Abstract

In this paper, we present new dynamic features derived from the modulation spectrum of the cepstral trajectories of the speech signal. Cepstral trajectories are projected over the basis of sines and cosines yielding the cepstral modulation frequency response of the speech signal. We show that the different sines and cosines basis vectors select different modulation frequencies, whereas the frequency responses of the delta and the double delta filters are only centered over 15 Hz. Therefore, projecting cepstral trajectories over the basis of sines and cosines yield a more complementary and discriminative range of features. In this work, the cepstrum reconstructed from the lower cepstral modulation frequency components is used as the static feature. In experiments, it is shown that, as well as providing an improvement in clean conditions, these new dynamic features yield a significant increase in the speech recognition performance in various noise conditions when compared directly to the standard temporal derivative features and C-JRASTA PLP features.

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