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Histogram Equalization-Based Features for Speech, Music, and Song Discrimination

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2 Author(s)
AscensiĆ³n Gallardo-Antolin ; Department of Signal Theory and Communications, Universidad Carlos III de Madrid, Madrid, Spain ; Juan M. Montero

In this letter, we present a new class of segment-based features for speech, music and song discrimination. These features, called PHEQ (Polynomial-Fit Histogram Equalization), are derived from the nonlinear relationship between the short-term feature distributions computed at segment level and a reference distribution. Results show that PHEQ characteristics outperform short-term features such as Mel Frequency Cepstrum Coefficients (MFCC) and conventional segment-based ones such as MFCC mean and variance. Furthermore, the combination of short-term and PHEQ features significantly improves the performance of the whole system.

Published in:

IEEE Signal Processing Letters  (Volume:17 ,  Issue: 7 )