2005 | OriginalPaper | Buchkapitel
Support Vector Machines for Bass and Snare Drum Recognition
verfasst von : Dirk Van Steelant, Koen Tanghe, Sven Degroeve, Bernard De Baets, Marc Leman, Jean-Pierre Martens
Erschienen in: Classification — the Ubiquitous Challenge
Verlag: Springer Berlin Heidelberg
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In this paper we attempt to extract information concerning percussive instruments from a musical audio signal. High-dimensional vectors of descriptors are computed from the signal and classified by means of Support Vector Machines (SVM). We investigate the performance on 2 important classes of drum sounds in Western popular music: bass and snare drums, possibly overlapping. The results are encouraging: SVM achieve a high accuracy and
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-measure, with linear kernels performing (nearly) as good as Gaussian kernels, but requiring 1000 times less computation time.