acids-ircam/RAVE

Health v2 · maintenance only

Flags: no_license

Adoption not part of the score

1790 stars · 224 forks observed · 2026-08-28

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

RAVE is the official PyTorch implementation of a realtime audio variational autoencoder for fast, high-quality neural audio synthesis. It supports dataset preparation, model training, and export for use in live performance tools such as VST plugins and Max/MSP.

Use cases

• train a neural audio synthesis model on my own sound corpus
• generate realtime audio from a trained latent model in a DAW
• compress audio into a compact latent representation for live performance
• create a VST or Max/MSP instrument from custom training data
• run neural audio synthesis on GPU with low latency

When to choose

• you need realtime neural audio synthesis with a trained model
• you want to train a generative audio model on custom datasets
• you need exportable models for VST or Max 8 integration

When to avoid

• you only need simple audio effects without machine learning
• you lack a GPU or cannot install PyTorch and ffmpeg
• you need general-purpose speech recognition or TTS rather than synthesis

Facets

library · maturity active

machine-learning deep-learning audio-processing llm-training deep-learning machine-learning media python cross-platform variational-autoencoder neural-audio-synthesis realtime-audio generative-model music torch audio gpu

Member repositories

For agents

markdown · JSON · MCP: product_card(name="acids-ircam/RAVE")