0adf29c35b
fix : 解决在未安装vs时会报错"Microsoft Visual C++ 14.0 is required"的问题 |
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archived_untest_files | ||
encoder | ||
samples | ||
synthesizer | ||
toolbox | ||
utils | ||
vocoder | ||
.gitattributes | ||
.gitignore | ||
CODE_OF_CONDUCT.md | ||
demo_toolbox.py | ||
LICENSE.txt | ||
README-CN.md | ||
README.md | ||
requirements.txt | ||
synthesizer_preprocess_audio.py | ||
synthesizer_preprocess_embeds.py | ||
synthesizer_train.py |
This repository is forked from Real-Time-Voice-Cloning which only support English.
English | 中文
Features
🌍 Chinese supported mandarin and tested with multiple datasets: aidatatang_200zh, magicdata
🤩 PyTorch worked for pytorch, tested in version of 1.9.0(latest in August 2021), with GPU Tesla T4 and GTX 2060
🌍 Windows + Linux tested in both Windows OS and linux OS after fixing nits
🤩 Easy & Awesome effect with only newly-trained synthesizer, by reusing the pretrained encoder/vocoder
DEMO VIDEO
Quick Start
1. Install Requirements
Follow the original repo to test if you got all environment ready. **Python 3.7 or higher ** is needed to run the toolbox.
- Install PyTorch.
- Install ffmpeg.
- Run
pip install -r requirements.txt
to install the remaining necessary packages.
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.
2. Train synthesizer with your dataset
-
Download aidatatang_200zh or SLR68 dataset and unzip: make sure you can access all .wav in train folder
-
Preprocess with the audios and the mel spectrograms:
python synthesizer_preprocess_audio.py <datasets_root>
Allow parameter--dataset {dataset}
to support adatatang_200zh, magicdata -
Preprocess the embeddings:
python synthesizer_preprocess_embeds.py <datasets_root>/SV2TTS/synthesizer
-
Train the synthesizer:
python synthesizer_train.py mandarin <datasets_root>/SV2TTS/synthesizer
-
Go to next step when you see attention line show and loss meet your need in training folder synthesizer/saved_models/.
FYI, my attention came after 18k steps and loss became lower than 0.4 after 50k steps.
2.2 Use pretrained model of synthesizer
Thanks to the community, some models will be shared:
author | Download link | Previow Video |
---|---|---|
@miven | https://pan.baidu.com/s/1PI-hM3sn5wbeChRryX-RCQ code:2021 | https://www.bilibili.com/video/BV1uh411B7AD/ |
A link to my early trained model: Baidu Yun Code:aid4
3. Launch the Toolbox
You can then try the toolbox:
python demo_toolbox.py -d <datasets_root>
or
python demo_toolbox.py
Good news🤩: Chinese Characters are supported
TODO
- Add demo video
- Add support for more dataset
- Upload pretrained model
- Support parallel tacotron
- Service orianted and docterize
- 🙏 Welcome to add more