Stochastic models of jitter

Abstract

This study presents stochastic models of jitter. Jitter designates small, random, involuntary perturbations of the glottal cycle lengths. Jitter is a base-line phenomenon that may be observed in all voiced speech sounds. Knowledge of its properties is therefore relevant to the acoustic modeling, analysis, and synthesis of voice quality. Also, models of jitter are conceptual frameworks that enable experimenters and clinicians to distinguish jitter in particular from aperiodic cycle length patterns in general. Vocal jitter is modeled by means of the ribbon model of the glottal vibration combined with stochastic models of the disturbances of the instantaneous frequency. The disturbance model comprises correlation-free noise and vocal microtremor. Properties of jitter that are simulated are the stochasticity, stationarity, and normality of the decorrelated cycle length perturbations, the size of decorrelated jitter, the correlation between the perturbations of neighboring glottal cycles, the modulation level and modulation frequency owing to microtremor, the asynchrony between external disturbances and glottal cycles, the dependence of the size of jitter on the average glottal cycle length, and the relation between jitter and laryngeal pathologies. Modeled jitter is discussed in the light of measured jitter, as well as the physiological and statistical plausibility of the model parameters.

Modeling vocal fold asymmetries with coupled van der Pol oscillators

“…Also, it increases when the coupling parameter α is decreased. This variation of jitter with Q and α matches previous results from a kinematic model of the vocal fold oscillation (Schoentgen, 2001). The dependance of jitter on the coupling α is very small and only appears towards the boundaries of the phase-locked region.…”

“…White noise was simulated as (Schoentgen, 2001). The scaling parameter was set at a = 0.05, which produces jitter values around 1%.…”

“…It has been shown that laryngeal pathologies increase the size of jitter. However, such increase may not necessarily be the result of a larger external perturbation, but also consequence of the asymmetry between the left and right oscillators, owing to the pathology (Schoentgen, 2001). …”

A Stochastic Mechanical Model to Generate Jitter in the Production of Voiced Sounds

“…In general, the authors who work with models of jitter do not consider mathematical models for the voice production and just a few consider stochastic models [14,15,16].…”

Generation of growl-type voice qualities by spectral morphing

“…Schoentgen [3] for instance gives an extensive overview of different methods of generating jitter and shimmer patterns, which is typically derived by statistical analysis of real recordings, or using models inspired by the physiology of the voice source. The modulation patterns are then typically applied by identifying and transforming individual voice source pulses in the input signal using (e.g.…”