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@@ -44,8 +44,8 @@ Here we provided several pretrained models on different datasets. The details of
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| Model Name | Training Data | Parameters | Sampling Rate | Notes |
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|:----------------------------------------------------------------------------------------------:|:----------------------------:|:----------:|:-------------:|:------|
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-| [FSMN-VAD](https://modelscope.cn/models/damo/speech_fsmn_vad_zh-cn-16k-common-pytorch/summary) | Alibaba Speech Data (?hours) | 0.4M | 16000 | |
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-| [FSMN-VAD](https://modelscope.cn/models/damo/speech_fsmn_vad_zh-cn-8k-common/summary) | Alibaba Speech Data (?hours) | 0.4M | 8000 | |
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+| [FSMN-VAD](https://modelscope.cn/models/damo/speech_fsmn_vad_zh-cn-16k-common-pytorch/summary) | Alibaba Speech Data (5000hours) | 0.4M | 16000 | |
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+| [FSMN-VAD](https://modelscope.cn/models/damo/speech_fsmn_vad_zh-cn-8k-common/summary) | Alibaba Speech Data (5000hours) | 0.4M | 8000 | |
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### Punctuation Restoration Models
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lingyunfly