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 F1-measure, with linear kernels performing (nearly) as good as Gaussian kernels, but requiring 1000 times less computation time. © Springer-Verlag Berlin, Heidelberg 2005.
CITATION STYLE
Van Steelant, D., Tanghe, K., Degroeve, S., De Baets, B., Leman, M., & Martens, J. P. (2005). Support Vector Machines for bass and snare drum recognition. In Studies in Classification, Data Analysis, and Knowledge Organization (pp. 616–623). Kluwer Academic Publishers. https://doi.org/10.1007/3-540-28084-7_73
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