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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 !
# Belle-distilwhisper-large-v2-zh
Fine tune [distilwhisper-large-v2](https://huggingface.co/distil-whisper/distil-large-v2) to enhance Chinese speech recognition capabilities.
Similar to distilwhisper-large-v2, Belle-distilwhisper-large-v2-zh is **5.8 times faster** and has **51% fewer parameters** compared to whisper-large-v2.
Despite having 51% fewer parameters, Belle-distilwhisper-large-v2-zh achieves a relative improvement of **-3% to 35%** over whisper-large-v2.
It's important to note that the original distilwhisper-large-v2 cannot transcribe Chinese (it only outputs English).
## Usage
```python
from transformers import pipeline
transcriber = pipeline(
"automatic-speech-recognition",
model="BELLE-2/Belle-distilwhisper-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-distilwhisper-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 | Parameters(M) |Language Tag | aishell_1_test |aishell_2_test| wenetspeech_net | wenetspeech_meeting | HKUST_dev|
|:----------------:|:-------:|:-------:|:-----------:|:-----------:|:--------:|:-----------:|:-------:|
| whisper-large-v2 |1550 |Chinese | 8.818% | 6.183% | 12.343% | 26.413% | 31.917% |
| distilwhisper-large-v2 |756| Chinese | - | - | - | - | - |
| Belle-distilwhisper-large-v2-zh| 756 | Chinese | 5.958% | 6.477% | 12.786% | 17.039% | 20.771% |
## 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}},
}
``` |