An efficient mel-LPC analysis method for speech recognition

This paper proposes a simple and e cient time domain technique to estimate an all-poll model on a mel-frequency axis (Mel-LPC). This method requires only two-fold computational cost as compared to conventional linear prediction analysis. The recognition performance of mel-cepstral parameters obtained by the Mel LPC analysis is compared with those of conventional LP mel-cepstra and the melfrequency cepstrum coe cients (MFCC) through genderdependent phoneme and word recognition tests. The results show that the Mel-LPC cepstrum attains a signi cant improvement in recognition accuracy over conventional LP mel-cepstrum, and gives slightly higher accuracy for male speakers and slightly lower accuracy for female speakers than MFCC.