--- 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-v2-zh Fine tune whisper-large-v2 to enhance Chinese speech recognition capabilities, Belle-whisper-large-v2-zh demonstrates a **30-70%** relative improvement in performance on Chinese ASR benchmarks, including AISHELL1, AISHELL2, WENETSPEECH, and HKUST. ## Usage ```python 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](https://openslr.magicdatatech.com/resources/33/) [AISHELL-2](https://www.aishelltech.com/aishell_2) [WenetSpeech](https://wenet.org.cn/WenetSpeech/) [HKUST](https://catalog.ldc.upenn.edu/LDC2005S15) | [full fine-tuning](https://github.com/shuaijiang/Whisper-Finetune) | If you want to fine-thuning the model on your datasets, please reference to the [github repo](https://github.com/shuaijiang/Whisper-Finetune) ## CER(%) ↓ | Model | Language Tag | aishell_1_test(↓) |aishell_2_test(↓)| wenetspeech_net(↓) | wenetspeech_meeting(↓) | HKUST_dev(↓)| |:----------------:|:-------:|:-----------:|:-----------:|:--------:|:-----------:|:-------:| | whisper-large-v2 | Chinese | 8.818 | 6.183 | 12.343 | 26.413 | 31.917 | | Belle-whisper-large-v2-zh | Chinese | 2.549 | 3.746 | 8.503 | 14.598 | 16.289 | ## 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}}, } ```