Scaffolding for interactively evolving novel drum tracks for existing songs

  • Authors:

  • Amy K. Hoover;Michael P. Rosario;Kenneth O. Stanley

  • Affiliations:

  • Evolutionary Complexity Research Group, School of Electrical Engineering and Computer Science, University of Central Florida, Orlando, FL;Evolutionary Complexity Research Group, School of Electrical Engineering and Computer Science, University of Central Florida, Orlando, FL;Evolutionary Complexity Research Group, School of Electrical Engineering and Computer Science, University of Central Florida, Orlando, FL

  • Venue:
  • Evo'08 Proceedings of the 2008 conference on Applications of evolutionary computing
  • Year:
  • 2008

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Abstract

A major challenge in computer-generated music is to produce music that sounds natural. This paper introduces NEAT Drummer, which takes steps toward natural creativity. NEAT Drummer evolves a kind of artificial neural network called a Compositional Pattern Producing Network (CPPN) with the NeuroEvolution of Augmenting Topologies (NEAT) method to produce drum patterns. An important motivation for this work is that instrument tracks can be generated as a function of other song parts, which, if written by humans, thereby provide a scaffold for the remaining auto-generated parts. Thus, NEAT Drummer is initialized with inputs from an existing MIDI song and through interactive evolution allows the user to evolve increasingly appealing rhythms for that song. This paper explains how NEAT Drummer processes MIDI inputs and outputs drum patterns. The net effect is that a compelling drum track can be automatically generated and evolved for any song.