Accelerating Query-by-Humming on GPU

Abstract : Searching for similarities in large musical databases has become a common procedure. Local alignment methods, based on dynamic programming, explore all the possible matchings between two musical pieces; and as a result return the optimal local alignment. Unfortunately these very powerful methods have a very high computational cost. The exponential growth of musical databases makes exact alignment algorithm unrealistic for searching similarities. Alternatives have been proposed in bioinformatics either by using heuristics or by developing faster implementation of exact algorithm. The main motivation of this work is to exploit the huge computational power of commonly available graphic cards to develop high performance solutions for Query-by-Humming applications. In this paper, we present a fast implementation of a local alignment method, which allows to retrieve a hummed query in a database of MIDI files, with good accuracy, in a time up to 160 times faster than other comparable systems.
Type de document :
Communication dans un congrès
ISMIR'2009: 10th International Society for Music Information Retrieval Conference, Oct 2009, Kobe, Japan. pp.279-284, 2009
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-00595214
Contributeur : Laurent Imbert <>
Soumis le : mardi 24 mai 2011 - 10:39:06
Dernière modification le : jeudi 11 janvier 2018 - 06:26:07

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  • HAL Id : lirmm-00595214, version 1

Citation

Pascal Ferraro, Pierre Hanna, Laurent Imbert, Thomas Izard. Accelerating Query-by-Humming on GPU. ISMIR'2009: 10th International Society for Music Information Retrieval Conference, Oct 2009, Kobe, Japan. pp.279-284, 2009. 〈lirmm-00595214〉

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