Detailed Introduction
GPT-SoVITS is an open-source WebUI project focused on few-shot voice conversion and text-to-speech (TTS). It supports zero-shot (5s) and few-shot (1min) modes, and includes tools for dataset slicing, Chinese ASR, text labeling, and more to help users prepare data, fine-tune models, and deploy locally or in containers. See the linked documentation and demos for examples and guides.
Main Features
- Zero-shot / few-shot operation: perform instant conversion from short reference audio or fine-tune with small datasets for higher timbre similarity.
- Cross-lingual inference: supports English, Japanese, Korean, Cantonese and Chinese.
- WebUI toolset: integrated utilities such as vocal separation, automatic dataset segmentation, ASR and labeling to streamline data preparation.
- Flexible deployment: local runs, Docker images and Hugging Face demos are supported for quick validation and production use.
Use Cases
- Voice cloning prototyping and demos: generate target-voice samples quickly for presentation or testing.
- Research and model development: evaluate fine-tuning strategies, front-end text processing, and model variants.
- Media tooling integration: incorporate conversion and TTS into content production pipelines.
Technical Features
- PyTorch-based implementation with Conda and Docker installation scripts supporting multiple CUDA and CPU environments.
- Distributed pretrained models and public demos (Hugging Face) provided for rapid verification.
- MIT-licensed, actively maintained repository with extensive README and Wiki documentation for installation, training and deployment.