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README.md
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# Belle-whisper-large-v3-turbo-zh
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Fine tune whisper-large-v3-turbo-zh to enhance Chinese speech recognition capabilities,
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Belle-whisper-large-v3-zh
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Same to Belle-whisper-large-v3-zh-punct, the punctuation marks come from model [punc_ct-transformer_cn-en-common-vocab471067-large](https://www.modelscope.cn/models/iic/punc_ct-transformer_cn-en-common-vocab471067-large/),
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and are added to the training datasets.
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| whisper-large-v3 | Chinese | 8.085 | 5.475 | 11.72 | 20.15 | 28.597 |
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| whisper-large-v3-turbo | Chinese | 8.639 | 6.014 | 13.507 | 20.313 | 37.324 |
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| Belle-whisper-large-v3-turbo-zh | Chinese |
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It is worth mentioning that compared to whisper-large-v3-turbo, Belle-whisper-large-v3-turbo-zh even has a significant improvement in complex acoustic scenes(such as wenetspeech_meeting).
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## Citation
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# Belle-whisper-large-v3-turbo-zh
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Fine tune whisper-large-v3-turbo-zh to enhance Chinese speech recognition capabilities,
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Belle-whisper-large-v3-turbo-zh demonstrates a 31~64% relative improvement in performance to whisper-large-v3-turbo on Chinese ASR benchmarks, including AISHELL1, AISHELL2, WENETSPEECH, and HKUST.
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Same to Belle-whisper-large-v3-zh-punct, the punctuation marks come from model [punc_ct-transformer_cn-en-common-vocab471067-large](https://www.modelscope.cn/models/iic/punc_ct-transformer_cn-en-common-vocab471067-large/),
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and are added to the training datasets.
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|:----------------:|:-------:|:-----------:|:-----------:|:--------:|:-----------:|:-------:|
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| whisper-large-v3 | Chinese | 8.085 | 5.475 | 11.72 | 20.15 | 28.597 |
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| whisper-large-v3-turbo | Chinese | 8.639 | 6.014 | 13.507 | 20.313 | 37.324 |
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| Belle-whisper-large-v3-turbo-zh | Chinese | 3.07 | 4.114 | 8.x | 13.357 | 18.944 |
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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.
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## Citation
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