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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 and https://github.com/shuaijiang/Whisper-Finetune

Belle-whisper-large-v3-turbo-zh

Fine tune whisper-large-v3-turbo-zh to enhance Chinese speech recognition capabilities, Belle-whisper-large-v3-turbo-zh demonstrates a 24-64% relative improvement in performance to whisper-large-v3-turbo on Chinese ASR benchmarks, including AISHELL1, AISHELL2, WENETSPEECH, and HKUST.

Same to Belle-whisper-large-v3-zh-punct, the punctuation marks come from model punc_ct-transformer_cn-en-common-vocab471067-large, and are added to the training datasets.

Usage


from transformers import pipeline

transcriber = pipeline(
  "automatic-speech-recognition", 
  model="BELLE-2/Belle-whisper-large-v3-turbo-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-v3-turbo-zh 16KHz AISHELL-1 AISHELL-2 WenetSpeech HKUST full fine-tuning

To incorporate punctuation marks without compromising performance, Lora fine-tuning was employed. If you want to fine-thuning the model on your datasets, please reference to the github repo

CER(%) ↓

Model Language Tag aishell_1_test(↓) aishell_2_test(↓) wenetspeech_net(↓) wenetspeech_meeting(↓) HKUST_dev(↓)
whisper-large-v3 Chinese 8.085 5.475 11.72 20.15 28.597
whisper-large-v3-turbo Chinese 8.639 6.014 13.507 20.313 37.324
Belle-whisper-large-v3-turbo-zh Chinese 3.070 4.114 10.230 13.357 18.944

It is worth mentioning that compared to whisper-large-v3 and whisper-large-v3-turbo, Belle-whisper-large-v3-turbo-zh has a significant improvement.

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}},
}