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A framework for Anticipatory Machine Improvisation and Style Imitation

Abstract : We present a first step towards anticipatory machine improvisation systems. The proposed system, based on fundamentals of music cognition, is a multi-agent memory-based collaborative and competitive reinforcement learning architecture, capable of live interaction with a musician or a music score. Results demonstrate the ability to model long-term stylistic planning and need for much less training data than reported in previous works.
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Submitted on : Thursday, June 27, 2013 - 11:12:48 AM
Last modification on : Tuesday, March 15, 2022 - 3:22:06 AM
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  • HAL Id : hal-00839074, version 1


Arshia Cont, Shlomo Dubnov, Gerard Assayag. A framework for Anticipatory Machine Improvisation and Style Imitation. Anticipatory Behavior in Adaptive Learning Systems (ABiALS), 2006, Rome, Italy. ⟨hal-00839074⟩



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