Simulation of tremulous voices using a biomechanical model

Rubén Fraile,Juan Ignacio Godino-Llorente,Malte Kob

doi:10.1186/s13636-014-0045-2

Abstract

Vocal tremor has been simulated using a high-dimensional discrete vocal fold model. Specifically, respiratory, phonatory, and articulatory tremors have been modeled as instabilities in six parameters of the model. Reported results are consistent with previous knowledge in that respiratory tremor mainly causes amplitude modulation of the voice signal while laryngeal tremor causes both amplitude and frequency modulation. In turn, articulatory tremor is commonly assumed to produce only amplitude modulations but the simulation results indicate that it also produces a high-frequency modulation of the output signal. Furthermore, articulatory tremor affects the frequency response of the vocal tract and it might thus be detected by analyzing the spectral envelope of the acoustic signal.

Highlights

Tremor can be defined as an involuntary oscillatory movement of a body part [1]
This paper reports on the results of using a highdimensional multiple-mass vocal fold model for simulating vocal tremor
For low variability in lung pressure (σ p < 2%), only amplitude modulation is produced in the voice signal

Summary

Introduction

Tremor can be defined as an involuntary oscillatory movement of a body part [1]. Correspondingly, vocal tremor can be defined as a low-frequency fluctuation (i.e. modulation) in the amplitude or frequency (or both) of voice [2]. The fact that vocal tremor is more related to modulation extents than to modulation rates is consistent with results indicating that the severity of tremor is correlated with acoustic measures of amplitude and frequency perturbations [11] This is due to perturbation measures such as jitter or shimmer not including information on the autocorrelation properties of the varying magnitude; i.e. they are perturbation functions of order 0 [12]. Simulation parameters and acoustic analysis The voice production and tremor models described in preceding sections have been used to generate voice signals with duration equal to 2 s and sampling rate equal to 8, 000 Hz. In order to isolate the effects of different anatomical sources of tremor, time variability has only been modeled in one of the six aforementioned variables at a time. Obtained from unbounded distributions, the modulation extent has been defined as the normalized standard deviation of their values along a given voice signal: σ f for frequency modulation and σ A for amplitude modulation (Equation 7)

Results

Discussion

Conclusions