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    The Importance of Cross Database Evaluation in Sound Classification

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    Date
    2003-10-26
    Author
    Arie Livshin
    Xavier Rodet
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    Abstract
    In numerous articles (Martin and Kim, 1998; Fraser and Fujinaga, 1999; and many others) sound classification algorithms are evaluated using "self classification" - the learning and test groups are randomly selected out of the same sound database. We will show that "self classification" is not necessarily a good statistic for the ability of a classification algorithm to learn, generalize or classify well. We introduce the alternative "Minus-1 DB" evaluation method and demonstrate that it does not have the shortcomings of "self classification".
    URI
    http://jhir.library.jhu.edu/handle/1774.2/42
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