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| | | (Note: 🤗 represents the Huggingface model zoo link, ⭐ represents the ModelScope model zoo link) |
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| | | | Model Name | Task Details | Training Date | Parameters | |
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| | | |:---------------------------------------------------------------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------:|:--------------------------------:|:----------:| |
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| | | | paraformer-zh ([⭐](https://www.modelscope.cn/models/damo/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch/summary) [🤗]() ) | speech recognition, with timestamps, non-streaming | 60000 hours, Mandarin | 220M | |
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| | | | paraformer-zh-spk ( [⭐](https://modelscope.cn/models/damo/speech_paraformer-large-vad-punc-spk_asr_nat-zh-cn/summary) [🤗]() ) | speech recognition with speaker diarization, with timestamps, non-streaming | 60000 hours, Mandarin | 220M | |
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| | | | paraformer-zh-online ( [⭐](https://modelscope.cn/models/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-online/summary) [🤗]() ) | speech recognition, non-streaming | 60000 hours, Mandarin | 220M | |
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| | | | paraformer-en ( [⭐](https://www.modelscope.cn/models/damo/speech_paraformer-large-vad-punc_asr_nat-en-16k-common-vocab10020/summary) [🤗]() ) | speech recognition, with timestamps, non-streaming | 50000 hours, English | 220M | |
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| | | | paraformer-en-spk ([🤗]() [⭐]() ) | speech recognition with speaker diarization, non-streaming | 50000 hours, English | 220M | |
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| | | | conformer-en ( [⭐](https://modelscope.cn/models/damo/speech_conformer_asr-en-16k-vocab4199-pytorch/summary) [🤗]() ) | speech recognition, non-streaming | 50000 hours, English | 220M | |
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| | | | ct-punc ( [⭐](https://modelscope.cn/models/damo/punc_ct-transformer_cn-en-common-vocab471067-large/summary) [🤗]() ) | punctuation restoration | 100M, Mandarin and English | 1.1G | |
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| | | | fsmn-vad ( [⭐](https://modelscope.cn/models/damo/speech_fsmn_vad_zh-cn-16k-common-pytorch/summary) [🤗]() ) | voice activity detection | 5000 hours, Mandarin and English | 0.4M | |
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| | | | fa-zh ( [⭐](https://modelscope.cn/models/damo/speech_timestamp_prediction-v1-16k-offline/summary) [🤗]() ) | timestamp prediction | 5000 hours, Mandarin | 38M | |
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| | | | Model Name | Task Details | Training Date | Parameters | |
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| | | |:------------------------------------------------------------------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------:|:--------------------------------:|:----------:| |
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| | | | paraformer-zh <br> ([⭐](https://www.modelscope.cn/models/damo/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch/summary) [🤗]() ) | speech recognition, with timestamps, non-streaming | 60000 hours, Mandarin | 220M | |
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| | | | paraformer-zh-spk <br> ( [⭐](https://modelscope.cn/models/damo/speech_paraformer-large-vad-punc-spk_asr_nat-zh-cn/summary) [🤗]() ) | speech recognition with speaker diarization, with timestamps, non-streaming | 60000 hours, Mandarin | 220M | |
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| | | | <nobr>paraformer-zh-online <br> ( [⭐](https://modelscope.cn/models/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-online/summary) [🤗]() )</nobr> | speech recognition, streaming | 60000 hours, Mandarin | 220M | |
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| | | | paraformer-en <br> ( [⭐](https://www.modelscope.cn/models/damo/speech_paraformer-large-vad-punc_asr_nat-en-16k-common-vocab10020/summary) [🤗]() ) | speech recognition, with timestamps, non-streaming | 50000 hours, English | 220M | |
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| | | | paraformer-en-spk <br> ([⭐]()[🤗]() ) | speech recognition with speaker diarization, non-streaming | Undo | Undo | |
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| | | | conformer-en <br> ( [⭐](https://modelscope.cn/models/damo/speech_conformer_asr-en-16k-vocab4199-pytorch/summary) [🤗]() ) | speech recognition, non-streaming | 50000 hours, English | 220M | |
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| | | | ct-punc <br> ( [⭐](https://modelscope.cn/models/damo/punc_ct-transformer_cn-en-common-vocab471067-large/summary) [🤗]() ) | punctuation restoration | 100M, Mandarin and English | 1.1G | |
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| | | | fsmn-vad <br> ( [⭐](https://modelscope.cn/models/damo/speech_fsmn_vad_zh-cn-16k-common-pytorch/summary) [🤗]() ) | voice activity detection | 5000 hours, Mandarin and English | 0.4M | |
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| | | | fa-zh <br> ( [⭐](https://modelscope.cn/models/damo/speech_timestamp_prediction-v1-16k-offline/summary) [🤗]() ) | timestamp prediction | 5000 hours, Mandarin | 38M | |
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| | | FunASR supports inference and fine-tuning of models trained on industrial data for tens of thousands of hours. For more details, please refer to [modelscope_egs](https://alibaba-damo-academy.github.io/FunASR/en/modelscope_pipeline/quick_start.html). It also supports training and fine-tuning of models on academic standard datasets. For more information, please refer to [egs](https://alibaba-damo-academy.github.io/FunASR/en/academic_recipe/asr_recipe.html). |
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| | | Below is a quick start tutorial. Test audio files ([Mandarin](https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/vad_example.wav), [English]()). |
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| | | |
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| | | ### Command-line usage |
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| | | |
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| | | ```shell |
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| | | funasr --model paraformer-zh asr_example_zh.wav |
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| | | ``` |
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| | | Notes: Support recognition of single audio file, as well as file list in Kaldi-style wav.scp format: `wav_id wav_pat` |
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| | | |
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| | | ### Speech Recognition (Non-streaming) |
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| | | ```python |
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| | | from funasr import infer |
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| | | For more detailed information, please refer to the [service deployment documentation](runtime/readme.md). |
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| | | <a name="Community Communication"></a> |
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| | | <a name="contact"></a> |
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| | | ## Community Communication |
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| | | If you encounter problems in use, you can directly raise Issues on the github page. |
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| | | |
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| | | ## Contributors |
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| | | |
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| | | | <div align="left"><img src="docs/images/nwpu.png" width="260"/> | <img src="docs/images/China_Telecom.png" width="200"/> </div> | <img src="docs/images/RapidAI.png" width="200"/> </div> | <img src="docs/images/aihealthx.png" width="200"/> </div> | <img src="docs/images/XVERSE.png" width="250"/> </div> | |
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| | | |:---------------------------------------------------------------:|:--------------------------------------------------------------:|:-------------------------------------------------------:|:-----------------------------------------------------------:|:------------------------------------------------------:| |
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| | | | <div align="left"><img src="docs/images/alibaba.png" width="260"/> | <div align="left"><img src="docs/images/nwpu.png" width="260"/> | <img src="docs/images/China_Telecom.png" width="200"/> </div> | <img src="docs/images/RapidAI.png" width="200"/> </div> | <img src="docs/images/aihealthx.png" width="200"/> </div> | <img src="docs/images/XVERSE.png" width="250"/> </div> | |
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| | | |:------------------------------------------------------------------:|:---------------------------------------------------------------:|:--------------------------------------------------------------:|:-------------------------------------------------------:|:-----------------------------------------------------------:|:------------------------------------------------------:| |
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| | | The contributors can be found in [contributors list](./Acknowledge.md) |
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