---
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
```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)   |    




## 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 |