Optimization of Parameter Settings for Genetic Algorithms in Music Segmentation

  • Brigitte Rafael
  • Stefan Oertl
  • Michael Affenzeller
  • Stefan Wagner
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6927)

Abstract

Genetic algorithms have been introduced to the field of media segmentation including image, video, and also music segmentation since segmentation problems usually have complex fitness landscapes. Music segmentation can provide insight into the structure of a music composition so it is an important task in music information retrieval (MIR). The authors have already presented the application of genetic algorithms for the music segmentation problem in an earlier paper. This paper focuses on the optimization of parameter settings for genetic algorithms in the field of MIR as well as on the comparison of their results.

Keywords

Genetic Algorithm Crossover Operator Dynamic Time Warping Selection Operator Video Segmentation 
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 2012

Authors and Affiliations

  • Brigitte Rafael
    • 1
  • Stefan Oertl
    • 1
  • Michael Affenzeller
    • 2
  • Stefan Wagner
    • 2
  1. 1.Re-Compose GmbHViennaAustria
  2. 2.Heuristic and Evolutionary Algorithms Laboratory School of Informatics, Communications and MediaUpper Austria University of Applied SciencesHagenbergAustria

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