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Towards Music Fitness Evaluation with the Hierarchical SOM

  • Edwin Hui Hean Law
  • Somnuk Phon-Amnuaisuk
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4974)

Abstract

In any evolutionary search system, the fitness raters are most crucial in determining successful evolution. In this paper, we propose a Hierarchical Self Organizing Map based sequence predictor as a fitness evaluator for a music evolution system. The hierarchical organization of information in the HSOM allows prediction to be performed with multiple levels of contextual information. Here, we detail the design and implementation of such a HSOM system. From the experimental setup, we show that the HSOM’s prediction performance exceeds that of a Markov prediction system when using randomly generated and musical phrases.

Keywords

Fitness Evaluation for Music Generation Self Organizing Map Hierarchical SOM 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Edwin Hui Hean Law
    • 1
  • Somnuk Phon-Amnuaisuk
    • 1
  1. 1.Music Informatics Research Group, Faculty of Information TechnologyMultimedia University, Jln MultimediaCyberjayaMalaysia

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