Schierz, A. C. and Budka, M., 2011. High--Performance music information retrieval system for song genre classification. In: Proc. of the 19th International Symposium on Methodologies for Intelligent Systems (ISMIS'11), June 2011, Warsaw, Poland, pp. 725-733.
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Official URL: http://ismis2011.ii.pw.edu.pl/index.php
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:||Conference or Workshop Item (Paper)|
|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|
|Deposited By:||Dr Amanda C. Schierz LEFT|
|Deposited On:||15 Jul 2011 11:48|
|Last Modified:||07 Mar 2013 15:47|
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- High--Performance Music Information Retrieval System for Song Genre Classification. (deposited 27 Apr 2011 14:04)
- High--Performance music information retrieval system for song genre classification. (deposited 15 Jul 2011 11:48) [Currently Displayed]
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