Bayesian deconvolution of speech containing pulsed excitation

This paper presents a recursive approach to the estimation of pulses in speech excitation. The detector is derived from the generalized likelihood ratio method but does not assume that the system parameters are known exactly. It utilizes some of the characteristics of the speech signal to determine the a-priori probability of the primary pulse in an excitation sequence and estimates the pulse interval and amplitude envelope. This algorithm is particularly useful in conjunction with recursive or pitch-synchronous analysis methods. It not only provides a means for estimating signal features such as pitch, but also for synchronizing and adapting analysis methods with changing excitation patterns. Examples are presented for a synthetic vowel with linearly time-varying pitch and a segment of real speech.