0120\u00d1\u0125\u00d1\u012a",
+ "\u0120\u00d1\u0129\u00d0\u00b8\u00d1\u0124",
+ "\u0120subsidies",
+ "\u0120blossom",
+ "\u0120Twilight",
+ "\u0120hyv\u00c3\u00a4",
+ "\u0120Pompe",
+ "\u0120Cisco",
+ "\u0120\u00d0\u0141\u00d1\u0122\u00d0\u00be",
+ "\u0120biri",
+ "\u0120gern",
+ "\u0120rebuilt",
+ "\u0120wcze",
+ "\u0120benefici",
+ "\u0120drummer",
+ "\u0120solids",
+ "\u0120diyorsun",
+ "\u00e3\u0123\u0124\u00e3\u0124\u012c\u00e3\u0123\u012e\u00e3\u0123\u00a8\u00e3\u0123\u0128\u00e3\u0123\u0136\u00e3\u0123\u0138\u00e3\u0123\u0126\u00e3\u0123\u00be\u00e3\u0123\u0139\u00e3\u0123\u0141",
+ "lated",
+ "\u0120muddy",
+ "\u0120holog",
+ "\u0120claps",
+ "\u0120Rings",
+ "\u0120Okey",
+ "\u0120Brave",
+ "\u0120valuation",
+ "\u0120migrant",
+ "\u0120intermitt",
+ "\u0120eigene",
+ "iliary",
+ "\u00e3\u0125\u00bc\u00e3\u0125\u012a",
+ "markt",
+ "kr",
+ "\u0120Rib",
+ "\u00e1\u00bb\u013bi",
+ "\u0120accusations",
+ "\u0120arab",
+ "wash",
+ "\u0120Bardzo",
+ "\u0120ugh",
+ "esters",
+ "ophren",
+ "\u0120alimentos",
+ "\u0120Uz",
+ "\u00d6\u0124",
+ "\u0120650",
+ "\u0120\u00d0\u00bf\u00d1\u0122\u00d0\u00b8\u00d0\u00b5\u00d1\u0127",
+ "FI",
+ "\u0120sampai",
+ "\u0120parl\u00c3\u00a9",
+ "hesion",
+ "\u0120s\u00c4\u00b1r",
+ "\u0120apparatus",
+ "\u0120correlated",
+ "\u0120Principal",
+ "\u0120corr",
+ "\u0120Official",
+ "\u00d0\u00b8\u00d1\u0129\u00d0\u00b5\u00d1\u0123\u00d0\u00ba\u00d0\u00b8\u00d0\u00b5",
+ "\u0120terminals",
+ "Should",
+ "\u0120vacun",
+ "\u0120stellt",
+ "\u0120mooi",
+ "etzung",
+ "\u0120\u00d0\u00ba\u00d1\u0122\u00d0\u00b0",
+ "\u0120dai",
+ "\u0120\u00d0\u00bf\u00d0\u00be\u00d0\u00b6",
+ "Team",
+ "\u0120PPE",
+ "\u0120\u00d0\u0140\u00d1\u0123",
+ "\u0120Leah",
+ "\u0120Ivy",
+ "yst",
+ "\u0120uhhh",
+ "\u0120nighttime",
+ "\u0120trendy",
+ "\u0120securities",
+ "\u0120continents",
+ "\u0120firsthand",
+ "\u0120Veron",
+ "\u0120\u00eb\u0124\u00ae",
+ "\u0120browsing",
+ "\u0120Cada",
+ "tro",
+ "\u0120tramp",
+ "reib",
+ "\u0120erstmal",
+ "irler",
+ "\u0120psic",
+ "\u0120getir",
+ "\u0120NP",
+ "\u0120dzieci",
+ "\u00d0\u00be\u00d0\u00b1\u00d1\u0122\u00d0\u00b0\u00d0\u00b7",
+ "\u0120magician",
+ "\u0120scrutiny",
+ "\u0120slab",
+ "\u0120OT",
+ "isty",
+ "iries",
+ "orest",
+ "\u0120tasked",
+ "\u0120morally",
+ "\u00ec\u0137\u00bc\u00ec\u00a7\u0122",
+ "ustered",
+ "\u0120fools",
+ "\u0120irrespons",
+ "\u0120einf",
+ "\u0120vi\u00e1\u00bb\u0129c",
+ "\u0120scor",
+ "\u0120pillows",
+ "\u0120Gegen",
+ "\u0120tutte",
+ "\u0120quarterly",
+ "\u0120didnt",
+ "\u0120Gym",
+ "\u0120Ether",
+ "\u0120\u00d8\u00ab",
+ "\u00d0\u00bb\u00d0\u00b8\u00d1\u012a\u00d0\u00ba\u00d0\u00be\u00d0\u00bc",
+ "\u0120signaling",
+ "\u0120Node",
+ "\u0120Doncs",
+ "\u0120yah",
+ "\u0120Kanal",
+ "\u0120fading",
+ "etin",
+ "\u0120influencers",
+ "\u0120medals",
+ "\u0120engineered",
+ "\u0120fermented",
+ "\u00ea\u00b2\u0142\u00ec\u00a7\u0122\u00eb\u00a7\u012e",
+ "\u0120Beethoven",
+ "\u00d7\u0140\u00d7\u00a9",
+ "inental",
+ "\u0120\u00ec\u0137\u012e\u00eb\u0142\u00a4",
+ "\u00c3\u00bctfen",
+ "alnya",
+ "\u0120overe",
+ "\u0120denkt",
+ "\u00d0\u00b0\u00d0\u00ba\u00d1\u0124\u00d0\u00b5\u00d1\u0122",
+ "\u0120\u00e2\u013a",
+ "\u0120necesit",
+ "\u0120generators",
+ "grass",
+ "\u0120\u00d0\u00bf\u00d0\u00be\u00d0\u00b4\u00d1\u0125\u00d0\u00bc",
+ "lie\u00c3\u0141en",
+ "Bar",
+ "\u013e\u00eb\u0131\u013b",
+ "\u0120\u00d0\u00b4\u00d0\u00b5\u00d1\u0124\u00d0\u00b5\u00d0\u00b9",
+ "\u0120sucking",
+ "\u0120stencil",
+ "\u0120primo",
+ "\u0120Breath",
+ "strom",
+ "\u0120immensely",
+ "\u0120appreh",
+ "\u00ec\u0142\u0137\u00ec\u013f\u00b4",
+ "Pop",
+ "\u0120jong",
+ "\u0120Giul",
+ "\u0120ADHD",
+ "\u0120h\u00c3\u00b6ren",
+ "\u0120elo",
+ "ivent",
+ "\u0120rus",
+ "\u0120outrageous",
+ "\u0120mastered",
+ "\u0120\u00ec\u00bb\u00a4",
+ "\u00d9\u012a\u00d9\u0123",
+ "ipes",
+ "\u0120Rudy",
+ "Jacob",
+ "\u0120bullish",
+ "\u0120tapped",
+ "\u0120faud",
+ "izophren",
+ "\u0120\u00d1\u0123\u00d0\u00be\u00d1\u0127",
+ "\u0120Darling",
+ "\u01201963",
+ "\u0120Prevention",
+ "\u00b2\u0136",
+ "\u0120abdominal",
+ "stones",
+ "\u0120avaient",
+ "\u00e1\u00bb\u0137i",
+ "make",
+ "\u0120sare",
+ "\u0120Instant",
+ "\u00d0\u00ba\u00d0\u00b0\u00d0\u00bc",
+ "\u0120keeper",
+ "\u0120blankets",
+ "\u00e3\u0123\u00a7\u00e3\u0123\u0139\u00e3\u0124\u0129\u00e3\u0123\u0128",
+ "\u0120sweats",
+ "\u0120Minneapolis",
+ "\u00e5\u0127\u00a8\u00e9\u0125\u00a8",
+ "\u0120genommen",
+ "\u0120fasten",
+ "\u0120Brussels",
+ "\u00e5\u0133\u00bc",
+ "\u0120cafeter",
+ "\u0120absorbing",
+ "\u0120hago",
+ "\u0120Elmo",
+ "\u0120gusto",
+ "\u0120Yap",
+ "M\u00c3\u00basica",
+ "\u0120tert",
+ "\u0120banda",
+ "\u0120mily",
+ "\u0120thereafter",
+ "\u0120Stockholm",
+ "\u0120Carson",
+ "\u0120calibration",
+ "ava\u00c5\u0141",
+ "ansa",
+ "ikke",
+ "\u0120foresee",
+ "\u0120qualche",
+ "\u0120deste",
+ "\u00e6\u00a4",
+ "\u00c3\u00bcn\u00c3\u00bcz",
+ "\u0120forge",
+ "Dis",
+ "esten",
+ "\u0120\u00ce\u00b4\u00ce\u00b9\u00ce\u00b1",
+ "\u0120encaps",
+ "\u0120Gespr",
+ "\u0120chercher",
+ "ickets",
+ "\u00d1\u0124\u00d0\u00be\u00d1\u0122\u00d1\u012d",
+ "Cr",
+ "\u0120\u00d0\u00a2\u00d0\u00b0\u00d0\u00ba\u00d0\u00b6\u00d0\u00b5",
+ "\u0120rabbits",
+ "\u0120Dot",
+ "heiten",
+ "\u0120causal",
+ "\u0120Foster",
+ "aj\u00c4\u0127c",
+ "\u0120bereit",
+ "\u0120ayudar",
+ "\u00e9\u00ab\u013b",
+ "\u00e3\u0123\u00b3",
+ "song",
+ "comb",
+ "\u0120fringe",
+ "\u0120cybersecurity",
+ "\u0120\u00eb\u013e\u00a8",
+ "\u0120kier",
+ "\u0120besch\u00c3\u00a4ft",
+ "\u0120\u00d0\u00ba\u00d0\u00be\u00d0\u00bd\u00d1\u0128\u00d0\u00b5",
+ "\u0120facilit",
+ "\u0120Namen",
+ "\u0120bilateral",
+ "tx",
+ "\u0120Wissenschaft",
+ "\u0120nuances",
+ "\u0120ripping",
+ "\u0120fy",
+ "\u0120Sicherheit",
+ "\u0120Ghana",
+ "olon",
+ "\u0120topped",
+ "\u0120Morocco",
+ "\u0120radial",
+ "\u0120LEE",
+ "\u0120Andreas",
+ "edd",
+ "\u0120\u00ec\u0139\u00b4\u00eb",
+ "\u0120Airlines",
+ "\u00e3\u0123\u0135\u00e3\u0124\u012f",
+ "\u0120valores",
+ "\u00ea\u00b7\u013e",
+ "Hy",
+ "\u0120\u00d0\u00b7\u00d0\u00b0\u00d0\u00b4\u00d0\u00b0\u00d1\u0129",
+ "\u0120Kendall",
+ "\u0120\u00d1\u0127\u00d0\u00b0\u00d1\u0122",
+ "\u0120Vamp",
+ "\u0120python",
+ "\u0120manageable",
+ "\u0120Gente",
+ "oise",
+ "iciary",
+ "\u0120imposs",
+ "\u0120Bunny",
+ "iesta",
+ "Andrew",
+ "\u0120sert",
+ "\u0120Cec",
+ "zzarella",
+ "\u0120automobile",
+ "\u0120Tiere",
+ "allows",
+ "\u00e5\u0128\u0128",
+ "\u0120\u00eb\u00b0\u0122",
+ "\u0120Scorp",
+ "\u0120Jelly",
+ "agara",
+ "\u0120Stretch",
+ "\u0120redef",
+ "\u0120exacerb",
+ "\u0120SHA",
+ "\u00c3\u00a9f",
+ "orsa",
+ "\u0120flawed",
+ "\u0120Noel",
+ "?!?",
+ "\u0120procent",
+ "\u0120menstru",
+ "\u0120\u00d0\u00bf\u00d1\u0122\u00d0\u00be\u00d1\u0129",
+ "\u0120infants",
+ "\u00f0\u0141\u0130\u00b5",
+ "pause",
+ "\u0120Racing",
+ "\u01201948",
+ "\u0120superintendent",
+ "idores",
+ "idy",
+ "brahim",
+ "\u0120unlucky",
+ "\u0120perk",
+ "anci",
+ "\u0120\u00eb\u00a7\u012e\u00eb\u0124\u013a",
+ "\u0120\u00d0\u013e\u00d0\u00be\u00d1\u0123\u00d0\u00ba\u00d0\u00b2",
+ "\u0120finans",
+ "\u0120diferencia",
+ "\u0142\u012a\u00ec\u013f\u00b4",
+ "\u00e9\u0127\u012f",
+ "ORY",
+ "\u0120Tac",
+ "\u00db\u012e\u00d8\u00a7",
+ "\u0120desem",
+ "\u0120\u00d0\u00b2\u00d0\u00b0\u00d0\u00b6\u00d0\u00bd\u00d0\u00be",
+ "\u0120JU",
+ "\u0120\u00ec\u0140\u012a\u00ec\u0140\u0138\u00ec\u0137\u0126\u00ec\u013c\u0136",
+ "\u0120\u00ce\u013f",
+ "\u0120informations",
+ "\u0120HEL",
+ "hst",
+ "\u0120\u00d0\u00bf\u00d0\u00be\u00d0\u00b3\u00d0\u00be\u00d0\u00b2\u00d0\u00be\u00d1\u0122",
+ "\u0120voiture",
+ "\u0120reus",
+ "\u00c3\u00a4ndig",
+ "\u0120\u00d0\u00bf\u00d0\u00be\u00d1\u0127\u00d0\u00be\u00d0\u00b6",
+ "jing",
+ "\u0120dru",
+ "altra",
+ "\u0120produits",
+ "\u0120kite",
+ "\u0120eyeball",
+ "\u0120Belt",
+ "\u0120Restaurant",
+ "\u0120gamb",
+ "\u0120porridge",
+ "itters",
+ "\u0120converts",
+ "\u0120yard\u00c4\u00b1m",
+ "\u0120m\u00c3\u00a1ximo",
+ "wirtschaft",
+ "\u0120\u00ed\u0137\u013a\u00eb\u0124\u013a\u00eb",
+ "\u0120\u00ec\u00a4\u0122",
+ "\u0120iceberg",
+ "\u0120vorbei",
+ "\u0120256",
+ "ocratic",
+ "\u0120reckless",
+ "onner",
+ "\u0120m\u00c3\u00bas",
+ "\u0120logically",
+ "\u0120Prison",
+ "\u0120Netz",
+ "\u0120vacant",
+ "\u0120nimmt",
+ "\u0120HARR",
+ "\u0120\u00d0\u00b7\u00d0\u00be\u00d0\u00b2",
+ "\u0120Dee",
+ "ringe",
+ "niest",
+ "\u0120Rules",
+ "\u00ec\u012c\u00a4\u00eb\u0141\u00bd",
+ "cussions",
+ "\u0120floral",
+ "\u0120constrained",
+ "\u0120differentiation",
+ "\u0120Quebec",
+ "\u0120\u00db\u0123\u00db\u012e\u00da\u00ba",
+ "\u0120p\u00c3\u00bablica",
+ "itel",
+ "\u0120accommodations",
+ "\u0120Gr\u00c3\u00bc",
+ "\u00ed\u013e",
+ "\u0120pickles",
+ "\u00d0\u00b8\u00d1\u0129\u00d0\u00b5\u00d1\u0123\u00d0\u00ba\u00d0\u00b8\u00d1\u0127",
+ "\u0120commissions",
+ "\u0120Baek",
+ "\u0120\u00c3\u00a7ocu\u00c4\u0141",
+ "\u0120Medium",
+ "\u0120periodically",
+ "\u0120wonderfully",
+ "\u0120staffing",
+ "\u00ec\u013d\u0132\u00eb",
+ "rire",
+ "fle",
+ "\u0120McL",
+ "\u0120\u00d1\u0124\u00d0\u00b5\u00d0\u00bf",
+ "\u0120\u00d0\u00bf\u00d0\u00b5\u00d1\u0122\u00d0\u00b5\u00d0\u00ba",
+ "\u00d0\u00bd\u00d0\u00be\u00d0\u00bb\u00d0\u00be\u00d0\u00b3",
+ "\u0120\u00ed\u0123\u00ac\u00ea\u00b2\u012e",
+ "\u00e7\u013b\u00bc\u00e7\u0131\u00be",
+ "\u0120prosperous",
+ "\u0120Spiritual",
+ "\u0120Chick",
+ "DIA",
+ "\u0120\u00d0\u0141\u00d1\u0122\u00d0\u00b8\u00d0\u00b2\u00d0\u00b5\u00d1\u0124",
+ "\u0120per\u00c3\u0143",
+ "\u00d1\u012e\u00d1\u0130\u00d1\u0124",
+ "\u0120consultants",
+ "\u0120Earl",
+ "\u00e4\u00bb\u012c\u00e5\u00b9\u00b4",
+ "\u0120ruining",
+ "\u00d0\u00be\u00d1\u0122\u00d0\u00b5",
+ "\u0120penser",
+ "\u0120takiej",
+ "\u0120strengthened",
+ "\u0120Liquid",
+ "\u00d0\u00be\u00d0\u00bd\u00d0\u00b5\u00d1\u0128",
+ "\u00d0\u00b0\u00d0\u00b2\u00d0\u00b0\u00d1\u0124\u00d1\u012e",
+ "\u0120camer",
+ "\u0120disagreement",
+ "\u0120bathing",
+ "\u0120Yosh",
+ "aal",
+ "prechen",
+ "RISADAS",
+ "\u0120superstar",
+ "\u00e6\u0123\u0143",
+ "\u00d0\u00bb\u00d1\u0131\u00d1\u0124\u00d1\u012e",
+ "\u0120nib",
+ "\u0120Therm",
+ "\u0120DANIEL",
+ "\u0120paw",
+ "\u0120liquids",
+ "\u0120capacit",
+ "arken",
+ "\u0120vagina",
+ "\u0120mashed",
+ "\u0120emerges",
+ "yscy",
+ "\u0120unrelated",
+ "\u0120Guild",
+ "\u0120inverted",
+ "itives",
+ "Tra",
+ "\u0120begr",
+ "\u0120alte",
+ "\u00ec\u00a7\u0137",
+ "\u00e3\u0124\u0123\u00e3\u0123\u00a6",
+ "\u0120\u00d1\u0122\u00d0\u00b0\u00d0\u00b7\u00d1\u0122\u00d0\u00b0\u00d0\u00b1\u00d0\u00be\u00d1\u0124",
+ "finder",
+ "\u0120\u00d0\u00b4\u00d0\u00b0\u00d0\u00bb\u00d0\u00b5\u00d0\u00b5",
+ "\u0120\u00d0\u00b1\u00d0\u00bb\u00d0\u00b0\u00d0\u00b3\u00d0\u00be\u00d0\u00b4\u00d0\u00b0\u00d1\u0122",
+ "walker",
+ "\u0120crater",
+ "assadors",
+ "rences",
+ "inski",
+ "\u0120KIM",
+ "\u0120Elliot",
+ "2017",
+ "\u0120Sr",
+ "inka",
+ "anov",
+ "\u0120\u00ec\u0140\u013a\u00eb\u00aa\u00bb",
+ "\u0120proprietary",
+ "displaystyle",
+ "\u0120\u00d1\u0123\u00d0\u00b8\u00d0\u00bc",
+ "\u0120\u00d0\u00b8\u00d0\u00b7\u00d0\u00b1",
+ "\u0120Panel",
+ "\u0120instincts",
+ "\u0120Communications",
+ "\u00e9\u00ba\u00bb",
+ "midt",
+ "\u0120\u00eb\u00a7\u012e\u00eb\u0135\u00a4\u00ec\u0138\u00b4",
+ "\u0120\u00d1\u0123\u00d0\u00bb\u00d0\u00be\u00d0\u00b2\u00d0\u00b0",
+ "\u0120Gilbert",
+ "\u00e7\u013d\u00ae\u00e5\u012b\u012f",
+ "\u00d0\u00a2\u00d0\u00b0\u00d0\u00ba",
+ "voorbeeld",
+ "\u00d0\u00b5\u00d1\u0130\u00d1\u0123\u00d1\u012e",
+ "aryn",
+ "quez",
+ "\u0120dart",
+ "\u00d1\u0138\u00d1\u012a",
+ "\u0120Hut",
+ "Sal",
+ "\u0120southeast",
+ "\u0120pesticides",
+ "\u0120helicopters",
+ "\u0120endured",
+ "iada",
+ "\u0120brewing",
+ "\u00ec\u0139\u00ac\u00eb",
+ "\u0120\u00d1\u0123\u00d0\u00b2\u00d0\u00be\u00d0\u00b1\u00d0\u00be\u00d0\u00b4",
+ "\u0120Saints",
+ "\u0120Fran\u00c3\u00a7ais",
+ "\u0120Economics",
+ "\u0120disloc",
+ "ophobia",
+ "Camer",
+ "\u0120negotiated",
+ "\u0120\u00d1\u0123\u00d1\u0124\u00d0\u00b0\u00d0\u00bb\u00d0\u00b8",
+ "\u00ec\u012c\u00a4\u00ed\u0123",
+ "ogie",
+ "\u0120tsunami",
+ "\u0120peeled",
+ "\u0120motivations",
+ "\u00e8\u00a8\u0143",
+ "ostat",
+ "flan",
+ "\u0120DAC",
+ "\u0120kav",
+ "'RE",
+ "\u0120Pearson",
+ "bbe",
+ "czenie",
+ "\u0120aten\u00c3\u00a7\u00c3\u00a3o",
+ "\u00ed\u0128\u00b5\u00eb\u0142\u00b9",
+ "\u00e3\u0123\u00a3\u00e3\u0123\u00a1",
+ "\u0120\u00d1\u0125\u00d0\u00b4\u00d0\u00b0\u00d1\u0122",
+ "\u0120introductory",
+ "\u0120Ici",
+ "\u00eb\u012e\u0122\u00eb",
+ "akat",
+ "\u0120trench",
+ "\u0120proceeded",
+ "\u0120Coin",
+ "\u0120derecho",
+ "\u0120Rede",
+ "\u00e6\u00af\u013d",
+ "\u00d0\u00b0\u00d0\u00bd\u00d0\u00bd\u00d1\u012d\u00d0\u00b9",
+ "\u0120incarcerated",
+ "\u0120Richmond",
+ "Rock",
+ "\u0120Pav",
+ "\u0120Karma",
+ "uges",
+ "\u0120conte\u00c3\u00ba",
+ "\u00eb\u00b9\u0126",
+ "\u0120\u00ea\u00b7\u00b8\u00eb\u00a7\u012e",
+ "\u0120Gone",
+ "\u0120wsp\u00c3\u00b3\u00c5\u0124",
+ "\u0120Rahmen",
+ "unken",
+ "\u0120\u00ec\u00a4\u0133\u00ec\u013c\u0136\u00ed\u0137\u013e",
+ "\u0120ib",
+ "\u0120attaching",
+ "Hay",
+ "\u0120suka",
+ "\u00ec\u012f\u00b9",
+ "\u0120pivotal",
+ "\u0120Respect",
+ "\u00c3\u0143da",
+ "IB",
+ "\u0120Verantwort",
+ "wiet",
+ "\u0120forensic",
+ "\u00d1\u0122\u00d0\u00b8\u00d1\u0123\u00d1\u0124",
+ "\u0120\u00d0\u00bf\u00d1\u0122\u00d0\u00b8\u00d0\u00bd\u00d1\u0128\u00d0\u00b8\u00d0\u00bf\u00d0\u00b5",
+ "\u0120markings",
+ "\u0120kettle",
+ "\u0120Opera",
+ "\u0120Doctors",
+ "\u0120shredded",
+ "\u0120recuer",
+ "\u0120vigil",
+ "\u0120Fail",
+ "\u0120entrev",
+ "\u0120\u00d0\u00b4\u00d1\u0125\u00d1\u012a",
+ "\u0120outbreaks",
+ "\u00e8\u00b5\u00b0\u00e5\u0132\u00a7",
+ "\u0120\u00cf\u0122\u00ce\u00bf",
+ "\u0120rogue",
+ "angled",
+ "\u0120yearly",
+ "\u0120Creed",
+ "\u0120wam",
+ "\u0120lotus",
+ "\u00ea\u00b3\u00bc\u00eb",
+ "\u00e3\u0122\u0123\u00e3\u0122\u0123",
+ "\u0120Spit",
+ "\u0120Itu",
+ "\u0120strains",
+ "\u0120stamped",
+ "\u0120plaint",
+ "\u0120potion",
+ "\u0120consolidation",
+ "\u00e8\u00a9\u0137",
+ "\u00d0\u00be\u00d1\u0129\u00d0\u00ba\u00d1\u0125",
+ "\u0120vlogging",
+ "\u0120slate",
+ "\u0120Auft",
+ "\u0120Incor",
+ "\u00e1\u00bb\u00abng",
+ "\u00a7\u0132",
+ "enh",
+ "\u0120hei\u00c3\u0141",
+ "\u0120domest",
+ "\u0120Strom",
+ "\u00e5\u012f\u00b3",
+ "akis",
+ "\u0120fragen",
+ "\u0120finer",
+ "\u0120Sug",
+ "\u0120uphill",
+ "\u0120\u00c3\u00a9\u00c3\u00a9n",
+ "\u00e2\u0122\u00a6)",
+ "\u0120\u00d1\u0123\u00d0\u00be\u00d0\u00bf",
+ "\u0120Corey",
+ "\u0120siebie",
+ "\u0120muse",
+ "\u0120cloves",
+ "\u0120pous",
+ "\u0120Finanz",
+ "\u0120Route",
+ "amat",
+ "\u0120mutually",
+ "\u0120\u00d0\u00b2\u00d0\u00bd\u00d1\u0125\u00d1\u0124\u00d1\u0122\u00d0\u00b8",
+ "\u0120Selena",
+ "\u00eb\u0136",
+ "\u0120Gaussian",
+ "\u00eb\u00b6\u0122\u00ed\u0126\u00b0",
+ "\u0120\u00d7\u0133\u00d7\u013d",
+ "\u0120ejerc",
+ "\u00e5\u00be\u00ae",
+ "kea",
+ "\u0120Gerry",
+ "\u0120Sic",
+ "\u00e5\u00a4\u00a7\u00e7\u013c\u0126",
+ "\u01201966",
+ "iese",
+ "\u0120fossils",
+ "\u0120estad",
+ "\u0120Kane",
+ "ci\u00c4\u0129",
+ "\u0120\u00ec\u013e\u0142\u00ed\u012c\u013e\u00eb",
+ "\u0120\u00d0\u00bf\u00d0\u00b0\u00d0\u00bc",
+ "\u0120Cruise",
+ "int\u00c3\u00a9rieur",
+ "\u0120bekannt",
+ "\u0120Pode",
+ "\u0120demander",
+ "Rem",
+ "\u0120invade",
+ "\u0120decorating",
+ "ropic",
+ "\u0120cowboy",
+ "\u0120Photo",
+ "opolit",
+ "\u0120\u00ec\u00bb\u00ac\u00eb\u0141\u00ac\u00eb",
+ "\u0120reap",
+ "\u0120handwriting",
+ "\u00e0\u00b9\u0126\u00e0\u00b8\u00a3",
+ "\u0120\u00eb\u013c",
+ "\u0120\u00d8\u00a8\u00d8\u00b9\u00d8\u00af",
+ "\u0120Mt",
+ "\u00d9\u0122",
+ "\u0120spaceship",
+ "\u0120nationalism",
+ "\u0120councils",
+ "\u0120Griffin",
+ "\u0120Ahmed",
+ "\u0120clich",
+ "\u0120OL",
+ "wl",
+ "\u0120Pilot",
+ "\u00e5\u00ae\u00ae",
+ "\u0120acronym",
+ "\u0120gels",
+ "\u0120electroly",
+ "\u00e8\u0135",
+ "\u0120\u00d0\u00bc\u00d0\u00bd\u00d0\u00be\u00d0\u00b9",
+ "\u0120episod",
+ "\u0120Dieses",
+ "\u0120ATP",
+ "\u0120ediyorum",
+ "\u0120expresses",
+ "\u0120exhibits",
+ "Comm",
+ "\u0120\u00d0\u00ba\u00d1\u0122\u00d1\u0125\u00d0\u00bf",
+ "\u0120matar",
+ "\u01202025",
+ "\u0120Artem",
+ "vasive",
+ "r\u00c3\u0142",
+ "\u0120be\u00c5\u0141",
+ "\u00e9\u00bb\u0125",
+ "\u0120lizard",
+ "\u0120fille",
+ "\u0120\u00ec\u00a7\u012a\u00eb\u00ac\u00b8",
+ "\u0120\u00d0\u00bc\u00d0\u00be\u00d1\u012b",
+ "\u0120t\u00c3\u00bcr",
+ "\u0120culprit",
+ "\u0120woven",
+ "\u0120ANY",
+ "nim",
+ "\u0120tay",
+ "\u0120promin",
+ "\u0120acompa",
+ "\u0120id\u00c3\u00a9",
+ "\u0120boiler",
+ "\u0120Themen",
+ "\u0120avenue",
+ "\u0120Mud",
+ "\u0120\u00d0\u00bd\u00d0\u00be\u00d0\u00b2\u00d1\u012d\u00d0\u00b5",
+ "\u0120witnessing",
+ "\u0120lance",
+ "\u0120CHAN",
+ "\u0120Bever",
+ "\u00d8\u00aa\u00d9\u0127",
+ "\u0120chemotherapy",
+ "King",
+ "\u0120b\u00c4\u013bd\u00c4\u013b",
+ "\u0120atual",
+ "\u0120tive",
+ "\u0120talkin",
+ "\u0120quedar",
+ "ie\u00c3\u0141",
+ "edel",
+ "\u0120\u00ec\u0138\u00b4\u00ec\u0142\u013e",
+ "\u0120jogar",
+ "\u0120\u00c3\u00b6r",
+ "\u0120undertaking",
+ "\u0120Strength",
+ "\u0120milh\u00c3\u00b5es",
+ "\u0120Wine",
+ "\u0120Molt",
+ "\u00e8\u00ae\u00b2",
+ "\u00e3\u0123\u0133\u00e3\u0124\u012e",
+ "\u0120undermine",
+ "\u0120Archives",
+ "vana",
+ "mercial",
+ "MC",
+ "\u0120caste",
+ "\u00d0\u00bf\u00d1\u0122",
+ "\u0120legislators",
+ "ulators",
+ "\u00c3\u00aanio",
+ "\u0120\u00eb\u012f\u00b0\u00eb",
+ "\u0120\u00d1\u0127\u00d0\u00be\u00d1\u0124\u00d0\u00b8\u00d1\u0124\u00d0\u00b5",
+ "\u0120\u00d0\u00bd\u00d0\u00b5\u00d0\u00ba",
+ "\u0120surn",
+ "\u0120consci",
+ "\u0120POW",
+ "\u0120culinary",
+ "\u0120KAT",
+ "\u0120Folks",
+ "\u00d1\u012d\u00d0\u00b2\u00d0\u00b0\u00d0\u00b5\u00d0\u00bc",
+ "\u0120\u00d0\u00b2\u00d0\u00be\u00d0\u00ba",
+ "\u00e3\u0123\u0133\u00e3\u0124\u012d",
+ "service",
+ "pts",
+ "\u0120\u00d0\u00bf\u00d0\u00be\u00d0\u00b1\u00d0\u00b5\u00d0\u00b4",
+ "\u00e6\u013a\u00af\u00e5\u0137\u012c",
+ "\u0120tents",
+ "\u0120nord",
+ "STE",
+ "\u0120republican",
+ "\u0120wyk",
+ "\u0120minions",
+ "\u00e8\u013b\u0137",
+ "\u0120memang",
+ "jest",
+ "\u0120comparative",
+ "\u0120tyle",
+ "carbon",
+ "bedingt",
+ "ksen",
+ "\u0120negativity",
+ "\u0120sj\u00c3\u00a4lv",
+ "\u0120d\u00c3\u00ba",
+ "\u00e6\u012b\u0122\u00e6\u013e\u012b",
+ "\u0120recalled",
+ "cra",
+ "\u0120Tada",
+ "\u0120\u00d1\u0122\u00d1\u0125\u00d0\u00ba\u00d0\u00b8",
+ "\u0120\u00d0\u00be\u00d0\u00bf\u00d1\u0122\u00d0\u00b5\u00d0\u00b4\u00d0\u00b5\u00d0\u00bb",
+ "\u0120procrast",
+ "\u0120jogos",
+ "\u0120Oo",
+ "\u0120Hearts",
+ "\u0120\u00c3\u00a9ch",
+ "\u0120ksi\u00c4\u0127\u00c5\u00bc",
+ "\u0120coarse",
+ "\u0120Tube",
+ "\u0120Greens",
+ "\u0120\u00c3\u00a9n",
+ "\u0120dumbbell",
+ "\u0120\u00d1\u0124\u00d0\u00b8",
+ "\u0120querer",
+ "\u00d8\u00a7\u00d8\u0143",
+ "\u00cf\u0125\u00ce\u00b5\u00ce\u00b9",
+ "\u0120\u00d0\u00bf\u00d1\u0122\u00d0\u00b0\u00d0\u00b2\u00d0\u00b8\u00d0\u00bb\u00d1\u012e\u00d0\u00bd\u00d0\u00be",
+ "\u0120\u00d0\u00bf\u00d0\u00b0\u00d0\u00bf",
+ "\u0120compra",
+ "\u0120t\u00c3\u00a9r",
+ "\u0120Antes",
+ "\u0120optimum",
+ "\u0120biscuit",
+ "\u00ce\u00ba\u00ce\u00b9",
+ "aczego",
+ "\u0120\u00ec\u012d\u013e\u00ea\u00b0\u0126\u00ec\u013f\u00b4",
+ "\u0120Marines",
+ "vero",
+ "\u0120vaccinations",
+ "\u0120petty",
+ "riters",
+ "\u0120\u00d0\u00b0\u00d0\u00bb",
+ "country",
+ "\u0120counters",
+ "\u0120attendant",
+ "\u0120Hui",
+ "\u00e3\u0123\u00a8\u00e3\u0123\u0126\u00e3\u0123\u0128\u00e3\u0123\u0135\u00e3\u0123\u00a8\u00e3\u0123\u00a7",
+ "cka",
+ "\u00d1\u0123\u00d1\u0124\u00d0\u00b2\u00d0\u00b5\u00d0\u00bd\u00d0\u00bd\u00d1\u012d\u00d0\u00b9",
+ "guy",
+ "\u0120tricked",
+ "\u0120RED",
+ "\u0120thrilling",
+ "\u00cf\u0122\u00ce\u00bf\u00ce\u00b9",
+ "\u0120piggy",
+ "\u0120anunci",
+ "ORTER",
+ "\u0120Value",
+ "\u0120rond",
+ "\u0120ADA",
+ "\u0120poser",
+ "hores",
+ "\u0120Roland",
+ "\u0135\u00af",
+ "\u0120noir",
+ "\u0120\u00d7\u00a9\u00d7\u0132\u00d7",
+ "\u00eb\u00b0\u013e",
+ "iemand",
+ "\u0120\u00d0\u00bf\u00d0\u00be\u00d1\u0124\u00d0\u00b5\u00d1\u0122",
+ "\u00ea\u00b3\u00b3",
+ "\u0120\u00ea\u00b1\u00b1",
+ "\u0120formatting",
+ "\u0120Led",
+ "\u00e8\u00a7\u0122\u00e7\u013e\u00be",
+ "\u0120killers",
+ "\u0120\u00c4\u0133\u00e1\u00ba\u00a5y",
+ "\u0120haar",
+ "again",
+ "!>[",
+ "minster",
+ "\u0120\u00d0\u00b2\u00d0\u00bb\u00d0\u00b8",
+ "\u0120identifier",
+ "\u0120Lambda",
+ "\u0120tros",
+ "\u0120flawless",
+ "\u0120detrimental",
+ "\u0120bunlar\u00c4\u00b1",
+ "War",
+ "\u0120regi\u00c3\u00a3o",
+ "\u00e7\u013e\u0141\u00e7\u013c\u0126\u00e6\u013a\u00af",
+ "\u0120Bike",
+ "cessors",
+ "\u0120c\u00c3\u00b9ng",
+ "\u0120RN",
+ "\u0120\u00ea\u00bd\u0125",
+ "\u0120k\u00c3\u00bc\u00c3\u00a7\u00c3\u00bck",
+ "\u0120Beginning",
+ "\u00ed\u013a\u00b8\u00eb",
+ "\u0120gewe",
+ "\u0120denote",
+ "\u0120Alberto",
+ "\u0120probiot",
+ "\u0120ode",
+ "\u0120molar",
+ "\u0120bursting",
+ "assumed",
+ "\u0120footprints",
+ "veda",
+ "\u0120steroids",
+ "\u0120flaming",
+ "\u0120Eller",
+ "\u0120erkennen",
+ "\u00c3\u00a4tzen",
+ "\u0120lifecycle",
+ "\u0120DOU",
+ "\u0120Karena",
+ "\u0120Guerra",
+ "\u00e8\u00bf\u013a\u00e6\u013a\u00af",
+ "\u0120sinister",
+ "\u0120pod\u00c3\u00a9is",
+ "\u0120parab",
+ "\u0120oko",
+ "\u0120mat\u00c3\u00a9ri",
+ "\u0120caric",
+ "sonaro",
+ "\u0120praticamente",
+ "\u00d1\u0125\u00d1\u0123\u00d0\u00b0",
+ "\u0120comunque",
+ "\u0120vigilant",
+ "\u0120regimes",
+ "\u0120Shooting",
+ "\u0120raids",
+ "\u0120Nora",
+ "\u0120Wieder",
+ "mens",
+ "\u0120\u00d1\u0123\u00d0\u00be\u00d0\u00b4",
+ "\u0120\u00ea\u00b2\u00bd\u00ec\u013c\u00b0\u00ec\u0139\u0132\u00eb\u012c\u0136",
+ "\u0120\u00d0\u00b2\u00d1\u0127\u00d0\u00be\u00d0\u00b4",
+ "\u0120autobi",
+ "\u0120Schn",
+ "\u0120Robbie",
+ "\u0120Fitness",
+ "\u0120\u00d0\u00ba\u00d0\u00be\u00d0\u00bd\u00d1\u0126",
+ "\u0120penguin",
+ "\u00d0\u00bc\u00d0\u00be\u00d1\u0124\u00d1\u0122\u00d1\u0131",
+ "\u0120\u00d0\u00bc\u00d0\u00b8\u00d0\u00bd\u00d0\u00b8\u00d0\u00bc",
+ "plays",
+ "\u0120delegates",
+ "Mer",
+ "\u0120sistem",
+ "\u0120Michaels",
+ "male",
+ "\u00d8\u00a7\u00d8\u00b9",
+ "\u0120c\u00c3\u00a1ch",
+ "\u0120H\u00c3\u00a4",
+ "\u0120\u00d7\u013b\u00d7\u0137\u00d7\u0135\u00d7\u00a2",
+ "\u0120superpower",
+ "\u0120stron",
+ "\u0120rover",
+ "\u0120d\u00c3\u00a9pend",
+ "\u00e9\u013b\u00b3",
+ "\u0120retiring",
+ "\u0120vampires",
+ "\u0120merde",
+ "\u0120Changing",
+ "\u0120tame",
+ "\u0120spokesperson",
+ "\u0120cay",
+ "\u0120flirting",
+ "\u0120Gr\u00c3\u00b6",
+ "\u0120w\u00c3\u00a4r",
+ "\u0120wyb",
+ "\u0120coeur",
+ "\u00e1\u00ba\u00a1nh",
+ "\u0120\u00ec\u013b\u0122\u00ec\u0126\u013e",
+ "\u0120connais",
+ "\u0120Hundreds",
+ "\u0120Bea",
+ "\u0120\u00ce\u00b1\u00cf\u0122",
+ "pruch",
+ "\u0120sociedade",
+ "\u0120Whilst",
+ "\u0120Kait",
+ "espace",
+ "\u0120chia",
+ "\u0120Erm",
+ "\u0120\u00eb\u00b0\u0136\u00ea\u00bf",
+ "\u0120fences",
+ "\u0120Mortal",
+ "\u00ea\u00b2\u0123",
+ "\u0120\u00d0\u00b3\u00d1\u0122\u00d0\u00b0\u00d1\u0126",
+ "\u0120Homeland",
+ "\u0120JUN",
+ "isst",
+ "\u0120parlar",
+ "\u0120sporty",
+ "\u00c3\u00a9o",
+ "\u0120deepen",
+ "\u0120Behavior",
+ "\u00e9\u0122\u0131",
+ "\u00e5\u0135\u012a\u00e5\u0135\u012a\u00e5\u0135\u012a",
+ "\u0120errand",
+ "\u0120rotary",
+ "\u0120Wellington",
+ "Wind",
+ "\u0120mesela",
+ "\u00e1\u00ba\u00a3ng",
+ "iende",
+ "\u0120excell",
+ "\u0120Genius",
+ "\u0120Eduardo",
+ "\u00e6\u013e\u012b\u00e4\u00ba\u00ba",
+ "\u0120\u00c5\u0141unu",
+ "\u0120\u00c4\u00b0stanbul",
+ "\u0120produto",
+ "\u0120\u00e3\u0127\u0130\u00e3\u0127\u0130",
+ "OFF",
+ "\u0120wollt",
+ "\u00e7\u012a\u0128",
+ "\u0120\u00eb\u012b\u00b4\u00ec\u012c\u00a4",
+ "\u0120lass",
+ "\u0120hertz",
+ "\u0120aromatic",
+ "\u0120\u00d0\u00b7\u00d0\u00b2\u00d0\u00be\u00d0\u00bd",
+ "\u0120autoc",
+ "\u0120Lust",
+ "\u0120112",
+ "\u0120\u00ce\u0139",
+ "\u0120reviewers",
+ "\u0120receptive",
+ "\u00e5\u00b0\u012f\u00e4\u00ba\u0128",
+ "\u00c3\u00a2nd",
+ "oglo",
+ "\u0120\u00ec\u0137\u0126\u00eb\u012d\u013b",
+ "\u0120ngo",
+ "\u00d1\u0138\u00d1\u0124\u00d0\u00b8",
+ "\u00c3\u00a5t",
+ "cono",
+ "\u0120tekrar",
+ "\u0120\u00ec\u00a3\u00bc\u00ea\u00b3\u0142",
+ "\u0120gelmi\u00c5\u0141",
+ "\u0120bedtime",
+ "\u0120Argh",
+ "ADA",
+ "\u0120\u00d0\u00b3\u00d0\u00be\u00d1\u0122\u00d0\u00be\u00d0\u00b4\u00d0\u00b0",
+ "\u0120\u00c4\u0129",
+ "\u0120alliances",
+ "giggling",
+ "\u0120yerde",
+ "\u0120spies",
+ "\u0120gutes",
+ "\u00c3\u00a7i",
+ "\u0120alltid",
+ "\u0120Lah",
+ "\u0140\u0132\u00eb",
+ "\u0120dok\u00c5\u0124ad",
+ "\u00d9\u012a\u00d9\u012c",
+ "\u0120toxicity",
+ "\u0120cancellation",
+ "\u01201958",
+ "dro",
+ "\u0120\u00ec\u0140\u0133\u00ec\u013f\u0122",
+ "\u0120Motorola",
+ "\u0120multin",
+ "\u0120enthusiasts",
+ "\u0120Mighty",
+ "\u0120Coconut",
+ ":\u00e3\u0122\u012e",
+ "\u0120Pictures",
+ "\u0120sangre",
+ "\u0120blinking",
+ "olesome",
+ "\u0120\u00ec\u012c\u00a4\u00ed\u0125\u0122\u00ec\u013f\u00bc",
+ "FP",
+ "\u0120booming",
+ "\u0120\u00d0\u00b4\u00d0\u00b5\u00d1\u0123\u00d1\u0131\u00d1\u0124",
+ "\u0120ratchet",
+ "\u0120timelines",
+ "leness",
+ "\u0120cages",
+ "\u0120Goodnight",
+ "ometimes",
+ "\u0120cunning",
+ "\u0120Risk",
+ "uled",
+ "dade",
+ "\u0120prata",
+ "\u0120gustar\u00c3\u0143a",
+ "amus",
+ "\u0120Jinping",
+ "\u0120estrut",
+ "\u0120descobrir",
+ "\u0120M\u00c4\u0123",
+ "\u0120Allan",
+ "\u0120\u00e5\u012a\u0128",
+ "\u0120\u00d7\u013e\u00d7\u00a7",
+ "\u0120preserv",
+ "\u0120Strawberry",
+ "\u00c4\u0131",
+ "Lu",
+ "\u0120kro",
+ "\u0120Reports",
+ "\u00ec\u0127\u0136\u00ec\u0137\u00bc",
+ "\u0120valt",
+ "\u0120pouvait",
+ "\u0120appar",
+ "\u0120Bone",
+ "\u0120preferably",
+ "\u0120Rep\u00c3\u00bablica",
+ "\u00e5\u00b0\u00b1\u00e5\u012a\u00b0",
+ "\u0120herzlich",
+ "\u0120chimney",
+ "\u0120\u00c3\u00a7ev",
+ "\u0120visas",
+ "\u0120verr",
+ "\u0120cultivation",
+ "\u0120Armenia",
+ "\u0120\u00d0\u00b2\u00d0\u00b4\u00d1\u0122\u00d1\u0125\u00d0\u00b3",
+ "\u0120cockro",
+ "retched",
+ "artz",
+ "\u0120\u00d0\u00bb\u00d1\u0130\u00d0\u00b4\u00d1\u0131\u00d0\u00bc",
+ "\u0120pol\u00c3\u0143ticas",
+ "\u0120Panz",
+ "\u0120AKA",
+ "\u0120\u00eb\u012a\u012e\u00eb\u0141\u00ac",
+ "\u0120erro",
+ "\u0120camper",
+ "\u0120102",
+ "\u00e0\u00a4\u00b8",
+ "done",
+ "\u0120hoard",
+ "\u0120\u00d0\u0141\u00d0\u00be\u00d1\u0124\u00d0\u00be\u00d0\u00bc",
+ "jeong",
+ "\u0120desta",
+ "pak",
+ "\u0120inim",
+ "\u0120growers",
+ "\u0120Message",
+ "\u0120elector",
+ "engage",
+ "\u0120Forbes",
+ "\u0120Cincinnati",
+ "\u0120diff\u00c3\u00a9rence",
+ "df",
+ "\u0120spar",
+ "\u0120awaits",
+ "\u0120USSR",
+ "\u0120Rising",
+ "\u0120Ho\u00c5\u0141",
+ "\u0120footing",
+ "\u0120condiciones",
+ "\u00d1\u0124\u00d0\u00be\u00d1\u0122\u00d0\u00be\u00d0\u00b2",
+ "\u0120clinician",
+ "\u0120Diskuss",
+ "\u00e5\u00a3\u0135",
+ "\u00d7\u00a8\u00d7\u0134",
+ "\u00d7\u00a5",
+ "iteit",
+ "gren",
+ "\u0120charisma",
+ "\u0120leuke",
+ "\u0120irritating",
+ "\u0120circa",
+ "\u0120Rhodes",
+ "\u0120pior",
+ "\u0120handicap",
+ "royable",
+ "\u0120vull",
+ "OG",
+ "\u0120in\u00c3\u0143cio",
+ "ieri",
+ "\u0120splashing",
+ "\u0120demise",
+ "\u0120assistir",
+ "\u00d1\u0129\u00d1\u0124\u00d0\u00be",
+ "\u0120covert",
+ "\u0120Gud",
+ "\u00e0\u00b8\u012b",
+ "kl\u00c3\u00a4r",
+ "\u0120\u00ec\u0140\u0132\u00ea\u00be\u00b8",
+ "\u0120ver\u00c3\u00a4ndert",
+ "\u0120REM",
+ "\u0120Conven",
+ "atge",
+ "\u0120pierwsze",
+ "\u0120clergy",
+ "lington",
+ "liv",
+ "VPN",
+ "\u0120\u00d1\u0123\u00d0\u00be\u00d0\u00b6\u00d0\u00b0\u00d0\u00bb",
+ "\u0120Hate",
+ "\u00e3\u0123\u00a8\u00e3\u0123\u0135\u00e3\u0124\u012f",
+ "\u00cf\u0128\u00ce\u00bf",
+ "\u0120Respons",
+ "\u00d0\u00be\u00d0\u00b7\u00d0\u00b4",
+ "\u0120etmek",
+ "\u0120chemin",
+ "\u00d9\u0127\u00d8\u00a9",
+ "\u0120\u00ea\u00b0\u0122\u00ec\u00a1\u00b1",
+ "Tre",
+ "\u0120umas",
+ "\u0120Burton",
+ "\u0120patriarch",
+ "\u0120Smithsonian",
+ "\u00a5\u013a",
+ "Moon",
+ "Air",
+ "\u0120medios",
+ "\u0120eraser",
+ "\u0120wollten",
+ "\u0120pareil",
+ "\u0120Billie",
+ "\u00e6\u012c\u00bd",
+ "\u00d0\u00b5\u00d1\u0122\u00d1\u0124\u00d0\u00b2",
+ "\u0120parlament",
+ "\u0120agony",
+ "\u0120QUE",
+ "sequently",
+ "Another",
+ "\u0120Whew",
+ "\u0120Annual",
+ "\u0120seben",
+ "\u00ec\u0125\u0123\u00ec\u013f\u0126",
+ "values",
+ "\u0140\u013e\u00eb\u00a7\u012e",
+ "\u0120sinon",
+ "ereal",
+ "\u0120Enlight",
+ "\u0120Chemistry",
+ "\u0120Catalunya",
+ "\u0120doctr",
+ "anton",
+ "\u0120stuk",
+ "\u0120Plate",
+ "\u0120Kardashian",
+ "\u0120filos",
+ "\u0120Wet",
+ "\u0120\u00d0\u00bf\u00d0\u00be\u00d0\u00bf\u00d1\u012d\u00d1\u0124",
+ "\u0120unknowns",
+ "\u0120Schon",
+ "\u0120Baldwin",
+ "\u0120telescopes",
+ "\u0120Gucci",
+ "oxide",
+ "\u0120Conservative",
+ "\u00ec\u0126\u00b1\u00ec\u013f\u0126",
+ "\u0120hinaus",
+ "Power",
+ "\u0120\u00ea\u00b1\u00b4\u00ea\u00b0\u0137",
+ "\u0120prevail",
+ "orman",
+ "machine",
+ "\u01201946",
+ "\u0120unbel",
+ "\u0120schaut",
+ "\u0120piel",
+ "eenth",
+ "\u0120objectively",
+ "\u0120chakra",
+ "audio",
+ "\u0120chicos",
+ "\u0120Vault",
+ "\u00e5\u00b0\u012a",
+ "\u0120medicinal",
+ "\u0120Tail",
+ "While",
+ "\u0120asphalt",
+ "\u0120froze",
+ "\u0120EK",
+ "unching",
+ "nosis",
+ "2015",
+ "\u0120Gri",
+ "\u0120oddly",
+ "\u0120M\u00c3\u00a4r",
+ "\u0120Aeg",
+ "colo",
+ "Par",
+ "\u0120\u00eb\u0135\u00a4\u00ec\u0138\u00b4\u00eb",
+ "\u0120vinden",
+ "\u0120OVER",
+ "\u0120iced",
+ "\u0120scorp",
+ "\u0120hac",
+ "qualified",
+ "\u0120\u00d1\u0125\u00d0\u00b2\u00d0\u00b8\u00d0\u00b4\u00d0\u00b5\u00d1\u0124\u00d1\u012e",
+ "ermo",
+ "HEN",
+ "\u0120soi",
+ "\u0120multiples",
+ "\u0120layouts",
+ "\u0120blindness",
+ "\u0120Bowser",
+ "\u0120\u00d0\u00bf\u00d0\u00be\u00d0\u00b4\u00d1\u0124",
+ "\u0120\u00c3\u0130",
+ "ventional",
+ "\u0120mata",
+ "mad\u00c4\u00b1",
+ "\u0120geez",
+ "\u0120cadence",
+ "\u0120wa\u00c5\u00bcne",
+ "\u0120Christie",
+ "venge",
+ "Call",
+ "\u0120turnaround",
+ "\u0120blob",
+ "\u0120\u00d0\u00af\u00d0\u00ba",
+ "\u0120Voiceover",
+ "\u0120peril",
+ "\u0120Jaime",
+ "\u0120HOY",
+ "lane",
+ "\u0120sebel",
+ "\u0120Duo",
+ "\u0120Historical",
+ "\u0120dni",
+ "\u0120gema",
+ "yk",
+ "\u0120sabem",
+ "\u00e1\u00ba\u00afng",
+ "\u0120vars",
+ "\u0120Ronnie",
+ "\u0120Ronaldo",
+ "\u0120Perqu\u00c3\u00a8",
+ "nsinn",
+ "hair",
+ "\u0120relentless",
+ "\u0120lyn",
+ "\u0120traveler",
+ "\u00e6\u0122\u0130\u00e9\u00ba\u00bc\u00e4\u00ba\u0128",
+ "nine",
+ "\u0120antim",
+ "\u0120\u00ec\u00bc\u0122",
+ "\u0120snowball",
+ "\u0120\u00d1\u0127\u00d0\u00b0\u00d1\u0122\u00d0\u00b0\u00d0\u00ba\u00d1\u0124\u00d0\u00b5\u00d1\u0122",
+ "\u0120interns",
+ "\u0120constituency",
+ "\u0120\u00d0\u013f\u00d0\u00b0\u00d0\u00bc",
+ "\u00d7\u013e\u00d7\u013e",
+ "VEL",
+ "\u0120viktigt",
+ "\u0120apoyo",
+ "\u00d9\u0126\u00d8\u00a8",
+ "\u0120jard",
+ "\u0120heightened",
+ "\u00d1\u0122\u00d0\u00be\u00d1\u0123\u00d1\u0124",
+ "\u0120SMITH",
+ "\u0120\u00d0\u00b4\u00d0\u00b5\u00d0\u00bb\u00d0\u00b0",
+ "\u0120repairing",
+ "\u0120rigt",
+ "\u0120Sheikh",
+ "\u0120Britney",
+ "\u0120everytime",
+ "\u0120adventurous",
+ "ockey",
+ "ernt",
+ "\u0120ataque",
+ "\u0120Alternatively",
+ "effect",
+ "\u0120palavras",
+ "\u0120Elliott",
+ "\u0120r\u00c3\u00a9ussi",
+ "\u0120hypertension",
+ "\u0120Manual",
+ "\u0120prophetic",
+ "\u0120handc",
+ "\u00d1\u012e\u00d0\u00b5",
+ "\u0120refrain",
+ "\u0120Squid",
+ "\u00ec\u0140\u00a1",
+ "\u0120\u00d0\u00ba\u00d0\u00be\u00d0\u00bc\u00d0\u00b0\u00d0\u00bd",
+ "\u00c3\u00a4llen",
+ "\u0120lleg\u00c3\u00b3",
+ "\u0120bash",
+ "iony",
+ "\u0120\u00d1\u0123\u00d0\u00ba\u00d0\u00bb\u00d0\u00b0\u00d0\u00b4",
+ "\u0120\u00d0\u00ba\u00d0\u00b0\u00d0\u00b1",
+ "\u0120careless",
+ "\u0120Pool",
+ "\u0120tr\u00c3\u00a1s",
+ "\u0120fils",
+ "\u0120Schr",
+ "\u0120sprawd",
+ "\u0120Monaten",
+ "\u0120unforgettable",
+ "\u0120Cotton",
+ "\u0120inconvenient",
+ "\u0120RX",
+ "oris",
+ "\u0120humbled",
+ "\u00d7\u00aa\u00d7\u0139",
+ "\u0120\u00d8\u00a2\u00d9\u00be",
+ "\u0120incre\u00c3\u0143",
+ "\u0120Kommentare",
+ "\u00e8\u012a\u0134",
+ "raci\u00c3\u00b3n",
+ "\u0120vantage",
+ "\u0120Seal",
+ "\u0120\u00ec\u013f\u00b4\u00ea\u00b1\u00b0\u00eb\u00a5\u00bc",
+ "\u0120joue",
+ "\u00e3\u0123\u013f\u00e3\u0123\u0128\u00e3\u0123\u00a7\u00e3\u0123\u013b\u00e3\u0123\u0143",
+ "\u0120\u00ec\u013a\u00a4\u00eb\u0140\u013a",
+ "\u0120\u00d0\u00b8\u00d1\u0123\u00d0\u00bf\u00d1\u012d\u00d1\u0124",
+ "oben",
+ "\u0120grate",
+ "\u0120controle",
+ "\u0120Percy",
+ "\u00c5\u0124ada",
+ "\u0120simultaneous",
+ "\u0120prototy",
+ "\u0120gro\u00c3\u0141er",
+ "\u0120bewusst",
+ "inizi",
+ "\u0120passieren",
+ "\u0120Happiness",
+ "\u00e5\u012b\u0129",
+ "shi",
+ "geht",
+ "\u0120stationed",
+ "\u0120Ergebnis",
+ "\u0120directamente",
+ "\u0120survives",
+ "\u0120persones",
+ "BERG",
+ "\u0120vomiting",
+ "\u0120conhecer",
+ "\u0120adjour",
+ "\u0120Civic",
+ "pei",
+ "burst",
+ "\u0120\u00eb\u012d\u00a4\u00eb\u012d\u012a",
+ "\u00e9\u0131",
+ "\u0120sled",
+ "\u0120plataforma",
+ "\u0120Sect",
+ "\u0120Defin",
+ "\u00e7\u013b\u00bb\u00e9\u012e\u00b2",
+ "\u00c3\u00a9nom",
+ "chnet",
+ "\u0120profitability",
+ "\u0120erreicht",
+ "\u00e1\u00bb\u0131i",
+ "cation",
+ "\u0120\u00ec\u00a7\u0122\u00ea\u00b8",
+ "\u0120perdre",
+ "\u0120felony",
+ "\u01201957",
+ "\u00e6\u012a\u0133\u00e5\u00be\u012a",
+ "\u0120unsuccessful",
+ "\u0120nagyon",
+ "\u0120elasticity",
+ "\u0120facade",
+ "\u0120earthly",
+ "\u0120\u00d0\u00b0\u00d0\u00bc\u00d0\u00b5\u00d1\u0122\u00d0\u00b8\u00d0\u00ba\u00d0\u00b0\u00d0\u00bd",
+ "\u0120conn",
+ "cla",
+ "Du",
+ "\u0120politiques",
+ "\u0120halo",
+ "iantes",
+ "\u0120\u00d0\u00bc\u00d0\u00be\u00d0\u00b5\u00d0\u00b9",
+ "\u00e3\u0125\u00b3\u00e3\u0125\u012b",
+ "tones",
+ "elier",
+ "\u00e8\u00ae\u013c",
+ "htaking",
+ "\u0120wichtige",
+ "\u0120anno",
+ "\u0120Lok",
+ "illions",
+ "\u0120viver",
+ "\u0120solchen",
+ "\u0120suf",
+ "\u0120Salz",
+ "\u0120Nvidia",
+ "zuge",
+ "\u0120Spike",
+ "Video",
+ "\u0120twor",
+ "\u0120Ala",
+ "\u00e8\u0133\u012b",
+ "\u0120hanya",
+ "\u0120Adm",
+ "\u00ec\u013f\u00b5",
+ "\u0120Patienten",
+ "\u0120Onion",
+ "\u0120Kobe",
+ "\u0120Scene",
+ "\u0120Rash",
+ "\u00e6\u00a8\u013b",
+ "\u00d1\u0122\u00d0\u00b0\u00d1\u0123\u00d1\u0124",
+ "istani",
+ "General",
+ "leye",
+ "imbap",
+ "\u0120concealed",
+ "\u0120Fridays",
+ "\u0120Wool",
+ "\u0120\u00d0\u00bd\u00d0\u00be\u00d0\u00b2\u00d1\u012d\u00d1\u0127",
+ "\u00d8\u00b4\u00d8\u00b1",
+ "\u0120\u00ea\u00b2\u00b0\u00ea\u00b3\u00bc",
+ "\u0120jedoch",
+ "\u00b4\u00ec\u012d\u013e",
+ "\u0135\u00a4\u00eb\u0131\u0126",
+ "\u0120\u00ec\u0140\u00a5\u00eb\u0124\u013e",
+ "ukt",
+ "Lou",
+ "\u0120\u00eb\u00a8\u00b9\u00ec\u0138\u00b4",
+ "\u0120Expect",
+ "\u0120\u00d0\u00b4\u00d0\u00be\u00d0\u00bc\u00d0\u00be\u00d0\u00b9",
+ "\u0120irresponsible",
+ "\u0120acerca",
+ "\u0120Zust",
+ "\u00d7\u00a8\u00d7\u013a",
+ "UI",
+ "\u0120youtubers",
+ "\u0120Positive",
+ "\u0120socioe",
+ "\u0120snatch",
+ "\u00e8\u0125\u012e",
+ "\u0120refreshed",
+ "\u0120nominations",
+ "\u0120Patt",
+ "\u0120obsolete",
+ "\u0120demi\u00c5\u0141",
+ "\u00e5\u0131\u00a4",
+ "ormu\u00c5\u0141",
+ "\u0120\u00ec\u0128\u0136\u00ec\u00a7\u0123\u00ed\u0140\u012a",
+ "\u0120fla",
+ "\u0120craziest",
+ "\u0120Zie",
+ "\u0120T\u00c3\u00ba",
+ "zep",
+ "icem",
+ "\u0120\u00eb\u00a9\u012d\u00ec\u0140\u012a",
+ "\u0120cynical",
+ "\u00e3\u0123\u013f\u00e3\u0124\u0135\u00e3\u0123\u00aa",
+ "\u0120tresp",
+ "\u0120craz",
+ "\u00d5\u00a5\u00d5",
+ "\u0120nelle",
+ "\u0120mph",
+ "\u0120Nered",
+ "\u0120Kob",
+ "\u0120Eck",
+ "\u00a8\u00b8\u00eb\u012d\u012a",
+ "Jan",
+ "\u0120\u00d0\u00a2\u00d0\u00be\u00d0\u00b3\u00d0\u00b4\u00d0\u00b0",
+ "\u0120deci",
+ "\u0120Vog",
+ "\u0120bubbling",
+ "\u00e9\u0122\u0122",
+ "\u00c3\u00baa",
+ "\u0120productos",
+ "iberal",
+ "\u0120replicated",
+ "\u0120Improve",
+ "illary",
+ "Cha",
+ "\u0120r\u00c3\u00a9du",
+ "\u0125\u0132\u00ed\u0137\u013a\u00eb\u00a9\u00b4",
+ "\u0120connot",
+ "\u0120Krit",
+ "\u0120\u00d0\u00b4\u00d1\u0125\u00d1\u0127\u00d0\u00be\u00d0\u00b2",
+ "\u0120treadmill",
+ "\u0120PW",
+ "\u0120\u00d0\u00b7\u00d0\u00be\u00d0\u00b2\u00d1\u0125\u00d1\u0124",
+ "\u0120clams",
+ "\u0120drafting",
+ "\u01201956",
+ "unta",
+ "\u0120expenditures",
+ "\u0120Hoover",
+ "WOO",
+ "\u00d1\u012a\u00d0\u00b5\u00d0\u00b5",
+ "\u0120deduction",
+ "monary",
+ "\u0120recib",
+ "\u0120povo",
+ "\u0120\u00eb\u012f\u0136\u00eb",
+ "\u0120PAL",
+ "\u0120Blow",
+ "\u0120wyp",
+ "\u0120destac",
+ "deal",
+ "Graeme",
+ "\u0120n\u00c3\u00a9cessaire",
+ "\u0120damned",
+ "\u01201938",
+ "\u0120\u00ec\u012d\u00a4\u00ec\u0142\u013e\u00eb\u00a1\u013e",
+ "\u0120troop",
+ "\u0120insightful",
+ "\u0120TJ",
+ "\u0120\u00d0\u00be\u00d1\u0123\u00d0\u00b2",
+ "\u0120fidelity",
+ "\u0120Skip",
+ "\u0120Mayo",
+ "\u00eb\u00a7\u013f",
+ "appe",
+ "\u0120blas",
+ "\u0120WY",
+ "\u0120GN",
+ "ctar",
+ "Su",
+ "\u0120cuent",
+ "hews",
+ "\u0120corpses",
+ "Abs",
+ "\u0120wastewater",
+ "\u0120ciek",
+ "\u0120Onu",
+ "\u0120explosives",
+ "\u0120arma",
+ "\u0120STEPHAN",
+ "politik",
+ "\u0120Osaka",
+ "ta\u00c5\u0124",
+ "\u0120yap\u00c4\u00b1yor",
+ "\u0120izquier",
+ "\u0120beleza",
+ "\u0120Wyatt",
+ "\u00e5\u0132\u00b8",
+ "\u0120suk",
+ "\u0120specjal",
+ "\u0120danke",
+ "whistle",
+ "\u0120f\u00c3\u0143sica",
+ "\u0120Harriet",
+ "\u0120\u00ec\u0137\u0126\u00ed\u012e\u012e",
+ "\u0120willkommen",
+ "iping",
+ "\u0120\u00d1\u0123\u00d0\u00bc\u00d0\u00be\u00d1\u0124\u00d1\u0122\u00d0\u00b8\u00d1\u0124\u00d0\u00b5",
+ "\u0120\u00d0\u00bc\u00d0\u00be\u00d0\u00b6\u00d0\u00b5\u00d1\u012a\u00d1\u012e",
+ "\u0120inaccurate",
+ "\u0120arrogance",
+ "\u0120Remo",
+ "\u00ce\u00b3\u00ce\u00ac",
+ "assed",
+ "\u0120deliveries",
+ "\u0120stinky",
+ "\u0120\u00d0\u00bf\u00d0\u00b5\u00d1\u0122\u00d0\u00b5\u00d0\u00b6",
+ "jay",
+ "\u0120transitional",
+ "\u0120rere",
+ "\u0120NGOs",
+ "\u0120ATM",
+ "\u00d8\u00ae\u00d8\u00aa",
+ "iology",
+ "\u0120\u00d0\u00b2\u00d0\u00bb\u00d0\u00b0\u00d0\u00b4",
+ "\u0120schme",
+ "\u0120Shine",
+ "\u00ec\u0137\u00a1",
+ "pants",
+ "\u0120serge",
+ "\u0120senhor",
+ "\u0120abduct",
+ "\u0120Bryant",
+ "VES",
+ "\u0120awakened",
+ "\u0120Laz",
+ "ropolis",
+ "\u0120Lao",
+ "\u00e8\u00be\u013d\u00e8\u012d\u00a6",
+ "\u0120villa",
+ "\u0120summers",
+ "\u0120enthal",
+ "\u01201949",
+ "Via",
+ "\u0120\u00ec\u0138\u00b4\u00ec\u00a8",
+ "\u0120tendon",
+ "\u0120violet",
+ "\u0120intellectually",
+ "\u0120bounced",
+ "araus",
+ "\u01201919",
+ "\u0120vraag",
+ "\u0120spel",
+ "\u0120Schwar",
+ "Scott",
+ "\u0120Indo",
+ "\u0120\u00eb\u00a7\u013f",
+ "\u0120canonical",
+ "\u0120IKE",
+ "\u0120that\u00c3\u0143s",
+ "\u0120mellan",
+ "\u00e6\u00af\u0134",
+ "igmat",
+ "Could",
+ "...?)",
+ "\u0120foarte",
+ "\u0120Kumar",
+ "rendo",
+ "\u0120\u00c3\u00a9l\u00c3\u00a9",
+ "\u00e0\u00b4",
+ "valuation",
+ "cases",
+ "\u0120intuitively",
+ "hong",
+ "etted",
+ "\u0120souven",
+ "\u0120morb",
+ "\u0120cors",
+ "\u0120NV",
+ "\u0120Hasan",
+ "\u00e6\u0125\u0127\u00e5\u0128\u00b5",
+ "ieved",
+ "\u0120\u00ec\u00a7\u0122\u00ea\u00b8\u012a\u00ec\u013f\u0122",
+ "\u0120dumpling",
+ "\u0120contr\u00c3\u00b4le",
+ "\u0120ambiguity",
+ "\u00e6\u00a9\u0141\u00e6\u013e\u0125",
+ "\u0120cog",
+ "\u0120Scriptures",
+ "\u0120cai",
+ "\u0120bever",
+ "\u00e5\u00a4\u00a7\u00e5\u00ae\u00b6\u00e9\u0125\u00bd",
+ "\u0120huis",
+ "\u0120aime",
+ "\u0120erkl\u00c3\u00a4ren",
+ "\u0120LM",
+ "\u0120Fey",
+ "\u00e9\u013c\u00be",
+ "\u00e0\u00ae\u00b1\u00e0\u00ae\u00a4",
+ "\u0120supervised",
+ "\u0120jewe",
+ "spl",
+ "\u0120\u00d1\u0128\u00d0\u00b5\u00d0\u00bd\u00d1\u0124\u00d1\u0122",
+ "\u0120collisions",
+ "\u00d9\u0126\u00d9\u0123",
+ "\u0120Hogwarts",
+ "\u0120Durham",
+ "\u00d7\u0137\u00d7\u00a3",
+ "\u0120phosphate",
+ "\u0120oversee",
+ "\u0120inspections",
+ "\u0120brinc",
+ "\u0120Zak",
+ "\u0120payoff",
+ "\u0120chaud",
+ "\u0120Hunger",
+ "\u00c3\u00a3os",
+ "vir",
+ "\u0120fiance",
+ "\u0120boug",
+ "lived",
+ "cry",
+ "\u00e5\u013d\u0140\u00e4\u00be\u0128",
+ "\u0120jointly",
+ "\u0120girlfriends",
+ "\u0120Nexus",
+ "\u00a6\u00ac\u00ea\u00b2\u0142\u00ec\u012c\u00b5\u00eb\u012d\u012a\u00eb\u012d\u00a4",
+ "\u0120Kwang",
+ "\u00e5\u0135\u012a\u00e5\u013d\u012b",
+ "\u00e5\u00a7\u0133",
+ "\u00c5\u0124\u00c4\u013b",
+ "\u0120Neden",
+ "iece",
+ "\u0120inserting",
+ "\u00e6\u0141\u0135",
+ "\u0120Mummy",
+ "\u0120Globe",
+ "\u0120lee",
+ "\u0120german",
+ "\u0120creams",
+ "acho",
+ "\u0120ch\u00c6\u00b0a",
+ "\u0120Galile",
+ "\u0120f\u00c3\u00bcrs",
+ "\u0120estiver",
+ "cidos",
+ "Christian",
+ "\u0120lorsqu",
+ "\u0120cutest",
+ "vale",
+ "\u0120\u00d0\u00ba\u00d1\u0122\u00d0\u00b5\u00d0\u00bf",
+ "\u0120wary",
+ "\u0120slicing",
+ "\u0120esperando",
+ "\u0120Vander",
+ "\u0120Deixa",
+ "\u01201954",
+ "\u0120m\u00c3\u00b3wi\u00c4\u0127",
+ "\u00d1\u0138\u00d1\u0136",
+ "\u0120tooling",
+ "\u0120restor",
+ "\u0120posici\u00c3\u00b3n",
+ "\u0120intentar",
+ "\u0120Apache",
+ "OUL",
+ "\u0120\u00d9\u012a\u00d8\u00a8",
+ "\u0120mati\u00c3\u00a8re",
+ "\u00e3\u0125\u00bc\u00e3\u0124\u0135",
+ "\u0120linen",
+ "\u0120estrat\u00c3\u00a9g",
+ "\u0120Mutta",
+ "\u00e9\u00a1\u00af",
+ "\u00e8\u00a1\u012e\u00e4\u00ba\u0128",
+ "\u0120parting",
+ "\u0120minimizing",
+ "\u0120apprendre",
+ "\u00e6\u013e\u013f",
+ "\u0120\u00d0\u00b0\u00d0\u00bd\u00d0\u00b3\u00d0\u00bb\u00d0\u00b8\u00d0\u00b9",
+ "\u0120Doo",
+ "\u0120Firefox",
+ "c\u00c3\u00b3mo",
+ "\u0120geopolit",
+ "\u0120makan",
+ "\u0120mogelijk",
+ "\u0120\u00cf\u0122\u00ce\u00b5\u00cf\u0123\u00ce\u00b9",
+ "\u0120c\u00e1\u00bb\u00a9",
+ "\u0120installer",
+ "\u0120dibuj",
+ "\u0120Heath",
+ "loop",
+ "\u0120Broken",
+ "HYUN",
+ "shelf",
+ "\u0120fizer",
+ "\u0120enhances",
+ "\u00e4\u00be\u012d\u00e3\u0123\u012a\u00e3\u0123\u00b0",
+ "\u0120\u00d0\u00b4\u00d0\u00be\u00d1\u0123\u00d1\u0124\u00d0\u00b8",
+ "\u0120PUB",
+ "\u0120Kollegin",
+ "\u0120attained",
+ "\u00c4\u00be",
+ "\u0120mistress",
+ "\u0120Oftentimes",
+ "\u00d7\u0140\u00d7\u013b\u00d7\u013f",
+ "\u0120bewe",
+ "\u0120Sora",
+ "rauen",
+ "baum",
+ "\u0120rollers",
+ "\u0120mering",
+ "\u0120PAC",
+ "\u0120\u00d0\u00bd\u00d1\u0138",
+ "\u0120R\u00c3\u00a9publique",
+ "\u0120\u00d1\u0124\u00d1\u0122\u00d0\u00b0\u00d0\u00b2",
+ "\u0120Vanguard",
+ "uciones",
+ "\u0120\u00eb\u00ac\u00b4\u00eb\u012e\u0122",
+ "\u0120gour",
+ "\u00af\u00a4",
+ "\u0120\u00cf\u012b",
+ "\u0120sauna",
+ "\u0120peine",
+ "\u0120Valerie",
+ "\u0120Sikh",
+ "fendimiz",
+ "bero",
+ "\u0120\u00d1\u0129\u00d0\u00b8",
+ "\u0120do\u00c5\u013dwiad",
+ "\u0120Euros",
+ "\u0120commentaires",
+ "\u0120tweaks",
+ "\u0120Faster",
+ "\u0120\u00d1\u0122\u00d0\u00b0\u00d1\u0123\u00d0\u00ba",
+ "\u0120progressively",
+ "\u0120Euch",
+ "boro",
+ "\u0120Ingred",
+ "Cap",
+ "\u0120uncheck",
+ "\u0120\u00ec\u013a\u00a4\u00eb\u00a5\u00b8",
+ "\u0120wre",
+ "\u0120FT",
+ "\u00c3\u00b6rung",
+ "\u0120memorized",
+ "\u0120Dinner",
+ "\u0120Phew",
+ "oubl",
+ "\u0120puta",
+ "\u0120admits",
+ "\u00d0\u00b5\u00d0\u00b7\u00d0\u00b4\u00d0\u00b5",
+ "opod",
+ "\u0120panda",
+ "\u0120hinges",
+ "cipe",
+ "\u0120transact",
+ "\u0120podia",
+ "\u0120pics",
+ "\u0120criterion",
+ "\u0120Orchestra",
+ "\u0120Blog",
+ "\u0120solemn",
+ "\u0120Pixar",
+ "Three",
+ "\u0120\u00d0\u00b2\u00d0\u00bd\u00d0\u00b8\u00d0\u00b7",
+ "\u0120Volunte",
+ "\u0120Savage",
+ "\u0120PVC",
+ "\u0120Caf",
+ "\u0120wykon",
+ "\u0120graders",
+ "\u0120crouch",
+ "\u0120cliche",
+ "\u0120soybeans",
+ "\u0120MUR",
+ "\u0120Gonzalez",
+ "\u0120Mimi",
+ "\u0120Bolsonaro",
+ "\u0120diaphrag",
+ "\u0120bilang",
+ "\u00eb\u0132\u013a\u00eb\u012c\u0136",
+ "\u00e9\u0124\u00a3\u00e6\u012a\u0133\u00e5\u0122\u0133",
+ "\u0120regulating",
+ "Mc",
+ "Judge",
+ "\u0120\u00d0\u00bd\u00d0\u00be\u00d0\u00b6",
+ "\u0120jak\u00c4\u0127",
+ "itesse",
+ "\u0120Wij",
+ "\u0120lata",
+ "groaning",
+ "POSING",
+ "\u0120\u00d7\u0132\u00d7\u0137\u00d7\u00aa\u00d7\u0137",
+ "\u0120haga",
+ "\u0120grounding",
+ "\u0120violently",
+ "\u0120tills",
+ "\u0120engag",
+ "\u0120Hollow",
+ "\u0120\u00d0\u00bf\u00d0\u00be\u00d0\u00bf\u00d1\u0125\u00d0\u00bb\u00d1\u0131\u00d1\u0122",
+ "\u0120wprowad",
+ "\u0120replaces",
+ "\u0120fluorescent",
+ "urgical",
+ "iggly",
+ "\u0120Traditional",
+ "tte",
+ "\u0120\u00d9\u0126\u00d9\u0129",
+ "\u0120phosphorus",
+ "\u0120apron",
+ "\u0120Waters",
+ "\u0120Kultur",
+ "\u00d0\u00b0\u00d0\u00b2\u00d0\u00b0\u00d0\u00b9",
+ "\u0120olives",
+ "\u0120\u00d7\u0136\u00d7\u0132\u00d7\u013e",
+ "\u0120teilweise",
+ "\u0120sencill",
+ "\u0120prends",
+ "\u0120narrower",
+ "\u0120j\u00c3\u00a4tte",
+ "\u0120Informationen",
+ "\u00ec\u0125\u0123\u00ec\u013f\u00b4",
+ "\u0120starve",
+ "\u0120frick",
+ "\u0120Beweg",
+ "\u00e0\u00a4\u00b2",
+ "\u0120dolphin",
+ "\u0120LAUGHTER",
+ "\u0120INTERVIE",
+ "\u00e5\u0136\u012b",
+ "\u0120yanl\u00c4\u00b1\u00c5\u0141",
+ "\u0120torpedo",
+ "\u0120shortages",
+ "\u00ec\u013f\u00b4\u00eb\u0135\u013e",
+ "\u00c4\u00b1ld\u00c4\u00b1",
+ "\u0120paws",
+ "\u0120ozone",
+ "\u0120cultivated",
+ "\u0120Fot",
+ "\u0120notor",
+ "\u00d0\u00bd\u00d0\u00be\u00d0\u00b7",
+ "\u0120\u00d0\u00ba\u00d0\u00be\u00d1\u012a",
+ "\u0120touchscreen",
+ "\u0120Ally",
+ "\u00e6\u013e\u0122\u00e8\u00bf\u0133",
+ "\u0120\u00eb\u00a7\u013d\u00ec\u0140\u012a\u00ec\u0138\u00b4\u00ec\u013c\u0136",
+ "\u0120\u00d0\u00a1\u00d0\u00b5\u00d1\u0122",
+ "\u0120\u00d0\u00b2\u00d0\u00bf\u00d0\u00be\u00d0\u00bb\u00d0\u00bd\u00d0\u00b5",
+ "\u0120paprika",
+ "\u0120Dustin",
+ "\u0120efecto",
+ "\u0120opini",
+ "\u0120muut",
+ "\u0120h\u00e1\u00bb\u012fc",
+ "\u0120interject",
+ "\u00c4\u013bt",
+ "\u0120butts",
+ "urez",
+ "\u0120Pike",
+ "\u0120Hok",
+ "\u0120Guinea",
+ "\u0120Cathedral",
+ "\u01201400",
+ "Cra",
+ "+,",
+ "\u00eb\u00a7\u013d",
+ "\u00b3\u00b4\u00eb\u0131\u0126\u00eb\u00a1\u013f",
+ "abyrin",
+ "\u0120videog",
+ "\u0120\u00d0\u00be\u00d1\u0122\u00d1\u0125\u00d0\u00b6",
+ "\u0120u\u00c5\u00be",
+ "\u0120buscando",
+ "\u0120Assistance",
+ "\u00e9\u013b\u00bd",
+ "\u0120melhores",
+ "\u00ec\u00a1\u00b4",
+ "\u0120\u00eb\u0123\u00bc",
+ "\u0120RJ",
+ "\u0120\u00d8\u00aa\u00d9\u0127",
+ "\u0120omin",
+ "\u0120motorcycles",
+ "\u0120Sapp",
+ "\u0120supplying",
+ "\u0120Algun",
+ "\u0120aerospace",
+ "\u00d7\u00a2\u00d7\u013e",
+ "occup",
+ "leist",
+ "\u0120\u00ea\u00b1\u00b0\u00eb\u012c\u0136",
+ "\u0120completa",
+ "bres",
+ "!(",
+ "\u0120\u00d0\u0141\u00d1\u0122\u00d0\u00b5\u00d0\u00b4",
+ "\u0120disadvantaged",
+ "\u0120Attend",
+ "\u0120Judah",
+ "\u00e1\u00bb\u012dch",
+ "ylene",
+ "actly",
+ "\u0120setups",
+ "\u0120ammonia",
+ "\u0120Schweiz",
+ "\u0120Shame",
+ "\u0120bande",
+ "\u0120Fuel",
+ "\u0120troublesome",
+ "\u0120numero",
+ "\u0120MOM",
+ "\u0120\u00d0\u00bf\u00d1\u0122\u00d0\u00b5\u00d0\u00b4\u00d0\u00bb\u00d0\u00b0\u00d0\u00b3",
+ "mentioned",
+ "\u0120\u00d0\u00b1\u00d0\u00be\u00d0\u00bb\u00d1\u012e\u00d1\u012a\u00d0\u00be\u00d0\u00b5",
+ "\u0120Viktor",
+ "\u0120Styles",
+ "\u0120crucified",
+ "ructured",
+ "environ",
+ "\u0120morals",
+ "\u0120meditating",
+ "\u0120axial",
+ "isance",
+ "\u0120Abst",
+ "Green",
+ "\u0120\u00ea\u00b1\u00b4\u00ec",
+ "\u0120quadrant",
+ "\u0120pergi",
+ "\u0120cameraman",
+ "\u0120Sequ",
+ "\u0120paused",
+ "\u0120Laughing",
+ "\u00ea\u00b7\u0122",
+ "?..",
+ "\u0120\u00c5\u00bbe",
+ "\u0120permitir",
+ "\u0120detectors",
+ "\u0120HUD",
+ "aval",
+ "\u0120\u00ec\u0139\u00ac\u00ea\u00b8\u00b0\u00ea\u00b9\u012e\u00ec\u00a7\u0122",
+ "\u0120hubs",
+ "\u0120bestimmt",
+ "\u0120\u00d0\u00b1\u00d1\u0125\u00d0\u00b4\u00d0\u00b5\u00d1\u0124\u00d0\u00b5",
+ "INTERPOSING",
+ "\u0120tengan",
+ "\u0120crave",
+ "\u0120Bundesregierung",
+ "\u0120Bloody",
+ "\u0120usability",
+ "\u0120Eas",
+ "\u0120\u00c4\u0133\u00e1\u00bb\u013bng",
+ "\u01201955",
+ "\u0120kriegen",
+ "\u0120habitual",
+ "\u0120essentials",
+ "riminal",
+ "\u0120roommates",
+ "\u00e9\u0124\u00a3\u00e5\u00b0\u00b1",
+ "\u0120\u00d0\u00bf\u00d0\u00b5\u00d1\u0122\u00d0\u00b5\u00d1\u0127\u00d0\u00be\u00d0\u00b4",
+ "\u0120nghi",
+ "\u0120mening",
+ "\u0120Symphony",
+ "\u0120Hug",
+ "aggi",
+ "\u0120wied",
+ "\u0120mitad",
+ "\u00e3\u0123\u00a3\u00e3\u0123\u00a6\u00e3\u0123\u0126\u00e3\u0123\u0128",
+ "teenth",
+ "ida\u00c4\u0129",
+ "Save",
+ "\u0120robi\u00c4\u0129",
+ "\u0120bounces",
+ "\u00b0\u0138\u00ec\u0139\u0132",
+ "stars",
+ "\u0120pragmatic",
+ "\u0120cognition",
+ "\u0120wrapper",
+ "\u0120warten",
+ "adh",
+ "\u0120pensa",
+ "\u0120Hertz",
+ "\u0120n\u00c4\u013d",
+ "\u0120Reid",
+ "\u0120PCs",
+ "\u0120Mole",
+ "\u0120.....",
+ "\u0120precio",
+ "\u0120Championships",
+ "\u00ea\u00b0\u0122\u00eb\u013f\u00bd",
+ "\u0120v\u00c3\u00a9r",
+ "\u0120corridors",
+ "\u0120Electronic",
+ "Sl",
+ "\u0120\u00d0\u00b0\u00d0\u00bb\u00d0\u00b5",
+ "\u0120overthrow",
+ "\u0120kabul",
+ "\u0120RES",
+ "\u0120Cyberpunk",
+ "\u00d0\u00be\u00d0\u00b3\u00d0\u00be\u00d0\u00b4",
+ "\u0120\u00d0\u013f\u00d0\u00b0\u00d0\u00b2",
+ "\u0120wan",
+ "\u0120manifestations",
+ "\u0120cuales",
+ "\u0120Wise",
+ "\u0120L\u00c3\u00b6sung",
+ "\u0120exfol",
+ "\u0120earns",
+ "\u00d1\u0125\u00d1\u0123\u00d1\u0124\u00d0\u00b8\u00d1\u0124\u00d1\u012e",
+ "\u0120sapp",
+ "\u0120Braun",
+ "\u0120BRANDON",
+ "\u00ec\u00b9\u013b",
+ "\u0120sano",
+ "\u0120FEL",
+ "\u00d1\u012d\u00d0\u00b2\u00d0\u00b0\u00d0\u00b9\u00d1\u0124\u00d0\u00b5\u00d1\u0123\u00d1\u012e",
+ "\u00d0\u00be\u00d0\u00b6\u00d0\u00b4\u00d0\u00b5\u00d0\u00bd\u00d0\u00b8\u00d1\u0131",
+ "\u0120sewn",
+ "Fun",
+ "\u0120reciprocal",
+ "\u0120expansive",
+ "\u0120Traffic",
+ "\u0120kt\u00c3\u00b3rego",
+ "\u0120\u00d9\u012a\u00d8\u00b3",
+ "\u00e6\u013a\u00a5",
+ "\u0120\u00eb\u00b9\u00a8",
+ "prove",
+ "igare",
+ "\u0120loh",
+ "\u00d8\u00a7\u00d8\u00b6",
+ "Hope",
+ "\u0120devotees",
+ "\u0120Gom",
+ "\u0120steals",
+ "\u0120Ums",
+ "\u0120Twice",
+ "\u00e3\u0124\u00b2",
+ "iyim",
+ "\u0120rhythmic",
+ "\u0120Vorte",
+ "\u0120prefix",
+ "omination",
+ "\u0120dato",
+ "\u0120custard",
+ "\u0120VOICE",
+ "\u00e5\u00b7\u0140",
+ "\u0120meny",
+ "istors",
+ "\u0120\u00ed\u013a\u0133",
+ "\u0120\u00ec\u0124\u00b4\u00ec\u0137\u0126",
+ "\u0120\u00ed\u0125\u0126",
+ "\u0120kort",
+ "\u0120aba",
+ "\u0120Vera",
+ "epy",
+ "\u0120\u00ec\u00b9\u00b4\u00eb\u00a9\u0136\u00eb\u013f\u00bc",
+ "\u0120submerged",
+ "\u0120Clock",
+ "\u0120thumbnails",
+ "\u0120boast",
+ "\u0120Fare",
+ "!!]",
+ "\u0120\u00c5\u013dm",
+ "\u0120kaikki",
+ "\u0120Technologies",
+ "\u00ec\u013b\u00b8",
+ "\u00e3\u0125\u0134",
+ "\u00d0\u00b8\u00d1\u0124\u00d0\u00b0\u00d0\u00b9",
+ "\u00e5\u00b0\u0131\u00e6\u013b\u0124",
+ "\u0120\u00d0\u00b0\u00d1\u0124",
+ "\u0120knobs",
+ "\u0120reicht",
+ "\u00c6\u00b0\u00e1\u00bb\u00a3ng",
+ "glio",
+ "\u0120\u00eb\u00a7\u013d\u00ec\u013f\u00b4",
+ "\u00ea\u00b0\u0132\u00ec\u013f\u0126",
+ "\u0120jotka",
+ "\u0120Handy",
+ "\u0120Haben",
+ "nous",
+ "\u0120inland",
+ "\u0120amazon",
+ "hooting",
+ "SL",
+ "\u0120leisten",
+ "~\"",
+ "\u0120provoke",
+ "\u0120Twist",
+ "\u0120\u00d7\u0133\u00d7\u0139",
+ "\u0120departed",
+ "\u00ea\u00b0\u013e\u00eb\u00a5\u00bc",
+ "\u0120konse",
+ "\u0120Carwyn",
+ "\u00ed\u0137\u013a\u00ec\u012d\u0142",
+ "idental",
+ "ESCO",
+ "\u0120tteokbokki",
+ "\u0120dizendo",
+ "\u00e7\u00b7\u00b4",
+ "\u00c4\u00b1ndaki",
+ "imasu",
+ "afar",
+ "\u0120landfill",
+ "\u0120correcting",
+ "\u0120clears",
+ "\u0120Nummer",
+ "HAM",
+ "\u0120cartridges",
+ "\u0120Diesel",
+ "paced",
+ "\u0120obliv",
+ "\u0120moyens",
+ "\u0120Sinne",
+ "\u0120Preis",
+ "iliz",
+ "\u0120\u00d1\u0123\u00d0\u00bc\u00d0\u00be\u00d0\u00b6",
+ "\u0120broaden",
+ "\u00e4\u00bb\u0138\u00e6\u013a\u00af",
+ "xes",
+ "\u0120carbohydrate",
+ "\u00ed\u013a\u00b9",
+ "seok",
+ "\u0120echoes",
+ "\u0120cess",
+ "\u00eb\u00b0\u0136",
+ "\u0120\u00d0\u00b1\u00d0\u00b8\u00d0\u00b7\u00d0\u00bd\u00d0\u00b5\u00d1\u0123",
+ "\u0120llamado",
+ "\u0120essent",
+ "\u0120\u00ec\u013f\u00bc\u00eb\u00b0\u013a",
+ "\u0120Aires",
+ "phen",
+ "\u0120zebra",
+ "\u0120symbolism",
+ "Once",
+ "\u0120racks",
+ "\u0120Kafka",
+ "\u0120\u00d1\u0123\u00d0\u00b5\u00d1\u0122\u00d1\u012e\u00d0\u00b5\u00d0\u00b7",
+ "\u0120sinn",
+ "picious",
+ "kaa",
+ "\u0120motherfucker",
+ "\u0120apprenticeship",
+ "\u0120rpm",
+ "\u0120taxation",
+ "\u0120furry",
+ "\u0120Sacred",
+ "\u0120\u00d1\u0122\u00d0\u00b0\u00d0\u00b7\u00d0\u00bc",
+ "pora",
+ "enges",
+ "\u0120\u00ed\u0139\u012a\u00eb",
+ "\u0120\u00d1\u0123\u00d0\u00b8\u00d0\u00bd",
+ "\u0120sanitizer",
+ "\u0120cringe",
+ "\u0120Sca",
+ "\u00d0\u00be\u00d1\u0129\u00d0\u00bd\u00d0\u00be",
+ "\u0120ofere",
+ "\u0120melodies",
+ "\u0120Velvet",
+ "\u0120Ihrer",
+ "\u0120Hybrid",
+ "\u0120Giov",
+ "\u0120irgendwas",
+ "\u0120depende",
+ "\u0120Users",
+ "\u0120hump",
+ "driving",
+ "\u0120sf",
+ "\u0120ruthless",
+ "\u00e0\u00b9\u0122\u00e0\u00b8\u0126",
+ "\u0120lemons",
+ "\u0120f\u00c3\u00b6ret",
+ "\u0120Oj",
+ "\u0120\u00d0\u00bc\u00d0\u00b0\u00d0\u00bc\u00d0\u00b0",
+ "\u0120interpersonal",
+ "\u0120gev",
+ "\u0120abnorm",
+ "\u00d0\u00b8\u00d1\u0123\u00d0\u00bb",
+ "\u0120\u00d0\u00b8\u00d0\u00bd\u00d0\u00b4",
+ "\u0120kontroll",
+ "\u0120regres",
+ "\u0120ledge",
+ "\u0120erz\u00c3\u00a4hlt",
+ "\u0120Tact",
+ "\u0120arriv\u00c3\u00a9",
+ "\u0120substantive",
+ "\u0120spoonful",
+ "zwischen",
+ "ooooo",
+ "\u0120contenido",
+ "\u0120besl",
+ "\u00e1\u00bb\u0125m",
+ "kten",
+ "Jamie",
+ "\u0120sandy",
+ "\u00e4\u00b8\u012f\u00e5\u0132\u012e",
+ "\u00e2\u012d",
+ "\u0120pase",
+ "\u0120dette",
+ "\u0120Belgian",
+ "\u00ea\u00b0\u013e\u00eb",
+ "ulares",
+ "rud",
+ "igor",
+ "\u0120\u00ed\u012e\u00ac\u00eb",
+ "\u0120remedies",
+ "\u0120blasting",
+ "\u0120Sich",
+ "\u0120\u00d0\u00be\u00d0\u00b6\u00d0\u00b8\u00d0\u00b4",
+ "\u0120monstr",
+ "\u0120manifold",
+ "\u0120glauben",
+ "\u0120EST",
+ "\u0120streamline",
+ "\u0120lobbying",
+ "\u0120Gothic",
+ "toire",
+ "..'",
+ "\u0120d\u00c3\u00a9mocr",
+ "\u0120\u00d0\u00bd\u00d0\u00b0\u00d0\u00b1\u00d0\u00bb\u00d1\u0130\u00d0\u00b4",
+ "\u0120wsp\u00c3\u00b3l",
+ "\u0120cz\u00c4\u013b\u00c5\u013d\u00c4\u0129",
+ "\u00e4\u00b8\u012d\u00e9\u013f\u00a2",
+ "is\u00c3\u00a9s",
+ "gangen",
+ "\u0120bezpie",
+ "remlin",
+ "\u00ea\u00b0\u013f",
+ "Still",
+ "\u0120resides",
+ "\u0120gelecek",
+ "\u0120t\u00c3\u00a9l\u00c3\u00a9phone",
+ "\u0120pewn",
+ "\u0120leopard",
+ "\u0120complimentary",
+ "\u0120crib",
+ "\u0120Animals",
+ "\u0120geil",
+ "essel",
+ "\u0120garder",
+ "\u0120catchy",
+ "\u00e6\u00a8\u00b9",
+ "\u0120Ets",
+ "\u0120Commercial",
+ "\u0120DENNIS",
+ "\u0120Coordinator",
+ "\u0120Abigail",
+ "ffffff",
+ "\u00e1\u00ba\u00a5p",
+ "\u0120peque\u00c3\u00b1a",
+ "\u0120injections",
+ "cekt",
+ "\u0120philanthropy",
+ "\u0120puck",
+ "\u0120celebrates",
+ "\u0120Dunk",
+ "\u0120Dlatego",
+ "\u00e3\u0123\u00be\u00e3\u0123\u0142",
+ "\u00ce\u00b4\u00ce\u00ae",
+ "graduate",
+ "\u0120Mobil",
+ "till",
+ "acam",
+ "\u0120yolks",
+ "\u0120tangled",
+ "\u0120maniac",
+ "\u0120obliged",
+ "\u0120Laink",
+ "\u0120verder",
+ "\u0120Damon",
+ "\u0120mutant",
+ "\u0120hopping",
+ "\u0120reins",
+ "\u0120inverter",
+ "\u0120contempt",
+ "\u00d7\u0142\u00d7\u00a1",
+ "learning",
+ "Miss",
+ "\u0120\u00d0\u0135\u00d0\u00be\u00d1\u0123",
+ "\u0120Meyer",
+ "\u00ea\u00bb\u013a\u00ec\u0126\u013e",
+ "\u00e9\u00a3\u0130",
+ "\u00d7\u0137\u00d7\u0142\u00d7\u013b\u00d7\u013f",
+ "asking",
+ "\u0120trimming",
+ "\u0120treasury",
+ "\u0120sente",
+ "Aust",
+ "\u0120Unterst\u00c3\u00bctzung",
+ "\u0120Comedy",
+ "\u0120Anakin",
+ "\u00e9\u00b9",
+ "\u00d1\u0122\u00d1\u0125\u00d1\u0124",
+ "\u0120Hari",
+ "ographers",
+ "\u0120oatmeal",
+ "\u0120Bots",
+ "\u00e4\u00b8\u012f\u00e4\u00ba\u0128",
+ "\u0120\u00d0\u00bf\u00d0\u00b0\u00d0\u00bb\u00d1\u012e",
+ "\u0120acknowledgement",
+ "xic",
+ "\u0120\u00ea\u00b4\u0122\u00ec\u012d\u00ac",
+ "gasping",
+ "\u0120\u00e3\u0123\u0137",
+ "\u0120terrace",
+ "\u0120ornaments",
+ "\u0120MER",
+ "committee",
+ "\u0120\u00ec\u0139\u0128\u00ec\u012c\u00b5\u00eb\u012d\u012a\u00eb\u012d\u00a4",
+ "\u0120rij",
+ "\u00e9\u00b3",
+ "\u00d7\u00a6\u00d7\u013f",
+ "leme",
+ "\u0120liberties",
+ "\u0120fellas",
+ "\u0120Copper",
+ "bench",
+ "\u0120Idea",
+ "\u00e1\u00bb\u012fn",
+ "\u00d1\u012a\u00d0\u00b0",
+ "\u0120versi\u00c3\u00b3n",
+ "\u00cf\u0126\u00ce\u00bf\u00cf\u012f",
+ "\u0120\u00d0\u013e\u00d0\u00b8",
+ "\u0120\u00d0\u00bf\u00d1\u0122\u00d0\u00b8\u00d0\u00bb\u00d0\u00be\u00d0\u00b6",
+ "\u0120boxer",
+ "\u0120Tanner",
+ "\u0120Moy",
+ "\u00ec\u00b9\u013a\u00eb\u012c\u0136",
+ "Thr",
+ "\u0120tinham",
+ "\u0120polishing",
+ "\u0120consequently",
+ "\u0120amenities",
+ "\u0120KI",
+ "\u0120GREEN",
+ "\u0120Frankie",
+ "\u00d0\u00bd\u00d0\u00b8\u00d1\u0124",
+ "ittel",
+ "\u00d1\u0123\u00d0\u00ba\u00d0\u00be\u00d0\u00b5",
+ "ursed",
+ "\u0120upbringing",
+ "\u0120th\u00e1\u00bb\u00a9",
+ "\u0120\u00ec\u012d\u013f\u00ec\u013e\u00bc\u00eb\u00a1\u013e",
+ "\u0120whim",
+ "\u0120chinese",
+ "confidence",
+ "\u0120Jeder",
+ "\u00e3\u0123\u00aa\u00e3\u0123\u00ae\u00e3\u0123\u00a7",
+ "ajcie",
+ "\u0120Tous",
+ "\u0120Powers",
+ "\u00e1\u00bb\u00aba",
+ "othermal",
+ "\u0120\u00d0\u00b2\u00d1\u012d\u00d1\u012a\u00d0\u00b5",
+ "rale",
+ "\u00d8\u00a7\u00d8\u00ae",
+ "\u0120\u00ec\u00a7\u0122\u00ec\u013d\u0132",
+ "\u0120\u00c3\u00a9pisode",
+ "\u0120sulph",
+ "\u0120encara",
+ "kraft",
+ "alar\u00c4\u00b1",
+ "\u0120Comes",
+ "\u0120divul",
+ "\u0120Rudolph",
+ "\u0120Muse",
+ "\u0120utens",
+ "\u0120\u00ec\u0140\u0132\u00ec\u00a3\u00bc",
+ "\u0120pana",
+ "\u0120Vegeta",
+ "\u0120PHP",
+ "\u0120NSA",
+ "entin",
+ "\u0120Carnegie",
+ "\u00d8\u00a7\u00d9\u012c",
+ "i\u00c4\u013bcy",
+ "Harry",
+ "\u0120f\u00c4\u00b1r",
+ "\u00d0\u00a1\u00d0\u00bf",
+ "\u0120gladly",
+ "\u0120averaging",
+ "\u00ed\u0137\u013a\u00ea\u00b2\u0142\u00ec\u012c\u00b5\u00eb\u012d\u012a\u00eb\u012d\u00a4",
+ "\u00d0\u00bb\u00d1\u0131\u00d1\u0130\u00d1\u0124\u00d1\u0123\u00d1\u0131",
+ "\u0120\u00d0\u013e\u00d0\u00b5\u00d0\u00bd\u00d1\u0131",
+ "\u0120quotation",
+ "rires",
+ "itchens",
+ "ayed",
+ "\u0120unatt",
+ "\u0120Perez",
+ "\u0120\u00d0\u00be\u00d1\u0124\u00d0\u00bc\u00d0\u00b5\u00d1\u0124",
+ "\u0120tactile",
+ "\u0120Euh",
+ "isini",
+ "buh",
+ "\u0120hat\u00c4\u00b1r",
+ "\u0120\u00ec\u0140\u012a\u00ec\u013e\u00bc",
+ "\u0120policymakers",
+ "\u00b3\u00b4\u00ec\u0126\u00b8\u00ec\u013c\u0136",
+ "ac\u00c4\u00b1",
+ "\u0120\u00ce\u00ba\u00ce\u00b9",
+ "\u0120registering",
+ "reto",
+ "\u0120Sprinkle",
+ "\u0120Grammy",
+ "axter",
+ "\u0120\u00d0\u00b1\u00d0\u00b8",
+ "\u0120sitter",
+ "\u0120predic",
+ "\u0120thinly",
+ "\u0120strum",
+ "\u0120aggrav",
+ "\u0120aha",
+ "\u00d8\u00b1\u00d8\u00ac",
+ "mellow",
+ "\u0120constante",
+ "\u0120Laut",
+ "iston",
+ "\u0120transitioned",
+ "\u0120Cambodia",
+ "\u00e3\u0123\u0126\u00e3\u0123\u012f\u00e3\u0123\u00be\u00e3\u0123\u013b",
+ "\u00e8\u00b7\u0141\u00e5\u00a4\u00a7\u00e5\u00ae\u00b6",
+ "arted",
+ "\u0120misf",
+ "\u0120Punkte",
+ "\u012e\u00eb\u0135\u0142",
+ "\u0120trembling",
+ "\u0120gespannt",
+ "\u0120\u00d8\u00b9\u00d9\u0126\u00d9\u012c\u00d9\u0129",
+ "\u0120\u00d0\u00bd\u00d0\u00b8\u00d0\u00ba\u00d0\u00b0\u00d0\u00ba\u00d0\u00b8\u00d1\u0127",
+ "\u0120\u00eb\u00b6\u0122\u00eb\u0135\u013e\u00eb",
+ "\u0120\u00d1\u0122\u00d0\u00b0\u00d0\u00b7\u00d0\u00b2\u00d0\u00b8\u00d1\u0124",
+ "\u0120itchy",
+ "\u0120ciento",
+ "\u0120plains",
+ "\u0120kittens",
+ "\u0120backlog",
+ "\u0120Presiding",
+ "pta",
+ "\u0120havoc",
+ "\u0120Darrin",
+ "\u0120\u00d0\u013d\u00d1\u0130\u00d0\u00b1",
+ "\u0120segregated",
+ "\u0120ghetto",
+ "\u0120erlebt",
+ "\u0120drugiej",
+ "\u0120Sixt",
+ "\u00e5\u0131\u0125",
+ "\u00e0\u00b8\u00a3\u00e0\u00b8\u00b0",
+ "uencia",
+ "\u0120\u00ed\u0137\u013a\u00ea\u00b8\u00b0",
+ "\u0120\u00eb\u0128\u012f",
+ "\u0120robi",
+ "\u0120pioneers",
+ "\u0120milliards",
+ "\u0120Witcher",
+ "\u0120\u00eb\u00ac\u00b4\u00ec\u0139\u0129",
+ "orro",
+ "mass",
+ "\u0120divergence",
+ "\u0120Rivera",
+ "\u0120Noodles",
+ "\u0120endroit",
+ "\u0120Kosten",
+ "\u0120\u00d0\u00b4\u00d1\u0122\u00d1\u0125\u00d0\u00b3\u00d0\u00b0",
+ "\u0120m\u00c3\u0143nimo",
+ "\u0120Kazakhstan",
+ "\u00d8\u00aa\u00d9\u0129",
+ "\u0120\u00d0\u00b2\u00d0\u00be\u00d0\u00b7\u00d0\u00b4\u00d1\u0125",
+ "\u0120geschrieben",
+ "\u0120Nil",
+ "\u00d1\u0123\u00d0\u00ba\u00d0\u00b8",
+ "\u0120Fr\u00c3\u00bch",
+ "\u0120beverages",
+ "\u00e6\u00ba\u0132",
+ "\u0120Gon",
+ "\u00e6\u013a\u00a8",
+ "Arin",
+ "\u0120Intro",
+ "ocalyptic",
+ "\u0120exhaustion",
+ "\u0120Status",
+ "\u0120Battery",
+ "\u00c3\u00a9sz",
+ "\u00a3\u00bc\u00eb",
+ "airy",
+ "\u0120\u00eb\u00b3\u00b4\u00ec\u0139\u00ac\u00eb\u0135\u013e\u00eb",
+ "\u0120disparity",
+ "\u00d9\u012e",
+ "\u0120Tucson",
+ "\u0120brightly",
+ "problem",
+ "\u0120biomass",
+ "\u00e9\u013b\u012f",
+ "\u00a7\u012b",
+ "\u0120hurdle",
+ "\u0120wavelengths",
+ "\u0120<<",
+ "\u0120teamed",
+ "FFFF",
+ "\u0120Slim",
+ "omial",
+ "\u0120unveiled",
+ "\u0120Verein",
+ "\u00d9\u0124\u00d8\u00b7",
+ "estry",
+ "\u0120cl\u00c3\u00a1s",
+ "\u0120cheddar",
+ "\u0120accusing",
+ "\u0120Scientific",
+ "\u0120\u00d0\u00b1\u00d1\u0125\u00d0\u00b4\u00d0\u00b5",
+ "\u0120Cyrus",
+ "\u00ce\u00b5\u00cf\u0126\u00ce\u00b5",
+ "\u0128\u0135\u00ea\u00b3\u0142",
+ "\u0120\u00eb\u00b3\u0126",
+ "\u0120curd",
+ "\u0120referrals",
+ "shift",
+ "\u00e5\u012f\u0137",
+ "nik\u00c3\u00b3w",
+ "\u0120mier",
+ "\u0120confronting",
+ "\u00ea\u00b2\u0125\u00eb\u0131\u0126",
+ "awl",
+ "\u0120tryin",
+ "\u0120\u00ea\u00b7\u00b8\u00eb\u0140\u013a\u00ec\u013c\u0136",
+ "\u0120chiar",
+ "\u0120\u00ec\u013a\u00a4\u00eb\u012c\u013a\u00eb\u0131\u0126",
+ "\u00e6\u0136\u00bf\u00e6\u00b2\u00bb",
+ "esque",
+ "\u0120mismos",
+ "\u0120Shak",
+ "\u0120sociaux",
+ "\u0120pi\u00c5\u0141",
+ "\u0120ki\u00c5\u0141i",
+ "\u0120cyan",
+ "hay",
+ "bew",
+ "bod",
+ "\u0120\u00ce\u00b9",
+ "\u0120Mainly",
+ "\u00d1\u0130\u00d1\u0124\u00d1\u012e",
+ "habitude",
+ "\u0120\u00d1\u0123\u00d0\u00bf\u00d0\u00be\u00d0\u00ba\u00d0\u00be\u00d0\u00b9",
+ "\u00e8\u00b7\u0141\u00e6\u012a\u0133",
+ "\u0120precon",
+ "\u0120Mandy",
+ "\u00f0\u0141\u00a4\u00a3",
+ "illos",
+ "\u0120grupp",
+ "\u0120crumble",
+ "\u0120constructor",
+ "ervices",
+ "\u0120lighthouse",
+ "\u0120Concept",
+ "\u00d0\u00b0\u00d0\u00bd\u00d1\u0124\u00d0\u00b8",
+ "altro",
+ "hope",
+ "\u0120Alleg",
+ "\u00ec\u0138\u00b4\u00eb\u00a5\u00bc",
+ "pieces",
+ "ounter",
+ "\u0120\u00ed\u0137\u013a\u00eb\u012d\u012a\u00ea\u00b9\u012e",
+ "\u0120\u00ec\u013f\u00b8\u00ed\u0126\u00b0\u00eb",
+ "\u0120v\u00c3\u00a9ritable",
+ "\u0120threaded",
+ "blind",
+ "\u0124\u013a\u00eb\u013f\u00bc",
+ "\u0120trays",
+ "\u0120Edison",
+ "\u0120\u00c3\u0138z",
+ "\u0120Stevie",
+ "\u0120lender",
+ "\u0120brigade",
+ "\u0120deutsche",
+ "muffled",
+ "bart",
+ "\u0120insanity",
+ "\u0120savvy",
+ "\u0120sensational",
+ "\u0120derechos",
+ "\u0120MX",
+ "\u0120\u00d0\u00bf\u00d1\u0122\u00d0\u00b5\u00d0\u00bf",
+ "\u0120threatens",
+ "\u0120realt\u00c3\u0142",
+ "\u0120indicative",
+ "\u0120chops",
+ "\u0120benefiting",
+ "\u0120Vernon",
+ "\u0120Strand",
+ "nun",
+ "quently",
+ "101",
+ "\u0120eel",
+ "\u00ec\u012a\u013b",
+ "rints",
+ "\u0120\u00d9\u0127\u00d8\u00b3",
+ "\u0120\u00d8\u00a8\u00d8\u00af",
+ "\u0120\u00d0\u00bf\u00d0\u00be\u00d1\u0123\u00d1\u0124\u00d1\u0122\u00d0\u00be",
+ "\u0120yapm\u00c4\u00b1\u00c5\u0141",
+ "\u0120olmas\u00c4\u00b1",
+ "\u0120iedereen",
+ "ol\u00c3\u00a9",
+ "kef",
+ "\u0120\u00eb\u00b0\u013e\u00ec\u0125\u013f",
+ "\u0120rained",
+ "\u0120almighty",
+ "\u0120\u00d0\u00b2\u00d1\u012d\u00d0\u00b4",
+ "\u0120CPR",
+ "Fre",
+ "\u0120inhabited",
+ "\u0120arbets",
+ "\u0120akin",
+ "\u00d0\u00b0\u00d1\u0123\u00d1\u0124\u00d0\u00b2",
+ "vania",
+ "\u0120h\u00c3\u00a4ufig",
+ "\u0120Matte",
+ "sorry",
+ "Jenny",
+ "\u0120\u00d0\u00b3\u00d1\u0122\u00d0\u00b0\u00d0\u00b4",
+ "\u0120whit",
+ "\u0120brokers",
+ "\u00e5\u00af\u0141",
+ "\u0120hine",
+ "asten",
+ "\u0120\u00d0\u00b3\u00d1\u0122\u00d1\u0125",
+ "MB",
+ "\u0120PRI",
+ "Sab",
+ "\u0120wrestler",
+ "\u0120facilitating",
+ "\u0120ehk\u00c3\u00a4",
+ "\u0120Cred",
+ "\u0120127",
+ "\u0120nothin",
+ "\u0120mandated",
+ "\u00e5\u00af\u012e",
+ "\u00d1\u0125\u00d1\u0124\u00d1\u0123\u00d1\u0124\u00d0\u00b2",
+ "Frank",
+ "\u0120wors",
+ "\u0120dzie\u00c5\u0126",
+ "\u0120Underground",
+ "\u0120znajdu",
+ "\u0120B\u00c3\u00a4",
+ "\u0120Prinzip",
+ "\u00d0\u00b0\u00d1\u0124\u00d0\u00b5\u00d0\u00bb\u00d0\u00b5\u00d0\u00b9",
+ "\u0120veterinar",
+ "\u0120splendid",
+ "\u0120rozp",
+ "\u0120psychopath",
+ "igon",
+ "\u0120hops",
+ "\u0120c\u00e1\u00ba\u00a7n",
+ "\u0120Xian",
+ "\u0120troisi\u00c3\u00a8me",
+ "\u0120producto",
+ "\u0120de\u00c4\u0141er",
+ "\u0120Continuing",
+ "\u00d0\u00b8\u00d0\u00b2\u00d0\u00b0\u00d0\u00bb",
+ "c\u00c4\u00b1k",
+ "\u0120moisturizer",
+ "White",
+ "\u0120siis",
+ "\u0120Everest",
+ "ienced",
+ "\u0120c\u00e1\u00ba\u00a3m",
+ "\u0120Japon",
+ "\u00b4\u00ec\u0142\u0126",
+ "\u0120ten\u00c3\u0143an",
+ "\u0120encanta",
+ "Mm",
+ "\u0120dropdown",
+ "\u0120Iya",
+ "\u00b3\u00b4\u00eb\u00a9\u00b4",
+ "\u0120wording",
+ "\u0120Squeeze",
+ "\u0120Maple",
+ "\u0120clarified",
+ "\u0120Municip",
+ "\u0120Rouge",
+ "\u0120Nicki",
+ "\u0120Goo",
+ "volt",
+ "tek",
+ "fecture",
+ "fred",
+ "arrive",
+ "\u00e3\u0125\u00bc\u00e3\u0123\u0126",
+ "tez",
+ "Ep",
+ "\u0120obras",
+ "\u0120VID",
+ "\u0120Riv",
+ "\u0120Modi",
+ "ibe",
+ "\u0120acontecendo",
+ "\u0120imitation",
+ "\u0120camouflage",
+ "\u0120spanning",
+ "\u0120SECRET",
+ "\u0120Oreo",
+ "\u00ec\u0128\u012e\u00eb\u00a6\u00ac",
+ "\u0120hunch",
+ "\u0120ca\u00c5\u0124e",
+ "\u0120spontaneously",
+ "\u0120Perd",
+ "\u0120etap",
+ "\u0120Hole",
+ "\u0120Disability",
+ "\u0120afterlife",
+ "\u00e6\u0123\u00a9",
+ "\u0120testified",
+ "\u0120presup",
+ "\u0120petroleum",
+ "\u0120contrario",
+ "\u0120Assessment",
+ "\u00c4\u0141lu",
+ "\u0120pests",
+ "\u0120dilig",
+ "\u0120\u00d0\u00b2\u00d1\u0123\u00d1\u0124\u00d1\u0122\u00d0\u00b5\u00d1\u0124",
+ "\u0120cons\u00c3\u00a9qu",
+ "\u0120cannons",
+ "\u0120canoe",
+ "\u0120Mile",
+ "\u0120citoy",
+ "\u0120begged",
+ "\u0120Minnie",
+ "\u00c5\u0124ych",
+ "\u0120principe",
+ "\u00cf\u0122\u00cf\u012e\u00ce\u00bd",
+ "mniej",
+ "\u0120wert",
+ "\u0120\u00eb\u012d\u00a4\u00eb\u0135\u00a4",
+ "anse",
+ "\u0120uncles",
+ "\u0120provocative",
+ "\u0120intersections",
+ "\u0120democrats",
+ "\u0120Julius",
+ "\u00d0\u00b8\u00d0\u00bd\u00d0\u00ba\u00d0\u00b8",
+ "ygusal",
+ "\u0120\u00d7\u013e\u00d7\u0137",
+ "\u0120gjorde",
+ "\u0120gasket",
+ "\u0120Bock",
+ "\u0120\u00c4\u00b0n",
+ "breat",
+ "\u0120Equity",
+ "ard\u00c4\u00b1",
+ "\u0120\u00d0\u00ba\u00d0\u00b0\u00d0\u00bd\u00d0\u00b0\u00d0\u00bb\u00d0\u00b5",
+ "\u0120\u00d0\u00b4\u00d0\u00bd\u00d0\u00b5\u00d0\u00b9",
+ "\u0120t\u00e1\u00bb\u013di",
+ "\u0120fixture",
+ "\u0120abuses",
+ "\u0120vaya",
+ "\u0120ouvert",
+ "\u0120multicultural",
+ "\u0120contexto",
+ "\u0120Sesame",
+ "\u0120d\u00c3\u00a9pl",
+ "\u0120consomm",
+ "\u0120Parte",
+ "\u0120pem",
+ "\u0120Conan",
+ "\u0120\u00d0\u00b1\u00d1\u0138\u00d0\u00bb\u00d1\u012e",
+ "\u0120persuaded",
+ "\u0120drains",
+ "Moo",
+ "FORE",
+ "\u0120\u00d0\u00b1\u00d0\u00b0\u00d1\u0124",
+ "\u0120fod",
+ "\u0120Products",
+ "\u00ec\u00a7\u0126\u00ec\u00a7\u013e",
+ "\u0120\"[",
+ "\u0120Wick",
+ "\u0120Naruto",
+ "\u00d0\u00bd\u00d0\u00b0\u00d0\u00bb\u00d0\u00b8",
+ "ryw",
+ "\u0120lodge",
+ "\u0120inh",
+ "\u0120vontade",
+ "\u0120dij",
+ "\u0120Jes\u00c3\u00bas",
+ "Looking",
+ "\u0120forearm",
+ "\u0120Integration",
+ "\u0120HARRIS",
+ "\u0120toolbar",
+ "leader",
+ "\u0120seldom",
+ "\u0120\u00d0\u00b1\u00d1\u0122\u00d0\u00be\u00d1\u0123",
+ "\u0120Kook",
+ "\u00d0\u00be\u00d0\u00bd\u00d0\u00b4",
+ "\u0120monopol",
+ "\u0120millet",
+ "\u0120lira",
+ "\u0120Asians",
+ "\u01201890",
+ "ci\u00c4\u0141im",
+ "\u0120eden",
+ "\u0120IKEA",
+ "\u0120Neighbor",
+ "\u0120Kazuya",
+ "\u00c3\u00bcd",
+ "\u0120psychedel",
+ "\u0120envisioned",
+ "\u00e5\u013f\u0139",
+ "\u0120\u00ef\u00b7\u00bb",
+ "\u0120wunder",
+ "\u0120Bulgaria",
+ "Brid",
+ "\u0120marrow",
+ "\u0120depiction",
+ "\u0120Tin",
+ "\u0120Pharise",
+ "\u0120einzige",
+ "\u0120blindly",
+ "\u00e3\u0123\u013d\u00e3\u0123\u00a6",
+ "\u0120defens",
+ "Dire",
+ "\u0120vibrating",
+ "\u0120trolls",
+ "\u0120disrespectful",
+ "\u0120wod",
+ "\u0120stimuli",
+ "\u0120creeping",
+ "\u0120clairement",
+ "\u0120scariest",
+ "\u0120d\u00c3\u00a9couvrir",
+ "\u0120104",
+ "\u0120\u00d0\u00b2\u00d0\u00b5\u00d1\u0122\u00d1\u0127",
+ "\u0120\u00c5\u0124at",
+ "\u0120r\u00c3\u00b3\u00c5\u00bcne",
+ "\u0120barley",
+ "\u0120Repl",
+ "\u0120Twe",
+ "kke",
+ "\u0120\u00e3\u0123\u013f\u00e3\u0124\u012e",
+ "\u0120Redmi",
+ "\u0120Metroid",
+ "\u0120\u00ce\u00ae\u00cf\u0126\u00ce\u00b1\u00ce\u00bd",
+ "Check",
+ "\u0120SEN",
+ "\u0120ido",
+ "\u00d1\u0124\u00d0\u00be\u00d1\u0122\u00d0\u00b8\u00d0\u00b8",
+ "\u00c3\u00b3p",
+ "UNKNOWN",
+ "\u0120\u00c3\u00a4ndern",
+ "\u0120Juice",
+ "\u0120Gesicht",
+ "\u00e5\u00b0\u00b1\u00e6\u013e\u0125",
+ "\u0120\u00d0\u00bd\u00d0\u00b0\u00d1\u0123\u00d1\u0124\u00d0\u00be\u00d0\u00bb\u00d1\u012e\u00d0\u00ba\u00d0\u00be",
+ "\u00ed\u0125\u0137",
+ "\u00c2\u0143",
+ "exhales",
+ "\u0120\u00ec\u00b4\u012b",
+ "\u0120jsem",
+ "\u00cf\u0122\u00cf\u012b\u00cf\u0124",
+ "\u0120itt",
+ "\u00eb\u00aa\u0127\u00ec\u013f\u00b4",
+ "\u0120remix",
+ "\u0120blossoms",
+ "\u0120Renee",
+ "isations",
+ "\u00ec\u012c\u00a4\u00ed\u0126\u00b0",
+ "\u0120\u00eb\u00b3\u00b4\u00ec\u013f\u00b4\u00eb\u012c\u0136",
+ "uestas",
+ "opedia",
+ "\u0120Aim",
+ "\u00ec\u013f\u00b4\u00ec\u00a6\u012a",
+ "scene",
+ "\u0120leakage",
+ "uckt",
+ "Sad",
+ "Ask",
+ "\u0120suspense",
+ "\u0120impost",
+ "\u0120Strategic",
+ "\u0120It\u00c3\u0143s",
+ "\u00e2\u0122\u012e",
+ "\u0120keyboards",
+ "\u0120amusing",
+ "ogr",
+ "iderman",
+ "\u0140\u0138",
+ "\u0120\u00d0\u00b2\u00d0\u00b8\u00d0\u00b6\u00d1\u0125",
+ "\u0120dips",
+ "\u0120apologized",
+ "\u0120STAR",
+ "\u0120escuela",
+ "\u0120Ching",
+ "\u00d0\u00bd\u00d0\u00b5\u00d0\u00bd\u00d0\u00b8\u00d1\u0131",
+ "\u0120\u00eb\u00b6\u0122\u00eb\u00b6\u0126\u00ec\u013f\u00b4",
+ "\u0120Fleet",
+ "\u0120samb",
+ "\u0120entsprechend",
+ "\u0120electrodes",
+ "\u0120Freiheit",
+ "\u00e6\u012a\u0133\u00e4\u00b8\u012f\u00e7\u0141\u00a5\u00e9\u0123\u0135",
+ "\u0120Shrim",
+ "i\u00c3\u0141e",
+ "\u0120selections",
+ "\u0120fordi",
+ "\u0120doss",
+ "\u00d1\u0131\u00d1\u0129",
+ "\u0120discriminate",
+ "\u0120Au\u00c3\u0141erdem",
+ "\u0120desenvolv",
+ "\u0120Internal",
+ "\u0120Benedict",
+ "\u00e5\u00af\u0128",
+ "\u0120Shiv",
+ "Missy",
+ "\u0120\u00d0\u00be\u00d0\u00b1\u00d0\u00bd\u00d0\u00b0\u00d1\u0122\u00d1\u0125\u00d0\u00b6",
+ "\u0120\u00d0\u00bd\u00d0\u00b0\u00d1\u0123\u00d1\u0124\u00d1\u0122\u00d0\u00be",
+ "\u0120controlar",
+ "\u0120Lia",
+ "\u0120opioids",
+ "antu",
+ "\u0120cupboard",
+ "\u00e6\u0123\u0132",
+ "\u00d0\u00b3\u00d0\u00b5",
+ "achts",
+ "\u0120curated",
+ "\u0120xem",
+ "\u0120weary",
+ "\u0120brethren",
+ "\u0120budgeting",
+ "\u0120pourtant",
+ "\u00e9\u013c\u00bb",
+ "aisia",
+ "\u0120\u00d0\u00be\u00d1\u0124\u00d0\u00b2\u00d0\u00b5\u00d1\u0129",
+ "\u0120GIS",
+ "\u00ce\u00bc\u00ce\u00b1\u00ce\u00b9",
+ "\u0120\u00d7\u00a9\u00d7\u0136\u00d7\u0137\u00d7\u0132",
+ "\u0120saud",
+ "\u0120l\u00e1\u00bb\u013d",
+ "\u00d0\u0137\u00d0\u00a2",
+ "ubine",
+ "\u0120\u00d0\u00bd\u00d1\u0125\u00d0\u00b6\u00d0\u00b5\u00d0\u00bd",
+ "\u0120kidnapping",
+ "\u0120brat",
+ "\u0120Terre",
+ "\u0120Monet",
+ "\u0120\u00eb\u00a7\u012a\u00ec\u012c\u00a4\u00ed\u0123",
+ "\u0120flashy",
+ "\u0120ISBN",
+ "\u0120freelance",
+ "iage",
+ "\u0120junge",
+ "\u00ec\u00b6\u00a9",
+ "ceral",
+ "\u0120\u00d1\u0124\u00d0\u00be\u00d1\u0129\u00d0\u00ba\u00d0\u00b8",
+ "\u0120formulate",
+ "\u0120FER",
+ "\u0120Dartmouth",
+ "\u00ec\u013e\u00bc\u00eb\u00a9\u00b4\u00ec\u0126\u013e",
+ "\u00e5\u00a2\u0125",
+ "owi\u00c4\u0127",
+ "\u0120\u00eb\u0136\u0136\u00ec\u0140\u0132",
+ "\u0120regiment",
+ "\u0120metabolismo",
+ "\u0120Parr",
+ "\u0120\u00ec\u00b6\u00a9\u00eb\u00b6\u0126",
+ "\u0120sanity",
+ "\u0120Lal",
+ "\u0120G\u00c3\u00b6",
+ "\u0120Gla",
+ "\u0120proto",
+ "\u0120microscopic",
+ "\u0120kang",
+ "\u0120Scalia",
+ "\u0120pug",
+ "\u0120Score",
+ "\u0120Savannah",
+ "\u0120garde",
+ "\u0120NOR",
+ "\u00e5\u00b0\u012f\u00e5\u0132\u00a7",
+ "\u0120scheint",
+ "\u0120p\u00c3\u00b3\u00c5\u0124",
+ "\u0120corri",
+ "\u0120brute",
+ "\u0120\u00c5\u0124ad",
+ "\u00e4\u00bb\u0138\u00e4\u00bb\u00ac",
+ "\u0120succeeding",
+ "\u0120bicycles",
+ "Non",
+ "\u0120seekers",
+ "\u0120unconditional",
+ "\u0120rhymes",
+ "\u0120Garage",
+ "\u0120invoice",
+ "\u0120canvi",
+ "neck",
+ "\u0120customizable",
+ "iritual",
+ "Queen",
+ "\u00ed\u0137\u013a\u00ec\u012d\u013e\u00eb\u012c\u0136",
+ "\u0120powerless",
+ "\u0120csak",
+ "\u00e4\u00b8\u012f\u00e4\u00bc\u013c",
+ "isoft",
+ "\u0120\u00ec\u0142\u0137\u00ed\u013b\u0137",
+ "\u0120nh\u00c3\u00a2n",
+ "\u0120MAND",
+ "\u0120Haf",
+ "\u0120revolves",
+ "\u00e4\u00b9\u0141\u00e5\u0131\u00af\u00e4\u00bb\u00a5",
+ "ovan",
+ "aroo",
+ "\u0120Grind",
+ "\u00e9\u013d\u00aa",
+ "\u0120indispensable",
+ "\u0120consulted",
+ "\u0120Clinical",
+ "Acc",
+ "\u0120olhos",
+ "\u0120monter",
+ "\u0120Hana",
+ "etah",
+ "\u0120vaan",
+ "\u0120tigers",
+ "\u0120caucus",
+ "\u00f0\u0141\u013a\u0124",
+ "\u00b3\u00b4\u00ec\u0140\u0132",
+ "powers",
+ "iums",
+ "\u0120\u00ed\u0128\u0142\u00eb",
+ "\u0120tradicional",
+ "\u0120resonated",
+ "\u0120\u00ec\u012d\u0142\u00ea\u00b8\u00b0",
+ "them",
+ "Robert",
+ "\u0120elemento",
+ "\u0120antid",
+ "\u0120\u00d0\u00be\u00d0\u00b1\u00d1\u0123",
+ "\u0120natives",
+ "\u0120loca",
+ "owment",
+ "\u0120Tight",
+ "\u0120\u00e6\u0122\u013f",
+ "\u0120melan",
+ "\u0120Nue",
+ "amis",
+ "\u0120sorgen",
+ "as\u00c4\u00b1na",
+ "Home",
+ "\u0120PUBG",
+ "\u0120awfully",
+ "\u0120Shore",
+ "\u0120Perch\u00c3\u00a9",
+ "\u0120Lau",
+ "\u0120Cinderella",
+ "\u0120Chest",
+ "\u0120semantic",
+ "\u0120deserted",
+ "\u0120Momo",
+ "\u0120Hernandez",
+ "genes",
+ "\u0120Adult",
+ "\u00d0\u00b8\u00d1\u0129\u00d0\u00b5\u00d1\u0123\u00d0\u00ba\u00d0\u00be\u00d0\u00b3\u00d0\u00be",
+ "oshima",
+ "\u0120caracter\u00c3\u0143sticas",
+ "\u0120KL",
+ "\u00b4\u00ec\u0140\u00a5",
+ "ocar",
+ "\u0120fehlt",
+ "\u0120druk",
+ "\u0120Poppy",
+ "ENGLISH",
+ "\u0120Vergleich",
+ "Brien",
+ "\u0120recomp",
+ "\u0120\u00d1\u0123\u00d0\u00b4",
+ "\u0120merger",
+ "\u0120marketers",
+ "\u0120honeymoon",
+ "\u0120penso",
+ "\u0120belli",
+ "\u00d0\u00b5\u00d1\u0124\u00d1\u0125",
+ "\u0120banker",
+ "Camera",
+ "\u0120Stall",
+ "\u0120Stamp",
+ "\u0120Bite",
+ "\u00d0\u00b5\u00d0\u00b6\u00d0\u00b4\u00d0\u00b5",
+ "\u0120s\u00c3\u00bcr",
+ "\u0120g\u00c3\u00bc\u00c3\u00a7",
+ "\u0120Passover",
+ "\u0120Bug\u00c3\u00bcn",
+ "\u0120\u00d1\u0123\u00d0\u00be\u00d0\u00b6\u00d0\u00b0\u00d0\u00bb\u00d0\u00b5\u00d0\u00bd\u00d0\u00b8\u00d1\u0130",
+ "\u0120\u00d0\u00bd\u00d0\u00b8\u00d0\u00b7",
+ "\u0120manure",
+ "\u0120glacier",
+ "\u00e8\u00ab\u0129",
+ "RAY",
+ "terror",
+ "\u0120salads",
+ "\u0120hurricanes",
+ "\u0120Designer",
+ "atorio",
+ "\u0120factual",
+ "\u0120Tammy",
+ "\u0120\u00d0\u00b7\u00d0\u00b2\u00d1\u0125\u00d1\u0129",
+ "\u0120introductions",
+ "\u0120housekeeping",
+ "\u0120hanger",
+ "\u00eb\u012d\u013a\u00eb",
+ "akte",
+ "\u0120Cola",
+ "']",
+ "\u0120Gender",
+ "\u00d0\u00be\u00d1\u0122\u00d0\u00be\u00d0\u00bd",
+ "ipse",
+ "icias",
+ "\u0120successive",
+ "\u0120politic",
+ "\u0120h\u00c3\u00b6her",
+ "\u0120Qiao",
+ "\u0120Gimme",
+ "\u0120\u00d0\u00bb\u00d0\u00be\u00d0\u00b6",
+ "\u0120seb",
+ "\u0120Weiter",
+ "\u0120Sakura",
+ "\u0120Boulder",
+ "\u0120Am\u00c3\u00a9rica",
+ "pe\u00c5\u0124nie",
+ "\u0120tecnolog\u00c3\u0143a",
+ "ishops",
+ "fur",
+ "\u0120moonlight",
+ "\u0120dispersed",
+ "\u0120rez",
+ "\u00d0\u00b5\u00d0\u00bd\u00d0\u00bd\u00d0\u00be\u00d0\u00b5",
+ "\u00d0\u00b0\u00d0\u00bb\u00d1\u012e\u00d0\u00bd\u00d1\u0125\u00d1\u0130",
+ "\u0120Twelve",
+ "\u0120HOR",
+ "\u00ec\u012d\u00a4\u00ed\u0140\u012a",
+ "ilage",
+ "\u0120shaded",
+ "\u0120resumes",
+ "\u0120Peanut",
+ "\u0120MILL",
+ "apons",
+ "\u0120UFC",
+ "\u0120Sole",
+ "\u0120joystick",
+ "\u0120Olivier",
+ "warming",
+ "\u0120syllabus",
+ "\u0120\u00d0\u00be\u00d0\u00b1\u00d1\u012b\u00d0\u00b5",
+ "\u0120hi\u00e1\u00bb\u0129n",
+ "\u0120festa",
+ "\u0120cradle",
+ "\u0120Zac",
+ "\u0120remembrance",
+ "\u0120\u00ea\u00b0\u013b\u00ec\u0137\u0126\u00ec\u0126\u013e",
+ "\u0120pi\u00c4\u013bk",
+ "\u0120coexist",
+ "\u0120VII",
+ "\u0120\u00c3\u00a1reas",
+ "\u0120uwa\u00c5\u00bc",
+ "\u0120observers",
+ "\u0120m\u00c3\u00a4nniskor",
+ "coon",
+ "\u0120DAM",
+ "\u0120naszym",
+ "\u0120alligator",
+ "\u0120Freeze",
+ "\u0120Estate",
+ "\u0120\u00d1\u0124\u00d1\u0122\u00d0\u00b0\u00d0\u00b4\u00d0\u00b8",
+ "\u0120undercover",
+ "\u0120nies",
+ "\u0120Fehler",
+ "plin",
+ "\u0120Kabul",
+ "ilate",
+ "\u0120\u00ea\u00b3\u0142\u00ec\u0138\u0133",
+ "\u0120mop",
+ "\u00ec\u0126\u00bc",
+ "\u0120anderer",
+ "\u0120KELL",
+ "\u00d0\u00be\u00d0\u00ba\u00d0\u00b8",
+ "\u0120\u00d0\u00b6\u00d0\u00b5\u00d1\u0123\u00d1\u0124",
+ "\u0120grazing",
+ "\u0120da\u00c3\u0143",
+ "\u0120capitalize",
+ "\u0120apex",
+ "\u0120nurturing",
+ "\u0120cortar",
+ "\u0120contrac",
+ "\u00c4\u00b1m\u00c4\u00b1z\u00c4\u00b1",
+ "\u0120tandem",
+ "\u00e9\u0125\u00bd\u00e6\u013e\u012b",
+ "gement",
+ "\u0120\u00d1\u0123\u00d0\u00b8\u00d1\u0123\u00d1\u0124\u00d0\u00b5\u00d0\u00bc\u00d0\u00b0",
+ "\u0120manque",
+ "iaj\u00c4\u0127",
+ "WOR",
+ "\u0120\u00d8\u00a7\u00d8\u00a8",
+ "\u0120carts",
+ "ANO",
+ "\u0120\u00eb\u00b0\u013d\u00ea\u00b3\u0142",
+ "\u0120Cena",
+ "\u0120Biology",
+ "idar",
+ "\u0120a\u00c5\u00bc",
+ "erne",
+ "anu",
+ "\u0120thanked",
+ "\u0120submarines",
+ "\u0120manic",
+ "\u0120\u00d0\u00bc\u00d0\u00be\u00d0\u00b7",
+ "\u00e4\u00bc\u012c",
+ "instant",
+ "essential",
+ "\u0120samurai",
+ "\u0120pasti",
+ "\u0120alan",
+ "\u0120broch",
+ "\u0120baker",
+ "\u0120Guill",
+ "\u00a8\u00bc",
+ "\u0120withdrawn",
+ "\u00eb\u012d\u013f",
+ "Perfect",
+ "quency",
+ "\u0120streamlined",
+ "\u01201300",
+ "\u00b4\u00eb\u0131\u0126",
+ "\u0120\u00eb\u0138\u0142\u00eb",
+ "\u0120\u00e3\u0123\u00af\u00e3\u0123\u0126",
+ "\u0120hvad",
+ "\u00e4\u00b8\u0122\u00e5\u00ae\u013c\u00e8\u00a6\u0123",
+ "\u0120verbally",
+ "\u0120Kons",
+ "\u0120\u00ec\u00a1\u00b0\u00ec\u012d\u00ac",
+ "\u0120diez",
+ "\u00e6\u0130\u00b0\u00e6\u0130\u00b0",
+ "\u0120chuckling",
+ "\u0120Mih",
+ "\u0120rallies",
+ "\u0120manter",
+ "\u0120earnest",
+ "super",
+ "\u0120gece",
+ "\u0120Rend",
+ "\u0120Gerade",
+ "jenigen",
+ "\u0120Vall",
+ "\u0120\u00ec\u0140\u012a\u00eb\u0124\u013a",
+ "\u0120\u00d1\u0123\u00d0\u00ba\u00d0\u00b0\u00d0\u00b7\u00d0\u00b0\u00d0\u00bb\u00d0\u00b0",
+ "\u0120trabalh",
+ "\u0120\u00d0\u00bd\u00d0\u00b0\u00d1\u012a\u00d0\u00b5\u00d0\u00bc",
+ "\u0120\u00d0\u00bc\u00d0\u00b5\u00d1\u0127",
+ "ikit",
+ "\u0120nouns",
+ "\u0120neurological",
+ "\u0120motivational",
+ "\u0120McMahon",
+ "\u0120Finished",
+ "\u0120\u00eb\u00b3\u00b4\u00ec\u013f\u00b4",
+ "\u0120Fields",
+ "\u0120adolescents",
+ "\u0120Tisch",
+ "\u0120Neben",
+ "\u0120Flowers",
+ "\u0120Energ",
+ "\u0120diret",
+ "\u0120Thi",
+ "\u0120Picas",
+ "\u00e6\u0125\u013e",
+ "\u00e6\u0122\u0130\u00e4\u00b9\u012a\u00e6\u0142\u00b7",
+ "\u0120avete",
+ "\u0120Fors",
+ "\u0120Chapel",
+ "N\u00c3\u00a3o",
+ "Et",
+ "\u0120\u00d1\u0123\u00d0\u00be\u00d0\u00b4\u00d0\u00b5\u00d1\u0122\u00d0\u00b6",
+ "reno",
+ "\u0120sven",
+ "\u0120dost\u00c4\u013bp",
+ "nee",
+ "\u0120Snapdragon",
+ "\u0120IDs",
+ "\u00ec\u0137\u013a\u00eb\u012c\u0136\u00eb\u012f\u00b0",
+ "\u00d7\u00a8\u00d7\u013c",
+ "\u0120sunflower",
+ "\u0120perpetual",
+ "\u00e7\u00b3\u0138",
+ "\u0120knights",
+ "\u0120gird",
+ "\u0120Told",
+ "\u0120volcanoes",
+ "\u0120adversary",
+ "\u0120Economy",
+ "\u0120extrapol",
+ "\u0120bluetooth",
+ "\u0120zooming",
+ "\u0120skys",
+ "\u0120genial",
+ "\u00c3\u0143culos",
+ "ambre",
+ "\u0120\u00d0\u00bc\u00d0\u00b5\u00d1\u0122",
+ "\u0120teeny",
+ "\u0120stressing",
+ "\u00ec\u0137\u012e",
+ "ONY",
+ "\u0120translucent",
+ "\u0120rounding",
+ "\u0120grues",
+ "\u00d7\u013b\u00d7\u0142\u00d7\u0136",
+ "apr\u00c3\u00a8s",
+ "\u0120prueba",
+ "\u0120polygon",
+ "\u0120blueberry",
+ "\u0120Programm",
+ "\u0120trenches",
+ "\u0120sebagai",
+ "\u0120palate",
+ "\u0120laude",
+ "\u0120behaved",
+ "\u0120longitudinal",
+ "\u0120Module",
+ "\u0120admir",
+ "\u00ce\u00bb\u00ce\u00b9",
+ "Greg",
+ "\u0120wyst",
+ "\u0120propagate",
+ "\u0120molds",
+ "\u0120Tub",
+ "\u0120Loud",
+ "usto",
+ "\u0120unstoppable",
+ "\u0120reinforcing",
+ "\u00e9\u013f\u0140\u00e5\u00b8\u00b8\u00e7\u013c\u0126",
+ "\u0120\u00d0\u00bf\u00d1\u0122\u00d0\u00be\u00d0\u00b1\u00d0\u00bb\u00d0\u00b5\u00d0\u00bc\u00d0\u00b0",
+ "\u0120potencial",
+ "\u0120hemp",
+ "\u00ec\u0140\u0136",
+ "\u00e0\u00a4\u00af",
+ "\u0120optic",
+ "\u0120erfolgreich",
+ "\u00d1\u0123\u00d1\u012d",
+ "\u00d0\u00be\u00d0\u00bb\u00d1\u012e\u00d1\u012a\u00d0\u00b5",
+ "urst",
+ "\u0120Pois",
+ "\u0120respondents",
+ "\u0120nehme",
+ "\u0120External",
+ "olate",
+ "Hyun",
+ "\u0120quartz",
+ "\u0120mathematician",
+ "\u0120b\u00c3\u00a1sicamente",
+ "\u0120ail",
+ "\u00ec\u0142\u013e\u00eb\u00a5\u00bc",
+ "attutto",
+ "\u0120nooit",
+ "\u0120afflict",
+ "\u0120Olga",
+ "\u00e8\u0143\u00b7",
+ "\u0120\u00d0\u00bd\u00d0\u00b0\u00d1\u0124",
+ "\u0120dites",
+ "\u0120realidade",
+ "\u0120k\u00c3\u00a4n",
+ "\u0120uniqueness",
+ "\u0120padres",
+ "\u0120subsidi",
+ "\u0120pigeons",
+ "\u00ce\u00b2\u00ce\u00b1",
+ "stad",
+ "\u0120deren",
+ "\u0120\u00d0\u00a1\u00d0\u00bb\u00d0\u00b5\u00d0\u00b4",
+ "doo",
+ "\u0120\u00d0\u00be\u00d0\u00bf\u00d0\u00b8\u00d1\u0123\u00d0\u00b0\u00d0\u00bd\u00d0\u00b8\u00d0\u00b8",
+ "\u0120amber",
+ "\u0120goosebumps",
+ "\u0120fr\u00c3\u00a5gor",
+ "\u0120Vital",
+ "\u0120Israelites",
+ "wasser",
+ "Isn",
+ "\u0120commits",
+ "\u0120STEVEN",
+ "\u0120Bev\u00c3\u00b6lker",
+ "uitive",
+ "\u0120legen",
+ "\u0120bruk",
+ "\u00d0\u00b8\u00d1\u0122\u00d0\u00be\u00d0\u00b2\u00d0\u00b0\u00d0\u00bd",
+ "ynen",
+ "helm",
+ "\u0120generational",
+ "\u0120L\u00c3\u00a4ndern",
+ "\u00ce\u00bf\u00ce\u00b9\u00cf\u0122\u00cf\u012e\u00ce\u00bd",
+ "uzu",
+ "\u0120caller",
+ "\u00d0\u00be\u00d0\u00bd\u00d1\u012e",
+ "\u00c3\u00bcm\u00c3\u00bc",
+ "\u0120besar",
+ "\u0120plats",
+ "\u0120migrated",
+ "\u0120jap",
+ "\u0120WAR",
+ "\u0120dissect",
+ "\u0120Zusch",
+ "\u0120Zeiten",
+ "\u0120Lions",
+ "\u0120DF",
+ "\u00e2\u0136",
+ "\u00d0\u00ba\u00d0\u00b8\u00d0\u00b2",
+ "\u0120pedestrians",
+ "\u0120Marilyn",
+ "dock",
+ "\u0120yht",
+ "\u0120reincarn",
+ "\u0120Sono",
+ "\u0120Growth",
+ "\u00d1\u0125\u00d1\u0123\u00d0\u00be\u00d0\u00b2",
+ "\u0120dungeons",
+ "\u0120bagus",
+ "kich",
+ "\u0120\u00d1\u0125\u00d0\u00ba\u00d1\u0122\u00d0\u00b0\u00d1\u0139",
+ "\u00e9\u0128\u00ab",
+ "\u0120Keller",
+ "chemistry",
+ "Japanese",
+ "\u0120willst",
+ "\u0120decomposition",
+ "\u0120\u00d1\u0123\u00d1\u0124\u00d0\u00b5\u00d0\u00bd",
+ "\u0120revived",
+ "\u00ed\u0137\u013b\u00ea\u00b5\u0132",
+ "\u0120\u00c5\u0135",
+ "\u00e4\u00bd\u0132",
+ "\u00ec\u012d\u00b8",
+ "ippy",
+ "\u0120hourly",
+ "j\u00c3\u00a4n",
+ "\u0120Workshop",
+ "\u013f\u00bc\u00ec\u0126\u013e",
+ "\u0120cuarto",
+ "\u0120patrim",
+ "\u0120Burch",
+ "\u0120\u00ec\u0140\u012a\u00ea\u00b8\u00b0",
+ "\u0120hepat",
+ "\u0120h\u00c3\u0142ng",
+ "\u0120\u00eb\u012e\u0122\u00ed\u0137\u00b4",
+ "\u0120\u00d0\u00b2\u00d0\u00b0\u00d1\u012a\u00d0\u00b8",
+ "\u0120rework",
+ "\u0120parse",
+ "\u0120\u00c3\u00a7\u00c4\u00b1kt\u00c4\u00b1",
+ "\u0120Sax",
+ "\u0120Mongo",
+ "\u0120Aaah",
+ "ramble",
+ "DJ",
+ "\u0120stabilized",
+ "\u0120Speech",
+ "Books",
+ "\u0120hurdles",
+ "\u0120WO",
+ "\u0120Lamborg",
+ "\u01201933",
+ "\u0120vorbere",
+ "\u0120clinically",
+ "\u0120breathtaking",
+ "\u0120Gateway",
+ "\u00d0\u00bf\u00d0\u00b5\u00d1\u0122\u00d0\u00b2\u00d1\u012d\u00d1\u0127",
+ "uters",
+ "\u0120\u00eb\u00b9\u00b5",
+ "\u0120yeter",
+ "\u0120pulley",
+ "\u0120muffin",
+ "\u0120Prefer",
+ "\u0120Pence",
+ "\u0120informa\u00c3\u00a7\u00c3\u00a3o",
+ "\u00ec\u012c\u00a4\u00ed\u012c\u00b8\u00eb",
+ "\u00e3\u0124\u00b8\u00e3\u0125\u00a3",
+ "\u0120Turtle",
+ "\u0120Regina",
+ "\u0120Load",
+ "does",
+ "panze",
+ "\u00b8\u0136",
+ "\u0120mina",
+ "\u0120Latinos",
+ "ammers",
+ "\u0120Tort",
+ "\u0120Beyonce",
+ "\u00d0\u00b8\u00d0\u00bc\u00d0\u00be\u00d1\u0123\u00d1\u0124\u00d0\u00b8",
+ "\u0120\u00d0\u00b2\u00d0\u00be\u00d0\u00bf\u00d1\u0122\u00d0\u00be\u00d1\u0123\u00d1\u012d",
+ "\u0120bulun",
+ "\u00e8\u0122\u012e\u00e5\u00b7\u00b2",
+ "inek",
+ "bereich",
+ "\u0120pasture",
+ "\u0120OA",
+ "\u0120Melt",
+ "\u0120Ett",
+ "\u0120DY",
+ "\u0120obwohl",
+ "\u0120leagues",
+ "\u00d1\u0124\u00d0\u00b5\u00d1\u0123\u00d1\u012e",
+ "\u0120\u00d0\u00ba\u00d1\u0125\u00d1\u0123",
+ "\u0120vors",
+ "\u0120topp",
+ "ographical",
+ "asst",
+ "\u0120lindo",
+ "\u0120\u00eb\u00b0\u013f\u00ed\u013a\u0136",
+ "\u0120r\u00c3\u00a9fl",
+ "\u0120climbs",
+ "\u0120varsa",
+ "\u0120methyl",
+ "\u0120Karere",
+ "\u00c6\u00b0\u00e1\u00bb\u0141",
+ "Rad",
+ "\u0120preparedness",
+ "\u00d0\u00be\u00d0\u00bd\u00d1\u0129",
+ "\u0120OD",
+ "\u0120CGI",
+ "\u0120\u00e0\u00a4\u00ae",
+ "\u0120speechless",
+ "\u0120lasci",
+ "\u0120bolag",
+ "\u0120\u00d1\u0127\u00d0\u00be\u00d1\u0129\u00d0\u00b5\u00d1\u0124\u00d1\u0123\u00d1\u0131",
+ "\u0120grieving",
+ "\u0120Johannes",
+ "\u0120Carroll",
+ "adaki",
+ "\u012a\u00ac\u00eb",
+ "\u0120s\u00c5\u0124u",
+ "\u0120innerhalb",
+ "\u0120gymnastics",
+ "\u00d0\u00bf\u00d1\u0122\u00d0\u00b8",
+ "ifiques",
+ "\u0120karate",
+ "\u0120domu",
+ "\u00e3\u0123\u013f\u00e3\u0124\u012e\u00e3\u0123\u00a7",
+ "OTHER",
+ "\u0120demand\u00c3\u00a9",
+ "\u0120booklet",
+ "\u0120Kyoto",
+ "\u0120woh",
+ "\u0120Mar\u00c3\u0143a",
+ "violent",
+ "JE",
+ "\u0120l\u00c3\u00b3g",
+ "\u0120brutally",
+ "cot",
+ "\u0120\u00d9\u0127\u00db\u012e",
+ "\u0120Warsz",
+ "\u00e5\u00ae\u012a",
+ "wol",
+ "\u0120mik\u00c3\u00a4",
+ "\u0120Pronounce",
+ "\u0120Brendan",
+ "\u0120roup",
+ "\u0120italiano",
+ "\u00e5\u00a6\u0124\u00e6\u0143\u00a4",
+ "\u0120\u00d0\u00ba\u00d0\u00be\u00d0\u00bc\u00d0\u00bf\u00d1\u012e\u00d1\u0130\u00d1\u0124",
+ "\u0120urging",
+ "edes",
+ "\u0120carbono",
+ "\u0120Richardson",
+ "\u0120\u00d0\u013f\u00d0\u00b0\u00d1\u0129",
+ "\u0120Trainer",
+ "\u0120Crimea",
+ "\u0120diapers",
+ "\u0120covet",
+ "\u0120Mahar",
+ "\u0120Hutch",
+ "\u0120Ausw",
+ "berty",
+ "\u0120indifferent",
+ "\u00d0\u00ba\u00d1\u0122\u00d0\u00b5\u00d1\u0124",
+ "uldade",
+ "\u0120harms",
+ "\u00a2\u00d9\u0128",
+ "lesia",
+ "\u0120gio",
+ "\u0120Mistress",
+ "\u0120Knox",
+ "\u0120FREE",
+ "\u0120\u00eb\u00a3\u00a8\u00eb",
+ "\u0120\u00d0\u00bd\u00d0\u00b0\u00d1\u012a\u00d0\u00b0",
+ "\u0120invincible",
+ "\u0120maiden",
+ "\u0120Jeez",
+ "\u0120breve",
+ "pole",
+ "\u0120criticisms",
+ "\u0120Rusia",
+ "\u00e0\u00a4\u00ae",
+ "phin",
+ "\u0120Compare",
+ "\u0120BON",
+ "\u0120sneaking",
+ "\u0120Rails",
+ "\u0120Geral",
+ "\u01201953",
+ "Hola",
+ "\u0120\u00d0\u00be\u00d0\u00bf\u00d1\u012d\u00d1\u0124",
+ "\u0120rainforest",
+ "\u0120belum",
+ "\u0120Obi",
+ "\u0120ISS",
+ "\u00e3\u0124\u012e\u00e3\u0123\u00aa\u00e3\u0123\u0126",
+ "\u0120\u00d0\u00a1\u00d0\u00b2",
+ "\u0120blond",
+ "\u0120wzgl",
+ "\u0120powiedzia\u00c5\u0124",
+ "\u0120choking",
+ "\u0120Songs",
+ "\u0120Biraz",
+ "\u0120yells",
+ "\u0120stylist",
+ "\u00cf\u012e\u00cf\u0126\u00ce\u00b5",
+ "\u0120schreiben",
+ "\u0120Jaw",
+ "\u0120Eleven",
+ "\u0120Rif",
+ "/.",
+ "\u0120\u00ec\u013a\u00a4\u00eb\u0140\u013e\u00eb\u00a7\u012e",
+ "\u0120treaties",
+ "uffed",
+ "\u0120\u00e2\u012a\u0134",
+ "\u0120roofs",
+ "\u00e0\u00b9\u0122\u00e0\u00b8\u00aa",
+ "\u0120\u00eb\u00bb",
+ "\u0120sparkle",
+ "\u0120Kiev",
+ "\u0120Argu",
+ "erecht",
+ "\u0120\u00d0\u013f\u00d0\u00b0\u00d0\u00b4\u00d0\u00be",
+ "\u0120FIL",
+ "\u0120molta",
+ "\u0120Devi",
+ "\u0120campe",
+ "\u0120benevol",
+ "\u0120Tough",
+ "\u0120moim",
+ "\u0120evacuate",
+ "\u0120errado",
+ "\u00e5\u00a9\u0128",
+ "\u00d1\u0122\u00d1\u0125\u00d0\u00b3\u00d0\u00be",
+ "\u0120\u00ed\u0130\u013a",
+ "\u0120\u00ce\u0135\u00ce\u00b9\u00ce\u00b1",
+ "\u0120weaken",
+ "\u0120illuminated",
+ "\u0120siglo",
+ "\u0120Vacc",
+ "\u00d0\u00b8\u00d0\u00b5\u00d0\u00b9",
+ "alis",
+ "\u0120\u00d1\u0125\u00d1\u0123\u00d1\u0124\u00d1\u0122\u00d0\u00be\u00d0\u00b9",
+ "\u0120dona",
+ "\u00c5\u0124os",
+ "\u00c3\u00bcman",
+ "\u0120producci\u00c3\u00b3n",
+ "\u0120clot",
+ "\u0120Mango",
+ "\u0120uneasy",
+ "\u0120shuts",
+ "\u0120Examples",
+ "vell",
+ "ebe",
+ "\u0120promptly",
+ "\u0120Teles",
+ "\u0120\u00d0\u00bf\u00d1\u0122\u00d0\u00be\u00d1\u012a\u00d0\u00bb",
+ "\u0120puerta",
+ "\u0120\u00c3\u00bcberzeug",
+ "\u0120coch",
+ "social",
+ "\u0120Benson",
+ "\u0120Meth",
+ "\u0120Exped",
+ "\u0120supplemental",
+ "\u0120conceive",
+ "\u0120\u00d7\u013a\u00d7\u0137\u00d7\u0133",
+ "\u0120captivity",
+ "\u0131\u013b\u00ec\u0137\u012a",
+ "\u0120\u00d1\u0127\u00d1\u0125\u00d0\u00b4",
+ "forming",
+ "\u0120uploads",
+ "\u0120turbulence",
+ "joint",
+ "\u0120satisfactory",
+ "\u0120Anime",
+ "\u0120washes",
+ "\u0120liberals",
+ "\u0120Sunshine",
+ "\u0120REAL",
+ "ublik",
+ "binary",
+ "Tony",
+ "\u0120polarized",
+ "\u0120enriched",
+ "taking",
+ "\u0120\u00eb\u0123\u013f\u00eb\u0124\u013a",
+ "\u0120pleasures",
+ "\u0120extermin",
+ "inese",
+ "atl",
+ "v\u00c3\u00a4r",
+ "\u00d0\u00b0\u00d1\u0122\u00d1\u012d",
+ "\u0120my\u00c5\u013d",
+ "narrator",
+ "\u0120\u00d0\u00be\u00d0\u00b4\u00d0\u00bd\u00d0\u00be\u00d0\u00bc",
+ "\u0120najwi\u00c4\u013b",
+ "\u0120mobilize",
+ "\u0120millor",
+ "\u0120ata",
+ "\u00e6\u00b7\u00b7",
+ "\u0120pol\u00c3\u0143tico",
+ "\u0120plead",
+ "\u0120painters",
+ "\u0120Sow",
+ "\u00d0\u00be\u00d1\u0126",
+ "\u0120\u00ec\u013a\u013d\u00eb\u0124\u0142",
+ "\u0120\u00d1\u0129\u00d1\u0124\u00d0\u00be\u00d0\u00b1",
+ "\u0120sabor",
+ "\u0120Undert",
+ "\u0120JERRY",
+ "\u00c5\u00a1\u00c3\u0143",
+ "\u0120\u00eb\u00b0\u0138\u00ec\u0139\u0132",
+ "\u0120pr\u00c3\u00a9c\u00c3\u00a9d",
+ "\u0120annotation",
+ "\u0120Inaudible",
+ "\u0120textured",
+ "\u0120fisherman",
+ "vordan",
+ "icherung",
+ "\u0120\u00ec\u0142\u0123\u00ec\u013f\u00b4",
+ "\u0120gezeigt",
+ "\u0120mandates",
+ "\u0120beak",
+ "\u0120TWO",
+ "\u0120Akbar",
+ "ilian",
+ "\u0120ti\u00e1\u00ba\u00bfp",
+ "\u0120superiority",
+ "inku",
+ "\u0120lys",
+ "\u0120FCC",
+ "\u0120CPA",
+ "ustering",
+ "nicos",
+ "anja",
+ "\u0120chills",
+ "\u0120Cage",
+ "\u0120sealing",
+ "\u0120sa\u00c3\u00a7",
+ "\u0120dedans",
+ "\u0120Alger",
+ "\u0120spezie",
+ "\u0120coloss",
+ "\u00c4\u00b1y\u00c4\u00b1",
+ "clockwise",
+ "\u0120exactamente",
+ "\u0120iemand",
+ "am\u00c4\u00b1",
+ "\u0120mandar",
+ "raj",
+ "faced",
+ "agua",
+ "\u0120\u00ea\u00b9\u0136\u00eb",
+ "\u0120insbesondere",
+ "\u0120drizzle",
+ "\u0120diminish",
+ "\u0120Yoda",
+ "AI",
+ "\u0120bilmiyorum",
+ "\u0120MMA",
+ "ategory",
+ "\u0120\u00d0\u00bf\u00d0\u00b5\u00d1\u0122\u00d0\u00b5\u00d0\u00bf",
+ "\u0120participar",
+ "\u0120normalized",
+ "\u0120complexities",
+ "\u00e6\u00b4\u00b2",
+ "\u00e6\u0130\u00a7",
+ "\u00d0\u00b0\u00d1\u0122\u00d0\u00be\u00d0\u00b2",
+ "mist",
+ "icha",
+ "Group",
+ "\u0120resiliency",
+ "\u0120nogle",
+ "\u0120CNC",
+ "pr\u00c3\u00bc",
+ "\u0120physicists",
+ "\u00d0\u00bd\u00d0\u00be\u00d0\u00ba",
+ "LI",
+ "\u0120stuffs",
+ "\u0120sistemas",
+ "\u0120interfering",
+ "\u0120Marvin",
+ "\u00c3\u00a9rcito",
+ "\u0120\u00ec\u0139\u0128\u00ea\u00b3\u0142",
+ "\u0120sonic",
+ "\u0120equiv",
+ "\u0120abord",
+ "\u0120Ramen",
+ "\u012009",
+ "medim",
+ "atiques",
+ "\u0120\u00d0\u00b4\u00d0\u00b5\u00d0\u00bb\u00d0\u00b0\u00d1\u0130\u00d1\u0124",
+ "\u0120unanimously",
+ "\u0120skirts",
+ "\u0120\u00ed\u012c\u00b9\u00eb\u00b3\u0126",
+ "\u0120Prix",
+ "kami",
+ "\u0120fruition",
+ "\u0120birthdays",
+ "\u00d0\u00b8\u00d0\u00ba\u00d0\u00be\u00d0\u00bc",
+ "\u0120inaugural",
+ "\u0120correlate",
+ "\u0120Tory",
+ "\u0120\u00eb\u0124\u013a\u00ec\u0123",
+ "\u0120dew",
+ "\u0120Precis",
+ "ihi",
+ "\u0120\u00eb\u00ac\u00b8\u00ec\u0142\u013e\u00ea\u00b0\u0122",
+ "\u0120citing",
+ "\u0120Lana",
+ "\u0120Kag",
+ "\u0120playthrough",
+ "\u0120Protocol",
+ "frist",
+ "hovah",
+ "\u0120merciful",
+ "\u0120bilingual",
+ "\u0120Guitar",
+ "rh",
+ "\u0120glamorous",
+ "\u0120Vikings",
+ "\u0120Ooooh",
+ "\u00ed\u0137\u013a\u00eb\u012c\u0136\u00eb\u012f\u00b0",
+ "\u0120Uganda",
+ "\u0120collapses",
+ "entry",
+ "\u0120antioxidants",
+ "\u00eb\u0124\u013a\u00eb",
+ "\u00d1\u012a\u00d0\u00b0\u00d1\u0131",
+ "\u0120trivia",
+ "\u0120g\u00c3\u00a4ller",
+ "\u0120fungi",
+ "\u0120milks",
+ "\u0120dicht",
+ "\u00ce\u00bc\u00ce\u00b7",
+ "poke",
+ "\u0120\u00d0\u00b2\u00d1\u012d\u00d0\u00bf\u00d1\u0125\u00d1\u0123\u00d0\u00ba",
+ "\u0120feeder",
+ "\u0120Alcohol",
+ "hower",
+ "\u0120deserving",
+ "\u0120Rebel",
+ "iosis",
+ "\u0120103",
+ "\u0120handout",
+ "\u0120enm",
+ "\u0120landlords",
+ "\u0120geology",
+ "rils",
+ "\u0120cobra",
+ "\u0120Vold",
+ "\u0120Panch",
+ "\u0120GREG",
+ "\u0120pross",
+ "\u0120bracelets",
+ "\u0120Vega",
+ "\u0120rozum",
+ "\u00e6\u00ac\u00be",
+ "\u00d0\u00b0\u00d0\u00b7\u00d0\u00b4",
+ "\u0120Lynd",
+ "\u0120Honors",
+ "\u0120surrendered",
+ "\u0120librarians",
+ "125",
+ "\u0120\u00d1\u0123\u00d0\u00b8\u00d0\u00b3",
+ "\u0120uniformly",
+ "\u0120Eagles",
+ "\u00ec\u0137\u013b",
+ "\u00d0\u00b8\u00d1\u0124\u00d0\u00b0\u00d0\u00bd",
+ "andid",
+ "\u0120\u00ec\u0142\u012a\u00eb\u012e\u0122",
+ "\u0120\u00d8\u00b6",
+ "\u0120arrests",
+ "\u0120CSV",
+ "\u0120Azerbaijan",
+ "ortic",
+ "\u0120DX",
+ "\u0120Adventures",
+ "\u0120abus",
+ "\u0120Fau",
+ "\u0120schlimm",
+ "\u0120rattling",
+ "\u0120consumes",
+ "\u0120Tolkien",
+ "\u0120resurrected",
+ "\u0120XY",
+ "\u00ed\u012c\u00b8\u00ea\u00b0\u0122",
+ "\u0120\u00d0\u00b2\u00d1\u012d\u00d1\u0123\u00d1\u0124\u00d1\u0125\u00d0\u00bf",
+ "\u0120Angie",
+ "\u00c5\u00bcenia",
+ "Mic",
+ "\u0120Sheila",
+ "achtet",
+ "\u0120overst",
+ "\u0120l\u00c3\u00a2",
+ "\u0120ineffective",
+ "\u00e6\u013f\u00a1",
+ "\u00e6\u0122\u0130\u00e4\u00b9\u012a\u00e4\u00ba\u0128",
+ "\u00e5\u00bf\u013b",
+ "\u0120wichtiger",
+ "\u0120vino",
+ "\u0120pum",
+ "\u0120angled",
+ "\u0120Pione",
+ "\u0120M\u00e1\u00bb\u00b9",
+ "\u00e3\u0123\u013f\u00e3\u0124\u012e\u00e3\u0123\u00af",
+ "wo\u00c5\u013d\u00c4\u0129",
+ "draw",
+ "\u00e0\u00b8\u00b1\u00e0\u00b9\u012a",
+ "markets",
+ "\u0120cafes",
+ "\u0120Cem",
+ "\u00e2\u013f\u00a4",
+ "\u0120Suit",
+ "MK",
+ "\u0120emphasizes",
+ "\u0120tortilla",
+ "\u0120mejorar",
+ "\u0120Surviv",
+ "casting",
+ "\u0120educaci\u00c3\u00b3n",
+ "\u0120Gum",
+ "uely",
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+ "\u0120stretchy",
+ "en\u00c3\u00a7a",
+ "\u0120withhold",
+ "\u0120exiting",
+ "\u0120enthalpy",
+ "\u0120Transit",
+ "\u00c4\u00b1lm\u00c4\u00b1\u00c5\u0141",
+ "alies",
+ "\u0120salvar",
+ "\u0120leaned",
+ "\u0120gro\u00c3\u0141es",
+ "\u0120fitt",
+ "\u00d0\u00b0\u00d0\u00ba\u00d0\u00b8",
+ "Sarah",
+ "\u0120hostel",
+ "\u0120fingerna",
+ "\u0120nadziej\u00c4\u013b",
+ "wives",
+ "Rec",
+ "\u0120spool",
+ "\u00d0\u00b0\u00d1\u0124\u00d0\u00be\u00d0\u00b2",
+ "\u0120Enemy",
+ "\u0120fury",
+ "\u0120detta",
+ "\u0120Fay",
+ "\u00e9\u013c\u00a8",
+ "\u00d1\u0131\u00d1\u0130\u00d1\u0124",
+ "\u0120aproximadamente",
+ "\u0120silos",
+ "\u0120magist",
+ "\u0120cree",
+ "\u0120Krank",
+ "\u0120DOWN",
+ "\u0120startled",
+ "\u0120reborn",
+ "\u0120Umwelt",
+ "\u0120Suzanne",
+ "\u00d0\u00bd\u00d0\u00b8\u00d1\u0128\u00d1\u012d",
+ "outez",
+ "\u0120JAC",
+ "yards",
+ "radas",
+ "rau",
+ "ipts",
+ "hail",
+ "\u0120paragraphs",
+ "\u0120meglio",
+ "\u0120isolating",
+ "\u0120aceite",
+ "\u0120Harsh",
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+ "\u0120Blockchain",
+ "\u0120\u00d1\u0127\u00d0\u00be\u00d1\u0122\u00d0\u00be\u00d1\u012a\u00d0\u00b8\u00d0\u00b9",
+ "\u0120virtuous",
+ "\u0120investigaci\u00c3\u00b3n",
+ "\u0120devoir",
+ "\u0120masturb",
+ "\u0120Sale",
+ "\u00d9\u012c\u00d8\u00b1\u00d8\u00a9",
+ "\u0120\u00ce\u00a7",
+ "\u0120Stra\u00c3\u0141en",
+ "\u0120dikk",
+ "\u0120afore",
+ "\u0120Jungkook",
+ "\u0120chocia\u00c5\u00bc",
+ "\u0120Debatte",
+ "\u0120weirdly",
+ "\u0120viaje",
+ "regist",
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+ "\u0120kinderen",
+ "\u0120formulated",
+ "\u0120enfim",
+ "\u0120Towards",
+ "\u00d0\u00ba\u00d0\u00be\u00d1\u0139",
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+ "\u0120\u00d0\u00b4\u00d0\u00b5\u00d1\u0124\u00d0\u00b8",
+ "charger",
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+ "\u0120academically",
+ "\u0120Nurse",
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+ "\u0120refusal",
+ "\u0120depicts",
+ "\u0120Dracula",
+ "\u0120toasted",
+ "\u0120Zombie",
+ "\u0120Superior",
+ "\u0120Bold",
+ "\u0120quizzes",
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+ "450",
+ "\u0120come\u00c3\u00a7o",
+ "ynn",
+ "\u0120verst",
+ "\u0120Olaf",
+ "\u0120pomoc",
+ "\u0120Sask",
+ "\u00eb\u013a",
+ "\u0120TCP",
+ "\u0120Property",
+ "\u00ed\u0137\u013a\u00ec\u00a3\u0142",
+ "\u00e0\u00b8\u013e\u00e0\u00b8\u00a1",
+ "boom",
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+ "\u0120\u00d1\u0122\u00d0\u00be\u00d1\u0123\u00d1\u0123\u00d0\u00b8\u00d0\u00b9",
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+ "\u00e5\u0129\u00ba\u00e5\u0130\u00bb",
+ "\u0120\u00ec\u013f\u00b4\u00ec\u0137\u00bc\u00ea\u00b8\u00b0\u00eb\u00a5\u00bc",
+ "\u0120combien",
+ "vacc",
+ "\u0120ebenfalls",
+ "para",
+ "\u0120\u00d0\u00b7\u00d0\u00bc",
+ "\u0120desperation",
+ "ordre",
+ "\u0120\u00d7\u00a9\u00d7\u013e\u00d7\u013b",
+ "\u0120generously",
+ "\u0120\u00d0\u0140\u00d0\u00ba",
+ "\u0120orbiting",
+ ">",
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+ "<|21.80|>",
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+ "<|21.84|>",
+ "<|21.86|>",
+ "<|21.88|>",
+ "<|21.90|>",
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+ "<|21.94|>",
+ "<|21.96|>",
+ "<|21.98|>",
+ "<|22.00|>",
+ "<|22.02|>",
+ "<|22.04|>",
+ "<|22.06|>",
+ "<|22.08|>",
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+ "<|22.12|>",
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+ "<|22.18|>",
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+ "<|22.22|>",
+ "<|22.24|>",
+ "<|22.26|>",
+ "<|22.28|>",
+ "<|22.30|>",
+ "<|22.32|>",
+ "<|22.34|>",
+ "<|22.36|>",
+ "<|22.38|>",
+ "<|22.40|>",
+ "<|22.42|>",
+ "<|22.44|>",
+ "<|22.46|>",
+ "<|22.48|>",
+ "<|22.50|>",
+ "<|22.52|>",
+ "<|22.54|>",
+ "<|22.56|>",
+ "<|22.58|>",
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+ "<|22.62|>",
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+ "<|22.70|>",
+ "<|22.72|>",
+ "<|22.74|>",
+ "<|22.76|>",
+ "<|22.78|>",
+ "<|22.80|>",
+ "<|22.82|>",
+ "<|22.84|>",
+ "<|22.86|>",
+ "<|22.88|>",
+ "<|22.90|>",
+ "<|22.92|>",
+ "<|22.94|>",
+ "<|22.96|>",
+ "<|22.98|>",
+ "<|23.00|>",
+ "<|23.02|>",
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+ "<|23.08|>",
+ "<|23.10|>",
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+ "<|23.14|>",
+ "<|23.16|>",
+ "<|23.18|>",
+ "<|23.20|>",
+ "<|23.22|>",
+ "<|23.24|>",
+ "<|23.26|>",
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+ "<|23.30|>",
+ "<|23.32|>",
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+ "<|23.40|>",
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+ "<|23.48|>",
+ "<|23.50|>",
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+ "<|23.56|>",
+ "<|23.58|>",
+ "<|23.60|>",
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+ "<|23.90|>",
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+ "<|24.24|>",
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+ "<|25.12|>",
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+ "<|29.56|>",
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+ "<|29.62|>",
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+ "<|29.72|>",
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+ "<|29.78|>",
+ "<|29.80|>",
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+ "<|29.84|>",
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+ "<|29.90|>",
+ "<|29.92|>",
+ "<|29.94|>",
+ "<|29.96|>",
+ "<|29.98|>",
+ "<|30.00|>"
+]
\ No newline at end of file
diff --git a/whisper_pipeline/requirements.txt b/whisper_pipeline/requirements.txt
new file mode 100644
index 0000000000000000000000000000000000000000..3a88f890aa0a1fa1acace63d18350ea60b227786
--- /dev/null
+++ b/whisper_pipeline/requirements.txt
@@ -0,0 +1,4 @@
+fastapi==0.111.0
+uvicorn==0.22.0
+pynini
+transformers
\ No newline at end of file
diff --git a/whisper_pipeline/start.sh b/whisper_pipeline/start.sh
new file mode 100644
index 0000000000000000000000000000000000000000..1369f36a16b6df729218617de367426c44d39f51
--- /dev/null
+++ b/whisper_pipeline/start.sh
@@ -0,0 +1,4 @@
+#!/bin/bash
+
+# Start the FastAPI server with uvicorn
+exec uvicorn api:app --host $HOST --port $PORT --forwarded-allow-ips '*'
diff --git a/whisper_pipeline/text_processing/__init__.py b/whisper_pipeline/text_processing/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/whisper_pipeline/text_processing/__pycache__/__init__.cpython-310.pyc b/whisper_pipeline/text_processing/__pycache__/__init__.cpython-310.pyc
new file mode 100644
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new file mode 100644
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diff --git a/whisper_pipeline/text_processing/__pycache__/inverse_normalize.cpython-310.pyc b/whisper_pipeline/text_processing/__pycache__/inverse_normalize.cpython-310.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..dd05920ee8722f7776e856aeaed630d4ddbbb0db
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diff --git a/whisper_pipeline/text_processing/__pycache__/moses_tokenizers.cpython-310.pyc b/whisper_pipeline/text_processing/__pycache__/moses_tokenizers.cpython-310.pyc
new file mode 100644
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diff --git a/whisper_pipeline/text_processing/__pycache__/normalize.cpython-310.pyc b/whisper_pipeline/text_processing/__pycache__/normalize.cpython-310.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..46fbbe86fc118164d0d45308fba4c5087b10d617
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diff --git a/whisper_pipeline/text_processing/__pycache__/token_parser.cpython-310.pyc b/whisper_pipeline/text_processing/__pycache__/token_parser.cpython-310.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..8b79fad405c0a6351323f3b6f5bc30a321ab2665
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diff --git a/whisper_pipeline/text_processing/data_loader_utils.py b/whisper_pipeline/text_processing/data_loader_utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..31a9d68c94ae7be63120983e9832c36e6331d473
--- /dev/null
+++ b/whisper_pipeline/text_processing/data_loader_utils.py
@@ -0,0 +1,241 @@
+# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+
+import json
+import re
+from collections import defaultdict, namedtuple
+from typing import Dict, List, Optional, Set, Tuple
+
+EOS_TYPE = "EOS"
+PUNCT_TYPE = "PUNCT"
+PLAIN_TYPE = "PLAIN"
+Instance = namedtuple('Instance', 'token_type un_normalized normalized')
+known_types = [
+ "PLAIN",
+ "DATE",
+ "CARDINAL",
+ "LETTERS",
+ "VERBATIM",
+ "MEASURE",
+ "DECIMAL",
+ "ORDINAL",
+ "DIGIT",
+ "MONEY",
+ "TELEPHONE",
+ "ELECTRONIC",
+ "FRACTION",
+ "TIME",
+ "ADDRESS",
+]
+
+
+def load_kaggle_text_norm_file(file_path: str) -> List[Instance]:
+ """
+ https://www.kaggle.com/richardwilliamsproat/text-normalization-for-english-russian-and-polish
+ Loads text file in the Kaggle Google text normalization file format: \t\t<`self` if trivial class or normalized text>
+ E.g.
+ PLAIN Brillantaisia
+ PLAIN is
+ PLAIN a
+ PLAIN genus
+ PLAIN of
+ PLAIN plant
+ PLAIN in
+ PLAIN family
+ PLAIN Acanthaceae
+ PUNCT . sil
+
+
+ Args:
+ file_path: file path to text file
+
+ Returns: flat list of instances
+ """
+ res = []
+ with open(file_path, 'r') as fp:
+ for line in fp:
+ parts = line.strip().split("\t")
+ if parts[0] == "":
+ res.append(Instance(token_type=EOS_TYPE, un_normalized="", normalized=""))
+ else:
+ l_type, l_token, l_normalized = parts
+ l_token = l_token.lower()
+ l_normalized = l_normalized.lower()
+
+ if l_type == PLAIN_TYPE:
+ res.append(Instance(token_type=l_type, un_normalized=l_token, normalized=l_token))
+ elif l_type != PUNCT_TYPE:
+ res.append(Instance(token_type=l_type, un_normalized=l_token, normalized=l_normalized))
+ return res
+
+
+def load_files(file_paths: List[str], load_func=load_kaggle_text_norm_file) -> List[Instance]:
+ """
+ Load given list of text files using the `load_func` function.
+
+ Args:
+ file_paths: list of file paths
+ load_func: loading function
+
+ Returns: flat list of instances
+ """
+ res = []
+ for file_path in file_paths:
+ res.extend(load_func(file_path=file_path))
+ return res
+
+
+def clean_generic(text: str) -> str:
+ """
+ Cleans text without affecting semiotic classes.
+
+ Args:
+ text: string
+
+ Returns: cleaned string
+ """
+ text = text.strip()
+ text = text.lower()
+ return text
+
+
+def evaluate(preds: List[str], labels: List[str], input: Optional[List[str]] = None, verbose: bool = True) -> float:
+ """
+ Evaluates accuracy given predictions and labels.
+
+ Args:
+ preds: predictions
+ labels: labels
+ input: optional, only needed for verbosity
+ verbose: if true prints [input], golden labels and predictions
+
+ Returns accuracy
+ """
+ acc = 0
+ nums = len(preds)
+ for i in range(nums):
+ pred_norm = clean_generic(preds[i])
+ label_norm = clean_generic(labels[i])
+ if pred_norm == label_norm:
+ acc = acc + 1
+ else:
+ if input:
+ print(f"inpu: {json.dumps(input[i])}")
+ print(f"gold: {json.dumps(label_norm)}")
+ print(f"pred: {json.dumps(pred_norm)}")
+ return acc / nums
+
+
+def training_data_to_tokens(
+ data: List[Instance], category: Optional[str] = None
+) -> Dict[str, Tuple[List[str], List[str]]]:
+ """
+ Filters the instance list by category if provided and converts it into a map from token type to list of un_normalized and normalized strings
+
+ Args:
+ data: list of instances
+ category: optional semiotic class category name
+
+ Returns Dict: token type -> (list of un_normalized strings, list of normalized strings)
+ """
+ result = defaultdict(lambda: ([], []))
+ for instance in data:
+ if instance.token_type != EOS_TYPE:
+ if category is None or instance.token_type == category:
+ result[instance.token_type][0].append(instance.un_normalized)
+ result[instance.token_type][1].append(instance.normalized)
+ return result
+
+
+def training_data_to_sentences(data: List[Instance]) -> Tuple[List[str], List[str], List[Set[str]]]:
+ """
+ Takes instance list, creates list of sentences split by EOS_Token
+ Args:
+ data: list of instances
+ Returns (list of unnormalized sentences, list of normalized sentences, list of sets of categories in a sentence)
+ """
+ # split data at EOS boundaries
+ sentences = []
+ sentence = []
+ categories = []
+ sentence_categories = set()
+
+ for instance in data:
+ if instance.token_type == EOS_TYPE:
+ sentences.append(sentence)
+ sentence = []
+ categories.append(sentence_categories)
+ sentence_categories = set()
+ else:
+ sentence.append(instance)
+ sentence_categories.update([instance.token_type])
+ un_normalized = [" ".join([instance.un_normalized for instance in sentence]) for sentence in sentences]
+ normalized = [" ".join([instance.normalized for instance in sentence]) for sentence in sentences]
+ return un_normalized, normalized, categories
+
+
+def post_process_punctuation(text: str) -> str:
+ """
+ Normalized quotes and spaces
+
+ Args:
+ text: text
+
+ Returns: text with normalized spaces and quotes
+ """
+ text = (
+ text.replace('( ', '(')
+ .replace(' )', ')')
+ .replace('{ ', '{')
+ .replace(' }', '}')
+ .replace('[ ', '[')
+ .replace(' ]', ']')
+ .replace(' ', ' ')
+ .replace('”', '"')
+ .replace("’", "'")
+ .replace("»", '"')
+ .replace("«", '"')
+ .replace("\\", "")
+ .replace("„", '"')
+ .replace("´", "'")
+ .replace("’", "'")
+ .replace('“', '"')
+ .replace("‘", "'")
+ .replace('`', "'")
+ .replace('- -', "--")
+ )
+
+ for punct in "!,.:;?":
+ text = text.replace(f' {punct}', punct)
+ return text.strip()
+
+
+def pre_process(text: str) -> str:
+ """
+ Adds space around punctuation marks
+
+ Args:
+ text: string that may include semiotic classes
+
+ Returns: text with spaces around punctuation marks
+ """
+ space_both = '*<=>^[]{}'
+ for punct in space_both:
+ text = text.replace(punct, ' ' + punct + ' ')
+
+ text = text.replace('--', ' ' + '--' + ' ')
+ # remove extra space
+ text = re.sub(r' +', ' ', text)
+ return text
diff --git a/whisper_pipeline/text_processing/inverse_normalize.py b/whisper_pipeline/text_processing/inverse_normalize.py
new file mode 100644
index 0000000000000000000000000000000000000000..0c4938213badf6fe97cdfad1614f8e9d06d81560
--- /dev/null
+++ b/whisper_pipeline/text_processing/inverse_normalize.py
@@ -0,0 +1,191 @@
+# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from argparse import ArgumentParser
+from time import perf_counter
+from typing import List
+from difflib import SequenceMatcher
+
+from text_processing.normalize import Normalizer
+from text_processing.token_parser import TokenParser
+
+
+class InverseNormalizer(Normalizer):
+ """
+ Inverse normalizer that converts text from spoken to written form. Useful for ASR postprocessing.
+ Input is expected to have no punctuation outside of approstrophe (') and dash (-) and be lower cased.
+
+ Args:
+ lang: language specifying the ITN
+ cache_dir: path to a dir with .far grammar file. Set to None to avoid using cache.
+ overwrite_cache: set to True to overwrite .far files
+ """
+
+ def __init__(self, lang: str = 'en', cache_dir: str = None, overwrite_cache: bool = False):
+ if lang == 'vi':
+ from text_processing.vi.taggers.tokenize_and_classify import ClassifyFst
+ from text_processing.vi.verbalizers.verbalize_final import VerbalizeFinalFst
+ else:
+ raise NotImplementedError
+
+ self.tagger = ClassifyFst(cache_dir=cache_dir, overwrite_cache=overwrite_cache)
+ self.verbalizer = VerbalizeFinalFst()
+ self.parser = TokenParser()
+
+ def inverse_normalize_list(self, texts: List[str], verbose=False) -> List[str]:
+ """
+ NeMo inverse text normalizer
+
+ Args:
+ texts: list of input strings
+ verbose: whether to print intermediate meta information
+
+ Returns converted list of input strings
+ """
+ return self.normalize_list(texts=texts, verbose=verbose)
+
+ def inverse_normalize(self, text: str, verbose: bool = False) -> str:
+ """
+ Main function. Inverse normalizes tokens from spoken to written form
+ e.g. twelve kilograms -> 12 kg
+
+ Args:
+ text: string that may include semiotic classes
+ verbose: whether to print intermediate meta information
+
+ Returns: written form
+ """
+ chunk_size = 512
+ tokens = text.split()
+ if len(tokens) <= chunk_size:
+ return self.normalize(text=text, verbose=verbose)
+ else:
+ result = ""
+ for i in range(0, len(tokens), chunk_size):
+ sub_text = " ".join(tokens[i: i + chunk_size])
+ result += self.normalize(text=sub_text, verbose=verbose) + " "
+ return result.strip()
+
+ def inverse_normalize_list_with_metadata(self, text_metas: List, verbose=False) -> List[str]:
+ """
+ NeMo inverse text normalizer
+
+ Args:
+ texts: list of input strings
+ verbose: whether to print intermediate meta information
+
+ Returns converted list of input strings
+ """
+ res = []
+ for input in text_metas:
+ try:
+ text = self.inverse_normalize_with_metadata(input, verbose=verbose)
+ except:
+ print(input)
+ raise Exception
+ res.append(text)
+ return res
+
+ def inverse_normalize_with_metadata_text(self, text_meta: str, verbose: bool = False):
+ """
+ Main function. Inverse normalizes tokens from spoken to written form
+ e.g. twelve kilograms -> 12 kg
+
+ Args:
+ text_meta: list of tokens include text, start time, end time and score for each token
+ verbose: whether to print intermediate meta information
+
+ Returns: written form
+ """
+ # text = " ".join([token['text'] for token in text_meta])
+ normalize_text = self.inverse_normalize(text_meta, verbose=verbose)
+ # print(normalize_text)
+ # If no changes are made, return original
+ if text_meta == normalize_text:
+ return text_meta
+
+
+ return normalize_text
+ def inverse_normalize_with_metadata(self, text_meta: List, verbose: bool = False):
+ """
+ Main function. Inverse normalizes tokens from spoken to written form
+ e.g. twelve kilograms -> 12 kg
+
+ Args:
+ text_meta: list of tokens include text, start time, end time and score for each token
+ verbose: whether to print intermediate meta information
+
+ Returns: written form
+ """
+ text = " ".join([token['text'] for token in text_meta])
+ normalize_text = self.inverse_normalize(text, verbose=verbose)
+
+ # If no changes are made, return original
+ if text == normalize_text:
+ return text_meta
+
+ normalize_text_meta = []
+ source_tokens = text.split()
+ target_tokens = normalize_text.split()
+ matcher = SequenceMatcher(None, source_tokens, target_tokens)
+ diffs = list(matcher.get_opcodes())
+
+ for diff in diffs:
+ tag, i1, i2, j1, j2 = diff
+
+ if tag == "equal":
+ normalize_text_meta.extend(text_meta[i1:i2])
+ else:
+ start = text_meta[i1]['start']
+ end = text_meta[i2 - 1]['end']
+ num_target_tokens = j2 - j1
+ time_step = (end - start) / num_target_tokens
+ for c in range(num_target_tokens):
+ normalize_text_meta.append(
+ {
+ 'text': target_tokens[j1 + c],
+ 'start': start,
+ 'end': start + time_step,
+ }
+ )
+ start += time_step
+
+ return normalize_text_meta
+
+
+def parse_args():
+ parser = ArgumentParser()
+ parser.add_argument("input_string", help="input string", type=str)
+ parser.add_argument("--language", help="language", choices=['vi'], default="en", type=str)
+ parser.add_argument("--verbose", help="print info for debugging", action='store_true')
+ parser.add_argument("--overwrite_cache", help="set to True to re-create .far grammar files", action="store_true")
+ parser.add_argument(
+ "--cache_dir",
+ help="path to a dir with .far grammar file. Set to None to avoid using cache",
+ default=None,
+ type=str,
+ )
+ return parser.parse_args()
+
+
+if __name__ == "__main__":
+ args = parse_args()
+ start_time = perf_counter()
+ inverse_normalizer = InverseNormalizer(
+ lang=args.language, cache_dir=args.cache_dir, overwrite_cache=args.overwrite_cache
+ )
+ print(f'Time to generate graph: {round(perf_counter() - start_time, 2)} sec')
+ start_time = perf_counter()
+ print(inverse_normalizer.inverse_normalize(args.input_string, verbose=args.verbose))
+ print(f'Execution time: {round(perf_counter() - start_time, 2)} sec')
diff --git a/whisper_pipeline/text_processing/moses_tokenizers.py b/whisper_pipeline/text_processing/moses_tokenizers.py
new file mode 100644
index 0000000000000000000000000000000000000000..27e91e6c5262490842365f7b07728f61ea5bb8e6
--- /dev/null
+++ b/whisper_pipeline/text_processing/moses_tokenizers.py
@@ -0,0 +1,47 @@
+# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from typing import List
+
+from sacremoses import MosesDetokenizer, MosesPunctNormalizer, MosesTokenizer
+
+
+class MosesProcessor:
+ """
+ Tokenizer, Detokenizer and Normalizer utilities in Moses
+ """
+
+ def __init__(self, lang_id: str):
+ self.moses_tokenizer = MosesTokenizer(lang=lang_id)
+ self.moses_detokenizer = MosesDetokenizer(lang=lang_id)
+ self.normalizer = MosesPunctNormalizer(lang=lang_id)
+
+ def detokenize(self, tokens: List[str]) -> str:
+ """
+ Detokenizes a list of tokens
+ Args:
+ tokens: list of strings as tokens
+ Returns:
+ detokenized string
+ """
+ return self.moses_detokenizer.detokenize(tokens)
+
+ def tokenize(self, text: str):
+ """
+ Tokenizes text using Moses -> Sentencepiece.
+ """
+ return self.moses_tokenizer.tokenize(text, escape=False, return_str=True)
+
+ def normalize(self, text: str):
+ return self.normalizer.normalize(text)
diff --git a/whisper_pipeline/text_processing/normalize.py b/whisper_pipeline/text_processing/normalize.py
new file mode 100644
index 0000000000000000000000000000000000000000..cbfd2a6b06524713e18c7e54bbc8adbc03a7ff8b
--- /dev/null
+++ b/whisper_pipeline/text_processing/normalize.py
@@ -0,0 +1,295 @@
+# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import itertools
+import os
+from argparse import ArgumentParser
+from collections import OrderedDict
+from typing import List
+
+from text_processing.data_loader_utils import post_process_punctuation, pre_process
+from text_processing.token_parser import PRESERVE_ORDER_KEY, TokenParser
+from tqdm import tqdm
+
+try:
+ import pynini
+
+ PYNINI_AVAILABLE = True
+except (ModuleNotFoundError, ImportError):
+ PYNINI_AVAILABLE = False
+
+try:
+ from text_processing.moses_tokenizers import MosesProcessor
+
+ NLP_AVAILABLE = True
+except (ModuleNotFoundError, ImportError):
+ NLP_AVAILABLE = False
+
+
+class Normalizer:
+ """
+ Normalizer class that converts text from written to spoken form.
+ Useful for TTS preprocessing.
+
+ Args:
+ input_case: expected input capitalization
+ lang: language specifying the TN rules, by default: English
+ cache_dir: path to a dir with .far grammar file. Set to None to avoid using cache.
+ overwrite_cache: set to True to overwrite .far files
+ whitelist: path to a file with whitelist replacements
+ """
+
+ def __init__(
+ self,
+ input_case: str,
+ lang: str = 'en',
+ deterministic: bool = True,
+ cache_dir: str = None,
+ overwrite_cache: bool = False,
+ whitelist: str = None,
+ ):
+ raise NotImplementedError
+
+ # self.tagger = ClassifyFst(
+ # input_case=input_case,
+ # deterministic=deterministic,
+ # cache_dir=cache_dir,
+ # overwrite_cache=overwrite_cache,
+ # whitelist=whitelist,
+ # )
+ # self.verbalizer = VerbalizeFinalFst(deterministic=deterministic)
+ # self.parser = TokenParser()
+ # self.lang = lang
+
+ # if NLP_AVAILABLE:
+ # self.processor = MosesProcessor(lang_id=lang)
+ # else:
+ # self.processor = None
+ # print("NeMo NLP is not available. Moses de-tokenization will be skipped.")
+
+ def normalize_list(self, texts: List[str], verbose=False) -> List[str]:
+ """
+ NeMo text normalizer
+
+ Args:
+ texts: list of input strings
+ verbose: whether to print intermediate meta information
+
+ Returns converted list input strings
+ """
+ res = []
+ for input in tqdm(texts):
+ try:
+ text = self.normalize(input, verbose=verbose)
+ except:
+ print(input)
+ raise Exception
+ res.append(text)
+ return res
+
+ def normalize(
+ self, text: str, verbose: bool = False, punct_pre_process: bool = False, punct_post_process: bool = False
+ ) -> str:
+ """
+ Main function. Normalizes tokens from written to spoken form
+ e.g. 12 kg -> twelve kilograms
+
+ Args:
+ text: string that may include semiotic classes
+ verbose: whether to print intermediate meta information
+ punct_pre_process: whether to perform punctuation pre-processing, for example, [25] -> [ 25 ]
+ punct_post_process: whether to normalize punctuation
+
+ Returns: spoken form
+ """
+ if punct_pre_process:
+ text = pre_process(text)
+ text = text.strip()
+ if not text:
+ if verbose:
+ print(text)
+ return text
+ text = pynini.escape(text)
+ tagged_lattice = self.find_tags(text)
+ # if verbose:
+ # print(tagged_lattice)
+ tagged_text = self.select_tag(tagged_lattice)
+ if verbose:
+ print(tagged_text)
+ self.parser(tagged_text)
+ tokens = self.parser.parse()
+ tags_reordered = self.generate_permutations(tokens)
+ for tagged_text in tags_reordered:
+ tagged_text = pynini.escape(tagged_text)
+
+ verbalizer_lattice = self.find_verbalizer(tagged_text)
+ if verbalizer_lattice.num_states() == 0:
+ continue
+ output = self.select_verbalizer(verbalizer_lattice)
+ if punct_post_process:
+ output = post_process_punctuation(output)
+ # do post-processing based on Moses detokenizer
+ if self.processor:
+ output = self.processor.detokenize([output])
+ return output
+ raise ValueError()
+
+ def _permute(self, d: OrderedDict) -> List[str]:
+ """
+ Creates reorderings of dictionary elements and serializes as strings
+
+ Args:
+ d: (nested) dictionary of key value pairs
+
+ Return permutations of different string serializations of key value pairs
+ """
+ l = []
+ if PRESERVE_ORDER_KEY in d.keys():
+ d_permutations = [d.items()]
+ else:
+ d_permutations = itertools.permutations(d.items())
+ for perm in d_permutations:
+ subl = [""]
+ for k, v in perm:
+ if isinstance(v, str):
+ subl = ["".join(x) for x in itertools.product(subl, [f"{k}: \"{v}\" "])]
+ elif isinstance(v, OrderedDict):
+ rec = self._permute(v)
+ subl = ["".join(x) for x in itertools.product(subl, [f" {k} {{ "], rec, [f" }} "])]
+ elif isinstance(v, bool):
+ subl = ["".join(x) for x in itertools.product(subl, [f"{k}: true "])]
+ else:
+ raise ValueError()
+ l.extend(subl)
+ return l
+
+ def generate_permutations(self, tokens: List[dict]):
+ """
+ Generates permutations of string serializations of list of dictionaries
+
+ Args:
+ tokens: list of dictionaries
+
+ Returns string serialization of list of dictionaries
+ """
+
+ def _helper(prefix: str, tokens: List[dict], idx: int):
+ """
+ Generates permutations of string serializations of given dictionary
+
+ Args:
+ tokens: list of dictionaries
+ prefix: prefix string
+ idx: index of next dictionary
+
+ Returns string serialization of dictionary
+ """
+ if idx == len(tokens):
+ yield prefix
+ return
+ token_options = self._permute(tokens[idx])
+ for token_option in token_options:
+ yield from _helper(prefix + token_option, tokens, idx + 1)
+
+ return _helper("", tokens, 0)
+
+ def find_tags(self, text: str) -> 'pynini.FstLike':
+ """
+ Given text use tagger Fst to tag text
+
+ Args:
+ text: sentence
+
+ Returns: tagged lattice
+ """
+ lattice = text @ self.tagger.fst
+ return lattice
+
+ def select_tag(self, lattice: 'pynini.FstLike') -> str:
+ """
+ Given tagged lattice return shortest path
+
+ Args:
+ tagged_text: tagged text
+
+ Returns: shortest path
+ """
+ tagged_text = pynini.shortestpath(lattice, nshortest=1, unique=True).string()
+ return tagged_text
+
+ def find_verbalizer(self, tagged_text: str) -> 'pynini.FstLike':
+ """
+ Given tagged text creates verbalization lattice
+ This is context-independent.
+
+ Args:
+ tagged_text: input text
+
+ Returns: verbalized lattice
+ """
+ lattice = tagged_text @ self.verbalizer.fst
+ return lattice
+
+ def select_verbalizer(self, lattice: 'pynini.FstLike') -> str:
+ """
+ Given verbalized lattice return shortest path
+
+ Args:
+ lattice: verbalization lattice
+
+ Returns: shortest path
+ """
+ output = pynini.shortestpath(lattice, nshortest=1, unique=True).string()
+ return output
+
+
+def parse_args():
+ parser = ArgumentParser()
+ parser.add_argument("input_string", help="input string", type=str)
+ parser.add_argument("--language", help="language", choices=["en"], default="en", type=str)
+ parser.add_argument(
+ "--input_case", help="input capitalization", choices=["lower_cased", "cased"], default="cased", type=str
+ )
+ parser.add_argument("--verbose", help="print info for debugging", action='store_true')
+ parser.add_argument(
+ "--punct_post_process", help="set to True to enable punctuation post processing", action="store_true"
+ )
+ parser.add_argument(
+ "--punct_pre_process", help="set to True to enable punctuation pre processing", action="store_true"
+ )
+ parser.add_argument("--overwrite_cache", help="set to True to re-create .far grammar files", action="store_true")
+ parser.add_argument("--whitelist", help="path to a file with with whitelist", default=None, type=str)
+ parser.add_argument(
+ "--cache_dir",
+ help="path to a dir with .far grammar file. Set to None to avoid using cache",
+ default=None,
+ type=str,
+ )
+ return parser.parse_args()
+
+
+if __name__ == "__main__":
+ args = parse_args()
+ whitelist = os.path.abspath(args.whitelist) if args.whitelist else None
+ normalizer = Normalizer(
+ input_case=args.input_case, cache_dir=args.cache_dir, overwrite_cache=args.overwrite_cache, whitelist=whitelist
+ )
+ print(
+ normalizer.normalize(
+ args.input_string,
+ verbose=args.verbose,
+ punct_pre_process=args.punct_pre_process,
+ punct_post_process=args.punct_post_process,
+ )
+ )
diff --git a/whisper_pipeline/text_processing/token_parser.py b/whisper_pipeline/text_processing/token_parser.py
new file mode 100644
index 0000000000000000000000000000000000000000..3a05d4df5b4af36b66297342e9f091079fa360a1
--- /dev/null
+++ b/whisper_pipeline/text_processing/token_parser.py
@@ -0,0 +1,192 @@
+# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import string
+from collections import OrderedDict
+from typing import Dict, List, Union
+
+PRESERVE_ORDER_KEY = "preserve_order"
+EOS = ""
+
+
+class TokenParser:
+ """
+ Parses tokenized/classified text, e.g. 'tokens { money { integer: "20" currency: "$" } } tokens { name: "left"}'
+
+ Args
+ text: tokenized text
+ """
+
+ def __call__(self, text):
+ """
+ Setup function
+
+ Args:
+ text: text to be parsed
+
+ """
+ self.text = text
+ self.len_text = len(text)
+ self.char = text[0] # cannot handle empty string
+ self.index = 0
+
+ def parse(self) -> List[dict]:
+ """
+ Main function. Implements grammar:
+ A -> space F space F space F ... space
+
+ Returns list of dictionaries
+ """
+ l = list()
+ while self.parse_ws():
+ token = self.parse_token()
+ if not token:
+ break
+ l.append(token)
+ return l
+
+ def parse_token(self) -> Dict[str, Union[str, dict]]:
+ """
+ Implements grammar:
+ F-> no_space KG no_space
+
+ Returns: K, G as dictionary values
+ """
+ d = OrderedDict()
+ key = self.parse_string_key()
+ if key is None:
+ return None
+ self.parse_ws()
+ if key == PRESERVE_ORDER_KEY:
+ self.parse_char(":")
+ self.parse_ws()
+ value = self.parse_chars("true")
+ else:
+ value = self.parse_token_value()
+
+ d[key] = value
+ return d
+
+ def parse_token_value(self) -> Union[str, dict]:
+ """
+ Implements grammar:
+ G-> no_space :"VALUE" no_space | no_space {A} no_space
+
+ Returns: string or dictionary
+ """
+ if self.char == ":":
+ self.parse_char(":")
+ self.parse_ws()
+ self.parse_char("\"")
+ value_string = self.parse_string_value()
+ self.parse_char("\"")
+ return value_string
+ elif self.char == "{":
+ d = OrderedDict()
+ self.parse_char("{")
+ list_token_dicts = self.parse()
+ # flatten tokens
+ for tok_dict in list_token_dicts:
+ for k, v in tok_dict.items():
+ d[k] = v
+ self.parse_char("}")
+ return d
+ else:
+ raise ValueError()
+
+ def parse_char(self, exp) -> bool:
+ """
+ Parses character
+
+ Args:
+ exp: character to read in
+
+ Returns true if successful
+ """
+ assert self.char == exp
+ self.read()
+ return True
+
+ def parse_chars(self, exp) -> bool:
+ """
+ Parses characters
+
+ Args:
+ exp: characters to read in
+
+ Returns true if successful
+ """
+ ok = False
+ for x in exp:
+ ok |= self.parse_char(x)
+ return ok
+
+ def parse_string_key(self) -> str:
+ """
+ Parses string key, can only contain ascii and '_' characters
+
+ Returns parsed string key
+ """
+ assert self.char not in string.whitespace and self.char != EOS
+ incl_criterium = string.ascii_letters + "_"
+ l = []
+ while self.char in incl_criterium:
+ l.append(self.char)
+ if not self.read():
+ raise ValueError()
+
+ if not l:
+ return None
+ return "".join(l)
+
+ def parse_string_value(self) -> str:
+ """
+ Parses string value, ends with quote followed by space
+
+ Returns parsed string value
+ """
+ assert self.char not in string.whitespace and self.char != EOS
+ l = []
+ while self.char != "\"" or self.text[self.index + 1] != " ":
+ l.append(self.char)
+ if not self.read():
+ raise ValueError()
+
+ if not l:
+ return None
+ return "".join(l)
+
+ def parse_ws(self):
+ """
+ Deletes whitespaces.
+
+ Returns true if not EOS after parsing
+ """
+ not_eos = self.char != EOS
+ while not_eos and self.char == " ":
+ not_eos = self.read()
+ return not_eos
+
+ def read(self):
+ """
+ Reads in next char.
+
+ Returns true if not EOS
+ """
+ if self.index < self.len_text - 1: # should be unique
+ self.index += 1
+ self.char = self.text[self.index]
+ return True
+ self.char = EOS
+ return False
diff --git a/whisper_pipeline/text_processing/vi/__init__.py b/whisper_pipeline/text_processing/vi/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..071d53b10845a7d8f158398f1bf9607d33c706bd
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/__init__.py
@@ -0,0 +1,32 @@
+# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from text_processing.vi.taggers.tokenize_and_classify import ClassifyFst
+from text_processing.vi.verbalizers.verbalize import VerbalizeFst
+from text_processing.vi.verbalizers.verbalize_final import VerbalizeFinalFst
+
+import logging
+
+try:
+ import pynini
+
+ PYNINI_AVAILABLE = True
+except (ModuleNotFoundError, ImportError):
+ logging.warning(
+ "`pynini` is not installed ! \n"
+ "Please run the `text_processing/setup.sh` script"
+ "prior to usage of this toolkit."
+ )
+
+ PYNINI_AVAILABLE = False
diff --git a/whisper_pipeline/text_processing/vi/__pycache__/__init__.cpython-310.pyc b/whisper_pipeline/text_processing/vi/__pycache__/__init__.cpython-310.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..c0b96002a3bf3cf2f2f91e9e1f1ac68639cac847
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new file mode 100644
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diff --git a/whisper_pipeline/text_processing/vi/__pycache__/graph_utils.cpython-310.pyc b/whisper_pipeline/text_processing/vi/__pycache__/graph_utils.cpython-310.pyc
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new file mode 100644
index 0000000000000000000000000000000000000000..f42e3bf9b5a5b16224b56ed6a8d29ad47a39ddd2
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diff --git a/whisper_pipeline/text_processing/vi/__pycache__/utils.cpython-38.pyc b/whisper_pipeline/text_processing/vi/__pycache__/utils.cpython-38.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..2f75cde60ed613dca57792be0d705f71e8214216
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diff --git a/whisper_pipeline/text_processing/vi/data/__init__.py b/whisper_pipeline/text_processing/vi/data/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..bc443be41c4c3fcf0764eb9fd3e1828d63f8438c
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/data/__init__.py
@@ -0,0 +1,13 @@
+# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
diff --git a/whisper_pipeline/text_processing/vi/data/currency.tsv b/whisper_pipeline/text_processing/vi/data/currency.tsv
new file mode 100644
index 0000000000000000000000000000000000000000..7346ffdc4c8ce057c1e405df07afcaa1c4713de9
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/data/currency.tsv
@@ -0,0 +1,11 @@
+$ usd
+$ đô la
+$ đô la mỹ
+€ euro
+€ ơ rô
+₩ won
+₩ uôn
+RM ringgit
+RM ring gít
+RM rinh gít
+VND việt nam đồng
\ No newline at end of file
diff --git a/whisper_pipeline/text_processing/vi/data/electronic/__init__.py b/whisper_pipeline/text_processing/vi/data/electronic/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..bc443be41c4c3fcf0764eb9fd3e1828d63f8438c
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/data/electronic/__init__.py
@@ -0,0 +1,13 @@
+# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
diff --git a/whisper_pipeline/text_processing/vi/data/electronic/domain.tsv b/whisper_pipeline/text_processing/vi/data/electronic/domain.tsv
new file mode 100644
index 0000000000000000000000000000000000000000..c56c252adbea808bdc263c5752ad20d364af95a0
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/data/electronic/domain.tsv
@@ -0,0 +1,11 @@
+com
+uk
+fr
+net
+br
+in
+ru
+de
+it
+vn
+edu
\ No newline at end of file
diff --git a/whisper_pipeline/text_processing/vi/data/electronic/server_name.tsv b/whisper_pipeline/text_processing/vi/data/electronic/server_name.tsv
new file mode 100644
index 0000000000000000000000000000000000000000..4eadcaf5915a7546c523f9bdc62bcec47295513c
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/data/electronic/server_name.tsv
@@ -0,0 +1,16 @@
+g mail gmail
+gmail
+n vidia nvidia
+nvidia
+outlook
+hotmail
+yahoo
+aol
+gmx
+msn
+live
+yandex
+orange
+wanadoo
+web
+comcast
\ No newline at end of file
diff --git a/whisper_pipeline/text_processing/vi/data/electronic/symbols.tsv b/whisper_pipeline/text_processing/vi/data/electronic/symbols.tsv
new file mode 100644
index 0000000000000000000000000000000000000000..eccbe3d475124e813edd9571d04fd0e608ffdbbd
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/data/electronic/symbols.tsv
@@ -0,0 +1,20 @@
+. chấm
+- gạch
+_ gạch dưới
+_ shift gạch
+_ síp gạch
+! chấm than
+# thăng
+$ đô
+% phần trăm
+& và
+* sao
+: hai chấm
++ cộng
+/ sẹc
+= bằng
+? chấm hỏi
+? hỏi chấm
+^ mũ
+| hoặc
+, phẩy
\ No newline at end of file
diff --git a/whisper_pipeline/text_processing/vi/data/magnitudes.tsv b/whisper_pipeline/text_processing/vi/data/magnitudes.tsv
new file mode 100644
index 0000000000000000000000000000000000000000..727dc567011cbd36724dbdf7a7f91629a95ff5d3
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/data/magnitudes.tsv
@@ -0,0 +1,5 @@
+k nghìn
+k ngàn
+m triệu
+b tỉ
+b tỷ
\ No newline at end of file
diff --git a/whisper_pipeline/text_processing/vi/data/math/symbols.tsv b/whisper_pipeline/text_processing/vi/data/math/symbols.tsv
new file mode 100644
index 0000000000000000000000000000000000000000..2475c6ec39b8f27ce0b30da16c68b7cc257cee27
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/data/math/symbols.tsv
@@ -0,0 +1,10 @@
+% phần trăm
+& và
+* nhân
+* sao
++ cộng
+- trừ
+/ chia
+= bằng
+^ mũ
+| hoặc
\ No newline at end of file
diff --git a/whisper_pipeline/text_processing/vi/data/measurements.tsv b/whisper_pipeline/text_processing/vi/data/measurements.tsv
new file mode 100644
index 0000000000000000000000000000000000000000..fc62b107cedc6456fe0ea2313201b06172fb7166
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/data/measurements.tsv
@@ -0,0 +1,184 @@
+°f fahrenheit
+°f độ f
+°c celsius
+°c độ c
+km kilomet
+km ki lô met
+km ki lô mét
+km kilô mét
+km kilo mét
+m met
+m mét
+cm centimet
+cm cen ti mét
+cm xen ti mét
+cm xăng ti mét
+mm millimet
+mm mi li mét
+mm mili mét
+ha hecta
+ha héc ta
+mi mile
+m² met vuông
+m² mét vuông
+km² kilomet vuông
+km² ki lô met vuông
+km² kilo mét vuông
+km² ki lô mét vuông
+ft foot
+% phần trăm
+hz héc
+hz hẹc
+kw kilowatt
+kw kilo watt
+kw ki lô watt
+kw ki lô oát
+kw ki lô goát
+hp mã lực
+mg milligram
+mg milli gram
+mg mi li gram
+mg mi li gam
+mg mili gam
+kg kilogram
+kg kilo gram
+kg ki lô gram
+kg kilo gam
+kg ki lô gam
+kg kí lô
+ghz giga hẹc
+ghz giga héc
+ghz gi ga héc
+ghz gi ga hẹc
+khz kilo hẹc
+khz kilo héc
+khz ki lô héc
+khz ki lô hẹc
+mhz mega héc
+mhz mega hẹc
+mhz mê ga hẹc
+mhz mê ga héc
+v vôn
+h giờ
+phút phút
+giây giây
+nm nanomet
+nm nano mét
+nm na nô mét
+mA milli ampe
+mA mi li ampe
+mA mi li am pe
+kwh kilowatt giờ
+kwh kilo watt giờ
+kwh ki lô oát giờ
+kwh ki lô goát giờ
+m³ met khối
+m³ mét khối
+cm³ centimet khối
+cm³ cen ti mét khối
+cm³ xen ti mét khối
+cm³ xăng ti mét khối
+tw tera watt
+tw terawatt
+tw te ra watt
+tw tê ra watt
+tw tê ra oát
+tw tê ra goát
+mv milli vôn
+mv mi li vôn
+mw megawatt
+mw mega watt
+mw mê ga watt
+mw mê ga oát
+mw mê ga goát
+μm micromet
+μm micro mét
+μm muy crô mét
+μm mi crô mét
+μm muy cờ rô mét
+μm mi cờ rô mét
+inch inch
+tb terabyte
+tb tera byte
+tb te ra byte
+tb te ra bai
+tb tê ra byte
+tb tê ra bai
+g gram
+g gam
+ω ohm
+ω ôm
+db decibel
+db deci ben
+db đề xi ben
+μg microgram
+μg micro gram
+μg muy crô gram
+μg micro gam
+μg muy crô gam
+μg muy cờ rô gam
+pg petagram
+pg peta gam
+pg pê ta gam
+gb gigabyte
+gb giga byte
+gb giga bai
+gb gi ga byte
+gb gi ga bai
+mb megabyte
+mb mega byte
+mb mega bai
+mb me ga byte
+mb me ga bai
+mb mê ga byte
+mb mê ga bai
+kb kilobyte
+kb kilo byte
+kb kilo bai
+kb ki lô byte
+kb ki lô bai
+kbps kilobit trên giây
+mbps megabit trên giây
+kv kilovolt
+kv kilo vôn
+kv ki lô vôn
+mv megavolt
+mv mega vôn
+mv me ga vôn
+mv mê ga vôn
+yd yard
+rad radian
+gpa giga pascal
+gpa gi ga pascal
+gw gigawatt
+gw giga watt
+gw gi ga watt
+gw gi ga oát
+ns nano giây
+ns na nô giây
+μs micro giây
+μs muy crô giây
+μs muy cờ rô giây
+pa pascal
+ms milli giây
+ms mi li giây
+dm decimet
+dm đề xi mét
+dm³ đề xi mét khối
+dm³ decimet khối
+mm² millimet vuông
+mm² mi li mét vuông
+cm² centimet vuông
+cm² centi mét vuông
+cm² xăng ti mét vuông
+cm² xen ti mét vuông
+pb peta byte
+pb petabyte
+pb pê ta byte
+kcal kilocalories
+kcal kilocalo
+kcal ki lô calo
+l lít
+ml millilit
+ml mili lít
+ml mi li lít
\ No newline at end of file
diff --git a/whisper_pipeline/text_processing/vi/data/months.tsv b/whisper_pipeline/text_processing/vi/data/months.tsv
new file mode 100644
index 0000000000000000000000000000000000000000..93da6892e2ba87903e4769bc9c83f68b9a6aed0d
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/data/months.tsv
@@ -0,0 +1,14 @@
+một 1
+hai 2
+ba 3
+tư 4
+bốn 4
+năm 5
+sáu 6
+bảy 7
+bẩy 7
+tám 8
+chín 9
+mười 10
+mười một 11
+mười hai 12
\ No newline at end of file
diff --git a/whisper_pipeline/text_processing/vi/data/numbers/__init__.py b/whisper_pipeline/text_processing/vi/data/numbers/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..bc443be41c4c3fcf0764eb9fd3e1828d63f8438c
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/data/numbers/__init__.py
@@ -0,0 +1,13 @@
+# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
diff --git a/whisper_pipeline/text_processing/vi/data/numbers/digit.tsv b/whisper_pipeline/text_processing/vi/data/numbers/digit.tsv
new file mode 100644
index 0000000000000000000000000000000000000000..bdac5ded18ff400993bf25b2593c8f91074ab54b
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/data/numbers/digit.tsv
@@ -0,0 +1,10 @@
+một 1
+hai 2
+ba 3
+bốn 4
+năm 5
+sáu 6
+bảy 7
+bẩy 7
+tám 8
+chín 9
\ No newline at end of file
diff --git a/whisper_pipeline/text_processing/vi/data/numbers/hundred.tsv b/whisper_pipeline/text_processing/vi/data/numbers/hundred.tsv
new file mode 100644
index 0000000000000000000000000000000000000000..b2f35ae9fbf3dd092bd26e5f8208fb0fe105f2e8
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/data/numbers/hundred.tsv
@@ -0,0 +1 @@
+trăm
\ No newline at end of file
diff --git a/whisper_pipeline/text_processing/vi/data/numbers/teen.tsv b/whisper_pipeline/text_processing/vi/data/numbers/teen.tsv
new file mode 100644
index 0000000000000000000000000000000000000000..722dc678d4eb0e34f771231e6a188bdee24f0aae
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/data/numbers/teen.tsv
@@ -0,0 +1,11 @@
+mười 10
+mười một 11
+mười hai 12
+mười ba 13
+mười bốn 14
+mười lăm 15
+mười sáu 16
+mười bảy 17
+mười bẩy 17
+mười tám 18
+mười chín 19
\ No newline at end of file
diff --git a/whisper_pipeline/text_processing/vi/data/numbers/thousands.tsv b/whisper_pipeline/text_processing/vi/data/numbers/thousands.tsv
new file mode 100644
index 0000000000000000000000000000000000000000..d2ca259e8be8724ef3691ac07364d7a82dbf16a2
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/data/numbers/thousands.tsv
@@ -0,0 +1,6 @@
+nghìn
+triệu
+tỉ
+nghìn tỉ
+triệu tỉ
+tỉ tỉ
\ No newline at end of file
diff --git a/whisper_pipeline/text_processing/vi/data/numbers/ties.tsv b/whisper_pipeline/text_processing/vi/data/numbers/ties.tsv
new file mode 100644
index 0000000000000000000000000000000000000000..cca1f8008036ae6ae6984222c62b2704882d667c
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/data/numbers/ties.tsv
@@ -0,0 +1,9 @@
+hai 2
+ba 3
+bốn 4
+năm 5
+sáu 6
+bảy 7
+bẩy 7
+tám 8
+chín 9
\ No newline at end of file
diff --git a/whisper_pipeline/text_processing/vi/data/numbers/zero.tsv b/whisper_pipeline/text_processing/vi/data/numbers/zero.tsv
new file mode 100644
index 0000000000000000000000000000000000000000..70d6dcf26ae2f51b2696500e4b86259bee198e21
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/data/numbers/zero.tsv
@@ -0,0 +1 @@
+không 0
\ No newline at end of file
diff --git a/whisper_pipeline/text_processing/vi/data/ordinals/__init__.py b/whisper_pipeline/text_processing/vi/data/ordinals/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..bc443be41c4c3fcf0764eb9fd3e1828d63f8438c
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/data/ordinals/__init__.py
@@ -0,0 +1,13 @@
+# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
diff --git a/whisper_pipeline/text_processing/vi/data/ordinals/digit.tsv b/whisper_pipeline/text_processing/vi/data/ordinals/digit.tsv
new file mode 100644
index 0000000000000000000000000000000000000000..a1403b7ceb4b9fef31bed0962dd90cbbff72bfdd
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/data/ordinals/digit.tsv
@@ -0,0 +1,12 @@
+nhất 1
+nhì 2
+hai 2
+ba 3
+bốn 4
+tư 4
+năm 5
+sáu 6
+bảy 7
+bẩy 7
+tám 8
+chín 9
\ No newline at end of file
diff --git a/whisper_pipeline/text_processing/vi/data/time/__init__.py b/whisper_pipeline/text_processing/vi/data/time/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..bc443be41c4c3fcf0764eb9fd3e1828d63f8438c
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/data/time/__init__.py
@@ -0,0 +1,13 @@
+# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
diff --git a/whisper_pipeline/text_processing/vi/data/time/hours.tsv b/whisper_pipeline/text_processing/vi/data/time/hours.tsv
new file mode 100644
index 0000000000000000000000000000000000000000..48e35fc901305e1249ce2327d2cc05a3df3d5c47
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/data/time/hours.tsv
@@ -0,0 +1,29 @@
+không 0
+một 1
+hai 2
+ba 3
+bốn 4
+năm 5
+sáu 6
+bảy 7
+bẩy 7
+tám 8
+chín 9
+mười 10
+mười một 11
+mười hai 12
+mười ba 13
+mười bốn 14
+mười lăm 15
+mười sáu 16
+mười bảy 17
+mười bẩy 17
+mười tám 18
+mười chín 19
+hai mươi 20
+hai mươi mốt 21
+hai mốt 21
+hai mươi hai 22
+hai hai 22
+hai mươi ba 23
+hai ba 23
\ No newline at end of file
diff --git a/whisper_pipeline/text_processing/vi/data/time/hours_to.tsv b/whisper_pipeline/text_processing/vi/data/time/hours_to.tsv
new file mode 100644
index 0000000000000000000000000000000000000000..a5621957997573ffd0b4e9159c6ecb4906abded3
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/data/time/hours_to.tsv
@@ -0,0 +1,25 @@
+1 0
+2 1
+3 2
+4 3
+5 4
+6 5
+7 6
+8 7
+9 8
+10 9
+11 10
+12 11
+13 12
+14 13
+15 14
+16 15
+17 16
+18 17
+19 18
+20 19
+21 20
+22 21
+23 22
+24 23
+0 23
\ No newline at end of file
diff --git a/whisper_pipeline/text_processing/vi/data/time/hours_to_night.tsv b/whisper_pipeline/text_processing/vi/data/time/hours_to_night.tsv
new file mode 100644
index 0000000000000000000000000000000000000000..1374f45c0f5b0b4bb194074b8e52e96d99cb6bdb
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/data/time/hours_to_night.tsv
@@ -0,0 +1,12 @@
+1 13
+2 14
+3 15
+4 16
+5 17
+6 18
+7 19
+8 20
+9 21
+10 22
+11 23
+12 0
\ No newline at end of file
diff --git a/whisper_pipeline/text_processing/vi/data/time/minutes.tsv b/whisper_pipeline/text_processing/vi/data/time/minutes.tsv
new file mode 100644
index 0000000000000000000000000000000000000000..0d7872b948f46a295b27d11ff5f023a6c38b92d1
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/data/time/minutes.tsv
@@ -0,0 +1,118 @@
+không 0
+một 1
+hai 2
+ba 3
+bốn 4
+năm 5
+sáu 6
+bảy 7
+bẩy 7
+tám 8
+chín 9
+mười 10
+mười một 11
+mười hai 12
+mười ba 13
+mười bốn 14
+mười lăm 15
+mười sáu 16
+mười bảy 17
+mười bẩy 17
+mười tám 18
+mười chín 19
+hai mươi 20
+hai mươi mốt 21
+hai mươi hai 22
+hai mươi ba 23
+hai mươi tư 24
+hai mươi bốn 24
+hai mươi lăm 25
+hai mươi sáu 26
+hai mươi bảy 27
+hai mươi bẩy 27
+hai mươi tám 28
+hai mươi chín 29
+ba mươi 30
+ba mươi mốt 21
+ba mươi hai 22
+ba mươi ba 33
+ba mươi tư 34
+ba mươi bốn 34
+ba mươi lăm 35
+ba mươi sáu 36
+ba mươi bảy 37
+ba mươi bẩy 37
+ba mươi tám 38
+ba mươi chín 39
+bốn mươi 40
+bốn mươi mốt 41
+bốn mươi hai 42
+bốn mươi ba 43
+bốn mươi tư 44
+bốn mươi bốn 44
+bốn mươi lăm 45
+bốn mươi sáu 46
+bốn mươi bảy 47
+bốn mươi bẩy 47
+bốn mươi tám 48
+bốn mươi chín 49
+năm mươi 50
+năm mươi mốt 51
+năm mươi hai 52
+năm mươi ba 53
+năm mươi tư 54
+năm mươi bốn 54
+năm mươi lăm 55
+năm mươi sáu 56
+năm mươi bảy 57
+năm mươi bẩy 57
+năm mươi tám 58
+năm mươi chín 59
+hai mốt 21
+hai hai 22
+hai ba 23
+hai tư 24
+hai bốn 24
+hai lăm 25
+hai năm 25
+hai sáu 26
+hai bảy 27
+hai bẩy 27
+hai tám 28
+hai chín 29
+ba mốt 21
+ba hai 22
+ba ba 33
+ba tư 34
+ba bốn 34
+ba lăm 35
+ba năm 35
+ba sáu 36
+ba bảy 37
+ba bẩy 37
+ba tám 38
+ba chín 39
+bốn mốt 41
+bốn hai 42
+bốn ba 43
+bốn tư 44
+bốn bốn 44
+bốn lăm 45
+bốn năm 45
+bốn sáu 46
+bốn bảy 47
+bốn bẩy 47
+bốn tám 48
+bốn chín 49
+năm mốt 51
+năm hai 52
+năm ba 53
+năm tư 54
+năm bốn 54
+năm lăm 55
+năm năm 55
+năm sáu 56
+năm bảy 57
+năm bẩy 57
+năm tám 58
+năm chín 59
\ No newline at end of file
diff --git a/whisper_pipeline/text_processing/vi/data/time/minutes_to.tsv b/whisper_pipeline/text_processing/vi/data/time/minutes_to.tsv
new file mode 100644
index 0000000000000000000000000000000000000000..bcb3283651c49b4de67cda126be014c2713ab4c2
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/data/time/minutes_to.tsv
@@ -0,0 +1,59 @@
+1 59
+2 58
+3 57
+4 56
+5 55
+6 54
+7 53
+8 52
+9 51
+10 50
+11 49
+12 48
+13 47
+14 46
+15 45
+16 44
+17 43
+18 42
+19 41
+20 40
+21 39
+22 38
+23 37
+24 36
+25 35
+26 34
+27 33
+28 32
+29 31
+30 30
+31 29
+32 28
+33 27
+34 26
+35 25
+36 24
+37 23
+38 22
+39 21
+40 20
+41 19
+42 18
+43 17
+44 16
+45 15
+46 14
+47 13
+48 12
+49 11
+50 10
+51 9
+52 8
+53 7
+54 6
+55 5
+56 4
+57 3
+58 2
+59 1
\ No newline at end of file
diff --git a/whisper_pipeline/text_processing/vi/data/time/time_suffix.tsv b/whisper_pipeline/text_processing/vi/data/time/time_suffix.tsv
new file mode 100644
index 0000000000000000000000000000000000000000..b39a9ef9a92ccb3e54434abe6bd88a802dc6c900
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/data/time/time_suffix.tsv
@@ -0,0 +1,8 @@
+p m p.m.
+pm p.m.
+p.m.
+p.m p.m.
+am a.m.
+a.m.
+a.m a.m.
+a m a.m.
\ No newline at end of file
diff --git a/whisper_pipeline/text_processing/vi/data/time/time_zone.tsv b/whisper_pipeline/text_processing/vi/data/time/time_zone.tsv
new file mode 100644
index 0000000000000000000000000000000000000000..3e0ade467a844e4f040d51c3334341b729432174
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/data/time/time_zone.tsv
@@ -0,0 +1,7 @@
+cst c s t
+cet c e t
+pst p s t
+est e s t
+pt p t
+et e t
+gmt g m t
diff --git a/whisper_pipeline/text_processing/vi/data/whitelist.tsv b/whisper_pipeline/text_processing/vi/data/whitelist.tsv
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/whisper_pipeline/text_processing/vi/graph_utils.py b/whisper_pipeline/text_processing/vi/graph_utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..0b27f03f51f115dcbdcd7d8c3a518568e000f607
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/graph_utils.py
@@ -0,0 +1,187 @@
+# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# Copyright 2015 and onwards Google, Inc.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import os
+import string
+from pathlib import Path
+from typing import Dict
+
+try:
+ import pynini
+ from pynini import Far
+ from pynini.export import export
+ from pynini.lib import byte, pynutil, utf8
+
+ NEMO_CHAR = utf8.VALID_UTF8_CHAR
+
+ NEMO_DIGIT = byte.DIGIT
+ NEMO_LOWER = pynini.union(*string.ascii_lowercase).optimize()
+ NEMO_UPPER = pynini.union(*string.ascii_uppercase).optimize()
+ NEMO_ALPHA = pynini.union(NEMO_LOWER, NEMO_UPPER).optimize()
+ NEMO_ALNUM = pynini.union(NEMO_DIGIT, NEMO_ALPHA).optimize()
+ NEMO_HEX = pynini.union(*string.hexdigits).optimize()
+ NEMO_NON_BREAKING_SPACE = "\u00A0"
+ NEMO_SPACE = " "
+ NEMO_WHITE_SPACE = pynini.union(" ", "\t", "\n", "\r", "\u00A0").optimize()
+ NEMO_NOT_SPACE = pynini.difference(NEMO_CHAR, NEMO_WHITE_SPACE).optimize()
+ NEMO_NOT_QUOTE = pynini.difference(NEMO_CHAR, r'"').optimize()
+
+ NEMO_PUNCT = pynini.union(*map(pynini.escape, string.punctuation)).optimize()
+ NEMO_GRAPH = pynini.union(NEMO_ALNUM, NEMO_PUNCT).optimize()
+
+ NEMO_SIGMA = pynini.closure(NEMO_CHAR)
+
+ delete_space = pynutil.delete(pynini.closure(NEMO_WHITE_SPACE))
+ insert_space = pynutil.insert(" ")
+ delete_extra_space = pynini.cross(pynini.closure(NEMO_WHITE_SPACE, 1), " ")
+
+ # French frequently compounds numbers with hyphen.
+ delete_hyphen = pynutil.delete(pynini.closure("-", 0, 1))
+ insert_hyphen = pynutil.insert("-")
+
+ TO_LOWER = pynini.union(*[pynini.cross(x, y) for x, y in zip(string.ascii_uppercase, string.ascii_lowercase)])
+ TO_UPPER = pynini.invert(TO_LOWER)
+
+ PYNINI_AVAILABLE = True
+except (ModuleNotFoundError, ImportError):
+ # Create placeholders
+ NEMO_CHAR = None
+
+ NEMO_DIGIT = None
+ NEMO_LOWER = None
+ NEMO_UPPER = None
+ NEMO_ALPHA = None
+ NEMO_ALNUM = None
+ NEMO_HEX = None
+ NEMO_NON_BREAKING_SPACE = "\u00A0"
+ NEMO_SPACE = " "
+ NEMO_WHITE_SPACE = None
+ NEMO_NOT_SPACE = None
+ NEMO_NOT_QUOTE = None
+
+ NEMO_PUNCT = None
+ NEMO_GRAPH = None
+
+ NEMO_SIGMA = None
+
+ delete_space = None
+ insert_space = None
+ delete_extra_space = None
+
+ delete_hyphen = None
+ insert_hyphen = None
+
+ TO_LOWER = None
+ TO_UPPER = None
+
+ PYNINI_AVAILABLE = False
+
+
+def generator_main(file_name: str, graphs: Dict[str, pynini.FstLike]):
+ """
+ Exports graph as OpenFst finite state archive (FAR) file with given file name and rule name.
+
+ Args:
+ file_name: exported file name
+ graphs: Mapping of a rule name and Pynini WFST graph to be exported
+ """
+ exporter = export.Exporter(file_name)
+ for rule, graph in graphs.items():
+ exporter[rule] = graph.optimize()
+ exporter.close()
+ print(f"Created {file_name}")
+
+
+def convert_space(fst) -> "pynini.FstLike":
+ """
+ Converts space to nonbreaking space.
+ Used only in tagger grammars for transducing token values within quotes, e.g. name: "hello kitty"
+ This is making transducer significantly slower, so only use when there could be potential spaces within quotes, otherwise leave it.
+
+ Args:
+ fst: input fst
+
+ Returns output fst where breaking spaces are converted to non breaking spaces
+ """
+ return fst @ pynini.cdrewrite(pynini.cross(NEMO_SPACE, NEMO_NON_BREAKING_SPACE), "", "", NEMO_SIGMA)
+
+
+class GraphFst:
+ """
+ Base class for all grammar fsts.
+
+ Args:
+ name: name of grammar class
+ kind: either 'classify' or 'verbalize'
+ deterministic: if True will provide a single transduction option,
+ for False multiple transduction are generated (used for audio-based normalization)
+ """
+
+ def __init__(self, name: str, kind: str, deterministic: bool = True):
+ self.name = name
+ self.kind = str
+ self._fst = None
+ self.deterministic = deterministic
+
+ self.far_path = Path(os.path.dirname(__file__) + "/grammars/" + kind + "/" + name + ".far")
+ if self.far_exist():
+ self._fst = Far(self.far_path, mode="r", arc_type="standard", far_type="default").get_fst()
+
+ def far_exist(self) -> bool:
+ """
+ Returns true if FAR can be loaded
+ """
+ return self.far_path.exists()
+
+ @property
+ def fst(self) -> "pynini.FstLike":
+ return self._fst
+
+ @fst.setter
+ def fst(self, fst):
+ self._fst = fst
+
+ def add_tokens(self, fst) -> "pynini.FstLike":
+ """
+ Wraps class name around to given fst
+
+ Args:
+ fst: input fst
+
+ Returns:
+ Fst: fst
+ """
+ return pynutil.insert(f"{self.name} {{ ") + fst + pynutil.insert(" }")
+
+ def delete_tokens(self, fst) -> "pynini.FstLike":
+ """
+ Deletes class name wrap around output of given fst
+
+ Args:
+ fst: input fst
+
+ Returns:
+ Fst: fst
+ """
+ res = (
+ pynutil.delete(f"{self.name}")
+ + delete_space
+ + pynutil.delete("{")
+ + delete_space
+ + fst
+ + delete_space
+ + pynutil.delete("}")
+ )
+ return res @ pynini.cdrewrite(pynini.cross("\u00A0", " "), "", "", NEMO_SIGMA)
diff --git a/whisper_pipeline/text_processing/vi/taggers/__init__.py b/whisper_pipeline/text_processing/vi/taggers/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..bc443be41c4c3fcf0764eb9fd3e1828d63f8438c
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/taggers/__init__.py
@@ -0,0 +1,13 @@
+# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
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diff --git a/whisper_pipeline/text_processing/vi/taggers/address.py b/whisper_pipeline/text_processing/vi/taggers/address.py
new file mode 100644
index 0000000000000000000000000000000000000000..5591eb755fe2b0413c1bc8f5c9a29d89d753be94
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/taggers/address.py
@@ -0,0 +1,53 @@
+# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
+# Copyright 2015 and onwards Google, Inc.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from text_processing.vi.graph_utils import (
+ GraphFst,
+ delete_space,
+)
+
+
+try:
+ import pynini
+ from pynini.lib import pynutil
+
+ PYNINI_AVAILABLE = True
+except (ModuleNotFoundError, ImportError):
+ PYNINI_AVAILABLE = False
+
+
+class AddressFst(GraphFst):
+ """
+ Finite state transducer for classifying address
+ e.g. hai sẹc ba -> tokens { address { value: "2/3" } }
+ e.g. hai sẹc mười sẹc năm -> tokens { address{ value: "2/10/5" } }
+
+ Args:
+ cardinal: OrdinalFst
+ """
+
+ def __init__(self, cardinal: GraphFst):
+ super().__init__(name="address", kind="classify")
+
+ graph_cardinal = cardinal.graph_no_exception
+
+ split_component = pynini.cross(pynini.union("sẹc", "sẹt"), "/")
+ graph_address = (
+ pynini.closure(graph_cardinal + delete_space + split_component + delete_space, 1) + graph_cardinal
+ )
+ graph = pynutil.insert('value: "') + graph_address + pynutil.insert('"')
+
+ final_graph = self.add_tokens(graph)
+ self.fst = final_graph.optimize()
diff --git a/whisper_pipeline/text_processing/vi/taggers/cardinal.py b/whisper_pipeline/text_processing/vi/taggers/cardinal.py
new file mode 100644
index 0000000000000000000000000000000000000000..6fc6f1bdd1a9c3029ad76c3def5863e33b97ac86
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/taggers/cardinal.py
@@ -0,0 +1,165 @@
+# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
+# Copyright 2015 and onwards Google, Inc.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+
+from text_processing.vi.utils import get_abs_path
+from text_processing.vi.graph_utils import (
+ NEMO_DIGIT,
+ NEMO_SPACE,
+ GraphFst,
+ delete_space,
+)
+
+try:
+ import pynini
+ from pynini.lib import pynutil
+
+ PYNINI_AVAILABLE = True
+except (ModuleNotFoundError, ImportError):
+ PYNINI_AVAILABLE = False
+
+
+class CardinalFst(GraphFst):
+ """
+ Finite state transducer for classifying cardinals
+ e.g. trừ hai mươi ba -> cardinal { integer: "23" negative: "-" } }
+ e.g. hai nghìn lẻ chín -> cardinal { integer: "2009"} }
+ Numbers below ten are not converted.
+ """
+
+ def __init__(self):
+ super().__init__(name="cardinal", kind="classify")
+ graph_zero = pynini.string_file(get_abs_path("data/numbers/zero.tsv"))
+ graph_digit = pynini.string_file(get_abs_path("data/numbers/digit.tsv"))
+ graph_ties = pynini.string_file(get_abs_path("data/numbers/ties.tsv"))
+ graph_teen = pynini.string_file(get_abs_path("data/numbers/teen.tsv"))
+
+ graph_one = pynini.cross("mốt", "1")
+ graph_four = pynini.cross("tư", "4")
+ graph_five = pynini.cross("lăm", "5")
+ graph_half = pynini.cross("rưỡi", "5")
+ graph_hundred = pynini.cross("trăm", "")
+ graph_ten = pynini.cross("mươi", "")
+ zero = pynini.cross(pynini.union("linh", "lẻ"), "0")
+
+ optional_ten = pynini.closure(delete_space + graph_ten, 0, 1)
+ last_digit_exception = pynini.project(pynini.cross("năm", "5"), "input")
+ last_digit = pynini.union(
+ (pynini.project(graph_digit, "input") - last_digit_exception.arcsort()) @ graph_digit,
+ graph_one,
+ graph_four,
+ graph_five,
+ )
+
+ graph_hundred_ties_component = (graph_digit | graph_zero) + delete_space + graph_hundred
+ graph_hundred_ties_component += delete_space
+ graph_hundred_ties_component += pynini.union(
+ graph_teen,
+ (graph_half | graph_four | graph_one) + pynutil.insert("0"),
+ graph_ties + optional_ten + ((delete_space + last_digit) | pynutil.insert("0")),
+ zero + delete_space + (graph_digit | graph_four),
+ pynutil.insert("00"),
+ )
+ graph_hundred_ties_component |= (
+ pynutil.insert("0")
+ + delete_space
+ + pynini.union(
+ graph_teen,
+ graph_ties + delete_space + graph_ten + delete_space + last_digit,
+ graph_ties + delete_space + pynini.union(graph_one, graph_four, graph_five),
+ graph_ties + delete_space + graph_ten + pynutil.insert("0"),
+ zero + delete_space + (graph_digit | graph_four),
+ )
+ )
+ graph_hundred_component = pynini.union(
+ graph_hundred_ties_component,
+ graph_ties + delete_space + graph_digit,
+ pynutil.insert("00") + delete_space + graph_digit
+ )
+
+ graph_hundred_component_at_least_one_none_zero_digit = graph_hundred_component @ (
+ pynini.closure(NEMO_DIGIT) + (NEMO_DIGIT - "0") + pynini.closure(NEMO_DIGIT)
+ )
+ self.graph_hundred_component_at_least_one_none_zero_digit = graph_hundred_component_at_least_one_none_zero_digit
+ graph_hundred_ties_zero = graph_hundred_ties_component | pynutil.insert("000")
+
+ graph_thousands = pynini.union(
+ graph_hundred_component_at_least_one_none_zero_digit
+ + delete_space
+ + pynutil.delete(pynini.union("nghìn", "ngàn")),
+ pynutil.insert("000", weight=0.1),
+ )
+
+ graph_ten_thousand = pynini.union(
+ graph_hundred_component_at_least_one_none_zero_digit + delete_space + pynutil.delete("vạn"),
+ pynutil.insert("0000", weight=0.1),
+ )
+
+ graph_ten_thousand_suffix = pynini.union(
+ graph_digit + delete_space + pynutil.delete(pynini.union("nghìn", "ngàn")),
+ pynutil.insert("0", weight=0.1),
+ )
+
+ graph_million = pynini.union(
+ graph_hundred_component_at_least_one_none_zero_digit + delete_space + pynutil.delete("triệu"),
+ pynutil.insert("000", weight=0.1),
+ )
+ graph_billion = pynini.union(
+ graph_hundred_component_at_least_one_none_zero_digit
+ + delete_space
+ + pynutil.delete(pynini.union("tỉ", "tỷ")),
+ pynutil.insert("000", weight=0.1),
+ )
+
+ graph = pynini.union(
+ graph_billion
+ + delete_space
+ + graph_million
+ + delete_space
+ + graph_thousands
+ + delete_space
+ + graph_hundred_ties_zero,
+ graph_ten_thousand + delete_space + graph_ten_thousand_suffix + delete_space + graph_hundred_ties_zero,
+ graph_hundred_component_at_least_one_none_zero_digit
+ + delete_space
+ + pynutil.delete(pynini.union("nghìn", "ngàn"))
+ + delete_space
+ + (((last_digit | graph_half) + pynutil.insert("00")) | graph_hundred_ties_zero),
+ graph_digit,
+ graph_zero,
+ )
+
+ graph = graph @ pynini.union(
+ pynutil.delete(pynini.closure("0")) + pynini.difference(NEMO_DIGIT, "0") + pynini.closure(NEMO_DIGIT),
+ "0",
+ )
+
+ # don't convert cardinals from zero to nine inclusive
+ graph_exception = pynini.project(pynini.union(graph_digit, graph_zero), "input")
+
+ self.graph_no_exception = graph
+
+ self.graph = (pynini.project(graph, "input") - graph_exception.arcsort()) @ graph
+
+ optional_minus_graph = pynini.closure(
+ pynutil.insert("negative: ") + pynini.cross(pynini.union("âm", "trừ"), '"-"') + NEMO_SPACE,
+ 0,
+ 1,
+ )
+
+ final_graph = optional_minus_graph + pynutil.insert('integer: "') + self.graph + pynutil.insert('"')
+
+ final_graph = self.add_tokens(final_graph)
+ self.fst = final_graph.optimize()
diff --git a/whisper_pipeline/text_processing/vi/taggers/date.py b/whisper_pipeline/text_processing/vi/taggers/date.py
new file mode 100644
index 0000000000000000000000000000000000000000..1785346f5093384eaec9040ba7361d628eb97b3a
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/taggers/date.py
@@ -0,0 +1,175 @@
+# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
+# Copyright 2015 and onwards Google, Inc.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from text_processing.vi.utils import get_abs_path
+from text_processing.vi.graph_utils import (
+ GraphFst,
+ delete_extra_space,
+ delete_space,
+)
+
+try:
+ import pynini
+ from pynini.lib import pynutil
+
+ graph_teen = pynini.string_file(get_abs_path("data/numbers/teen.tsv")).optimize()
+ graph_digit = pynini.string_file(get_abs_path("data/numbers/digit.tsv")).optimize()
+ graph_zero = pynini.string_file(get_abs_path("data/numbers/zero.tsv")).optimize()
+ ties_graph = pynini.string_file(get_abs_path("data/numbers/ties.tsv")).optimize()
+
+ PYNINI_AVAILABLE = True
+except (ModuleNotFoundError, ImportError):
+ graph_teen = None
+ graph_digit = None
+ graph_zero = None
+ ties_graph = None
+
+ PYNINI_AVAILABLE = True
+
+
+def _get_month_graph():
+ """
+ Transducer for month, e.g. march -> march
+ """
+ month_graph = pynini.string_file(get_abs_path("data/months.tsv")).optimize()
+ return month_graph
+
+
+def _get_ties_graph():
+ """
+ Transducer for 20-99 e.g
+ hai ba -> 23
+ """
+ graph_one = pynini.cross("mốt", "1")
+ graph_four = pynini.cross("tư", "4")
+ graph_five = pynini.cross("lăm", "5")
+ graph_ten = pynini.cross("mươi", "")
+ optional_ten = pynini.closure(delete_space + graph_ten, 0, 1)
+
+ graph = pynini.union(
+ ties_graph + optional_ten + delete_space + (graph_digit | graph_one | graph_four | graph_five),
+ ties_graph + delete_space + graph_ten + pynutil.insert("0"),
+ )
+ return graph
+
+
+def _get_year_graph():
+ """
+ Transducer for year, e.g. hai không hai mươi -> 2020
+ """
+
+ def _get_digits_graph():
+ zero = pynini.cross((pynini.union("linh", "lẻ")), "0")
+ four = pynini.cross("tư", "4")
+ graph = pynini.union(
+ zero + delete_space + (graph_digit | four),
+ graph_zero + delete_space + graph_digit,
+ )
+ graph.optimize()
+ return graph
+
+ def _get_hundreds_graph(graph_ties, graph_digits):
+ graph = (
+ graph_digit
+ + delete_space
+ + pynutil.delete("trăm")
+ + delete_space
+ + (graph_teen | graph_ties | graph_digits)
+ )
+ return graph
+
+ def _get_thousands_graph(graph_ties, graph_digits):
+ graph_hundred_component = ((graph_digit | graph_zero) + delete_space + pynutil.delete("trăm")) | pynutil.insert(
+ "0"
+ )
+ graph = (
+ graph_digit
+ + delete_space
+ + pynutil.delete(pynini.union("nghìn", "ngàn"))
+ + delete_space
+ + graph_hundred_component
+ + delete_space
+ + (graph_teen | graph_ties | graph_digits)
+ )
+ return graph
+
+ graph_ties = _get_ties_graph()
+ graph_digits = _get_digits_graph()
+ graph_hundreds = _get_hundreds_graph(graph_ties, graph_digits)
+ graph_thousands = _get_thousands_graph(graph_ties, graph_digits)
+ year_graph = (
+ # 20 19, 40 12, 2012, 2 0 0 5, 2 0 17, 938 - assuming no limit on the year
+ graph_digit
+ + delete_space
+ + (graph_digit | graph_zero)
+ + delete_space
+ + (graph_teen | graph_ties | graph_digits)
+ | graph_thousands
+ | graph_hundreds
+ | (graph_digit + pynutil.insert("0") + delete_space + (graph_ties | graph_digits | graph_teen))
+ )
+ year_graph.optimize()
+ return year_graph
+
+
+class DateFst(GraphFst):
+ """
+ Finite state transducer for classifying date,
+ e.g. mười lăm tháng một năm hai nghìn mười hai -> date { day: "15" month: "1" year: "2012" preserve_order: true }
+ e.g. ngày ba mốt tháng mười hai năm một chín chín chín -> date { day: "31" month: "12" year: "2012" preserve_order: true }
+ e.g. năm hai không hai mốt -> date { year: "2021" preserve_order: true }
+
+ Args:
+ cardinal: CardinalFst
+ """
+
+ def __init__(self, cardinal: GraphFst):
+ super().__init__(name="date", kind="classify")
+
+ cardinal_graph = cardinal.graph_no_exception
+ year_graph = _get_year_graph()
+ YEAR_WEIGHT = 0.001
+ year_graph = pynutil.add_weight(year_graph, YEAR_WEIGHT)
+ month_graph = _get_month_graph()
+
+ month_graph = pynutil.insert('month: "') + month_graph + pynutil.insert('"')
+ month_exception = pynini.project(pynini.cross("năm", "5"), "input")
+ month_graph_exception = (pynini.project(month_graph, "input") - month_exception.arcsort()) @ month_graph
+
+ day_graph = pynutil.insert('day: "') + cardinal_graph + pynutil.insert('"')
+ # day_suffix = pynini.union("ngày", "mùng")
+ # optional_day = pynini.closure(day_suffix + delete_space, 0, 1)
+
+ graph_month = pynutil.delete("tháng") + delete_space + month_graph_exception
+ graph_year = (
+ delete_extra_space
+ + pynutil.delete("năm")
+ + delete_extra_space
+ + pynutil.insert('year: "')
+ + pynutil.add_weight(year_graph, -YEAR_WEIGHT)
+ + pynutil.insert('"')
+ )
+ optional_graph_year = pynini.closure(graph_year, 0, 1)
+ graph_my = pynutil.delete("tháng") + delete_space + month_graph + graph_year
+ graph_dmy = (
+ day_graph + delete_space + pynutil.delete("tháng") + delete_extra_space + month_graph + optional_graph_year
+ )
+ graph_year = (
+ pynutil.delete("năm") + delete_extra_space + pynutil.insert('year: "') + year_graph + pynutil.insert('"')
+ )
+
+ final_graph = (graph_dmy | graph_my | graph_month | graph_year) + pynutil.insert(" preserve_order: true")
+ final_graph = self.add_tokens(final_graph)
+ self.fst = final_graph.optimize()
diff --git a/whisper_pipeline/text_processing/vi/taggers/decimal.py b/whisper_pipeline/text_processing/vi/taggers/decimal.py
new file mode 100644
index 0000000000000000000000000000000000000000..b9f7ce9bf95ab0422a6408da63c8355343f12a65
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/taggers/decimal.py
@@ -0,0 +1,135 @@
+# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
+# Copyright 2015 and onwards Google, Inc.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from text_processing.vi.utils import get_abs_path
+from text_processing.vi.graph_utils import (
+ NEMO_DIGIT,
+ GraphFst,
+ delete_extra_space,
+ delete_space,
+)
+
+try:
+ import pynini
+ from pynini.lib import pynutil
+
+ PYNINI_AVAILABLE = True
+except (ModuleNotFoundError, ImportError):
+ PYNINI_AVAILABLE = False
+
+graph_digit = pynini.string_file(get_abs_path("data/numbers/digit.tsv"))
+
+
+def get_quantity(decimal: "pynini.FstLike", cardinal_up_to_hundred: "pynini.FstLike") -> "pynini.FstLike":
+ """
+ Returns FST that transforms either a cardinal or decimal followed by a quantity into a numeral,
+ e.g. một triệu -> integer_part: "1" quantity: "triệu"
+ e.g. một tỷ rưỡi -> integer_part: "1" fractional_part: "5" quantity: "tỷ"
+
+ Args:
+ decimal: decimal FST
+ cardinal_up_to_hundred: cardinal FST
+ """
+ numbers = cardinal_up_to_hundred @ (
+ pynutil.delete(pynini.closure("0")) + pynini.difference(NEMO_DIGIT, "0") + pynini.closure(NEMO_DIGIT)
+ )
+ suffix = pynini.union("triệu", "tỉ", "tỷ", "vạn")
+ graph_four = pynini.cross("tư", "4")
+ graph_one = pynini.cross("mốt", "1")
+ graph_half = pynini.cross("rưỡi", "5")
+ last_digit_exception = pynini.project(pynini.cross("năm", "5"), "input")
+ last_digit = pynini.union(
+ (pynini.project(graph_digit, "input") - last_digit_exception.arcsort()) @ graph_digit,
+ graph_one,
+ graph_four,
+ graph_half,
+ )
+ optional_fraction_graph = pynini.closure(
+ delete_extra_space
+ + pynutil.insert('fractional_part: "')
+ + (last_digit | graph_half | graph_one | graph_four)
+ + pynutil.insert('"'),
+ 0,
+ 1,
+ )
+
+ res = (
+ pynutil.insert('integer_part: "')
+ + numbers
+ + pynutil.insert('"')
+ + delete_extra_space
+ + pynutil.insert('quantity: "')
+ + suffix
+ + pynutil.insert('"')
+ + optional_fraction_graph
+ )
+ res |= (
+ decimal + delete_extra_space + pynutil.insert('quantity: "') + (suffix | "ngàn" | "nghìn") + pynutil.insert('"')
+ )
+ return res
+
+
+class DecimalFst(GraphFst):
+ """
+ Finite state transducer for classifying decimal
+ e.g. âm hai hai phẩy không năm tư năm tỉ -> decimal { negative: "true" integer_part: "22" fractional_part: "054" quantity: "tỉ" }
+ e.g. không chấm ba lăm -> decimal { integer_part: "0" fractional_part: "35" }
+ e.g. một triệu rưỡi -> decimal { integer_part: "1" quantity: "triệu" fractional_part: "5" }
+ Args:
+ cardinal: CardinalFst
+ """
+
+ def __init__(self, cardinal: GraphFst):
+ super().__init__(name="decimal", kind="classify")
+
+ cardinal_graph = cardinal.graph_no_exception
+
+ graph_decimal = graph_digit | pynini.string_file(get_abs_path("data/numbers/zero.tsv"))
+ graph_one = pynini.cross("mốt", "1")
+ graph_four = pynini.cross("tư", "4")
+ graph_five = pynini.cross("lăm", "5")
+
+ graph_decimal = pynini.union(
+ graph_decimal,
+ graph_four,
+ pynini.closure(graph_decimal + delete_space, 1) + (graph_decimal | graph_four | graph_five | graph_one),
+ )
+ self.graph = graph_decimal
+
+ point = pynutil.delete("chấm") | pynutil.delete("phẩy")
+
+ optional_graph_negative = pynini.closure(
+ pynutil.insert("negative: ") + pynini.cross(pynini.union("âm", "trừ"), '"true"') + delete_extra_space,
+ 0,
+ 1,
+ )
+
+ graph_fractional = pynutil.insert('fractional_part: "') + graph_decimal + pynutil.insert('"')
+ graph_integer = pynutil.insert('integer_part: "') + cardinal_graph + pynutil.insert('"')
+ final_graph_wo_sign = (
+ pynini.closure(graph_integer + delete_extra_space, 0, 1) + point + delete_extra_space + graph_fractional
+ )
+ final_graph = optional_graph_negative + final_graph_wo_sign
+
+ self.final_graph_wo_negative = final_graph_wo_sign | get_quantity(
+ final_graph_wo_sign,
+ cardinal.graph_hundred_component_at_least_one_none_zero_digit,
+ )
+ final_graph |= optional_graph_negative + get_quantity(
+ final_graph_wo_sign,
+ cardinal.graph_hundred_component_at_least_one_none_zero_digit,
+ )
+ final_graph = self.add_tokens(final_graph)
+ self.fst = final_graph.optimize()
diff --git a/whisper_pipeline/text_processing/vi/taggers/electronic.py b/whisper_pipeline/text_processing/vi/taggers/electronic.py
new file mode 100644
index 0000000000000000000000000000000000000000..7d359b68b2a2bd350fdecfd612e8ad3f669c067c
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/taggers/electronic.py
@@ -0,0 +1,103 @@
+# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
+# Copyright 2015 and onwards Google, Inc.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from text_processing.vi.utils import get_abs_path
+from text_processing.vi.graph_utils import (
+ NEMO_ALPHA,
+ GraphFst,
+ insert_space,
+)
+
+try:
+ import pynini
+ from pynini.lib import pynutil
+
+ PYNINI_AVAILABLE = True
+except (ModuleNotFoundError, ImportError):
+ PYNINI_AVAILABLE = False
+
+
+class ElectronicFst(GraphFst):
+ """
+ Finite state transducer for classifying electronic: as URLs, email addresses, etc.
+ e.g. c d f một a còng a b c dot e d u -> tokens { electronic { username: "cdf1" domain: "abc.edu" } }
+ """
+
+ def __init__(self):
+ super().__init__(name="electronic", kind="classify")
+
+ delete_extra_space = pynutil.delete(" ")
+ alpha_num = (
+ NEMO_ALPHA
+ | pynini.string_file(get_abs_path("data/numbers/digit.tsv"))
+ | pynini.string_file(get_abs_path("data/numbers/zero.tsv"))
+ )
+
+ symbols = pynini.string_file(get_abs_path("data/electronic/symbols.tsv")).invert()
+
+ accepted_username = alpha_num | symbols
+ process_dot = pynini.cross("chấm", ".")
+ username = (
+ pynutil.insert('username: "')
+ + alpha_num
+ + pynini.closure(delete_extra_space + accepted_username)
+ + pynutil.insert('"')
+ )
+ single_alphanum = pynini.closure(alpha_num + delete_extra_space) + alpha_num
+ server = single_alphanum | pynini.string_file(get_abs_path("data/electronic/server_name.tsv"))
+ domain = single_alphanum | pynini.string_file(get_abs_path("data/electronic/domain.tsv"))
+ multi_domain = (
+ pynini.closure(process_dot + delete_extra_space + domain + delete_extra_space)
+ + process_dot
+ + delete_extra_space
+ + domain
+ )
+ domain_graph = pynutil.insert('domain: "') + server + delete_extra_space + multi_domain + pynutil.insert('"')
+ graph = (
+ username
+ + delete_extra_space
+ + pynutil.delete(pynini.union("a còng", "a móc", "a vòng"))
+ + insert_space
+ + delete_extra_space
+ + domain_graph
+ )
+
+ ############# url ###
+ protocol_end = pynini.cross(pynini.union("w w w", "www"), "www")
+ protocol_start = (pynini.cross("h t t p", "http") | pynini.cross("h t t p s", "https")) + pynini.cross(
+ " hai chấm sẹc sẹc ", "://"
+ )
+ # .com,
+ ending = (
+ delete_extra_space
+ + symbols
+ + delete_extra_space
+ + (domain | pynini.closure(accepted_username + delete_extra_space) + accepted_username)
+ )
+
+ protocol = (
+ pynini.closure(protocol_start, 0, 1)
+ + protocol_end
+ + delete_extra_space
+ + process_dot
+ + pynini.closure(delete_extra_space + accepted_username, 1)
+ + pynini.closure(ending, 1, 2)
+ )
+ protocol = pynutil.insert('protocol: "') + protocol + pynutil.insert('"')
+ graph |= protocol
+ ########
+
+ final_graph = self.add_tokens(graph)
+ self.fst = final_graph.optimize()
diff --git a/whisper_pipeline/text_processing/vi/taggers/fraction.py b/whisper_pipeline/text_processing/vi/taggers/fraction.py
new file mode 100644
index 0000000000000000000000000000000000000000..1ad7826827e671acf81119ecbbe74add5b923b4a
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/taggers/fraction.py
@@ -0,0 +1,68 @@
+# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
+# Copyright 2015 and onwards Google, Inc.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from text_processing.vi.graph_utils import (
+ GraphFst,
+ delete_space,
+ delete_extra_space,
+)
+
+
+try:
+ import pynini
+ from pynini.lib import pynutil
+
+ PYNINI_AVAILABLE = True
+except (ModuleNotFoundError, ImportError):
+ PYNINI_AVAILABLE = False
+
+
+class FractionFst(GraphFst):
+ """
+ Finite state transducer for classifying fraction
+ e.g. 2 phần 3 -> tokens { fraction { numerator: "2" denominator: "3" } }
+ e.g. 2 trên 3 -> tokens { fraction { numerator: "2" denominator: "3" } }
+ e.g. 2 chia 3 -> tokens { fraction { numerator: "2" denominator: "3" } }
+
+ Args:
+ cardinal: OrdinalFst
+ """
+
+ def __init__(self, cardinal: GraphFst):
+ super().__init__(name="fraction", kind="classify")
+ # integer_part # numerator # denominator
+
+ graph_cardinal = cardinal.graph_no_exception
+ graph_four = pynini.cross("tư", "4")
+
+ numerator = pynutil.insert('numerator: "') + graph_cardinal + pynutil.insert('"')
+ fraction_component = pynutil.delete(pynini.union("phần", "trên", "chia"))
+ denominator = pynutil.insert('denominator: "') + (graph_cardinal | graph_four) + pynutil.insert('"')
+
+ graph_fraction_component = numerator + delete_space + fraction_component + delete_extra_space + denominator
+ self.graph_fraction_component = graph_fraction_component
+
+ graph = graph_fraction_component
+ graph = graph.optimize()
+ self.final_graph_wo_negative = graph
+
+ optional_graph_negative = pynini.closure(
+ pynutil.insert("negative: ") + pynini.cross(pynini.union("âm", "trừ"), '"true"') + delete_extra_space,
+ 0,
+ 1,
+ )
+ graph = optional_graph_negative + graph
+ final_graph = self.add_tokens(graph)
+ self.fst = final_graph.optimize()
diff --git a/whisper_pipeline/text_processing/vi/taggers/math.py b/whisper_pipeline/text_processing/vi/taggers/math.py
new file mode 100644
index 0000000000000000000000000000000000000000..f1cd3a36b4f436e81d7772ab3c0f7494c9b64389
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/taggers/math.py
@@ -0,0 +1,94 @@
+# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
+# Copyright 2015 and onwards Google, Inc.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from text_processing.vi.utils import get_abs_path
+from text_processing.vi.graph_utils import (
+ GraphFst,
+ delete_space,
+ delete_extra_space,
+ NEMO_ALPHA,
+)
+
+
+try:
+ import pynini
+ from pynini.lib import pynutil
+
+ PYNINI_AVAILABLE = True
+except (ModuleNotFoundError, ImportError):
+ PYNINI_AVAILABLE = False
+
+
+class MathFst(GraphFst):
+ """
+ Finite state transducer for classifying math equation
+ e.g. x cộng y cộng z -> tokens { math { equation: "x + y + z" } }
+ e.g. hai bình phương cộng trừ năm -> tokens { math { equation: "2² + -5" } }
+
+ Args:
+ cardinal: OrdinalFst
+ """
+
+ def __init__(self, cardinal: GraphFst):
+ super().__init__(name="math", kind="classify")
+ # integer_part # numerator # denominator
+
+ graph_digit = pynini.string_file(get_abs_path("data/numbers/digit.tsv"))
+ graph_zero = pynini.string_file(get_abs_path("data/numbers/zero.tsv"))
+ graph_symbols = pynini.string_file(get_abs_path("data/math/symbols.tsv")).invert()
+ graph_one = pynini.cross("mốt", "1")
+ graph_four = pynini.cross("tư", "4")
+ graph_five = pynini.cross("lăm", "5")
+
+ graph_cardinal = cardinal.graph_no_exception
+ optional_graph_negative = pynini.closure(pynini.cross(pynini.union("âm", "trừ"), "-") + delete_space, 0, 1)
+ optional_graph_power = pynini.closure(
+ delete_space + pynini.cross("bình phương", "²") | delete_space + pynini.cross("lập phương", "³"),
+ 0,
+ 1,
+ )
+
+ graph_digit = graph_digit | graph_zero
+ graph_fraction = pynini.union(
+ graph_digit,
+ graph_four,
+ pynini.closure(graph_digit + delete_space, 1) + (graph_digit | graph_four | graph_five | graph_one),
+ )
+ optional_graph_fraction = pynini.closure(
+ delete_space + pynini.cross(pynini.union("chấm", "phẩy"), ".") + delete_space + graph_fraction,
+ 0,
+ 1,
+ )
+ graph_decimal = graph_cardinal + optional_graph_fraction
+
+ alpha_num = NEMO_ALPHA | graph_decimal
+ graph_equation = (
+ pynini.closure(
+ optional_graph_negative
+ + alpha_num
+ + optional_graph_power
+ + delete_extra_space
+ + graph_symbols
+ + delete_extra_space,
+ 1,
+ )
+ + optional_graph_negative
+ + alpha_num
+ + optional_graph_power
+ )
+
+ graph = pynutil.insert('equation: "') + graph_equation + pynutil.insert('"')
+ final_graph = self.add_tokens(graph)
+ self.fst = final_graph.optimize()
diff --git a/whisper_pipeline/text_processing/vi/taggers/measure.py b/whisper_pipeline/text_processing/vi/taggers/measure.py
new file mode 100644
index 0000000000000000000000000000000000000000..690f77d086d86523d9a3aa28215a0a09663bb985
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/taggers/measure.py
@@ -0,0 +1,109 @@
+# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
+# Copyright 2015 and onwards Google, Inc.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from text_processing.vi.utils import get_abs_path
+from text_processing.vi.graph_utils import (
+ GraphFst,
+ convert_space,
+ delete_extra_space,
+ delete_space,
+)
+
+try:
+ import pynini
+ from pynini.lib import pynutil
+
+ PYNINI_AVAILABLE = True
+except (ModuleNotFoundError, ImportError):
+ PYNINI_AVAILABLE = False
+
+
+class MeasureFst(GraphFst):
+ """
+ Finite state transducer for classifying measure
+ e.g. trừ mười hai ki lô gam -> measure { negative: "true" cardinal { integer: "12" } units: "kg" }
+
+ Args:
+ cardinal: CardinalFst
+ decimal: DecimalFst
+ """
+
+ def __init__(self, cardinal: GraphFst, decimal: GraphFst):
+ super().__init__(name="measure", kind="classify")
+
+ cardinal_graph = cardinal.graph_no_exception
+
+ graph_digit = pynini.string_file(get_abs_path("data/numbers/digit.tsv"))
+ graph_four = pynini.cross("tư", "4")
+ graph_one = pynini.cross("mốt", "1")
+ graph_half = pynini.cross("rưỡi", "5")
+
+ graph_unit = pynini.string_file(get_abs_path("data/measurements.tsv"))
+ graph_unit_singular = pynini.invert(graph_unit) # singular -> abbr
+
+ optional_graph_negative = pynini.closure(
+ pynutil.insert("negative: ") + pynini.cross(pynini.union("âm", "trừ"), '"true"') + delete_extra_space,
+ 0,
+ 1,
+ )
+
+ unit_singular = convert_space(graph_unit_singular)
+ unit_misc = pynutil.insert("/") + pynutil.delete("trên") + delete_space + convert_space(graph_unit_singular)
+
+ unit_singular = (
+ pynutil.insert('units: "')
+ + (unit_singular | unit_misc | pynutil.add_weight(unit_singular + delete_space + unit_misc, 0.01))
+ + pynutil.insert('"')
+ )
+
+ subgraph_decimal = (
+ pynutil.insert("decimal { ")
+ + optional_graph_negative
+ + decimal.final_graph_wo_negative
+ + pynutil.insert(" }")
+ + delete_extra_space
+ + unit_singular
+ )
+
+ subgraph_cardinal = (
+ pynutil.insert("cardinal { ")
+ + optional_graph_negative
+ + pynutil.insert('integer: "')
+ + cardinal_graph
+ + pynutil.insert('"')
+ + pynutil.insert(" }")
+ + delete_extra_space
+ + unit_singular
+ )
+ fraction_graph = (
+ delete_extra_space
+ + pynutil.insert('fractional_part: "')
+ + (graph_digit | graph_half | graph_one | graph_four)
+ + pynutil.insert('"')
+ )
+
+ subgraph_cardinal |= (
+ pynutil.insert("cardinal { ")
+ + optional_graph_negative
+ + pynutil.insert('integer: "')
+ + cardinal_graph
+ + pynutil.insert('" }')
+ + delete_extra_space
+ + unit_singular
+ + fraction_graph
+ )
+ final_graph = subgraph_decimal | subgraph_cardinal
+ final_graph = self.add_tokens(final_graph)
+ self.fst = final_graph.optimize()
diff --git a/whisper_pipeline/text_processing/vi/taggers/money.py b/whisper_pipeline/text_processing/vi/taggers/money.py
new file mode 100644
index 0000000000000000000000000000000000000000..60792e6060218a317cc56b187d1a1744fc39c4b7
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/taggers/money.py
@@ -0,0 +1,81 @@
+# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
+# Copyright 2015 and onwards Google, Inc.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from text_processing.vi.utils import get_abs_path
+from text_processing.vi.graph_utils import (
+ NEMO_DIGIT,
+ GraphFst,
+ convert_space,
+ delete_extra_space,
+)
+
+try:
+ import pynini
+ from pynini.lib import pynutil
+
+ PYNINI_AVAILABLE = True
+except (ModuleNotFoundError, ImportError):
+ PYNINI_AVAILABLE = False
+
+
+class MoneyFst(GraphFst):
+ """
+ Finite state transducer for classifying money
+ e.g. mười hai đô la mỹ -> money { integer_part: "12" currency: "$" }
+ e.g. mười phẩy chín đồng -> money { integer_part: "10.9" currency: "đ" }
+
+ Args:
+ cardinal: CardinalFst
+ decimal: DecimalFst
+ """
+
+ def __init__(self, cardinal: GraphFst, decimal: GraphFst):
+ super().__init__(name="money", kind="classify")
+ # quantity, integer_part, fractional_part, currency
+
+ cardinal_graph = cardinal.graph_no_exception
+ graph_decimal_final = decimal.final_graph_wo_negative
+ graph_half = pynini.cross("rưỡi", "5")
+
+ unit = pynini.string_file(get_abs_path("data/currency.tsv"))
+ unit_singular = pynini.invert(unit)
+
+ graph_unit_singular = pynutil.insert('currency: "') + convert_space(unit_singular) + pynutil.insert('"')
+
+ add_leading_zero_to_double_digit = (NEMO_DIGIT + NEMO_DIGIT) | (pynutil.insert("0") + NEMO_DIGIT)
+
+ # twelve dollars fifty, only after integer
+ optional_cents_suffix = pynini.closure(
+ delete_extra_space
+ + pynutil.insert('fractional_part: "')
+ + (pynutil.add_weight(cardinal_graph @ add_leading_zero_to_double_digit, -0.7) | graph_half)
+ + pynutil.insert('"'),
+ 0,
+ 1,
+ )
+
+ graph_integer = (
+ pynutil.insert('integer_part: "')
+ + cardinal_graph
+ + pynutil.insert('"')
+ + delete_extra_space
+ + graph_unit_singular
+ + optional_cents_suffix
+ )
+
+ graph_decimal = graph_decimal_final + delete_extra_space + graph_unit_singular + optional_cents_suffix
+ final_graph = graph_integer | graph_decimal
+ final_graph = self.add_tokens(final_graph)
+ self.fst = final_graph.optimize()
diff --git a/whisper_pipeline/text_processing/vi/taggers/ordinal.py b/whisper_pipeline/text_processing/vi/taggers/ordinal.py
new file mode 100644
index 0000000000000000000000000000000000000000..d37c55a9a1dbaddc9635ea56d8f04f47808182f6
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/taggers/ordinal.py
@@ -0,0 +1,47 @@
+# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
+# Copyright 2015 and onwards Google, Inc.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from text_processing.vi.utils import get_abs_path
+from text_processing.vi.graph_utils import (
+ delete_space,
+ GraphFst,
+)
+
+try:
+ import pynini
+ from pynini.lib import pynutil
+
+ PYNINI_AVAILABLE = True
+except (ImportError, ModuleNotFoundError):
+ PYNINI_AVAILABLE = False
+
+
+class OrdinalFst(GraphFst):
+ """
+ Finite state transducer for classifying ordinal
+ e.g. thứ nhất -> ordinal { integer: "1" }
+ """
+
+ def __init__(self):
+ super().__init__(name="ordinal", kind="classify")
+
+ graph_digit = pynini.string_file(get_abs_path("data/ordinals/digit.tsv"))
+ graph_ordinal = pynini.cross("thứ", "")
+ graph = graph_digit
+
+ self.graph = graph
+ final_graph = pynutil.insert('integer: "') + graph_ordinal + delete_space + self.graph + pynutil.insert('"')
+ final_graph = self.add_tokens(final_graph)
+ self.fst = final_graph.optimize()
diff --git a/whisper_pipeline/text_processing/vi/taggers/punctuation.py b/whisper_pipeline/text_processing/vi/taggers/punctuation.py
new file mode 100644
index 0000000000000000000000000000000000000000..99ebcab416bcdb9d73af4d42f4cd731744c42418
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/taggers/punctuation.py
@@ -0,0 +1,41 @@
+# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
+# Copyright 2015 and onwards Google, Inc.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from text_processing.vi.graph_utils import GraphFst
+
+try:
+ import pynini
+ from pynini.lib import pynutil
+
+ PYNINI_AVAILABLE = False
+except (ModuleNotFoundError, ImportError):
+ PYNINI_AVAILABLE = False
+
+
+class PunctuationFst(GraphFst):
+ """
+ Finite state transducer for classifying punctuation
+ e.g. a, -> tokens { name: "a" } tokens { name: "," }
+ """
+
+ def __init__(self):
+ super().__init__(name="punctuation", kind="classify")
+
+ s = "!#$%&'()*+,-./:;<=>?@^_`{|}~"
+ punct = pynini.union(*s)
+
+ graph = pynutil.insert('name: "') + punct + pynutil.insert('"')
+
+ self.fst = graph.optimize()
diff --git a/whisper_pipeline/text_processing/vi/taggers/telephone.py b/whisper_pipeline/text_processing/vi/taggers/telephone.py
new file mode 100644
index 0000000000000000000000000000000000000000..f7a332dfa6dd7f021a3fe333a0a569ba0ffb0507
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/taggers/telephone.py
@@ -0,0 +1,62 @@
+# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
+# Copyright 2015 and onwards Google, Inc.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from text_processing.vi.utils import get_abs_path
+from text_processing.vi.graph_utils import (
+ GraphFst,
+ delete_space,
+)
+
+try:
+ import pynini
+ from pynini.lib import pynutil
+
+ PYNINI_AVAILABLE = True
+except (ModuleNotFoundError, ImportError):
+ PYNINI_AVAILABLE = False
+
+
+class TelephoneFst(GraphFst):
+ """
+ Finite state transducer for classifying telephone numbers, e.g.
+ một hai ba một hai ba năm sáu bảy tám -> { number_part: "1231235678" }
+ """
+
+ def __init__(self):
+ super().__init__(name="telephone", kind="classify")
+ graph_zero = pynini.string_file(get_abs_path("data/numbers/zero.tsv"))
+ graph_digit = pynini.string_file(get_abs_path("data/numbers/digit.tsv"))
+ graph_one = pynini.cross("mốt", "1")
+ graph_four = pynini.cross("tư", "4")
+ graph_five = pynini.cross("lăm", "5")
+ digit = graph_digit | graph_zero
+ last_digit_exception = pynini.project(pynini.cross("năm", "5"), "input")
+ last_digit_with_exception = pynini.union(
+ (pynini.project(digit, "input") - last_digit_exception.arcsort()) @ digit,
+ graph_one,
+ graph_four,
+ graph_five,
+ )
+ last_digit = digit | graph_one | graph_four | graph_five
+
+ graph_number_part = pynini.union(
+ pynini.closure(digit + delete_space, 2, 3) + last_digit_with_exception,
+ pynini.closure(digit + delete_space, 3) + last_digit,
+ )
+ number_part = pynutil.insert('number_part: "') + graph_number_part + pynutil.insert('"')
+
+ graph = number_part
+ final_graph = self.add_tokens(graph)
+ self.fst = final_graph.optimize()
diff --git a/whisper_pipeline/text_processing/vi/taggers/time.py b/whisper_pipeline/text_processing/vi/taggers/time.py
new file mode 100644
index 0000000000000000000000000000000000000000..5f6d550a5be051cb2db6606316c4add05c49d8c3
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/taggers/time.py
@@ -0,0 +1,131 @@
+# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
+# Copyright 2015 and onwards Google, Inc.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+
+from text_processing.vi.utils import get_abs_path
+from text_processing.vi.graph_utils import (
+ GraphFst,
+ convert_space,
+ delete_extra_space,
+ delete_space,
+ insert_space,
+)
+
+try:
+ import pynini
+ from pynini.lib import pynutil
+
+ PYNINI_AVAILABLE = True
+except (ModuleNotFoundError, ImportError):
+ PYNINI_AVAILABLE = False
+
+
+class TimeFst(GraphFst):
+ """
+ Finite state transducer for classifying time
+ e.g. hai rưỡi -> time { hours: "2" minutes: "30" }
+ e.g. chín giờ kém hai mươi -> time { hours: "8" minutes: "40" }
+ e.g. ba phút hai giây -> time { minutes: "3" seconds: "2" }
+ e.g. mười giờ chín phút bốn mươi lăm giây -> time { hours: "10" minutes: "9" seconds: "45" }
+ """
+
+ def __init__(self):
+ super().__init__(name="time", kind="classify")
+ # hours, minutes, seconds, suffix, zone, style, speak_period
+
+ graph_hours_to = pynini.string_file(get_abs_path("data/time/hours_to.tsv"))
+ graph_minutes_to = pynini.string_file(get_abs_path("data/time/minutes_to.tsv"))
+ graph_hours = pynini.string_file(get_abs_path("data/time/hours.tsv"))
+ graph_minutes = pynini.string_file(get_abs_path("data/time/minutes.tsv"))
+ time_zone_graph = pynini.invert(pynini.string_file(get_abs_path("data/time/time_zone.tsv")))
+
+ graph_half = pynini.cross("rưỡi", "30")
+ oclock = pynini.cross("giờ", "")
+ minute = pynini.cross("phút", "")
+ optional_minute = pynini.closure(delete_space + minute, 0, 1)
+ second = pynini.cross("giây", "")
+
+ final_graph_hour = pynutil.insert('hours: "') + graph_hours + pynutil.insert('"') + delete_space + oclock
+ graph_minute = graph_minutes + optional_minute
+ graph_second = graph_minutes + delete_space + second
+ final_time_zone_optional = pynini.closure(
+ delete_space
+ + insert_space
+ + pynutil.insert('zone: "')
+ + convert_space(time_zone_graph)
+ + pynutil.insert('"'),
+ 0,
+ 1,
+ )
+
+ graph_hm = (
+ final_graph_hour
+ + delete_extra_space
+ + pynutil.insert('minutes: "')
+ + (graph_minute | graph_half)
+ + pynutil.insert('"')
+ )
+
+ graph_hms = (
+ final_graph_hour
+ + delete_extra_space
+ + pynutil.insert('minutes: "')
+ + graph_minutes
+ + delete_space
+ + minute
+ + pynutil.insert('"')
+ + delete_extra_space
+ + pynutil.insert('seconds: "')
+ + graph_second
+ + pynutil.insert('"')
+ )
+
+ graph_ms = (
+ pynutil.insert('minutes: "')
+ + graph_minutes
+ + delete_space
+ + minute
+ + pynutil.insert('"')
+ + delete_extra_space
+ + pynutil.insert('seconds: "')
+ + (graph_second | graph_half)
+ + pynutil.insert('"')
+ )
+
+ graph_hours_to_component = graph_hours @ graph_hours_to
+ graph_minutes_to_component = graph_minutes @ graph_minutes_to
+
+ graph_time_to = (
+ pynutil.insert('hours: "')
+ + graph_hours_to_component
+ + pynutil.insert('"')
+ + delete_space
+ + oclock
+ + delete_space
+ + pynutil.delete("kém")
+ + delete_extra_space
+ + pynutil.insert('minutes: "')
+ + graph_minutes_to_component
+ + pynutil.insert('"')
+ + optional_minute
+ )
+
+ final_graph = (final_graph_hour | graph_hm | graph_hms) + final_time_zone_optional
+ final_graph |= graph_ms
+ final_graph |= graph_time_to
+
+ final_graph = self.add_tokens(final_graph)
+
+ self.fst = final_graph.optimize()
diff --git a/whisper_pipeline/text_processing/vi/taggers/tokenize_and_classify.py b/whisper_pipeline/text_processing/vi/taggers/tokenize_and_classify.py
new file mode 100644
index 0000000000000000000000000000000000000000..f4da5b6dbe13bc467c64bf19f9c3a1bb747a8709
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/taggers/tokenize_and_classify.py
@@ -0,0 +1,128 @@
+# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
+# Copyright 2015 and onwards Google, Inc.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import os
+
+from text_processing.vi.taggers.address import AddressFst
+from text_processing.vi.taggers.cardinal import CardinalFst
+from text_processing.vi.taggers.date import DateFst
+from text_processing.vi.taggers.decimal import DecimalFst
+from text_processing.vi.taggers.electronic import ElectronicFst
+from text_processing.vi.taggers.fraction import FractionFst
+from text_processing.vi.taggers.measure import MeasureFst
+from text_processing.vi.taggers.math import MathFst
+from text_processing.vi.taggers.money import MoneyFst
+from text_processing.vi.taggers.ordinal import OrdinalFst
+from text_processing.vi.taggers.punctuation import PunctuationFst
+from text_processing.vi.taggers.telephone import TelephoneFst
+from text_processing.vi.taggers.time import TimeFst
+from text_processing.vi.taggers.whitelist import WhiteListFst
+from text_processing.vi.taggers.word import WordFst
+from text_processing.vi.graph_utils import (
+ GraphFst,
+ delete_extra_space,
+ delete_space,
+ generator_main,
+)
+
+import logging
+
+try:
+ import pynini
+ from pynini.lib import pynutil
+
+ PYNINI_AVAILABLE = True
+except (ModuleNotFoundError, ImportError):
+ PYNINI_AVAILABLE = False
+
+
+class ClassifyFst(GraphFst):
+ """
+ Final class that composes all other classification grammars. This class can process an entire sentence, that is lower cased.
+ For deployment, this grammar will be compiled and exported to OpenFst Finate State Archiv (FAR) File.
+ More details to deployment at NeMo/tools/text_processing_deployment.
+
+ Args:
+ cache_dir: path to a dir with .far grammar file. Set to None to avoid using cache.
+ overwrite_cache: set to True to overwrite .far files
+ """
+
+ def __init__(self, cache_dir: str = None, overwrite_cache: bool = False):
+ super().__init__(name="tokenize_and_classify", kind="classify")
+
+ far_file = None
+ if cache_dir is not None and cache_dir != "None":
+ os.makedirs(cache_dir, exist_ok=True)
+ far_file = os.path.join(cache_dir, "_en_itn.far")
+ if not overwrite_cache and far_file and os.path.exists(far_file):
+ self.fst = pynini.Far(far_file, mode="r")["tokenize_and_classify"]
+ logging.info(f"ClassifyFst.fst was restored from {far_file}.")
+ else:
+ logging.info(f"Creating ClassifyFst grammars.")
+ cardinal = CardinalFst()
+ cardinal_graph = cardinal.fst
+
+ fraction = FractionFst(cardinal)
+ fraction_graph = fraction.fst
+
+ ordinal = OrdinalFst()
+ ordinal_graph = ordinal.fst
+
+ decimal = DecimalFst(cardinal)
+ decimal_graph = decimal.fst
+
+ address_graph = AddressFst(cardinal=cardinal).fst
+ math_graph = MathFst(cardinal=cardinal).fst
+ measure_graph = MeasureFst(cardinal=cardinal, decimal=decimal).fst
+ date_graph = DateFst(cardinal=cardinal).fst
+ word_graph = WordFst().fst
+ time_graph = TimeFst().fst
+ money_graph = MoneyFst(cardinal=cardinal, decimal=decimal).fst
+ whitelist_graph = WhiteListFst().fst
+ punct_graph = PunctuationFst().fst
+ electronic_graph = ElectronicFst().fst
+ telephone_graph = TelephoneFst().fst
+
+ classify = (
+ pynutil.add_weight(whitelist_graph, 1.01)
+ | pynutil.add_weight(time_graph, 1.05)
+ | pynutil.add_weight(date_graph, 1.09)
+ | pynutil.add_weight(decimal_graph, 1.08)
+ | pynutil.add_weight(measure_graph, 1.1)
+ | pynutil.add_weight(cardinal_graph, 1.1)
+ | pynutil.add_weight(ordinal_graph, 1.1)
+ | pynutil.add_weight(math_graph, 1.1)
+ | pynutil.add_weight(fraction_graph, 1.09)
+ | pynutil.add_weight(address_graph, 1.09)
+ | pynutil.add_weight(money_graph, 1.07)
+ | pynutil.add_weight(telephone_graph, 1.1)
+ | pynutil.add_weight(electronic_graph, 1.1)
+ | pynutil.add_weight(word_graph, 100)
+ )
+
+ punct = pynutil.insert("tokens { ") + pynutil.add_weight(punct_graph, weight=1.1) + pynutil.insert(" }")
+ token = pynutil.insert("tokens { ") + classify + pynutil.insert(" }")
+ token_plus_punct = (
+ pynini.closure(punct + pynutil.insert(" ")) + token + pynini.closure(pynutil.insert(" ") + punct)
+ )
+
+ graph = token_plus_punct + pynini.closure(delete_extra_space + token_plus_punct)
+ graph = delete_space + graph + delete_space
+
+ self.fst = graph.optimize()
+
+ if far_file:
+ generator_main(far_file, {"tokenize_and_classify": self.fst})
+ logging.info(f"ClassifyFst grammars are saved to {far_file}.")
diff --git a/whisper_pipeline/text_processing/vi/taggers/whitelist.py b/whisper_pipeline/text_processing/vi/taggers/whitelist.py
new file mode 100644
index 0000000000000000000000000000000000000000..07e54cdba7e7cf0f4814989d5600f0bdc6ddb027
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/taggers/whitelist.py
@@ -0,0 +1,43 @@
+# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
+# Copyright 2015 and onwards Google, Inc.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from text_processing.vi.utils import get_abs_path
+from text_processing.vi.graph_utils import (
+ GraphFst,
+ convert_space,
+)
+
+try:
+ import pynini
+ from pynini.lib import pynutil
+
+ PYNINI_AVAILABLE = True
+except (ModuleNotFoundError, ImportError):
+ PYNINI_AVAILABLE = False
+
+
+class WhiteListFst(GraphFst):
+ """
+ Finite state transducer for classifying whitelisted tokens
+ e.g. misses -> tokens { name: "mrs." }
+ This class has highest priority among all classifier grammars. Whitelisted tokens are defined and loaded from "data/whitelist.tsv".
+ """
+
+ def __init__(self):
+ super().__init__(name="whitelist", kind="classify")
+
+ whitelist = pynini.string_file(get_abs_path("data/whitelist.tsv")).invert()
+ graph = pynutil.insert('name: "') + convert_space(whitelist) + pynutil.insert('"')
+ self.fst = graph.optimize()
diff --git a/whisper_pipeline/text_processing/vi/taggers/word.py b/whisper_pipeline/text_processing/vi/taggers/word.py
new file mode 100644
index 0000000000000000000000000000000000000000..3b4ec8d51b4b25fce22a5e854380a26ea8fb5830
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/taggers/word.py
@@ -0,0 +1,39 @@
+# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
+# Copyright 2015 and onwards Google, Inc.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from text_processing.vi.graph_utils import (
+ NEMO_NOT_SPACE,
+ GraphFst,
+)
+
+try:
+ import pynini
+ from pynini.lib import pynutil
+
+ PYNINI_AVAILABLE = True
+except (ModuleNotFoundError, ImportError):
+ PYNINI_AVAILABLE = False
+
+
+class WordFst(GraphFst):
+ """
+ Finite state transducer for classifying plain tokens, that do not belong to any special class. This can be considered as the default class.
+ e.g. sleep -> tokens { name: "sleep" }
+ """
+
+ def __init__(self):
+ super().__init__(name="word", kind="classify")
+ word = pynutil.insert('name: "') + pynini.closure(NEMO_NOT_SPACE, 1) + pynutil.insert('"')
+ self.fst = word.optimize()
diff --git a/whisper_pipeline/text_processing/vi/utils.py b/whisper_pipeline/text_processing/vi/utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..436f274135085271c389db8a57d6b90264489c4e
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/utils.py
@@ -0,0 +1,27 @@
+# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import os
+
+
+def get_abs_path(rel_path):
+ """
+ Get absolute path
+
+ Args:
+ rel_path: relative path to this file
+
+ Returns absolute path
+ """
+ return os.path.dirname(os.path.abspath(__file__)) + "/" + rel_path
diff --git a/whisper_pipeline/text_processing/vi/verbalizers/__init__.py b/whisper_pipeline/text_processing/vi/verbalizers/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..bc443be41c4c3fcf0764eb9fd3e1828d63f8438c
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/verbalizers/__init__.py
@@ -0,0 +1,13 @@
+# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
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diff --git a/whisper_pipeline/text_processing/vi/verbalizers/address.py b/whisper_pipeline/text_processing/vi/verbalizers/address.py
new file mode 100644
index 0000000000000000000000000000000000000000..fa7333acfe6cf576bdf0307865a20f5067c54435
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/verbalizers/address.py
@@ -0,0 +1,39 @@
+# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from text_processing.vi.graph_utils import (
+ NEMO_NOT_QUOTE,
+ GraphFst,
+)
+
+try:
+ import pynini
+ from pynini.lib import pynutil
+
+ PYNINI_AVAILABLE = True
+except (ModuleNotFoundError, ImportError):
+ PYNINI_AVAILABLE = False
+
+
+class AddressFst(GraphFst):
+ """
+ Finite state transducer for verbalizing address
+ e.g. address { value: "2/3"} -> 2/3
+ """
+
+ def __init__(self):
+ super().__init__(name="address", kind="verbalize")
+ value_part = pynutil.delete('value: "') + pynini.closure(NEMO_NOT_QUOTE, 1) + pynutil.delete('"')
+ delete_tokens = self.delete_tokens(value_part)
+ self.fst = delete_tokens.optimize()
diff --git a/whisper_pipeline/text_processing/vi/verbalizers/cardinal.py b/whisper_pipeline/text_processing/vi/verbalizers/cardinal.py
new file mode 100644
index 0000000000000000000000000000000000000000..3286b50f6158f2689e0b6e829161b8713c1e80de
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/verbalizers/cardinal.py
@@ -0,0 +1,58 @@
+# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from text_processing.vi.graph_utils import (
+ NEMO_NOT_QUOTE,
+ GraphFst,
+ delete_space,
+)
+
+try:
+ import pynini
+ from pynini.lib import pynutil
+
+ PYNINI_AVAILABLE = True
+except (ModuleNotFoundError, ImportError):
+ PYNINI_AVAILABLE = False
+
+
+class CardinalFst(GraphFst):
+ """
+ Finite state transducer for verbalizing cardinal
+ e.g. cardinal { integer: "23" negative: "-" } -> -23
+ """
+
+ def __init__(self):
+ super().__init__(name="cardinal", kind="verbalize")
+ optional_sign = pynini.closure(
+ pynutil.delete("negative:")
+ + delete_space
+ + pynutil.delete('"')
+ + NEMO_NOT_QUOTE
+ + pynutil.delete('"')
+ + delete_space,
+ 0,
+ 1,
+ )
+ graph = (
+ pynutil.delete("integer:")
+ + delete_space
+ + pynutil.delete('"')
+ + pynini.closure(NEMO_NOT_QUOTE, 1)
+ + pynutil.delete('"')
+ )
+ self.numbers = graph
+ graph = optional_sign + graph
+ delete_tokens = self.delete_tokens(graph)
+ self.fst = delete_tokens.optimize()
diff --git a/whisper_pipeline/text_processing/vi/verbalizers/date.py b/whisper_pipeline/text_processing/vi/verbalizers/date.py
new file mode 100644
index 0000000000000000000000000000000000000000..95e94f574f1946614beb92077aeb70a01ea307f1
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/verbalizers/date.py
@@ -0,0 +1,83 @@
+# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from text_processing.vi.graph_utils import (
+ NEMO_NOT_QUOTE,
+ GraphFst,
+ delete_space,
+)
+
+try:
+ import pynini
+ from pynini.lib import pynutil
+
+ PYNINI_AVAILABLE = True
+except (ModuleNotFoundError, ImportError):
+ PYNINI_AVAILABLE = False
+
+
+class DateFst(GraphFst):
+ """
+ Finite state transducer for verbalizing date, e.g.
+ date { month: "1" year: "2012"} -> tháng 1 năm 2012
+ date { day: "5" month: "10" year: "2021" preserve_order: true } -> 5 tháng 10 năm 2021
+ """
+
+ def __init__(self):
+ super().__init__(name="date", kind="verbalize")
+ day = (
+ pynutil.delete("day:")
+ + delete_space
+ + pynutil.delete('"')
+ + pynini.closure(NEMO_NOT_QUOTE, 1)
+ + pynutil.delete('"')
+ )
+ month = (
+ pynutil.delete("month:")
+ + delete_space
+ + pynutil.delete('"')
+ + pynini.closure(NEMO_NOT_QUOTE, 1)
+ + pynutil.delete('"')
+ )
+ year = (
+ pynutil.delete("year:")
+ + delete_space
+ + pynutil.delete('"')
+ + pynini.closure(NEMO_NOT_QUOTE, 1)
+ + delete_space
+ + pynutil.delete('"')
+ )
+
+ # (day) month year
+ # day month
+ graph_dm = day + delete_space + pynutil.insert(" tháng ") + month
+ graph_dmy = graph_dm + delete_space + pynutil.insert(" năm ") + year
+ graph_m = pynutil.insert("tháng ") + month
+ graph_my = pynutil.insert("tháng ") + month + delete_space + pynutil.insert(" năm ") + year
+ graph_y = pynutil.insert("năm ") + year
+
+ optional_preserve_order = pynini.closure(
+ pynutil.delete("preserve_order:") + delete_space + pynutil.delete("true") + delete_space
+ | pynutil.delete("field_order:")
+ + delete_space
+ + pynutil.delete('"')
+ + NEMO_NOT_QUOTE
+ + pynutil.delete('"')
+ + delete_space
+ )
+
+ final_graph = (graph_y | graph_m | graph_dm | graph_dmy | graph_my) + delete_space + optional_preserve_order
+
+ delete_tokens = self.delete_tokens(final_graph)
+ self.fst = delete_tokens.optimize()
diff --git a/whisper_pipeline/text_processing/vi/verbalizers/decimal.py b/whisper_pipeline/text_processing/vi/verbalizers/decimal.py
new file mode 100644
index 0000000000000000000000000000000000000000..c484af85e88bd473cbce717adfcc2bf677b349e5
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/verbalizers/decimal.py
@@ -0,0 +1,68 @@
+# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from text_processing.vi.graph_utils import (
+ NEMO_NOT_QUOTE,
+ GraphFst,
+ delete_space,
+)
+
+try:
+ import pynini
+ from pynini.lib import pynutil
+
+ PYNINI_AVAILABLE = True
+except (ModuleNotFoundError, ImportError):
+ PYNINI_AVAILABLE = False
+
+
+class DecimalFst(GraphFst):
+ """
+ Finite state transducer for verbalizing decimal, e.g.
+ decimal { negative: "true" integer_part: "12" fractional_part: "5006" quantity: "tỷ" } -> -12.5006 tỷ
+ """
+
+ def __init__(self):
+ super().__init__(name="decimal", kind="verbalize")
+ optionl_sign = pynini.closure(pynini.cross('negative: "true"', "-") + delete_space, 0, 1)
+ integer = (
+ pynutil.delete("integer_part:")
+ + delete_space
+ + pynutil.delete('"')
+ + pynini.closure(NEMO_NOT_QUOTE, 1)
+ + pynutil.delete('"')
+ )
+ optional_integer = pynini.closure(integer + delete_space, 0, 1)
+ fractional = (
+ pynutil.insert(".")
+ + pynutil.delete("fractional_part:")
+ + delete_space
+ + pynutil.delete('"')
+ + pynini.closure(NEMO_NOT_QUOTE, 1)
+ + pynutil.delete('"')
+ )
+ optional_fractional = pynini.closure(fractional + delete_space, 0, 1)
+ quantity = (
+ pynutil.delete("quantity:")
+ + delete_space
+ + pynutil.delete('"')
+ + pynini.closure(NEMO_NOT_QUOTE, 1)
+ + pynutil.delete('"')
+ )
+ optional_quantity = pynini.closure(pynutil.insert(" ") + quantity + delete_space, 0, 1)
+ graph = optional_integer + optional_fractional + optional_quantity
+ self.numbers = graph
+ graph = optionl_sign + graph
+ delete_tokens = self.delete_tokens(graph)
+ self.fst = delete_tokens.optimize()
diff --git a/whisper_pipeline/text_processing/vi/verbalizers/electronic.py b/whisper_pipeline/text_processing/vi/verbalizers/electronic.py
new file mode 100644
index 0000000000000000000000000000000000000000..cdd746c47f5da83c2c1b4502499f561d71adaa39
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/verbalizers/electronic.py
@@ -0,0 +1,65 @@
+# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from text_processing.vi.graph_utils import (
+ NEMO_NOT_QUOTE,
+ GraphFst,
+ delete_space,
+)
+
+try:
+ import pynini
+ from pynini.lib import pynutil
+
+ PYNINI_AVAILABLE = True
+except (ModuleNotFoundError, ImportError):
+ PYNINI_AVAILABLE = False
+
+
+class ElectronicFst(GraphFst):
+ """
+ Finite state transducer for verbalizing electronic
+ e.g. tokens { electronic { username: "cdf1" domain: "abc.edu" } } -> cdf1@abc.edu
+ """
+
+ def __init__(self):
+ super().__init__(name="electronic", kind="verbalize")
+ user_name = (
+ pynutil.delete("username:")
+ + delete_space
+ + pynutil.delete('"')
+ + pynini.closure(NEMO_NOT_QUOTE, 1)
+ + pynutil.delete('"')
+ )
+ domain = (
+ pynutil.delete("domain:")
+ + delete_space
+ + pynutil.delete('"')
+ + pynini.closure(NEMO_NOT_QUOTE, 1)
+ + pynutil.delete('"')
+ )
+
+ protocol = (
+ pynutil.delete("protocol:")
+ + delete_space
+ + pynutil.delete('"')
+ + pynini.closure(NEMO_NOT_QUOTE, 1)
+ + pynutil.delete('"')
+ )
+
+ graph = user_name + delete_space + pynutil.insert("@") + domain
+ graph |= protocol
+
+ delete_tokens = self.delete_tokens(graph)
+ self.fst = delete_tokens.optimize()
diff --git a/whisper_pipeline/text_processing/vi/verbalizers/fraction.py b/whisper_pipeline/text_processing/vi/verbalizers/fraction.py
new file mode 100644
index 0000000000000000000000000000000000000000..c752931e1bf6d2aee0c3babeed8789144889af20
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/verbalizers/fraction.py
@@ -0,0 +1,53 @@
+# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
+# Copyright 2015 and onwards Google, Inc.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from text_processing.vi.graph_utils import (
+ NEMO_NOT_QUOTE,
+ GraphFst,
+ delete_space,
+)
+
+try:
+ import pynini
+ from pynini.lib import pynutil
+
+ PYNINI_AVAILABLE = True
+except (ModuleNotFoundError, ImportError):
+ PYNINI_AVAILABLE = False
+
+
+class FractionFst(GraphFst):
+ """
+ Finite state transducer for verbalizing fraction,
+ e.g. fraction { numerator: "2" denominator: "3" } } -> 2/3
+ e.g. fraction { numerator: "20" denominator: "3" negative: "true"} } -> 2/3
+ """
+
+ def __init__(self):
+ super().__init__(name="fraction", kind="verbalize")
+ optional_sign = pynini.closure(pynini.cross('negative: "true"', "-") + delete_space, 0, 1)
+ numerator = pynutil.delete('numerator: "') + pynini.closure(NEMO_NOT_QUOTE, 1) + pynutil.delete('"')
+
+ denominator = (
+ pynutil.insert("/")
+ + pynutil.delete('denominator: "')
+ + pynini.closure(NEMO_NOT_QUOTE, 1)
+ + pynutil.delete('"')
+ )
+
+ graph = (numerator + delete_space + denominator).optimize()
+ self.numbers = graph
+ delete_tokens = self.delete_tokens(optional_sign + graph)
+ self.fst = delete_tokens.optimize()
diff --git a/whisper_pipeline/text_processing/vi/verbalizers/math.py b/whisper_pipeline/text_processing/vi/verbalizers/math.py
new file mode 100644
index 0000000000000000000000000000000000000000..8e14fc822d9f6c3deeedfcc638d6bcd3b3776bd8
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/verbalizers/math.py
@@ -0,0 +1,39 @@
+# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from text_processing.vi.graph_utils import (
+ NEMO_NOT_QUOTE,
+ GraphFst,
+)
+
+try:
+ import pynini
+ from pynini.lib import pynutil
+
+ PYNINI_AVAILABLE = True
+except (ModuleNotFoundError, ImportError):
+ PYNINI_AVAILABLE = False
+
+
+class MathFst(GraphFst):
+ """
+ Finite state transducer for verbalizing cardinal
+ e.g. math { equation: "2.5 * 2 = 5"} -> 2.5 * 2 = 5
+ """
+
+ def __init__(self):
+ super().__init__(name="math", kind="verbalize")
+ equation_part = pynutil.delete('equation: "') + pynini.closure(NEMO_NOT_QUOTE, 1) + pynutil.delete('"')
+ delete_tokens = self.delete_tokens(equation_part)
+ self.fst = delete_tokens.optimize()
diff --git a/whisper_pipeline/text_processing/vi/verbalizers/measure.py b/whisper_pipeline/text_processing/vi/verbalizers/measure.py
new file mode 100644
index 0000000000000000000000000000000000000000..662f63a1d55eef4d2beb6ec282735fb8a79cf17d
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/verbalizers/measure.py
@@ -0,0 +1,90 @@
+# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
+# Copyright 2015 and onwards Google, Inc.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from text_processing.vi.graph_utils import (
+ NEMO_CHAR,
+ NEMO_NOT_QUOTE,
+ GraphFst,
+ delete_space,
+)
+
+try:
+ import pynini
+ from pynini.lib import pynutil
+
+ PYNINI_AVAILABLE = True
+except (ModuleNotFoundError, ImportError):
+
+ PYNINI_AVAILABLE = False
+
+
+class MeasureFst(GraphFst):
+ """
+ Finite state transducer for verbalizing measure, e.g.
+ measure { negative: "true" cardinal { integer: "12" } units: "kg" } -> -12 kg
+
+ Args:
+ decimal: DecimalFst
+ cardinal: CardinalFst
+ """
+
+ def __init__(self, decimal: GraphFst, cardinal: GraphFst):
+ super().__init__(name="measure", kind="verbalize")
+ optional_sign = pynini.closure(pynini.cross('negative: "true"', "-"), 0, 1)
+ unit = (
+ pynutil.delete("units:")
+ + delete_space
+ + pynutil.delete('"')
+ + pynini.closure(NEMO_CHAR - " ", 1)
+ + pynutil.delete('"')
+ + delete_space
+ )
+ graph_decimal = (
+ pynutil.delete("decimal {")
+ + delete_space
+ + optional_sign
+ + delete_space
+ + decimal.numbers
+ + delete_space
+ + pynutil.delete("}")
+ )
+ graph_cardinal = (
+ pynutil.delete("cardinal {")
+ + delete_space
+ + optional_sign
+ + delete_space
+ + cardinal.numbers
+ + delete_space
+ + pynutil.delete("}")
+ )
+ fractional = (
+ pynutil.insert(".")
+ + pynutil.delete("fractional_part:")
+ + delete_space
+ + pynutil.delete('"')
+ + pynini.closure(NEMO_NOT_QUOTE, 1)
+ + pynutil.delete('"')
+ )
+ optional_fractional = pynini.closure(fractional + delete_space, 0, 1)
+ graph = (
+ (graph_cardinal | graph_decimal)
+ + delete_space
+ + optional_fractional
+ + pynutil.insert(" ")
+ + unit
+ + delete_space
+ )
+ delete_tokens = self.delete_tokens(graph)
+ self.fst = delete_tokens.optimize()
diff --git a/whisper_pipeline/text_processing/vi/verbalizers/money.py b/whisper_pipeline/text_processing/vi/verbalizers/money.py
new file mode 100644
index 0000000000000000000000000000000000000000..fe62e71109ddc8aa0f8fd8b0c8633884d2e55ff5
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/verbalizers/money.py
@@ -0,0 +1,52 @@
+# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
+# Copyright 2015 and onwards Google, Inc.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from text_processing.vi.graph_utils import (
+ NEMO_CHAR,
+ GraphFst,
+ delete_space,
+)
+
+try:
+ import pynini
+ from pynini.lib import pynutil
+
+ PYNINI_AVAILABLE = True
+except (ModuleNotFoundError, ImportError):
+
+ PYNINI_AVAILABLE = False
+
+
+class MoneyFst(GraphFst):
+ """
+ Finite state transducer for verbalizing money, e.g.
+ money { integer_part: "12" fractional_part: "05" currency: "$" } -> 12.05$
+
+ Args:
+ decimal: DecimalFst
+ """
+
+ def __init__(self, decimal: GraphFst):
+ super().__init__(name="money", kind="verbalize")
+ unit = (
+ pynutil.delete("currency:")
+ + delete_space
+ + pynutil.delete('"')
+ + pynini.closure(NEMO_CHAR - " ", 1)
+ + pynutil.delete('"')
+ )
+ graph = decimal.numbers + delete_space + unit
+ delete_tokens = self.delete_tokens(graph)
+ self.fst = delete_tokens.optimize()
diff --git a/whisper_pipeline/text_processing/vi/verbalizers/ordinal.py b/whisper_pipeline/text_processing/vi/verbalizers/ordinal.py
new file mode 100644
index 0000000000000000000000000000000000000000..44c607cbb2761234afb15cf897194348818bced9
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/verbalizers/ordinal.py
@@ -0,0 +1,49 @@
+# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
+# Copyright 2015 and onwards Google, Inc.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from text_processing.vi.graph_utils import (
+ NEMO_NOT_QUOTE,
+ GraphFst,
+ delete_space,
+)
+
+try:
+ import pynini
+ from pynini.lib import pynutil
+
+ PYNINI_AVAILABLE = True
+except (ModuleNotFoundError, ImportError):
+ PYNINI_AVAILABLE = False
+
+
+class OrdinalFst(GraphFst):
+ """
+ Finite state transducer for verbalizing ordinal, e.g.
+ ordinal { integer: "2" } -> thứ 2
+ """
+
+ def __init__(self):
+ super().__init__(name="ordinal", kind="verbalize")
+ graph = (
+ pynutil.delete("integer:")
+ + delete_space
+ + pynutil.delete('"')
+ + pynini.closure(NEMO_NOT_QUOTE, 1)
+ + pynutil.delete('"')
+ )
+
+ graph = pynutil.insert("thứ ") + graph
+ delete_tokens = self.delete_tokens(graph)
+ self.fst = delete_tokens.optimize()
diff --git a/whisper_pipeline/text_processing/vi/verbalizers/telephone.py b/whisper_pipeline/text_processing/vi/verbalizers/telephone.py
new file mode 100644
index 0000000000000000000000000000000000000000..c3bdb1c64fbf098b87e8532ddcaa8af966568f1e
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/verbalizers/telephone.py
@@ -0,0 +1,42 @@
+# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
+# Copyright 2015 and onwards Google, Inc.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from text_processing.vi.graph_utils import (
+ NEMO_NOT_QUOTE,
+ GraphFst,
+)
+
+try:
+ import pynini
+ from pynini.lib import pynutil
+
+ PYNINI_AVAILABLE = True
+except (ModuleNotFoundError, ImportError):
+ PYNINI_AVAILABLE = False
+
+
+class TelephoneFst(GraphFst):
+ """
+ Finite state transducer for verbalizing telephone, e.g.
+ telephone { number_part: "1231235678" }
+ -> 1231235678
+ """
+
+ def __init__(self):
+ super().__init__(name="telephone", kind="verbalize")
+
+ number_part = pynutil.delete('number_part: "') + pynini.closure(NEMO_NOT_QUOTE, 1) + pynutil.delete('"')
+ delete_tokens = self.delete_tokens(number_part)
+ self.fst = delete_tokens.optimize()
diff --git a/whisper_pipeline/text_processing/vi/verbalizers/time.py b/whisper_pipeline/text_processing/vi/verbalizers/time.py
new file mode 100644
index 0000000000000000000000000000000000000000..c4547ffbaa67e2c017e3585ce21015cfb736a18c
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/verbalizers/time.py
@@ -0,0 +1,97 @@
+# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
+# Copyright 2015 and onwards Google, Inc.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from text_processing.vi.graph_utils import (
+ NEMO_CHAR,
+ NEMO_DIGIT,
+ GraphFst,
+ delete_space,
+ insert_space,
+)
+
+try:
+ import pynini
+ from pynini.lib import pynutil
+
+ PYNINI_AVAILABLE = True
+except (ModuleNotFoundError, ImportError):
+ PYNINI_AVAILABLE = False
+
+
+class TimeFst(GraphFst):
+ """
+ Finite state transducer for verbalizing time, e.g.
+ time { hours: "3" } -> 3h
+ time { hours: "12" minutes: "30" } -> 12:30
+ time { hours: "1" minutes: "12" second: "22"} -> 1:12:22
+ time { minutes: "36" second: "45"} -> 36p45s
+ time { hours: "2" zone: "gmt" } -> 2h gmt
+ """
+
+ def __init__(self):
+ super().__init__(name="time", kind="verbalize")
+ add_leading_zero_to_double_digit = (NEMO_DIGIT + NEMO_DIGIT) | (pynutil.insert("0") + NEMO_DIGIT)
+ hour = (
+ pynutil.delete("hours:")
+ + delete_space
+ + pynutil.delete('"')
+ + pynini.closure(NEMO_DIGIT, 1)
+ + pynutil.delete('"')
+ )
+ minute = (
+ pynutil.delete("minutes:")
+ + delete_space
+ + pynutil.delete('"')
+ + pynini.closure(NEMO_DIGIT, 1)
+ + pynutil.delete('"')
+ )
+ second = (
+ pynutil.delete("seconds:")
+ + delete_space
+ + pynutil.delete('"')
+ + pynini.closure(NEMO_DIGIT, 1)
+ + pynutil.delete('"')
+ )
+ zone = (
+ delete_space
+ + insert_space
+ + pynutil.delete("zone:")
+ + delete_space
+ + pynutil.delete('"')
+ + pynini.closure(NEMO_CHAR - " ", 1)
+ + pynutil.delete('"')
+ )
+ optional_zone = pynini.closure(zone, 0, 1)
+ optional_second = pynini.closure(
+ delete_space + pynutil.insert(":") + (second @ add_leading_zero_to_double_digit),
+ 0,
+ 1,
+ )
+
+ graph_h = hour + pynutil.insert("h")
+ graph_hms = (
+ hour + delete_space + pynutil.insert(":") + (minute @ add_leading_zero_to_double_digit) + optional_second
+ )
+ graph_ms = (
+ minute
+ + delete_space
+ + pynutil.insert("p")
+ + (second @ add_leading_zero_to_double_digit)
+ + pynutil.insert("s")
+ )
+
+ graph = (graph_h | graph_ms | graph_hms) + optional_zone
+ delete_tokens = self.delete_tokens(graph)
+ self.fst = delete_tokens.optimize()
diff --git a/whisper_pipeline/text_processing/vi/verbalizers/verbalize.py b/whisper_pipeline/text_processing/vi/verbalizers/verbalize.py
new file mode 100644
index 0000000000000000000000000000000000000000..f3ee65c3c90011d4a9a7037785aba20a316a8c74
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/verbalizers/verbalize.py
@@ -0,0 +1,72 @@
+# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
+# Copyright 2015 and onwards Google, Inc.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from text_processing.vi.graph_utils import GraphFst
+from text_processing.vi.verbalizers.address import AddressFst
+from text_processing.vi.verbalizers.cardinal import CardinalFst
+from text_processing.vi.verbalizers.date import DateFst
+from text_processing.vi.verbalizers.decimal import DecimalFst
+from text_processing.vi.verbalizers.electronic import ElectronicFst
+from text_processing.vi.verbalizers.fraction import FractionFst
+from text_processing.vi.verbalizers.measure import MeasureFst
+from text_processing.vi.verbalizers.math import MathFst
+from text_processing.vi.verbalizers.money import MoneyFst
+from text_processing.vi.verbalizers.ordinal import OrdinalFst
+from text_processing.vi.verbalizers.telephone import TelephoneFst
+from text_processing.vi.verbalizers.time import TimeFst
+from text_processing.vi.verbalizers.whitelist import WhiteListFst
+
+
+class VerbalizeFst(GraphFst):
+ """
+ Composes other verbalizer grammars.
+ For deployment, this grammar will be compiled and exported to OpenFst Finate State Archiv (FAR) File.
+ More details to deployment at NeMo/tools/text_processing_deployment.
+ """
+
+ def __init__(self):
+ super().__init__(name="verbalize", kind="verbalize")
+ cardinal = CardinalFst()
+ cardinal_graph = cardinal.fst
+ ordinal_graph = OrdinalFst().fst
+ decimal = DecimalFst()
+ decimal_graph = decimal.fst
+ fraction = FractionFst()
+ fraction_graph = fraction.fst
+ address_graph = AddressFst().fst
+ math_graph = MathFst().fst
+ measure_graph = MeasureFst(decimal=decimal, cardinal=cardinal).fst
+ money_graph = MoneyFst(decimal=decimal).fst
+ time_graph = TimeFst().fst
+ date_graph = DateFst().fst
+ whitelist_graph = WhiteListFst().fst
+ telephone_graph = TelephoneFst().fst
+ electronic_graph = ElectronicFst().fst
+ graph = (
+ time_graph
+ | date_graph
+ | money_graph
+ | measure_graph
+ | ordinal_graph
+ | fraction_graph
+ | math_graph
+ | address_graph
+ | decimal_graph
+ | cardinal_graph
+ | whitelist_graph
+ | telephone_graph
+ | electronic_graph
+ )
+ self.fst = graph
diff --git a/whisper_pipeline/text_processing/vi/verbalizers/verbalize_final.py b/whisper_pipeline/text_processing/vi/verbalizers/verbalize_final.py
new file mode 100644
index 0000000000000000000000000000000000000000..1dae7cf29c62eee5750e206fb00ebfbdd18d6f23
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/verbalizers/verbalize_final.py
@@ -0,0 +1,56 @@
+# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
+# Copyright 2015 and onwards Google, Inc.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from text_processing.vi.verbalizers.verbalize import (
+ VerbalizeFst,
+)
+from text_processing.vi.verbalizers.word import WordFst
+from text_processing.vi.graph_utils import (
+ GraphFst,
+ delete_extra_space,
+ delete_space,
+)
+
+try:
+ import pynini
+ from pynini.lib import pynutil
+
+ PYNINI_AVAILABLE = True
+except (ModuleNotFoundError, ImportError):
+ PYNINI_AVAILABLE = False
+
+
+class VerbalizeFinalFst(GraphFst):
+ """
+ Finite state transducer that verbalizes an entire sentence, e.g.
+ tokens { name: "its" } tokens { time { hours: "12" minutes: "30" } } tokens { name: "now" } -> its 12:30 now
+ """
+
+ def __init__(self):
+ super().__init__(name="verbalize_final", kind="verbalize")
+ verbalize = VerbalizeFst().fst
+ word = WordFst().fst
+ types = verbalize | word
+ graph = (
+ pynutil.delete("tokens")
+ + delete_space
+ + pynutil.delete("{")
+ + delete_space
+ + types
+ + delete_space
+ + pynutil.delete("}")
+ )
+ graph = delete_space + pynini.closure(graph + delete_extra_space) + graph + delete_space
+ self.fst = graph
diff --git a/whisper_pipeline/text_processing/vi/verbalizers/whitelist.py b/whisper_pipeline/text_processing/vi/verbalizers/whitelist.py
new file mode 100644
index 0000000000000000000000000000000000000000..a48a39bb2e3debbab260ed9e8658026905d24117
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/verbalizers/whitelist.py
@@ -0,0 +1,49 @@
+# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
+# Copyright 2015 and onwards Google, Inc.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+
+from text_processing.vi.graph_utils import (
+ NEMO_CHAR,
+ NEMO_SIGMA,
+ GraphFst,
+ delete_space,
+)
+
+try:
+ import pynini
+ from pynini.lib import pynutil
+
+ PYNINI_AVAILABLE = True
+except (ModuleNotFoundError, ImportError):
+ PYNINI_AVAILABLE = False
+
+
+class WhiteListFst(GraphFst):
+ """
+ Finite state transducer for verbalizing whitelist
+ e.g. tokens { name: "mrs." } -> mrs.
+ """
+
+ def __init__(self):
+ super().__init__(name="whitelist", kind="verbalize")
+ graph = (
+ pynutil.delete("name:")
+ + delete_space
+ + pynutil.delete('"')
+ + pynini.closure(NEMO_CHAR - " ", 1)
+ + pynutil.delete('"')
+ )
+ graph = graph @ pynini.cdrewrite(pynini.cross(u"\u00A0", " "), "", "", NEMO_SIGMA)
+ self.fst = graph.optimize()
diff --git a/whisper_pipeline/text_processing/vi/verbalizers/word.py b/whisper_pipeline/text_processing/vi/verbalizers/word.py
new file mode 100644
index 0000000000000000000000000000000000000000..6d68122aa525ee197757fa150f633fcfaf1136ad
--- /dev/null
+++ b/whisper_pipeline/text_processing/vi/verbalizers/word.py
@@ -0,0 +1,44 @@
+# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
+# Copyright 2015 and onwards Google, Inc.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from text_processing.vi.graph_utils import (
+ NEMO_CHAR,
+ NEMO_SIGMA,
+ GraphFst,
+ delete_space,
+)
+
+try:
+ import pynini
+ from pynini.lib import pynutil
+
+ PYNINI_AVAILABLE = True
+except (ModuleNotFoundError, ImportError):
+ PYNINI_AVAILABLE = False
+
+
+class WordFst(GraphFst):
+ """
+ Finite state transducer for verbalizing plain tokens
+ e.g. tokens { name: "sleep" } -> sleep
+ """
+
+ def __init__(self):
+ super().__init__(name="word", kind="verbalize")
+ chars = pynini.closure(NEMO_CHAR - " ", 1)
+ char = pynutil.delete("name:") + delete_space + pynutil.delete('"') + chars + pynutil.delete('"')
+ graph = char @ pynini.cdrewrite(pynini.cross(u"\u00A0", " "), "", "", NEMO_SIGMA)
+
+ self.fst = graph.optimize()