Homomorphic linear predictive coding: a new estimation algorithm for all-pole speech modelling
Zhen Huang, Xiaojun Yang, Xun Zhu, Anthony Kuh · IEE Proceedings I Communications Speech and Vision · 1990
Conventional LPC algorithms give biased estimates for voiced speech signals in the case of pitch-asynchronous analysis. This paper presents a new estimation algorithm for an all-pole model, named as homomorphic linear predictive coding (HLPC) which models the vocal tract transfer function as an all-pole filter, but performs the estimation of the filter coefficients in the cep-strum domain by a minimum mean squared error method. By limiting the summation interval of squared errors in the cepstrum domain to the low time portion that is not affected by pitch components, the estimation results obtained by HLPC are unbiased and independent of the exciting signal type. Experiments on spectrum estimation and formant estimation under several conditions have been carried out for comparison. It is shown that for pitch-asynchronous analysis, HLPC has a higher accuracy than LPC in spectrum estimation as well as formant frequency and bandwidth estimation, especially for speech signals with high pitch frequencies.