Uncertainty quantification of voice signal production mechanical model and experimental updating

Abstract : The aim of this paper is to analyze the uncertainty quantification in a voice production mechanical model and update the probability density function corresponding to the tension parameter using the bayes method and experimental data. Three parameters are considered uncertain in the voice production mechanical model used: the tension parameter, the neutral glottal area and the subglottal pressure. The tension parameter of the vocal folds is mainly responsible for the changing of the fundamental frequency of a voice signal, generated by a mechanical/mathematical model for producing voiced sounds. The three uncertain parameters are modeled by random variables. Experimental data are available for the fundamental frequency and the posterior probability density function of the random tension parameter is then estimated using the Bayes method. In addition, an application is performed considering a case with a pathology in the vocal folds.
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Submitted on : Monday, July 22, 2013 - 10:11:47 AM
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Edson Cataldo, Christian Soize, Rubens Sampaio. Uncertainty quantification of voice signal production mechanical model and experimental updating. Mechanical Systems and Signal Processing, Elsevier, 2013, 40 (2), pp.718-726. ⟨10.1016/j.ymssp.2013.06.036⟩. ⟨hal-00839777⟩

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