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
If you want to fine-thuning the model on your datasets, please reference to the github repo
CER(%) ↓
Table with columns: Model, Language Tag, aishell_1_test(↓), aishell_2_test(↓), wenetspeech_net(↓), wenetspeech_meeting(↓), HKUST_dev(↓)| 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 |
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}},}