# GPT-SoVITS - Voice Conversion and Text-to-Speech WebUI ## Demo Video and Features Check out our demo video in Chinese: [Bilibili Demo](https://www.bilibili.com/video/BV12g4y1m7Uw/) https://github.com/RVC-Boss/GPT-SoVITS/assets/129054828/05bee1fa-bdd8-4d85-9350-80c060ab47fb ### Features: 1. **Zero-shot TTS:** Input a 5-second vocal sample and experience instant text-to-speech conversion. 2. **Few-shot TTS:** Fine-tune the model with just 1 minute of training data for improved voice similarity and realism. 3. **Cross-lingual Support:** Inference in languages different from the training dataset, currently supporting English, Japanese, and Chinese. 4. **WebUI Tools:** Integrated tools include voice accompaniment separation, automatic training set segmentation, Chinese ASR, and text labeling, assisting beginners in creating training datasets and GPT/SoVITS models. ## Todo List 0. **High Priority:** - Localization in Japanese and English. - User guide. 1. **Features:** - Zero-shot voice conversion (5s) / few-shot voice conversion (1min). - TTS speaking speed control. - Enhanced TTS emotion control. - Experiment with changing SoVITS token inputs to probability distribution of vocabs. - Improve English and Japanese text frontend. - Develop tiny and larger-sized TTS models. - Colab scripts. - Expand training dataset (2k -> 10k). ## Requirements (How to Install) ### Python and PyTorch Version Tested with Python 3.9, PyTorch 2.0.1, and CUDA 11. ### Quick Install with Conda ```bash conda create -n GPTSoVits python=3.9 conda activate GPTSoVits bash install.sh ``` ### Pip Packages ```bash pip install torch numpy scipy tensorboard librosa==0.9.2 numba==0.56.4 pytorch-lightning gradio==3.14.0 ffmpeg-python onnxruntime tqdm cn2an pypinyin pyopenjtalk g2p_en chardet ``` ### Additional Requirements If you need Chinese ASR (supported by FunASR), install: ```bash pip install modelscope torchaudio sentencepiece funasr ``` ### FFmpeg #### Ubuntu/Debian Users ```bash sudo apt install ffmpeg ``` #### MacOS Users ```bash brew install ffmpeg ``` #### Windows Users Download and place [ffmpeg.exe](https://huggingface.co/lj1995/VoiceConversionWebUI/blob/main/ffmpeg.exe) and [ffprobe.exe](https://huggingface.co/lj1995/VoiceConversionWebUI/blob/main/ffprobe.exe) in the GPT-SoVITS root. ### Pretrained Models Download pretrained models from [GPT-SoVITS Models](https://huggingface.co/lj1995/GPT-SoVITS) and place them in `GPT_SoVITS\pretrained_models`. For Chinese ASR, download models from [Damo ASR Models](https://modelscope.cn/models/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/files) and place them in `tools/damo_asr/models`. For UVR5 (Vocals/Accompaniment Separation & Reverberation Removal), download models from [UVR5 Weights](https://huggingface.co/lj1995/VoiceConversionWebUI/tree/main/uvr5_weights) and place them in `tools/uvr5/uvr5_weights`. ## Dataset Format The TTS annotation .list file format: ``` vocal_path|speaker_name|language|text ``` Example: ``` D:\GPT-SoVITS\xxx/xxx.wav|xxx|en|I like playing Genshin. ``` Language dictionary: - 'zh': Chinese - 'ja': Japanese - 'en': English ## Credits Special thanks to the following projects and contributors: - [ar-vits](https://github.com/innnky/ar-vits) - [SoundStorm](https://github.com/yangdongchao/SoundStorm/tree/master/soundstorm/s1/AR) - [vits](https://github.com/jaywalnut310/vits) - [TransferTTS](https://github.com/hcy71o/TransferTTS/blob/master/models.py#L556) - [Chinese Speech Pretrain](https://github.com/TencentGameMate/chinese_speech_pretrain) - [contentvec](https://github.com/auspicious3000/contentvec/) - [hifi-gan](https://github.com/jik876/hifi-gan) - [Chinese-Roberta-WWM-Ext-Large](https://huggingface.co/hfl/chinese-roberta-wwm-ext-large) - [fish-speech](https://github.com/fishaudio/fish-speech/blob/main/tools/llama/generate.py#L41) - [ultimatevocalremovergui](https://github.com/Anjok07/ultimatevocalremovergui) - [audio-slicer](https://github.com/openvpi/audio-slicer) - [SubFix](https://github.com/cronrpc/SubFix) - [FFmpeg](https://github.com/FFmpeg/FFmpeg) - [gradio](https://github.com/gradio-app/gradio)