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fishaudio/Bert-VITS2 ★ 8796 1306 APPLICATION

Bert-VITS2 is a multilingual text-to-speech system based on VITS2 (Variational Inference Text-to-Speech with improved Transformer backbone). It supports Chinese, Japanese, and English synthesis with optional emotion conditioning via pre-trained models (WavLM, wav2vec2-emotion, CLAP). The codebase provides a complete pipeline: data preprocessing (resampling, text normalization, BERT feature extraction), multi-speaker training with distributed support, inference through a Gradio web UI or FastAPI server (hiyoriUI.py), and ONNX export for deployment. The architecture uses separate per-language BERT models for text encoding, a flow-based decoder, stochastic duration predictor, and multi-scale discriminators (including a WavLM-based discriminator). The repository includes numerous versioned subdirectories (oldVersion/, onnx_modules/) for backward compatibility with model versions 1.0.1 through 2.4, resulting in significant code duplication and maintenance overhead. The README explicitly states the project is no longer maintained and recommends the successor project Fish-Speech.

RATING: 4.8/10 MAINT: stale DRIFT: high
#text-to-speech #vits2 #multilingual #voice-cloning #onnx #gradio #pytorch #bert #bert-vits2 #tts #vits #bert-vits #llm #fish #vocoder #fish-speech #agent
▸ 5 reusable components found
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