Spectral Peak-Weighted Liftering of Cepstral Coefficients for Speech Recognition

摘要

In this paper, we propose a peak-weighted cepstral lifter (PWL) for enhancing the spectral peaks of an all--pole model spectrum in the cepstral domain. The design parameter of the PWL is the degree of pole enhancement or pole shifting to- ward the unit circle. The optimal pole shifting factor is chosen by considering the sensitivity to spectral resonance peaks, the vari- ability of cepstral variances, and the recognition accuracy. Next, we generalize the PWL so that the optimal shifting factor is adaptively determined in frame-by-frame basis. Compared with other cepstral lifters, a speech recognizer employing the frame-adaptive PWL provides better recognition performance.