PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Melody Characterization by a Genetic Fuzzy System
Ponce de León Pedro J., Rizo David, Ramírez Rafael and José Iñesta
In: Proceedings of the 5th Sound and Music Computing Conference (SMC 2008) (2008) Universitätsverlag der TU Berlin , Berlin, Germany , pp. 15-23. ISBN 978–3–7983–2094–9

Abstract

We present preliminary work on automatic human-readable melody characterization. In order to obtain such a characterization, we (1) extract a set of statistical descriptors from the tracks in a dataset of MIDI files, (2) apply a rule induction algorithm to obtain a set of (crisp) classification rules for melody track identification, and (3) automatically transform the crisp rules into fuzzy rules by applying a genetic algorithm to generate the membership functions for the rule attributes. Some results are presented and discussed.

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EPrint Type:Book Section
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Information Retrieval & Textual Information Access
ID Code:5295
Deposited By:José Iñesta
Deposited On:24 March 2009