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### 3.1 启动Web程序：
`python web.py`
运行成功后在浏览器打开地址, 默认为 `http://localhost:8080`
<img width="578" alt="bd64cd80385754afa599e3840504f45" src="https://user-images.githubusercontent.com/7423248/134275205-c95e6bd8-4f41-4eb5-9143-0390627baee1.png">
> 注：目前界面比较buggy,
> * 第一次点击`录制`要等待几秒浏览器正常启动录音，否则会有重音
> * 录制结束不要再点`录制`而是`停止`
@ -78,6 +80,7 @@
### 3.2 启动工具箱：
`python demo_toolbox.py -d <datasets_root>`
> 请指定一个可用的数据集文件路径，如果有支持的数据集则会自动加载供调试，也同时会作为手动录制音频的存储目录。
<img width="1042" alt="d48ea37adf3660e657cfb047c10edbc" src="https://user-images.githubusercontent.com/7423248/134275227-c1ddf154-f118-4b77-8949-8c4c7daf25f0.png">
## Release Note
2021.9.8 新增Hifi-GAN Vocoder支持
@ -165,4 +168,4 @@ voc_pad =2
#### 7.什么时候算训练完成？
首先一定要出现注意力模型，其次是loss足够低，取决于硬件设备和数据集。拿本人的供参考，我的注意力是在 18k 步之后出现的，并且在 50k 步之后损失变得低于 0.4
![attention_step_20500_sample_1](https://user-images.githubusercontent.com/7423248/128587252-f669f05a-f411-4811-8784-222156ea5e9d.png)
![step-135500-mel-spectrogram_sample_1](https://user-images.githubusercontent.com/7423248/128587255-4945faa0-5517-46ea-b173-928eff999330.png)
![step-135500-mel-spectrogram_sample_1](https://user-images.githubusercontent.com/7423248/128587255-4945faa0-5517-46ea-b173-928eff999330.png)