Probabilistic modeling of a nonlinear dynamical system used for producing voice

This paper is devoted to the construction of a stochastic nonlinear dynamical system for signal generation such as the production of voiced sounds. The dynamical system is highly nonlinear, and the output signal generated is very sensitive to a few parameters of the system. In the context of the production of voiced sounds the measurements have a significant variability. We then propose a statistical treatment of the experiments and we developed a probability model of the sensitive parameters in order that the stochastic dynamical system has the capability to predict the experiments in the probability distribution sense. The computational nonlinear dynamical system is presented, the Maximum Entropy Principle is used to construct the probability model and an experimental validation is shown.

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