ShiLiang Zhang
2023-09-06 b87273a856effc4f1bcff953d09b9e89662e28dd
docs/model_zoo/modelscope_models_zh.md
@@ -20,8 +20,8 @@
| [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          |
|               [Paraformer实时](https://www.modelscope.cn/models/damo/speech_paraformer_asr_nat-zh-cn-16k-common-vocab8404-实时/summary)                | 中文和英文  | 阿里巴巴语音数据 (50000hours) |       8404        | 68M  | 实时  | 能够处理流式输入                   |
|         [Paraformer-large实时](https://www.modelscope.cn/models/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-实时/summary)          | 中文和英文  | 阿里巴巴语音数据 (60000hours) |       8404        | 220M | 实时  | 能够处理流式输入                   |
|               [Paraformer实时](https://modelscope.cn/models/damo/speech_paraformer_asr_nat-zh-cn-16k-common-vocab8404-online/summary)                | 中文和英文  | 阿里巴巴语音数据 (50000hours) |       8404        | 68M  | 实时  | 能够处理流式输入                   |
|         [Paraformer-large实时](https://modelscope.cn/models/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-online/summary)          | 中文和英文  | 阿里巴巴语音数据 (60000hours) |       8404        | 220M | 实时  | 能够处理流式输入                   |
|       [Paraformer-tiny](https://www.modelscope.cn/models/damo/speech_paraformer-tiny-commandword_asr_nat-zh-cn-16k-vocab544-pytorch/summary)       |   中文   |  阿里巴巴语音数据 (200hours)  |        544        | 5.2M | 非实时 | 轻量级Paraformer模型,支持普通话命令词识别 |
|                   [Paraformer-aishell](https://www.modelscope.cn/models/damo/speech_paraformer_asr_nat-aishell1-pytorch/summary)                   |   中文   |  AISHELL (178hours)   |       4234        | 43M  | 非实时 | 学术模型                       |
|       [ParaformerBert-aishell](https://modelscope.cn/models/damo/speech_paraformerbert_asr_nat-zh-cn-16k-aishell1-vocab4234-pytorch/summary)       |   中文   |  AISHELL (178hours)   |       4234        | 43M  | 非实时 | 学术模型                       |