Update srt/001.srt

.gitattributes

@@ -44,8 +44,6 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.mp3 filter=lfs diff=lfs merge=lfs -text
 *.ogg filter=lfs diff=lfs merge=lfs -text
 *.wav filter=lfs diff=lfs merge=lfs -text
-*.opus filter=lfs diff=lfs merge=lfs -text
-*.webm filter=lfs diff=lfs merge=lfs -text
 # Image files - uncompressed
 *.bmp filter=lfs diff=lfs merge=lfs -text
 *.gif filter=lfs diff=lfs merge=lfs -text
@@ -55,3 +53,7 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.jpg filter=lfs diff=lfs merge=lfs -text
 *.jpeg filter=lfs diff=lfs merge=lfs -text
 *.webp filter=lfs diff=lfs merge=lfs -text
+001.webm filter=lfs diff=lfs merge=lfs -text
+*.webm filter=lfs diff=lfs merge=lfs -text
+002.webm filter=lfs diff=lfs merge=lfs -text
+003.webm filter=lfs diff=lfs merge=lfs -text

README.md

@@ -1,62 +1,54 @@
 ---
 language:
-  - yue
+- yue
 license: cc0-1.0
 size_categories:
-  - 10K<n<100K
+- 10K<n<100K
 task_categories:
-  - automatic-speech-recognition
-  - text-to-speech
-  - text-generation
-  - feature-extraction
-  - audio-to-audio
-  - audio-classification
-  - text-to-audio
+- automatic-speech-recognition
+- text-to-speech
+- text-generation
+- feature-extraction
+- audio-to-audio
+- audio-classification
+- text-to-audio
 pretty_name: c
 configs:
-  - config_name: default
-    data_files:
-      - split: saamgwokjinji
-        path: data/saamgwokjinji-*
-      - split: seoiwuzyun
-        path: data/seoiwuzyun-*
+- config_name: default
+  data_files:
+  - split: train
+    path: data/train-*
 tags:
-  - cantonese
-  - audio
-  - art
+- cantonese
+- audio
+- art
 dataset_info:
   features:
-    - name: audio
-      dtype: audio
-    - name: id
-      dtype: string
-    - name: episode_id
-      dtype: int64
-    - name: audio_duration
-      dtype: float64
-    - name: transcription
-      dtype: string
+  - name: audio
+    dtype: audio
+  - name: id
+    dtype: string
+  - name: episode_id
+    dtype: int64
+  - name: audio_duration
+    dtype: float64
+  - name: transcription
+    dtype: string
   splits:
-    - name: saamgwokjinji
-      num_bytes: 2398591354.589
-      num_examples: 39173
-    - name: seoiwuzyun
-      num_bytes: 1243416911.25
-      num_examples: 18881
-  download_size: 3690072406
-  dataset_size: 3642008265.839
+  - name: train
+    num_bytes: 38792803349.64
+    num_examples: 39190
+  download_size: 38782029113
+  dataset_size: 38792803349.64
 ---
 
-# 張悦楷講《三國演義》《水滸傳》語音數據集
+# 張悦楷講《三國演義》語音數據集
 
-[English](#the-zoeng-jyut-gaai-story-telling-speech-dataset)
+[主頁 Home page](https://canclid.github.io/zoengjyutgaai/)
 
-## Dataset Description
+[English](#zoeng-jyut-gaai-story-telling-romance-of-the-three-kingdoms-dataset)
 
-- **Homepage:** [張悦楷講古語音數據集 The Zoeng Jyut Gaai Story-telling Speech Dataset](https://canclid.github.io/zoengjyutgaai/)
-- **License:** [CC0 1.0 Universal](https://creativecommons.org/publicdomain/zero/1.0/)
-
-呢個係張悦楷講《三國演義》同《水滸傳》語音數據集。[張悦楷](https://zh.wikipedia.org/wiki/%E5%BC%A0%E6%82%A6%E6%A5%B7)係廣州最出名嘅講古佬 / 粵語説書藝人。佢從上世紀七十年代開始就喺廣東各個收音電台度講古，佢把聲係好多廣州人嘅共同回憶。本數據集《三國演義》係佢最知名嘅作品一。
+呢個係張悦楷講《三國演義》語音數據集。[張悦楷](https://zh.wikipedia.org/wiki/%E5%BC%A0%E6%82%A6%E6%A5%B7)係廣州最出名嘅講古佬 / 粵語説書藝人。佢從上世紀七十年代開始就喺廣東各個收音電台度講古，佢把聲係好多廣州人嘅共同回憶。本數據集《三國演義》係佢最知名嘅作品一。
 
 數據集用途：
 
@@ -72,15 +64,11 @@ TTS 效果演示：https://huggingface.co/spaces/laubonghaudoi/zoengjyutgaai_tts
 - 所有文本都根據 https://jyutping.org/blog/typo/ 同 https://jyutping.org/blog/particles/ 規範用字。
 - 所有文本都使用全角標點，冇半角標點。
 - 所有文本都用漢字轉寫，無阿拉伯數字無英文字母
-- 所有音頻源都存放喺`/source`，為方便直接用作訓練數據，切分後嘅音頻都放喺 `opus/`
-- 所有 opus 音頻皆為 48000 Hz 採樣率。
-- 所有源字幕 SRT 文件都存放喺 `srt/` 路經下，搭配 `source/` 下嘅音源可以直接作為帶字幕嘅錄音直接欣賞。
-- `cut.py` 係切分腳本，將對應嘅音源根據 srt 切分成短句並生成一個文本轉寫 csv。
-- `stats.py` 係統計腳本，運行佢就會顯示成個數據集嘅各項統計數據。
+- 所有音頻源都存放喺`/webm`，為方便直接用作訓練數據，切分後嘅音頻都重採樣升 44100Hz 放喺 `wav/`
 
-## 下載使用
+要使用呢個數據集，可以喺 Python 入面直接跑：
 
-要下載使用呢個數據集，可以喺 Python 入面直接跑：
+## 使用
 
 ```python
 from datasets import load_dataset
@@ -88,30 +76,16 @@ from datasets import load_dataset
 ds = load_dataset("CanCLID/zoengjyutgaai_saamgwokjinji")
 ```
 
-如果想單純將 `opus/` 入面所有嘢下載落嚟，可以跑下面嘅 Python 代碼，注意要安裝 `pip install --upgrade huggingface_hub` 先：
-
-```python
-from huggingface_hub import snapshot_download
-
-# 如果你淨係想下載啲字幕或者源音頻，噉就將下面嘅 `wav/*` 改成 `srt/*` 或者 `webm/*`
-snapshot_download(repo_id="CanCLID/zoengjyutgaai_saamgwokjinji",allow_patterns="opus/*",local_dir="./",repo_type="dataset")
-```
-
-如果唔想用 python，你亦都可以用命令行叫 git 針對克隆個`opus/`或者其他路經，避免將成個 repo 都克隆落嚟浪費空間同下載時間：
+如果想單純將所有 wav 文件同對應嘅轉寫複製落嚟，可以跑下面嘅命令行嚟針對克隆個`wav/`路經，避免將成個 repo 都克隆落嚟浪費空間同下載時間：
 
 ```bash
-mkdir zoengjyutgaai_saamgwokjinji
+git clone --filter=blob:none --sparse https://huggingface.co/datasets/CanCLID/zoengjyutgaai_saamgwokjinji
+
 cd zoengjyutgaai_saamgwokjinji
-git init
 
-git remote add origin https://huggingface.co/datasets/CanCLID/zoengjyutgaai_saamgwokjinji
 git sparse-checkout init --cone
-
-# 指定凈係下載個別路徑
-git sparse-checkout set opus
-
-# 開始下載
-git pull origin main
+git sparse-checkout set wav
+git checkout
 ```
 
 ### 數據集構建流程
@@ -120,21 +94,14 @@ git pull origin main
 
 1. 從 YouTube 或者國內評書網站度下載錄音源文件，一般都係每集半個鐘長嘅 `.webm` 或者 `.mp3`。
 1. 用加字幕工具幫呢啲錄音加字幕，得到對應嘅 `.srt` 文件。
-1. 將啲源錄音用下面嘅命令儘可能無壓縮噉轉換成 `.opus` 格式。
-1. 運行`cut.py`，將每一集 `.opus` 按照 `.srt` 入面嘅時間點切分成一句一個 `.opus`，然後對應嘅文本寫入本數據集嘅 `xxx.csv`。
+1. 將啲源錄音用下面嘅命令儘可能無壓縮噉轉換成 `.wav` 格式。
+1. 運行`cut.py`，將每一集 `.wav` 按照 `.srt` 入面嘅時間點切分成一句一個 `.wav`，然後對應嘅文本寫入本數據集嘅 `xxx.csv`。
 1. 然後打開一個 IPython，逐句跑下面嘅命令，將啲數據推上 HuggingFace。
 
 ```python
-from datasets import load_dataset, DatasetDict
+from datasets import load_dataset
 from huggingface_hub import login
-
-sg = load_dataset('audiofolder', data_dir='./opus/saamgwokjinji')
-sw = load_dataset('audiofolder', data_dir='./opus/seoiwuzyun')
-dataset = DatasetDict({
-    "saamgwokjinji": sg["train"],
-    "seoiwuzyun": sw["train"],
-})
-
+dataset = load_dataset('audiofolder', data_dir='./wav')
 # 檢查下讀入嘅數據有冇問題
 dataset['train'][0]
 # 準備好個 token 嚟登入
@@ -143,31 +110,19 @@ login()
 dataset.push_to_hub("CanCLID/zoengjyutgaai_saamgwokjinji")
 ```
 
-### 音頻格式轉換
+### 將`.webm`無損轉為`.wav`
 
 首先要安裝 [ffmpeg](https://www.ffmpeg.org/download.html)，然後運行：
 
 ```bash
-# 將下載嘅音源由 webm 轉成 opus
-ffmpeg -i webm/saamgwokjinji/001.webm -c:a copy source/saamgwokjinji/001.opus
-# 或者轉 mp3
-ffmpeg -i mp3/mouzaakdung/001.mp3 -c:a libopus -map_metadata -1 -b:a 48k -vbr on source/mouzaakdung/001.opus
-# 將 opus 轉成無損 wav
-ffmpeg -i source/saamgwokjinji/001.opus wav/saamgwokjinji/001.wav
+ffmpeg -i "001.webm" -vn -ar 44100 -c:a pcm_s16le "001.wav"
 ```
 
-如果想將所有 opus 文件全部轉換成 wav，可以直接運行`to_wav.sh`:
+如果唔想指定採樣率，儘可能無損轉換，可以將上面嘅`-ar 44100`刪去。**本數據集入面所有 wav 都已經轉為 44100 採樣率**。
 
-```
-chmod +x to_wav.sh
-./to_wav.sh
-```
+# Zoeng Jyut Gaai story-telling _Romance of the Three Kingdoms_ voice dataset
 
-跟住就會生成一個 `wav/` 路經，入面都係 `opus/` 對應嘅音頻。注意 wav 格式非常掗埞，成個 `opus/` 轉晒後會佔用至少 500GB 儲存空間，所以轉換之前記得確保有足夠空間。如果你想對音頻重採樣，亦都可以修改 `to_wav.sh` 入面嘅命令順便做重採樣。
-
-# The Zoeng Jyut Gaai Story-telling Speech Dataset
-
-This is a speech dataset of Zoeng Jyut Gaai story-telling _Romance of the Three Kingdoms_ and _Water Margin_. [Zoeng Jyut Gaai](https://zh.wikipedia.org/wiki/%E5%BC%A0%E6%82%A6%E6%A5%B7) is a famous actor, stand-up commedian and story-teller (講古佬) in 20th centry Canton. His voice remains in the memories of thousands of Cantonese people. This dataset is built from one of his most well-known story-telling piece: _Romance of the Three Kingdoms_.
+This is a speech dataset of Zoeng Jyut Gaai story-telling _Romance of the Three Kingdoms_. [Zoeng Jyut Gaai](https://zh.wikipedia.org/wiki/%E5%BC%A0%E6%82%A6%E6%A5%B7) is a famous actor, stand-up commedian and story-teller (講古佬) in 20th centry Canton. His voice remains in the memories of thousands of Cantonese people. This dataset is built from one of his most well-known story-telling piece: _Romance of the Three Kingdoms_.
 
 Use case of this dataset:
 
@@ -183,11 +138,7 @@ TTS demo: https://huggingface.co/spaces/laubonghaudoi/zoengjyutgaai_tts
 - All transcriptions follow the prescribed orthography detailed in https://jyutping.org/blog/typo/ and https://jyutping.org/blog/particles/
 - All transcriptions use full-width punctuations, no half-width punctuations is used.
 - All transcriptions are in Chinese characters, no Arabic numbers or Latin letters.
-- All source audio are stored in `source/`. For the convenice of training, segmented audios are stored in `opus/`.
-- All opus audio are in 48000 Hz sampling rate.
-- All source subtitle SRT files are stored in `srt/`. Use them with the webm files to enjoy subtitled storytelling pieces.
-- `cut.py` is the script for cutting opus audios into senteneces based on the srt, and generates a csv file for transcriptions.
-- `stats.py` is the script for getting stats of this dataset.
+- All source audio are stored in `/webm`. For the convenice of training, segmented audios are resampled into 44.1 kHz and stored in `wav/`.
 
 ## Usage
 
@@ -199,50 +150,14 @@ from datasets import load_dataset
 ds = load_dataset("CanCLID/zoengjyutgaai_saamgwokjinji")
 ```
 
-If you only want to download a certain directory to save time and space from cloning the entire repo, run the Python codes below. Make sure you have `pip install --upgrade huggingface_hub` first：
-
-```python
-from huggingface_hub import snapshot_download
-
-# If you only want to download the source audio or the subtitles, change the `wav/*` below into `srt/*` or `webm/*`
-snapshot_download(repo_id="CanCLID/zoengjyutgaai_saamgwokjinji",allow_patterns="opus/*",local_dir="./",repo_type="dataset")
-```
-
-If you don't want to run python codes and want to do this via command lines, you can selectively clone only a directory of the repo:
+To save space and downloading time and avoid clonin the entire repo, you can selectively clone only the `wav./` directory which contains all the wav files and transcriptions:
 
 ```bash
-mkdir zoengjyutgaai_saamgwokjinji
+git clone --filter=blob:none --sparse https://huggingface.co/datasets/CanCLID/zoengjyutgaai_saamgwokjinji
+
 cd zoengjyutgaai_saamgwokjinji
-git init
 
-git remote add origin https://huggingface.co/datasets/CanCLID/zoengjyutgaai_saamgwokjinji
 git sparse-checkout init --cone
-
-# Tell git which directory you want
-git sparse-checkout set opus
-
-# Pull the content
-git pull origin main
-```
-
-### Audio format conversion
-
-Install [ffmpeg](https://www.ffmpeg.org/download.html) first, then run：
-
-```bash
-# convert all webm into opus
-ffmpeg -i webm/saamgwokjinji/001.webm -c:a copy source/saamgwokjinji/001.opus
-# or into mp3
-ffmpeg -i mp3/mouzaakdung/001.mp3 -c:a libopus -map_metadata -1 -b:a 48k -vbr on source/mouzaakdung/001.opus
-# convert all opus into loseless wav
-ffmpeg -i source/saamgwokjinji/001.opus wav/saamgwokjinji/001.wav
-```
-
-If you want to convert all opus to wav, run `to_wav.sh`:
-
-```
-chmod +x to_wav.sh
-./to_wav.sh
-```
-
-It will generate a `wav/` path which contains all audios converted from `opus/`. Be aware the wav format is very space-consuming. A full conversion will take up at least 500GB space so make sure you have enough storage. If you want to resample the audio, modify the line within `to_wav.sh` to resample the audio while doing the conversion.
+git sparse-checkout set wav
+git checkout
+```

align.py

@@ -1,81 +0,0 @@
-import re
-import audioread
-
-
-def fix_srt_delay(input_file, output_file, delay_start_ms, delay_end_ms, audio_file):
-    """
-    Fixes a progressive delay in an SRT file by linearly adjusting timestamps.
-    Gets video duration from an associated audio file.
-
-    Args:
-        input_file: Path to the input SRT file.
-        output_file: Path to the output SRT file with corrected timestamps.
-        delay_start_ms: Delay at the beginning of the video (in milliseconds).
-        delay_end_ms: Delay at the end of the video (in milliseconds).
-        audio_file: Path to the audio file to get duration from.
-    """
-
-    try:
-        with audioread.audio_open(audio_file) as f:
-            total_duration_ms = int(f.duration * 1000)  # Get duration in milliseconds
-    except audioread.NoBackendError:
-        print("Error: No suitable audio backend found. Please install ffmpeg or another supported library.")
-        return
-    except Exception as e:
-        print(f"Error reading audio file: {e}")
-        return
-
-    with open(input_file, 'r', encoding='utf-8') as infile, open(output_file, 'w', encoding='utf-8') as outfile:
-        for line in infile:
-            if '-->' in line:
-                # Extract start and end timestamps
-                start_time_str, end_time_str = line.strip().split(' --> ')
-                start_time_ms = srt_time_to_milliseconds(start_time_str)
-                end_time_ms = srt_time_to_milliseconds(end_time_str)
-
-                # Calculate the adjusted delay for this subtitle
-                progress = start_time_ms / total_duration_ms
-                current_delay_ms = delay_start_ms + progress * (delay_end_ms - delay_start_ms)
-
-                # Adjust the timestamps
-                adjusted_start_time_ms = start_time_ms - current_delay_ms
-                adjusted_end_time_ms = end_time_ms - current_delay_ms
-
-                # Convert back to SRT time format
-                adjusted_start_time_str = milliseconds_to_srt_time(adjusted_start_time_ms)
-                adjusted_end_time_str = milliseconds_to_srt_time(adjusted_end_time_ms)
-
-                # Write the corrected line to the output file
-                outfile.write(f"{adjusted_start_time_str} --> {adjusted_end_time_str}\n")
-            else:
-                # Write non-timestamp lines as they are
-                outfile.write(line)
-
-
-def srt_time_to_milliseconds(time_str):
-    """Converts an SRT timestamp string to milliseconds."""
-    hours, minutes, seconds_milliseconds = time_str.split(':')
-    seconds, milliseconds = seconds_milliseconds.split(',')
-    total_milliseconds = (int(hours) * 3600 + int(minutes) * 60 + int(seconds)) * 1000 + int(milliseconds)
-    return total_milliseconds
-
-
-def milliseconds_to_srt_time(milliseconds):
-    """Converts milliseconds to an SRT timestamp string."""
-    milliseconds = int(milliseconds)
-    seconds, milliseconds = divmod(milliseconds, 1000)
-    minutes, seconds = divmod(seconds, 60)
-    hours, minutes = divmod(minutes, 60)
-    return f"{hours:02d}:{minutes:02d}:{seconds:02d},{milliseconds:03d}"
-
-
-delay_at_start_ms = 10  # Delay at the beginning (you think it starts from 0)
-delay_at_end_ms = 2200  # Delay at the end in milliseconds
-
-for i in range(46, 51):
-    input_srt_file = f'srt/seoiwuzyun/{i:03d}.srt'  # Your input SRT file
-    output_srt_file = f'{i:03d}.srt'  # Output file name
-    audio_file_path = f'source/seoiwuzyun/{i:03d}.opus'  # Your Opus audio file
-
-    fix_srt_delay(input_srt_file, output_srt_file, delay_at_start_ms, delay_at_end_ms, audio_file_path)
-    print(f"SRT file fixed and saved to {output_srt_file}")

cut.py

@@ -1,38 +1,25 @@
 import csv
 import os
-from typing import Literal
 
 import pysrt
 from pydub import AudioSegment
 
 
-def srt_to_segments_with_metadata(srt_file, episode, audio_file, output_dir, metadata_file, subset: Literal["saamgwokjinji", "seoiwuzyun"]):
+def srt_to_segments_with_metadata(srt_file, episode, audio_file, output_dir, metadata_file):
     # Load the SRT file
     subs = pysrt.open(srt_file)
 
-    # Load the audio file (handling Opus)
-    try:
-        audio = AudioSegment.from_file(audio_file, codec="opus")
-    except Exception as e:
-        print(f"Error loading audio file: {audio_file}")
-        print(f"Error message: {e}")
-        return  # Skip this file and move to the next
+    # Load the audio file
+    audio = AudioSegment.from_wav(audio_file)
 
     # Ensure the output directory exists
     os.makedirs(output_dir, exist_ok=True)
 
-    # Prepare the metadata file (appending to a single file)
+    # Prepare the metadata file
     with open(metadata_file, mode='a', newline='', encoding='utf-8') as csvfile:
         csvwriter = csv.writer(csvfile)
-
-        # Write header row if the file is empty
-        if os.stat(metadata_file).st_size == 0:
-            csvwriter.writerow(['id', 'episode_id', 'file_name', 'audio_duration', 'transcription'])
-
-        if subset == "saamgwokjinji":
-            prefix = "sg"
-        elif subset == "seoiwuzyun":
-            prefix = "sw"
+        # csvwriter.writerow(['id', 'episode_id', 'file_name', 'audio_duration',
+        #                    'transcription'])
 
         for index, sub in enumerate(subs):
             # Get start and end times in milliseconds
@@ -45,46 +32,31 @@ def srt_to_segments_with_metadata(srt_file, episode, audio_file, output_dir, met
             # Extract the audio segment
             segment = audio[start_time:end_time]
 
-            # Define output filenames (using .opus extension)
-            segment_filename = f"{episode}_{index + 1:03d}.opus"
-            segment_id = f"{prefix}_{episode}_{index + 1:03d}"
+            # Define output filenames
+            segment_filename = f"{episode}_{index + 1:03d}.wav"
+            segment_id = f"{episode}_{index + 1:03d}"
             audio_filename = os.path.join(output_dir, segment_filename)
 
-            # Export the audio segment as Opus
-            try:
-                segment.export(audio_filename, format="opus", codec="libopus")
-            except Exception as e:
-                print(f"Error exporting segment: {audio_filename}")
-                print(f"Error message: {e}")
-                continue  # Skip to the next segment
+            # Export the audio segment
+            segment.export(audio_filename, format="wav")
 
             # Write to the metadata CSV file
             csvwriter.writerow(
                 [segment_id, episode, f'{episode}/{segment_filename}', f'{duration:.3f}', sub.text])
 
-    print(f"Segmentation of {audio_file} complete. Files saved to: {output_dir}")
-    print(f"Metadata appended to: {metadata_file}")
+    print("Segmentation complete. Files saved to:", output_dir)
+    print("Metadata saved to:", metadata_file)
 
 
 if __name__ == "__main__":
-    # subset = "saamgwokjinji"
-    subset = "seoiwuzyun"
-
-    print(f"Processing subset: {subset}")
-    # If append to existing metadata file
-    metadata_file = os.path.join("opus", subset, "metadata.csv")  # Define metadata file path here
-
-    for episode in range(46, 51):
-        # If creating new csv
-        # metadata_file = f"{episode}.csv"
-        episode_str = f'{episode:03d}'  # Format episode as 3-digit string
-
-        srt_file = f'srt/{subset}/{episode_str}.srt'
-        audio_file = f'source/{subset}/{episode_str}.opus'
-        output_dir = f'opus/{subset}/{episode_str}'
-
-        # Only process if the audio file exists
-        if os.path.exists(audio_file):
-            srt_to_segments_with_metadata(srt_file, episode_str, audio_file, output_dir, metadata_file, subset)
-        else:
-            print(f"Audio file not found: {audio_file}. Skipping.")
+    metadata_file = 'full.csv'
+
+    # ffmpeg -i "webm/110.webm" -vn -ar 44100 -c:a pcm_s16le "110.wav"
+    for episode in range(110, 111):
+        episode = f'{episode:03d}'
+
+        srt_file = f'srt/{episode}.srt'
+        audio_file = f'{episode}.wav'
+        output_dir = f'./wav/{episode}'
+        srt_to_segments_with_metadata(
+            srt_file, episode, audio_file, output_dir, metadata_file)

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