PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Classifier ensembles for genre recognition
Pedro J. Ponce de León, José Iñesta and Carlos Pérez-Sancho
In: Pattern Recognition: Progress, Directions and Applications (2006) Centre de Visió per Computador. Universitat Autònoma de Barcelona , pp. 41-53. ISBN 84-933652-6-2

Abstract

Previous work done in genre recognition and characterization from symbolic sources (monophonic melodies extracted from MIDI files) have pointed our research to the use of classifier ensembles to better accomplish the task. This work presents current research in the use of voting ensembles of classifiers trained on statistical description models of melodies, in order to improve both the accuracy and robustness of single classifier systems in the genre recognition task. Different voting schemes are discussed and compared, and results for a corpus of Jazz and Classical music pieces are presented and assesed.

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EPrint Type:Book Section
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Computational, Information-Theoretic Learning with Statistics
Information Retrieval & Textual Information Access
ID Code:5788
Deposited By:Carlos Pérez-Sancho
Deposited On:08 March 2010