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Evolving musical performance profiles using genetic algorithms with structural fitness

Published: 08 July 2006 Publication History

Abstract

This paper presents a system that uses Genetic Algorithm (GA) to evolve hierarchical pulse sets (i.e., hierarchical duration vs. amplitude matrices) for expressive music performance by machines. The performance profile for a piece of music is represented using pulse sets and the fitness (for the GA) is derived from the structure of the piece to be performed; hence the term "structural fitness". Randomly initiated pulse sets are selected and evolved using GA. The fitness value is calculated by measuring the pulse set's ability of highlighting musical structures. This measurement is based upon generative rules for expressive music performance. This is the first stage of a project, which is aimed at the design of a dynamic model for the evolution of expressive performance profiles by interacting agents in an artificial society of musicians and listeners.

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Cited By

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  • (2021)Artificial Intelligence Based Music Composition System-Multi Algorithmic Music Arranger(MAGMA)2021 Second International Conference on Electronics and Sustainable Communication Systems (ICESC)10.1109/ICESC51422.2021.9532706(1808-1813)Online publication date: 4-Aug-2021
  • (2021)Performance Creativity in Computer Systems for Expressive Performance of MusicHandbook of Artificial Intelligence for Music10.1007/978-3-030-72116-9_19(521-584)Online publication date: 3-Jul-2021
  • (2012)2011 Robert S. Engelmore Memorial Lecture AwardAI Magazine10.1609/aimag.v33i4.240533:4(22-32)Online publication date: 1-Dec-2012
  • Show More Cited By

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cover image ACM Conferences
GECCO '06: Proceedings of the 8th annual conference on Genetic and evolutionary computation
July 2006
2004 pages
ISBN:1595931864
DOI:10.1145/1143997
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 08 July 2006

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Author Tags

  1. application
  2. art and music
  3. entertainment and media

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GECCO06
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GECCO06: Genetic and Evolutionary Computation Conference
July 8 - 12, 2006
Washington, Seattle, USA

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GECCO '06 Paper Acceptance Rate 205 of 446 submissions, 46%;
Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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Cited By

View all
  • (2021)Artificial Intelligence Based Music Composition System-Multi Algorithmic Music Arranger(MAGMA)2021 Second International Conference on Electronics and Sustainable Communication Systems (ICESC)10.1109/ICESC51422.2021.9532706(1808-1813)Online publication date: 4-Aug-2021
  • (2021)Performance Creativity in Computer Systems for Expressive Performance of MusicHandbook of Artificial Intelligence for Music10.1007/978-3-030-72116-9_19(521-584)Online publication date: 3-Jul-2021
  • (2012)2011 Robert S. Engelmore Memorial Lecture AwardAI Magazine10.1609/aimag.v33i4.240533:4(22-32)Online publication date: 1-Dec-2012
  • (2012)Artificial Evolution of Expressive Performance of Music: An Imitative Multi-Agent Systems ApproachGuide to Computing for Expressive Music Performance10.1007/978-1-4471-4123-5_4(99-121)Online publication date: 31-May-2012
  • (2010)Artificial evolution of expressive performance of musicComputer Music Journal10.1162/comj.2010.34.1.8034:1(80-96)Online publication date: 1-Mar-2010
  • (2009)A survey of computer systems for expressive music performanceACM Computing Surveys10.1145/1592451.159245442:1(1-41)Online publication date: 14-Dec-2009
  • (2006)Towards an Evolution Model of Expressive Music PerformanceSixth International Conference on Intelligent Systems Design and Applications10.1109/ISDA.2006.253781(1189-1194)Online publication date: Oct-2006

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