MoonInTheRiver/DiffSinger

Health v2 · maintenance only

Adoption not part of the score

4851 stars · 828 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Official PyTorch implementation of DiffSinger, an AAAI 2022 paper on singing voice synthesis and text-to-speech using a shallow diffusion mechanism. It includes training and inference code for SVS (with MIDI input) and TTS (DiffSpeech), plus acceleration plugins like PNDM.

Use cases

• synthesize singing voice from MIDI and lyrics
• generate speech from text with diffusion models
• train a singing voice synthesis model on the PopCS or Opencpop datasets
• accelerate diffusion-based speech synthesis with PNDM
• reproduce AAAI 2022 DiffSinger paper results
• build a demo of neural singing synthesis

When to choose

• you need a research-grade implementation of diffusion-based singing voice synthesis
• you want to experiment with shallow diffusion for speech or singing generation
• you need MIDI-conditioned singing synthesis with training code
• you want to reproduce or extend the DiffSinger/DiffSpeech papers

When to avoid

• you need a production-ready, user-friendly TTS product with pretrained voices and simple APIs
• you want real-time low-latency synthesis out of the box
• you need a maintained general-purpose TTS toolkit rather than a research codebase
• you lack a GPU or ML engineering experience

Facets

library · maturity maintenance

machine-learning deep-learning audio-processing speech-recognition tts artificial-intelligence deep-learning speech-processing machine-learning python diffusion-model singing-voice-synthesis text-to-speech svs pytorch research-code aaai-2022 midi audio linux gpu

Member repositories

For agents

markdown · JSON · MCP: product_card(name="MoonInTheRiver/DiffSinger")