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Voice signals produced with jitter through a stochastic one-mass mechanical model

Abstract : The quasi-periodic oscillation of the vocal folds causes perturbations in the length of the glottal cycles which 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 objective of the paper is the construction of a stochastic model for jitter using an one-mass mechanical model of the vocal folds, which assumes complete right-left symmetry of the vocal folds, and which considers motions of the vocal folds only in the horizontal direction. Concerning the study design, 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. Concerning the model, the corresponding stiffness of each vocal fold is considered as a stochastic process and its modeling is proposed. The results that are presented concern the probability density function of the fundamental frequency related to the voice signals produced, which are constructed and are compared for different levels of jitter. Some samples of synthesized voices in these cases are obtained. As conclusions, it is showed that jitter could be obtained using the model proposed. The Praat software was also used in order to verify the measures of jitter in the synthesized voice signals.
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Contributor : Christian Soize Connect in order to contact the contributor
Submitted on : Friday, February 19, 2016 - 2:16:27 PM
Last modification on : Saturday, January 15, 2022 - 4:09:17 AM
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Edson Cataldo, Christian Soize. Voice signals produced with jitter through a stochastic one-mass mechanical model. Journal of Voice, Elsevier, 2017, 31 (1), pp.111.e9-111.e18. ⟨10.1016/j.jvoice.2016.01.001⟩. ⟨hal-01276465⟩



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