The Artificial Creative Intelligence and Data Science (ACIDS) group at IRCAM aims to model musical creativity by extending probabilistic learning approaches to the use of multivariate and multimodal time series. Our main object of study lies in the properties and perception of musical synthesis and artificial creativity. In this context, we experiment with deep AI models applied to creative materials, aiming to develop artificial creative intelligence.

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Our highlight projects

  • Neurorack // the first deep AI-based eurorack synthesizer
  • RAVE // a realtime audio variational auto-encoder for timbre transfer, unconditional generation or latent manipulation. Available as max/msp and puredata externals, as well as a VST plugin.
  • FlowSynth // find the presets of a synthesizer from a wav file