On Bernoulli-Gaussian process modeling of speech excitation source

In the multipulse linear predictive coding (LPC) speech synthesis, an autoregressive filter is excited by a multipulse excitation consisting of impulses of various amplitudes and locations. The authors statistically model the excitation signal as a zero mean Bernoulli-Gaussian process. The pulse locations are independently distributed with a probability distribution, and the pulse amplitudes are expressed as a Gaussian sequence with zero mean and finite variance. An algorithm is described for estimation of pulse amplitudes and locations based on the Bernoulli-Gaussian process when the number of pulses is given. Results from computer simulation are presented