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Genetic Programming for Musical Sound Analysis

  • Róisín Loughran
  • Jacqueline Walker
  • Michael O’Neill
  • James McDermott
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7247)

Abstract

This study uses Genetic Programming (GP) in developing a classifier to distinguish between five musical instruments. Using only simple arithmetic and boolean operators with 95 features as terminals, a program is developed that can classify 300 unseen samples with an accuracy of 94%. The experiment is then run again using only 14 of the most often chosen features. Limiting the features in this way raised the best classification to 94.3% and the average accuracy from 68.2% to 75.67%. This demonstrates that not only can GP be used to create a classifier but it can be used to determine the best features to choose for accurate musical instrument classification, giving an insight into timbre.

Keywords

Musical Information Retrieval timbre Genetic Programming 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Róisín Loughran
    • 1
  • Jacqueline Walker
    • 1
  • Michael O’Neill
    • 2
  • James McDermott
    • 2
  1. 1.University of LimerickLimerickIreland
  2. 2.NCRAUniversity College DublinIreland

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