EaseVoice Trainer is a backend system for voice cloning and speech model training, designed to be more accessible and user-friendly than its predecessor, GPT-SoVITS. It targets researchers and developers looking for a stable, observable, and modular solution for voice synthesis and transformation tasks.

How It Works

The project is built on GPT-SoVITS concepts but features a clean, modular architecture with separate frontend and backend repositories. It offers a RESTful API for integration and is designed for scalability. Key improvements include simplified workflows, enhanced stability, and comprehensive monitoring tools, including Tensorboard integration for real-time training visualization.

Quick Start & Requirements

• Install: uv sync followed by uv pip install whl/LangSegment-0.3.5-py3-none-any.whl and uv run src/main.py. Docker is also supported.
• Prerequisites: Python 3.9+, uv. Pretrained models need to be downloaded and placed in the models directory.
• Links: EaseVoice Trainer Frontend

Highlighted Details

• Streamlined workflows and intuitive configurations for ease of use.
• Integrated Tensorboard for real-time monitoring and visualization of training progress.
• RESTful API for seamless integration with other services.
• Modular design with separate frontend and backend repositories for improved maintainability.

Maintenance & Community

The project welcomes community contributions. Further community engagement details (e.g., Discord/Slack) are not specified in the README.

Licensing & Compatibility

Released under the Apache 2.0 license, permitting commercial use and integration with closed-source projects.

Limitations & Caveats

The README does not detail specific limitations, known bugs, or deprecation status. The project is presented as a backend component, implying a separate frontend is required for a complete user experience.