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

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URI: https://hdl.handle.net/10016/32892
ISSN: 1070-9908
DOI: https://doi.org/10.1109/LSP.2010.2049877
UXXI: AR/0000007800
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Equalization_PL_2010_ps.pdf (528.77 KB)
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2010-07
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IEEE
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Abstract
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.
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Speech/Music/Song discrimination, Audio classification, HEQ-based features, Acoustic features, Parameterization
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Gallardo-Antolin, A. & Montero, J. M. (2010). Histogram Equalization-Based Features for Speech, Music, and Song Discrimination. IEEE Signal Processing Letters, 17(7), pp. 659–662.
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