Towards an Evolution Model of Expressive Music Performance

  • Authors:
  • Qijun Zhang;Eduardo Reck Miranda

  • Affiliations:
  • University of Plymouth, UK;University of Plymouth, UK

  • Venue:
  • ISDA '06 Proceedings of the Sixth International Conference on Intelligent Systems Design and Applications - Volume 02
  • Year:
  • 2006

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Abstract

This paper presents the design of representing the performance profile with hierarchical pulse sets (i.e., hierarchical duration vs. amplitude matrices), and then applying Genetic Algorithm (GA) to evolve the hierarchical pulse sets for music interpretation, where the fitness of GA is derived from the structure of the music to be performed. In previous work [19], we have shown that GA can evolve suitable pulse sets for musical performance. Also, commonality and diversity are found among the performance profiles decided by those evolved pulse sets. This paper reports the experiment results from an improved system where a new version of fitness rules has been devised. On basis of this system, we are proposing the next steps for the research, that is, to build a dynamic model that evolves expressive music performance through agent performers' interactions.