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From Motion to Musical Gesture: Experiments with Machine Learning in Computer-Aided Composition

Jean Bresson 1 Paul Best 1 Diemo Schwarz 2 Alireza Farhang 3, 4 
1 Repmus - Représentations musicales
STMS - Sciences et Technologies de la Musique et du Son
2 Interaction Son Musique Mouvement
STMS - Sciences et Technologies de la Musique et du Son
3 IRCAM - Institut de Recherche et Coordination Acoustique/Musique
4 Royal Conservatoire Antwerp
Abstract : This paper presents preliminary works exploring the use of machine learning in computer-aided composition processes. We propose a work direction using motion recognition and audio descriptors to learn abstract musical gestures.
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https://hal.archives-ouvertes.fr/hal-01815988
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Submitted on : Thursday, June 14, 2018 - 4:10:54 PM
Last modification on : Wednesday, April 13, 2022 - 3:39:44 AM
Long-term archiving on: : Monday, September 17, 2018 - 5:31:46 PM

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  • HAL Id : hal-01815988, version 1

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CNRS | IRCAM | STMS | SORBONNE-UNIVERSITE | SU-SCIENCES | MUSCI

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Jean Bresson, Paul Best, Diemo Schwarz, Alireza Farhang. From Motion to Musical Gesture: Experiments with Machine Learning in Computer-Aided Composition. MUME 2018: International Workshop on Musical Metacreation, 2018, Salamanca, Spain. ⟨hal-01815988⟩

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