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Evolutionary Computation Applied to Sound Synthesis

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Part of the Natural Computing Series book series (NCS)

Summary

Sound synthesis is a natural domain in which to apply evolutionary computation (EC). The EC concepts of the genome, the phenotype, and the fitness function map naturally to the synthesis concepts of control parameters, output sound, and comparison with a desired sound. More importantly, sound synthesis can be a very unintuitive technique, since changes in input parameters can give rise, via non-linearities and interactions among parameters, to unexpected changes in output sounds. The novice synthesizer user and the simple hill-climbing search algorithm will both fail to produce a desired sound in this context, whereas an EC technique is well-suited to the task.

In this chapter we introduce and provide motivation for the application of EC to sound synthesis, surveying previous work in this area. We focus on the problem of automatically matching a target sound using a given synthesizer. The ability to mimic a given sound can be used in several ways to augment interactive sound synthesis applications. We report on several sets of experiments run to determine the best EC algorithms, parameters, and fitness functions for this problem.

Keywords

  • Random Search
  • Parameter Distance
  • Target Sound
  • Evolutionary Computation Technique
  • Sound Synthesis

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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McDermott, J., Griffith, N.J.L., O’Neill, M. (2008). Evolutionary Computation Applied to Sound Synthesis. In: Romero, J., Machado, P. (eds) The Art of Artificial Evolution. Natural Computing Series. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72877-1_4

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  • DOI: https://doi.org/10.1007/978-3-540-72877-1_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-72876-4

  • Online ISBN: 978-3-540-72877-1

  • eBook Packages: Computer ScienceComputer Science (R0)