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Physical Manifestation of Generative AI Music Systems for Live Performance

Author(s)
Naseck, Perry; Blanchard, Lancelot; Lavakare, Madhav; Lecamwasam, Kimaya; Paradiso, Joseph
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Abstract
This paper explores the physical manifestation of generative AI music systems for live performance, focusing on bridging the expressive gap between AI-generated music and audience perception. Through a year-long collaboration with a human performer, we constructed a kinetic sculpture that visualizes the outputs of an AI jam_bot during concerts. The sculpture, powered by ML-based and pattern-driven mapping methodologies, interprets real-time AI musical decisions as expressive movements. Audience feedback indicates increased engagement and curiosity, although interpretability remains a challenge. Our work highlights the potential of embodied visualization to establish communicative presence for AI performers and suggests avenues for future research.
Description
SA Art Papers ’25, Hong Kong, Hong Kong
Date issued
2025-12-14
URI
https://hdl.handle.net/1721.1/164526
Department
Massachusetts Institute of Technology. Media Laboratory
Publisher
ACM|SIGGRAPH Asia 2025 Art Papers
Citation
Perry Naseck, Lancelot Blanchard, Madhav Lavakare, Kimaya Lecamwasam, and Joseph A. Paradiso. 2025. Physical Manifestation of Generative AI Music Systems for Live Performance. In Proceedings of the SIGGRAPH Asia 2025 Art Papers (SA Art Papers '25). Association for Computing Machinery, New York, NY, USA, Article 28, 1–6.
Version: Final published version
ISBN
979-8-4007-2129-8

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