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--- |
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license: cc-by-4.0 |
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task_categories: |
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- automatic-speech-recognition |
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language: |
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- en |
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size_categories: |
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- 100K<n<1M |
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--- |
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# How to Use |
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- Almost the same with [Librispeech](https://huggingface.co/datasets/openslr/librispeech_asr) dataset module since i refered to the [source code](https://huggingface.co/datasets/openslr/librispeech_asr/blob/main/librispeech_asr.py). |
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```python |
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from datasets import load_dataset |
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from pprint import pprint |
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from IPython.display import display, Audio |
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import aiohttp |
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import os |
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# set huggingface cache directory for the extracted raw files and huggingface-cli token |
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os.environ['HF_HOME'] = "/data/to/download" |
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!export HF_HOME="/data/to/download" |
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# download dataset |
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# if already have librispeech_asr in the cache_dir it will use the same audio files. |
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libripc = load_dataset("yoom618/librispeech_pc", |
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"all", # all, clean, other |
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cache_dir="/data/to/download", |
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trust_remote_code=True, |
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# storage_options={'client_kwargs': {'timeout': aiohttp.ClientTimeout(total=7200)}}, # add if you need to increase the timeout |
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# check dataset info |
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print(libripc) |
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display(Audio(libripc['train.clean.100'][0]['audio']['array'], |
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rate=libripc['train.clean.100'][0]['audio']['sample_rate']), |
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autoplay=False) |
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pprint(libripc['train.clean.100'][0]['audio']) |
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``` |