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