Algorithmic music composition using dynamic Markov chains and genetic algorithms

  • Authors:
  • Chip Bell

  • Affiliations:
  • ScienceTRAX, Macon, GA

  • Venue:
  • Journal of Computing Sciences in Colleges
  • Year:
  • 2011

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Abstract

Music has always been considered to be something uniquely "human" because of the creativity involved in its composition. Although this is the case, almost all composed music follows a set of rules chosen by either the composer or the musical norms at the time. These composers are following a set of rules and, despite their possible complexity, these rules can be followed by a computer to automate the composition process. I present a novel method for algorithmic music composition using two techniques employed in previous computational systems: Markov Chains and Genetic Algorithms. Markov Chains are utilized in this system to choose the next pitch, rhythm, and chord. Genetic algorithms are employed as a search method that finds the set of Markov chains that yield the most pleasant sounding music.