Bert-VITS2 is a text-to-speech (TTS) system that integrates a VITS2 backbone with multilingual BERT for enhanced voice synthesis. It is designed for advanced users and researchers interested in TTS technology, offering a foundation for custom voice model training and experimentation.

How It Works

This project builds upon the VITS2 architecture, incorporating multilingual BERT embeddings to improve prosody and naturalness in speech generation. The core idea is to leverage BERT's contextual understanding of text to inform the VITS2 model, leading to more expressive and human-like synthesized speech.

Quick Start & Requirements

• Install: Refer to webui_preprocess.py for guidance.
• Prerequisites: Python, PyTorch. Specific version requirements are not detailed in the README.
• Resources: Training custom models will likely require significant GPU resources and time.
• Links:
  • Demo Video: https://www.bilibili.com/video/BV18E421371Q
  • Tech Slides Video: https://www.bilibili.com/video/BV1zJ4m1K7cj
  • UI Project: https://github.com/jiangyuxiaoxiao/Bert-VITS2-UI

Highlighted Details

• Core ideas are inspired by MassTTS and VITS.
• Aims for state-of-the-art open-source TTS quality.
• Includes references to related projects like fish-speech and so-vits-svc.

Maintenance & Community

The project states it will no longer be actively maintained, recommending FishAudio's Fish-Speech as a successor.

Licensing & Compatibility

The README does not specify a license. Given the project's nature and references, it's likely intended for research and non-commercial use. Users should exercise caution regarding commercial applications.

Limitations & Caveats

The project is no longer actively maintained. The README explicitly warns against using the project for any illegal purposes, particularly those violating Chinese laws, and prohibits political use.