Evolving musical performance profiles using genetic algorithms with structural fitness

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. Categories and Subject Descriptors I.2 [Artificial Intelligence]: General

• Type: Conference
• Year: 2006
• Where: GECCO
• Authors: Qijun Zhang, Eduardo Reck Miranda
• Keywords: Expressive Music Performance, GECCO 2006, Hierarchical Pulse Sets, Optimization, Pulse Set