Locating Segments with Drums in Music Signals Locating Segments with Drums in Music Signals

A system is described which segments musical signals according to the presence or absence of drum instruments. Two different yet approximately equally accurate approaches were taken to solve the problem. The first is based on periodicity detection in the amplitude envelopes of the signal at subbands. The band-wise periodicity estimates are aggregated into a summary autocorrelation function, the characteristics of which reveal the drums. The other mechanism applies straightforward acoustic pattern recognition with mel-frequency cepstrum coefficients as features and a Gaussian mixture model classifier. The integrated system achieves 88 % correct segmentation over a database of 28 hours of music from different musical genres. For the both methods, errors occur for borderline cases with soft percussivelike drum accompaniment, or transient-like instrumentation without drums.