Identifying a stochastic process related to the stiffness in a voice production mechanical model

Edson Cataldo (1) , Christian Soize (2)

1 Mathematics Department [Fluminense]
2 MSME - Laboratoire de Modélisation et Simulation Multi Echelle

The quasi-periodic oscillation of the vocal folds causes perturbations in the length of the glottal cycles that are known as jitter. The observation of the glottal cycles variations suggests that jitter is a random phenomenon described by random deviations of the glottal cycle lengths in relation to a corresponding mean value and, in general, its values are expressed as a percentage of the duration of the glottal pulse. The jitter has been the subject for researchers due to its important applications such as the identification of pathological voices (nodules in the vocal folds, paralysis of the vocal folds, or even, the vocal aging, among others). Large values for jitter variations can indicate a pathological characteristic of the voice. In this paper the construction a stochastic model for jitter using an one-mass mechanical model of the vocal folds is proposed. The corresponding stiffness of each vocal fold is considered as a stochastic process and its modeling is propose d. The probability density function of the fundamental frequency related to the voice signals produced are constructed and compared for different levels of jitter. Some samples of synthesized voices in these cases are obtained. Then, using experimental voice signals, the stochastic process modelled will be identified. The idea is to generate voice signals which the level of jitter which can be associated to the experimental voice used.

Mots clés: Stochastic modeling; Identification of stochastic processes; voice production; mechanical models; jitter

Domaines: Mécanique [physics.med-ph]; Probabilités [math.PR]; Statistiques [math.ST]

Edson Cataldo, Christian Soize. Identifying a stochastic process related to the stiffness in a voice production mechanical model. 10th International Conference on Structural Dynamics, EURODYN 2017, EASD, Sep 2017, Rome, Italy. pp.912-917. ⟨hal-01585707⟩