metadata

license: apache-2.0
metrics:
  - cer

Welcome

If you find this model helpful, please like this model and star us on https://github.com/LianjiaTech/BELLE !

Belle-whisper-large-v2-zh

Fine tune whisper-large-v2 to improve Chinese speech recognition, Belle-whisper-large-v2-zh has 30-70% relative improvements on Chinese ASR benchmark(AISHELL1, AISHELL2, WENETSPEECH, HKUST).

Usage


from transformers import pipeline

transcriber = pipeline(
  "automatic-speech-recognition", 
  model="BELLE-2/Belle-whisper-large-v2-zh"
)

transcriber.model.config.forced_decoder_ids = (
  transcriber.tokenizer.get_decoder_prompt_ids(
    language="zh", 
    task="transcribe"
  )
)

transcription = transcriber("my_audio.wav")

Fine-tuning

Model	(Re)Sample Rate	Train Datasets	Fine-tuning (full or peft)
Belle-whisper-large-v2-zh	16KHz	AISHELL-1 AISHELL-2 WenetSpeech HKUST	full fine-tuning

If you want to fine-thuning the model on your datasets, please reference to our github repo

CER

Model	Language Tag	aishell_1_test	aishell_2_test	wenetspeech_net	wenetspeech_meeting	HKUST_dev
whisper-large-v2	Chinese	0.08818	0.06183	0.12343	0.26413	0.31917
Belle-whisper-large-v2-zh	Chinese	0.02549	0.03746	0.08503	0.14598	0.16289

Citation

Please cite our paper and github when using our code, data or model.

@misc{BELLE,
  author = {BELLEGroup},
  title = {BELLE: Be Everyone's Large Language model Engine},
  year = {2023},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/LianjiaTech/BELLE}},
}