Clustering and Classification of Music by Interval Categories

  • Aline Honingh
  • Rens Bod
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6726)

Abstract

We present a novel approach to clustering and classification of music, based on the concept of interval categories. Six interval categories exist, each with its own musical character. A piece of music can be represented by six numbers, reflecting the percentages of occurrences of each interval category. A piece of music can, in this way, be visualized as a point in a six dimensional space. The three most significant dimensions are chosen from these six. Using this approach, a successful visual clustering of music is possible for 1) composers through various musical time periods, and 2) the three periods of Beethoven, which illustrates the use of our approach on both a general and a specific level. Furthermore, we will see that automatic classification between tonal and atonal music can be achieved.

Keywords

Interval Category Pitch-class Set Classification Clustering 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Aline Honingh
    • 1
  • Rens Bod
    • 1
  1. 1.Institute for Logic, Language and ComputationUniversity of AmsterdamNetherlands

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