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update:增加SenseVoiceSmall模型下载路线
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@@ -182,8 +182,9 @@ pip install -r requirements.txt
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### 3.下载语音识别模型
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### 3.下载语音识别模型
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下载模型文件[SenseVoiceSmall](https://modelscope.cn/models/iic/SenseVoiceSmall/resolve/master/model.pt)到
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默认使用`SenseVoiceSmall`模型,进行语音转文字。因为模型较大,需要独立下载,下载后把`model.pt`文件放在`model/SenseVoiceSmall`目录下。下面两个下载路线任选一个。
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`model/SenseVoiceSmall`目录下
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- 线路一:阿里魔塔下载[SenseVoiceSmall](https://modelscope.cn/models/iic/SenseVoiceSmall/resolve/master/model.pt)
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- 线路二:百度网盘下载[SenseVoiceSmall](https://pan.baidu.com/share/init?surl=QlgM58FHhYv1tFnUT_A8Sg&pwd=qvna) 提取码: `qvna`
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### 4.配置项目
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### 4.配置项目
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@@ -196,6 +196,15 @@ pip install -r requirements.txt
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Download [SenseVoiceSmall](https://modelscope.cn/models/iic/SenseVoiceSmall/resolve/master/model.pt) to
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Download [SenseVoiceSmall](https://modelscope.cn/models/iic/SenseVoiceSmall/resolve/master/model.pt) to
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`model/SenseVoiceSmall`.
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`model/SenseVoiceSmall`.
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By default, the `SenseVoiceSmall` model is used to convert voice to text. Because the model is large, it needs to be
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downloaded independently. After downloading, place the `model.pt` file in the `model/SenseVoiceSmall` directory. Choose
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any of the following two download routes.
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- Line 1: Download Ali Magic
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Tower[SenseVoiceSmall](https://modelscope.cn/models/iic/SenseVoiceSmall/resolve/master/model.pt)
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- Line 2: Baidu Netdisk download[SenseVoiceSmall](https://pan.baidu.com/share/init?surl=QlgM58FHhYv1tFnUT_A8Sg&pwd=qvna)
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提取码: `qvna`
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### 4.Configure Project
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### 4.Configure Project
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Modify the `config.yaml` file to configure the various parameters required for this project. The default LLM uses
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Modify the `config.yaml` file to configure the various parameters required for this project. The default LLM uses
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@@ -373,4 +382,5 @@ VAD:
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- This project is inspired by the [Bailin Voice Dialogue Robot](https://github.com/wwbin2017/bailing) project, and the
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- This project is inspired by the [Bailin Voice Dialogue Robot](https://github.com/wwbin2017/bailing) project, and the
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basic idea of the project is completed。
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basic idea of the project is completed。
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- Thanks to [Tencent Cloud] (https://cloud.tencent.com/) for providing free docker space for this project。
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- Thanks to [Tencent Cloud] (https://cloud.tencent.com/) for providing free docker space for this project。
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- Thanks to [tenclass](https://www.tenclass.com/)Provide adequate documentation support on Xiaozhi Communication Protocol。
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- Thanks to [tenclass](https://www.tenclass.com/)Provide adequate documentation support on Xiaozhi Communication
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Protocol。
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