mirror of
https://github.com/babysor/MockingBird.git
synced 2024-03-22 13:11:31 +08:00
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9f30ca8e92
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@ -34,6 +34,8 @@
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可以传入参数 --dataset `{dataset}` 支持 adatatang_200zh, magicdata
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> 假如你下载的 `aidatatang_200zh`文件放在D盘,`train`文件路径为 `D:\data\aidatatang_200zh\corpus\train` , 你的`datasets_root`就是 `D:\data\`
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>假如發生 `頁面文件太小,無法完成操作`,請參考這篇[文章](https://blog.csdn.net/qq_17755303/article/details/112564030),將虛擬內存更改為100G(102400),例如:档案放置D槽就更改D槽的虚拟内存
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* 预处理嵌入:
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`python synthesizer_preprocess_embeds.py <datasets_root>/SV2TTS/synthesizer`
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@ -48,8 +50,8 @@
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### 2.2 使用预先训练好的合成器
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> 实在没有设备或者不想慢慢调试,可以使用网友贡献的模型(欢迎持续分享):
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| 作者 | 下载链接 | 效果预览 |
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| --- | ----------- | ----- |
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| 作者 | 下载链接 | 效果预览 |
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| --- | ----------- | ----- |
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|@miven| https://pan.baidu.com/s/1PI-hM3sn5wbeChRryX-RCQ 提取码:2021 | https://www.bilibili.com/video/BV1uh411B7AD/
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### 3. 启动工具箱
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20
README.md
20
README.md
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@ -3,14 +3,14 @@
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[![MIT License](https://img.shields.io/badge/license-MIT-blue.svg?style=flat)](http://choosealicense.com/licenses/mit/)
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> This repository is forked from [Real-Time-Voice-Cloning](https://github.com/CorentinJ/Real-Time-Voice-Cloning) which only support English.
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> English | [中文](README-CN.md)
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> English | [中文](README-CN.md)
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## Features
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🌍 **Chinese** supported mandarin and tested with multiple datasets: aidatatang_200zh, magicdata
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🤩 **PyTorch** worked for pytorch, tested in version of 1.9.0(latest in August 2021), with GPU Tesla T4 and GTX 2060
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🌍 **Windows + Linux** tested in both Windows OS and linux OS after fixing nits
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🌍 **Windows + Linux** tested in both Windows OS and linux OS after fixing nits
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🤩 **Easy & Awesome** effect with only newly-trained synthesizer, by reusing the pretrained encoder/vocoder
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@ -27,19 +27,23 @@
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> If you get an `ERROR: Could not find a version that satisfies the requirement torch==1.9.0+cu102 (from versions: 0.1.2, 0.1.2.post1, 0.1.2.post2 )` This error is probably due to a low version of python, try using 3.9 and it will install successfully
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* Install [ffmpeg](https://ffmpeg.org/download.html#get-packages).
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* Run `pip install -r requirements.txt` to install the remaining necessary packages.
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* Install webrtcvad `pip install webrtcvad-wheels`(If you need)
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> Note that we are using the pretrained encoder/vocoder but synthesizer, since the original model is incompatible with the Chinese sympols. It means the demo_cli is not working at this moment.
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### 2. Train synthesizer with your dataset
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* Download aidatatang_200zh or SLR68 dataset and unzip: make sure you can access all .wav in *train* folder
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* Preprocess with the audios and the mel spectrograms:
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`python synthesizer_preprocess_audio.py <datasets_root>`
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Allow parameter `--dataset {dataset}` to support adatatang_200zh, magicdata
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>If it happens `the page file is too small to complete the operation`, please refer to this [video](https://www.youtube.com/watch?v=Oh6dga-Oy10&ab_channel=CodeProf) and change the virtual memory to 100G (102400), for example : When the file is placed in the D disk, the virtual memory of the D disk is changed.
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* Preprocess the embeddings:
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`python synthesizer_preprocess_embeds.py <datasets_root>/SV2TTS/synthesizer`
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* Train the synthesizer:
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`python synthesizer_train.py mandarin <datasets_root>/SV2TTS/synthesizer`
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* Go to next step when you see attention line show and loss meet your need in training folder *synthesizer/saved_models/*.
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* Go to next step when you see attention line show and loss meet your need in training folder *synthesizer/saved_models/*.
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> FYI, my attention came after 18k steps and loss became lower than 0.4 after 50k steps.
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![attention_step_20500_sample_1](https://user-images.githubusercontent.com/7423248/128587252-f669f05a-f411-4811-8784-222156ea5e9d.png)
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![step-135500-mel-spectrogram_sample_1](https://user-images.githubusercontent.com/7423248/128587255-4945faa0-5517-46ea-b173-928eff999330.png)
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### 2.2 Use pretrained model of synthesizer
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> Thanks to the community, some models will be shared:
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| author | Download link | Previow Video |
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| --- | ----------- | ----- |
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| author | Download link | Previow Video |
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| --- | ----------- | ----- |
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|@miven| https://pan.baidu.com/s/1PI-hM3sn5wbeChRryX-RCQ code:2021 | https://www.bilibili.com/video/BV1uh411B7AD/
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> A link to my early trained model: [Baidu Yun](https://pan.baidu.com/s/10t3XycWiNIg5dN5E_bMORQ)
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@ -56,9 +60,9 @@ Code:aid4
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### 3. Launch the Toolbox
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You can then try the toolbox:
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`python demo_toolbox.py -d <datasets_root>`
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or
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`python demo_toolbox.py`
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`python demo_toolbox.py -d <datasets_root>`
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or
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`python demo_toolbox.py`
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> Good news🤩: Chinese Characters are supported
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