Support Vector Machines for Bass and Snare Drum Recognition

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