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    A survey of query-by-humming similarity methods

    Kotsifakos, A. and Papapetrou, Panagiotis and Hollmen, J. and Gunopulos, D. and Athitsos, V. (2012) A survey of query-by-humming similarity methods. In: UNSPECIFIED (ed.) Proceedings of the 5th International Conference on PErvasive Technologies Related to Assistive Environments. New York, USA: ACM Publications. ISBN 9781450313001.

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    Abstract

    Performing similarity search in large databases is a problem of particular interest in many communities, such as music, database, and data mining. Although several solutions have been proposed in the literature that perform well in many application domains, there is no best method to solve this kind of problem in a Query-By-Humming (QBH) application. In QBH the goal is to find the song(s) most similar to a hummed query in an efficient manner. In this paper, we focus on providing a brief overview of the representations to encode music pieces, and also on the methods that have been proposed for QBH or other similarly defined problems.

    Metadata

    Item Type: Book Section
    School: Birkbeck Schools and Departments > School of Business, Economics & Informatics > Computer Science and Information Systems
    Depositing User: Sarah Hall
    Date Deposited: 26 Jul 2013 10:58
    Last Modified: 26 Jul 2013 10:58
    URI: http://eprints.bbk.ac.uk/id/eprint/7849

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