In this paper, we present new dynamic features derived from the modulation spectrum of the cepstral traje ctories of the speech signal. Cepstral trajectories are projected over the basis of sines and cosines yie lding the cepstral modulation frequency response of the speech signal. We show that the different sines a nd cosines basis vectors select different modulation frequencies, whereas, the frequency responses of the delta and the double delta filters are only centered over 15Hz. Therefore, projecting cepstral trajector ies 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 co nditions, 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.