PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Style recognition through statistical event models
Carlos Pérez-Sancho, José Iñesta and Jorge Calera-Rubio
Journal of new Music Research Volume 34, pp. 331-340, 2005. ISSN 0929-8215

Abstract

The automatic classification of music fragments into styles is one challenging problem within the music information retrieval (MIR) domain and also for the understanding of music style perception. This has a number of applications, including the indexation and exploration of musical databases. Some technologies employed in text classification can be applied to this problem. The key point here is to establish the music equivalent to the words in texts. A number of works use the combination of intervals and duration ratios for this purpose. In this paper, different statistical text recognition algorithms are applied to style recognition using this kind of melody representation, exploring their performance for different word sizes.

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EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Information Retrieval & Textual Information Access
ID Code:1503
Deposited By:José Iñesta
Deposited On:28 November 2005