Jitter generation in voice signals produced by a two-mass stochastic mechanical model. (May 2016)

• Record Type: Journal Article
• Authors: Cataldo, E.; Soize, C.
• Is Part Of: Biomedical signal processing and control. Volume 27(2016)
• Page Start: 87
• Page End: 95
• Publication Date: 2016-05
• Subjects: Stochastic modeling -- Voice production -- Mechanical models -- Jitter; Signal processing -- Periodicals; Biomedical engineering -- Periodicals; Signal Processing, Computer-Assisted -- Periodicals; Image Processing, Computer-Assisted -- Periodicals; Biomedical Engineering -- Periodicals; 610.28
• DOI: 10.1016/j.bspc.2016.02.003
• Languages: English
• ISSNs: 1746-8094

Abstract

Abstract : Highlights: Jitter modeling is proposed considering a nonlinear stochastic mechanical system. Construction of stochastic models for the stiffnesses of the model are proposed. The corresponding stochastic differential equations are solved. Voice signals are synthesized considering different levels of jitter. The random signal analysis corresponding to the synthesized voice is performed. Abstract: Jitter is a phenomenon caused by the perturbation in the length of the glottal cycles due to the quasi-periodic oscillation of the vocal folds in the production of the voice. It can be modeled as a random phenomenon described by the deviations of the glottal cycle length in relation to a mean value. Its study has been developed due to important applications such as aid in identification of voices with pathological characteristics, when its values are large, because a normal voice has naturally a low level of jitter. The aim of this paper is to construct a stochastic model of jitter using a two-mass mechanical model of the vocal folds, assuming complete right–left symmetry of the vocal folds and considering the motion of the vocal folds only in the horizontal direction. The stiffnesses taken into account in the model are considered as stochastic processes and their modeling are proposed. Glottal signals and voice signals are generated with jitter and the probability density function of the fundamental frequency is constructed for several values of the hyperparameters that control the level of jitter.