Toward User-Directed Evolution of Sound Synthesis Parameters

  • James McDermott
  • Niall J. L. Griffith
  • Michael O’Neill
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3449)


Experiments are described which use genetic algorithms operating on the parameter settings of an FM synthesizer, with the aim of mimicking known synthesized sounds. The work is considered as a precursor to the development of synthesis plug-ins using evolution directed by a user. Attention is focussed on the fitness functions used to drive the evolution: the main result is that a composite fitness function – based on a combination of perceptual measures, spectral analysis, and low-level sample-by-sample comparison – drives more successful evolution than fitness functions which use only one of these types of criterion.


Genetic Algorithm Sine Wave Perceptual Measure Target Sound Interactive Genetic Algorithm 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • James McDermott
    • 1
  • Niall J. L. Griffith
    • 1
  • Michael O’Neill
    • 1
  1. 1.University of LimerickIreland

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