Stochastic mechanical model of vocal folds for producing jitter and for identifying pathologies through real voices

Edson Cataldo (1) , Christian Soize (2)

1 Departamento de Matematica Aplicada
2 MSME - Laboratoire de Modélisation et Simulation Multi Echelle

Jitter, in voice production applications, is a random phenomenon characterized by the deviation of the glottal cycle length with respect to a mean value. Its study can help in identifying pathologies related to the vocal folds according to the values obtained through the different ways to measure it. This paper aims to propose a stochastic model, considering three control parameters, to generate jitter based on a deterministic one-mass model for the dynamics of the vocal folds and to identify parameters from the stochastic model taking into account real voice signals experimentally obtained. To solve the corresponding stochastic inverse problem, the cost function used is based on the distance between probability density functions of the random variables associated with the fundamental frequencies obtained by the experimental voices and the simulated ones, and also on the distance between features extracted from the voice signals , simulated and experimental, to calculate jitter. The results obtained show that the model proposed is valid and some samples of voices are synthesized considering the identified parameters for normal and pathological cases. The strategy adopted is also a novelty and mainly because a solution was obtained. In addition to the use of three parameters to construct the model of jitter, is the discussion of a parameter related to the bandwidth of the power spectral density function of the stochastic process to measure the quality of the signal generated. A study about the influence of all the main parameters is also performed. The identification of the parameters of the model considering pathological cases is maybe of all novelties introduced by the paper the most interesting.

Mots clés: stochastic mechanical models; jitter; Voice production; experimental identification; statistical inverse problem; Uncertainty quantification UQ

Domaines: Sciences de l'ingénieur [physics]; Mécanique [physics.med-ph]; Probabilités [math.PR]; Statistiques [math.ST]

Edson Cataldo, Christian Soize. Stochastic mechanical model of vocal folds for producing jitter and for identifying pathologies through real voices. Journal of Biomechanics, 2018, 74, pp.126-133. ⟨10.1016/j.jbiomech.2018.04.031⟩. ⟨hal-01780416⟩