Full publication By Gérard Assayag, Laurent Bonnasse-Gahot, Joakim Borg Abstract: Somax2 is an artificial intelligence (AI)-based multiagent system for human–machine co-improvisation that generates stylistically coherent streams while continuously listening and adapting to musicians or other agents. The model on which it is based can be used with little configuration to interact with humans in full autonomy, […]
Software
Somax2
Go to Somax2 project page at Ircam Showcasing the latest breakthroughs in responsive music-performance technology and creative AI Somax2 live generative environment is developed by researchers at IRCAM (Boulez’s world-renowned institute for sound and music research and creation). Based on machine learning, cognitive modeling and corpus based generation, Somax2 is designed to provide real-time machine improvisations […]
Somax2 – A Distributed Co-Creative System for Human-Machine Co-Improvisation
Marco Fiorini, Mikhail Malt. Somax2 – A Distributed Co-Creative System for Human-Machine Co-Improvisation. Proceedings of the Second International Conference on Hybrid Human-Artificial Intelligence HHAI 2023, Jun 2023, Munich, Germany. ⟨hal-04444997⟩ Full publication Download PDF Abstract: Somax2 is a multi-agent interactive system, based on machine-listening, machine learning and generative units, performing live machine co-improvisation with musicians. […]
Somax 2 a Reactive Multi-Agent Environment for Co-Improvisation
Joakim Borg, Gérard Assayag, Mikhail Malt SMC 2022 – Sound Music & Computing, Jun 2022, Saint-Étienne, France. Proceedings of the 19th Sound and Music Computing Conference, 2022 Read full publication. Abstract: Somax 2 is a multi-agent interactive system performing live machine co-improvisation with musicians, based on machine-listening, machine-learning, and generative units. The actual version ([Borg […]
Dicy2 for Ableton Live
Jérôme Nika, Augustin Muller, Joakim Borg, Manuel Poletti, Gérard Assayag Ircam. 2022 Read full article. Abstract: Dicy2 for Live is an Ableton Live plugin using machine learning to interactively generate sequences in a musical relationship to a real-time analysis of an incoming audio stream. It can be integrated into musical situations ranging from the production […]
Dicy2 for Max
Jérôme Nika, Augustin Muller, Joakim Borg, Gérard Assayag, Matthew Ostrowski Ircam UMR STMS 9912. 2022 Read full article. Abstract: Dicy2 for Max is a suite of Max abstractions which use machine learning for interactive generation of musical sequences. It can be integrated into musical situations ranging from the production of structured material within a compositional […]






