Robust speech recognition based on dynamic one-sided autocorrelation sequence and frequency warped linear predictive coding

A representation of speech that invariant to noise is introduced. The idea is to filter the temporal trajectories of short time One-Sided Autocorrelation Sequence (OSAS) of speech such that the noise effect is removed. The filtered sequences are denoted as Dynamic Autocorrelation Sequences (DAS). Then frequency warped LPC (WLPC) algorithm is applied to the DAS instead of the original speech. This speech feature set, which not only corresponds to the performance of human auditory property, but also improves the noise robustness of speech recognition, is denoted as DAS-WLPCC. Chinese digit recognition experiment based on continuous density HMM shows the effectiveness of DAS-WLPCC features in presence of white noise and color noise.