Libsyn
Professional podcast hosting, distribution, and monetization with integrated AI workflow automation.
Professional Open-Source End-to-End Voice Conversion and Singing Synthesis Framework
Fish Diffusion is a state-of-the-art, professional-grade neural audio synthesis framework built on PyTorch, specifically optimized for high-fidelity Singing Voice Conversion (SVC) and Singing Voice Synthesis (SVS). By 2026, it has emerged as the definitive successor to traditional Diff-SVC implementations, offering a modular architecture that integrates diffusion probabilistic models with advanced vocoders like HiFi-GAN and BigVGAN. The system excels in capturing nuanced vocal textures, vibrato, and emotional delivery that typical VITS-based models often flatten. Its technical core utilizes RMVPE (Robust MVP-based Pitch Estimation) for ultra-accurate F0 extraction, ensuring that pitch tracking remains stable even in complex polyphonic backgrounds. Positioned as the 'Stable Diffusion of Audio,' the framework allows researchers and studio engineers to train custom voice models with as little as 30 minutes of clean audio. It supports multi-speaker training, cross-lingual synthesis, and shallow diffusion techniques which significantly reduce inference latency without sacrificing the 44.1kHz studio-quality output. The project is maintained by Fish Audio, providing a robust bridge between open-source community innovation and commercial-grade reliability.
A technique that initializes the diffusion process from a predicted mel-spectrogram rather than pure noise.
Professional podcast hosting, distribution, and monetization with integrated AI workflow automation.
Professional-grade AI stem separation and noise reduction for audio and video.
AI-powered real-time noise reduction for seamless communication across AMD-powered systems.
Professional AI-powered audio restoration for high-end video post-production and podcasting.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Robust Multi-resolution Vocal Pitch Estimator designed specifically for singing voices.
Utilizes a speaker encoder to map multiple vocal identities into a single latent space.
Supports seamless switching between HiFi-GAN, NSF-Hifigan, and BigVGAN-MLP.
Directly synthesizes singing from MIDI pitch data and lyric text input.
Maps phonemes across different languages (CN, EN, JP, KR) during the conversion process.
Support for exporting trained diffusion weights into optimized ONNX graphs.
Creating high-quality cover songs for virtual characters without the original actor having professional singing skills.
Registry Updated:2/7/2026
Fine-tune the energy and breathiness parameters in the WebUI.
Render the final 44.1kHz audio and mix into the instrumental track.
Retaining the specific character voice across 10+ different dubbed languages.
Songwriters needing to hear how a specific famous artist might sound on their demo before pitching.