prophesier/diff-svc

Health v2 · maintenance only

Adoption not part of the score

2717 stars · 812 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Diff-SVC is a deep learning project that performs singing voice conversion using diffusion models, transforming input singing audio into a target singer's timbre with basic pitch correction support. It includes preprocessing, training, and inference pipelines for training custom voice conversion models on user datasets.

Use cases

• convert a singing voice into another singer's timbre
• train a custom singing voice conversion model on my own dataset
• do real-time voice changing during singing
• apply pitch correction to converted vocals
• run voice conversion inference on a consumer GPU
• create AI cover songs with a target voice

When to choose

• you need diffusion-based singing voice conversion with trainable custom timbres
• you want GPU inference on modest hardware like a GTX 1060
• you need both offline conversion and real-time voice-changing support

When to avoid

• you need a production-ready, commercially licensed system (AGPL-3.0, academic-use disclaimer)
• you only need speech-to-speech conversion rather than singing
• you want a plug-and-play app with no training or Python setup

Facets

library · maturity active

machine-learning deep-learning audio-processing speech-recognition llm-training machine-learning artificial-intelligence deep-learning python cross-platform windows singing-voice-conversion diffusion-model voice-conversion timbre-transfer pitch-correction vocoder hubert audio-synthesis audio gpu linux

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markdown · JSON · MCP: product_card(name="prophesier/diff-svc")