Proceedings of the XXth Conference of Open Innovations Association FRUCT (Nov 2018)

Characterizing and Classifying Music Subgenres

  • Adam Lefaivre,
  • John Z. Zhang

Journal volume & issue
Vol. 602, no. 23
pp. 505 – 509

Abstract

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We consider the problem of subgenre classification in music datasets. We propose an adaptation of association analysis, a technique to explore the inherent relationships among data objects in a problem domain, to capture subgenres’ char- acteristics through acoustical features. We further propose to use those characteristics to engage in a pairwise comparison among subgenres when classifying a new music piece. The initial investigation on our approach is examined through empirical experiments on a number of music datasets. The results are presented and discussed, with various related issues addressed.

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