High--Performance Music Information Retrieval System for Song Genre Classification.

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Schierz, A. C. and Budka, M., 2011. High--Performance Music Information Retrieval System for Song Genre Classification. In: Kryszkiewicz, M., Rybinski, H., Skowron, A. and Ras, Z.W., eds. Proceedings of the 19th International Symposium on Methodologies for Intelligent Systems (ISMIS'11). Springer-Verlag. (In Press)

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Official URL: http://ismis2011.ii.pw.edu.pl/index.php

Abstract

With the large amounts of multimedia data produced, recorded and made available every day, there is a clear need for well--performing automatic indexing and search methods. This paper describes a music genre classification system, which was a winning solution in the Music Information Retrieval ISMIS 2011 contest. The system consisted of a powerful ensemble classifier using the Error Correcting Output Coding coupled with an original, multi--resolution clustering and iterative relabelling scheme. The two approaches used together outperformed other competing solutions by a large margin, reaching the final accuracy close to 88%.

Item Type:Book Section
Series Name:Lecture Notes in Computer Science
Series Name:Lecture Notes in Computer Science
Additional Information:19th International Symposium on Methodologies for Intelligent Systems (ISMIS'11), Warsaw University of Technology, Poland, 28-30 June 2011.
Subjects:Generalities > Computer Science and Informatics > Artificial Intelligence
Arts > Music
Group:School of Design, Engineering & Computing > Smart Technology Research Centre
ID Code:17679
Deposited By:Dr Amanda C. Schierz LEFT
Deposited On:27 Apr 2011 14:04
Last Modified:07 Mar 2013 15:43

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