On the use of residual cepstrum in speech recognition

In speech recognition based on LPC analysis the prediction residues are usually ignored, only the LPC-derived cepstral coefficients (LPCC) are used to compose feature vectors. In this study, a number of parameters (called the residual cepstrum or RCEP) were calculated from these residues and their effectiveness for speech recognition was evaluated. It was shown that the RCEP do contain useful information, in particular, they are complementary to the LPCC. In an evaluation experiment, if the LPCC were used jointly with a few RCEP coefficients, the recognition rate of the English E-set letters was improved from 54% to 67% and from 69% to 71% by the use of HMMs based recognizer and the DTW based recognizer, respectively. In addition, Mel-scaled FFT based cepstrum (MFCC) was found to be superior to LPCC