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OFAI-TR-2000-16 ( 177kB g-zipped PostScript file,  113kB PDF file)

Melodic Cue Abstraction, Similarity and Category Formation: A Computational Approach.

Emilios Cambouropoulos

This study attempts to replicate, by means of computational modeling, two psychological experiments on cue abstraction and categorisation performed on a monophonic piece by J.S.Bach. The Unscramble clustering algorithm organises a number of melodic segments into motivic categories, determines a prototype for each cluster and uses these prototypical descriptions for membership prediction tasks. The results of the computational approach are compared to the empirical results, and convergences and deviations are reported. The clusters produced by the algorithm correspond closely to the categories provided in the empirical study. The application of the algorithm confirms most of the suggestions presented in the psychological studies regarding which cues play a most significant role in categorisation tasks.

Keywords: Music, Melodic Similarity, Clustering, Categorisation

Citation: In Proceedings of ICMPC 2000 (International Conference on Music Perception and Cognition), 5-10 August 2000, Keele, U.K.