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--- |
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license: apache-2.0 |
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metrics: |
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- cer |
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--- |
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## Welcome |
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If you find this model helpful, please *like* this model and star us on https://github.com/LianjiaTech/BELLE ! |
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# Belle-distilwhisper-large-v2-zh |
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Fine tune [distilwhisper-large-v2](https://huggingface.co/distil-whisper/distil-large-v2) to enhance Chinese speech recognition capabilities. |
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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. |
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Despite having 51% fewer parameters, Belle-distilwhisper-large-v2-zh achieves a relative improvement of **-3% to 35%** over whisper-large-v2. |
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It's important to note that the original distilwhisper-large-v2 cannot transcribe Chinese (it only outputs English). |
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## Usage |
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```python |
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from transformers import pipeline |
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transcriber = pipeline( |
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"automatic-speech-recognition", |
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model="BELLE-2/Belle-distilwhisper-large-v2-zh" |
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) |
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transcriber.model.config.forced_decoder_ids = ( |
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transcriber.tokenizer.get_decoder_prompt_ids( |
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language="zh", |
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task="transcribe" |
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) |
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) |
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transcription = transcriber("my_audio.wav") |
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``` |
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## Fine-tuning |
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| Model | (Re)Sample Rate | Train Datasets | Fine-tuning (full or peft) | |
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|:----------------:|:-------:|:----------------------------------------------------------:|:-----------:| |
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| 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) | |
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If you want to fine-thuning the model on your datasets, please reference to the [github repo](https://github.com/shuaijiang/Whisper-Finetune) |
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## CER(%) ↓ |
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| Model | Parameters(M) |Language Tag| aishell_1_test( ↓ ) |aishell_2_test( ↓ )| wenetspeech_net ( ↓ )| wenetspeech_meeting( ↓ )| HKUST_dev( ↓ )| |
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|:----------------:|:-------:|:-------:|:-----------:|:-----------:|:--------:|:-----------:|:-------:| |
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| whisper-large-v2 |1550 |Chinese | 8.818% | 6.183% | 12.343% | 26.413% | 31.917% | |
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| distilwhisper-large-v2 |756| Chinese | - | - | - | - | - | |
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| Belle-distilwhisper-large-v2-zh| 756 | Chinese | 5.958% | 6.477% | 12.786% | 17.039% | 20.771% | |
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## Citation |
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Please cite our paper and github when using our code, data or model. |
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``` |
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@misc{BELLE, |
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author = {BELLEGroup}, |
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title = {BELLE: Be Everyone's Large Language model Engine}, |
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year = {2023}, |
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publisher = {GitHub}, |
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journal = {GitHub repository}, |
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howpublished = {\url{https://github.com/LianjiaTech/BELLE}}, |
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} |
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``` |
