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update modelscope model zoo

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docs/model_zoo/modelscope_models.md
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@ -17,7 +17,8 @@ Here we provided several pretrained models on different datasets. The details of
| Model Name | Language | Training Data | Vocab Size | Parameter | Offline/Online | Notes |
|:--------------------------------------------------------------------------------------------------------------------------------------------------:|:--------:|:--------------------------------:|:----------:|:---------:|:--------------:|:--------------------------------------------------------------------------------------------------------------------------------|
| [Paraformer-large](https://www.modelscope.cn/models/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/summary) | CN & EN | Alibaba Speech Data (60000hours) | 8404 | 220M | Offline | Duration of input wav <= 20s |
| [Paraformer-large-long](https://www.modelscope.cn/models/damo/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch/summary) | CN & EN | Alibaba Speech Data (60000hours) | 8404 | 220M | Offline | Which would deal with arbitrary length input wav |
| [Paraformer-large-long](https://www.modelscope.cn/models/damo/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch/summary) | CN & EN | Alibaba Speech Data (60000hours) | 8404 | 220M | Offline | Which would deal with arbitrary length input wav |
| [Paraformer-large-en-long](https://www.modelscope.cn/models/damo/speech_paraformer-large-vad-punc_asr_nat-en-16k-common-vocab10020/summary) | EN | Alibaba Speech Data (50000hours) | 10020 | 220M | Offline | Which would deal with arbitrary length input wav |
| [Paraformer-large-Spk](https://modelscope.cn/models/damo/speech_paraformer-large-vad-punc-spk_asr_nat-zh-cn/summary) | CN & EN | Alibaba Speech Data (60000hours) | 8404 | 220M | Offline | Supporting speaker diarizatioin for ASR results based on paraformer-large-long |
| [Paraformer-large-contextual](https://www.modelscope.cn/models/damo/speech_paraformer-large-contextual_asr_nat-zh-cn-16k-common-vocab8404/summary) | CN & EN | Alibaba Speech Data (60000hours) | 8404 | 220M | Offline | Which supports the hotword customization based on the incentive enhancement, and improves the recall and precision of hotwords. |
| [Paraformer](https://modelscope.cn/models/damo/speech_paraformer_asr_nat-zh-cn-16k-common-vocab8358-tensorflow1/summary) | CN & EN | Alibaba Speech Data (50000hours) | 8358 | 68M | Offline | Duration of input wav <= 20s |

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docs/model_zoo/modelscope_models_zh.md
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@ -17,7 +17,8 @@
| 模型名字 | 语言 | 训练数据 | 词典大小 | 参数量 | 非实时/实时 | 备注 |
|:--------------------------------------------------------------------------------------------------------------------------------------------------:|:--------:|:---------------------:|:-----------------:|:----:|:-------:|:---------------------------|
| [Paraformer-large](https://www.modelscope.cn/models/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/summary) | 中文和英文 | 阿里巴巴语音数据（60000小时） | 8404 | 220M | 非实时 | 输入wav文件持续时间不超过20秒 |
| [Paraformer-large长音频版本](https://www.modelscope.cn/models/damo/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch/summary) | 中文和英文 | 阿里巴巴语音数据（60000小时） | 8404 | 220M | 非实时 | 能够处理任意长度的输入wav文件 |
| [Paraformer-large长音频版本](https://www.modelscope.cn/models/damo/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch/summary) | 中文和英文 | 阿里巴巴语音数据（60000小时） | 8404 | 220M | 非实时 | 能够处理任意长度的输入wav文件 |
| [Paraformer-large-en长音频版本](https://www.modelscope.cn/models/damo/speech_paraformer-large-vad-punc_asr_nat-en-16k-common-vocab10020/summary) | 英文 | 阿里巴巴语音数据（50000小时） | 10020 | 220M | 非实时 | 能够处理任意长度的输入wav文件 |
| [Paraformer-large-Spk](https://modelscope.cn/models/damo/speech_paraformer-large-vad-punc-spk_asr_nat-zh-cn/summary) | 中文和英文 | 阿里巴巴语音数据（60000小时） | 8404 | 220M | 非实时 | 在长音频功能的基础上添加说话人识别功能 |
| [Paraformer-large热词](https://www.modelscope.cn/models/damo/speech_paraformer-large-contextual_asr_nat-zh-cn-16k-common-vocab8404/summary) | 中文和英文 | 阿里巴巴语音数据（60000小时） | 8404 | 220M | 非实时 | 基于激励增强的热词定制支持，可以提高热词的召回率和准确率，输入wav文件持续时间不超过20秒 |
| [Paraformer](https://modelscope.cn/models/damo/speech_paraformer_asr_nat-zh-cn-16k-common-vocab8358-tensorflow1/summary) | 中文和英文 | 阿里巴巴语音数据（50000小时） | 8358 | 68M | 离线 | 输入wav文件持续时间不超过20秒 |