Musical Agent Systems: MACAT and MACataRT

Keon Ju M. Lee, Philippe Pasquier
1/19/2025
cs.MAcs.AIcs.HC

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Abstract

Our research explores the development and application of musical agents, human-in-the-loop generative AI systems designed to support music performance and improvisation within co-creative spaces. We introduce MACAT and MACataRT, two distinct musical agent systems crafted to enhance interactive music-making between human musicians and AI. MACAT is optimized for agent-led performance, employing real-time synthesis and self-listening to shape its output autonomously, while MACataRT provides a flexible environment for collaborative improvisation through audio mosaicing and sequence-based learning. Both systems emphasize training on personalized, small datasets, fostering ethical and transparent AI engagement that respects artistic integrity. This research highlights how interactive, artist-centred generative AI can expand creative possibilities, empowering musicians to explore new forms of artistic expression in real-time, performance-driven and music improvisation contexts.

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Cite this paper

@article{lee2025musical,
  title  = {Musical Agent Systems: MACAT and MACataRT},
  author = {Keon Ju M. Lee and Philippe Pasquier},
  year   = {2025},
  eprint = {2502.00023},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2502.00023v1}
}

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