Using Bayesian method for updating the probability density function related to the tension parameter in a voice production model

Abstract : The aim of this paper is to use the Bayesian method for updating a probability density function (pdf) related to the tension parameter of the vocal folds. This parameter is mainly responsible for the changing of the fundamental frequency of a voice signal, generated by a mechanical/mathematical model for producing voiced sounds. Three parameters are considered uncertain in the model used: the tension parameter, the neutral glottal area and the subglottal pressure. These uncertain parameters are modeled by random variables and their prior probability density functions are constructed using the Maximum Entropy Principle. The output of the stochastic computational model is the random voice signal and the Monte Carlo method is used to solve the stochastic equations allowing realizations of the random voice signals to be generated.