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--- |
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language: |
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- kr |
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license: cc-by-4.0 |
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library_name: nemo |
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datasets: |
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- RealCallData |
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thumbnail: null |
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tags: |
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- automatic-speech-recognition |
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- speech |
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- audio |
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- Citrinet1024 |
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- NeMo |
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- pytorch |
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model-index: |
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- name: stt_kr_citrinet1024_PublicCallCenter_1000H_0.22 |
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results: [] |
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--- |
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## Model Overview |
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<DESCRIBE IN ONE LINE THE MODEL AND ITS USE> |
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## NVIDIA NeMo: Training |
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To train, fine-tune or play with the model you will need to install [NVIDIA NeMo](https://github.com/NVIDIA/NeMo). We recommend you install it after you've installed latest Pytorch version. |
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``` |
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pip install nemo_toolkit['all'] |
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``` |
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## How to Use this Model |
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The model is available for use in the NeMo toolkit [1], and can be used as a pre-trained checkpoint for inference or for fine-tuning on another dataset. |
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### Automatically instantiate the model |
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```python |
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import nemo.collections.asr as nemo_asr |
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asr_model = nemo_asr.models.ASRModel.from_pretrained("ypluit/stt_kr_citrinet1024_PublicCallCenter_1000H_0.22") |
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``` |
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### Transcribing using Python |
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First, let's get a sample |
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``` |
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get any korean telephone voice wave file |
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``` |
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Then simply do: |
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``` |
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asr_model.transcribe(['sample-kr.wav']) |
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``` |
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### Transcribing many audio files |
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```shell |
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python [NEMO_GIT_FOLDER]/examples/asr/transcribe_speech.py pretrained_name="model" audio_dir="<DIRECTORY CONTAINING AUDIO FILES>" |
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``` |
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### Input |
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This model accepts 16000Hz Mono-channel Audio (wav files) as input. |
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### Output |
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This model provides transcribed speech as a string for a given audio sample. |
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## Model Architecture |
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See nemo toolkit and reference papers. |
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## Training |
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Learned about 30 days on 2 A6000 |
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### Datasets |
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Private call center real data (1100hour) |
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## Performance |
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< 0.13 CER |
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## Limitations |
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This model was trained with 650 hours of Korean telephone voice data for customer service in a call center. might be Poor performance for general-purpose dialogue and specific accents. |
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## References |
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[1] [NVIDIA NeMo Toolkit](https://github.com/NVIDIA/NeMo) |
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