LaDIVA: A neurocomputational model providing laryngeal motor control for speech acquisition and production

Many voice disorders are the result of intricate neural and/or biomechanical impairments that are poorly understood. The limited knowledge of their etiological and pathophysiological mechanisms hampers effective clinical management. Behavioral studies have been used concurrently with computational models to better understand typical and pathological laryngeal motor control. Thus far, however, a unified computational framework that quantitatively integrates physiologically relevant models of phonation with the neural control of speech has not been developed. Here, we introduce LaDIVA, a novel neurocomputational model with physiologically based laryngeal motor control. We combined the DIVA model (an established neural network model of speech motor control) with the extended body-cover model (a physics-based vocal fold model). The resulting integrated model, LaDIVA, was validated by comparing its model simulations with behavioral responses to perturbations of auditory vocal fundamental frequency (fo) feedback in adults with typical speech. LaDIVA demonstrated capability to simulate different modes of laryngeal motor control, ranging from short-term (i.e., reflexive) and long-term (i.e., adaptive) auditory feedback paradigms, to generating prosodic contours in speech. Simulations showed that LaDIVA’s laryngeal motor control displays properties of motor equivalence, i.e., LaDIVA could robustly generate compensatory responses to reflexive vocal fo perturbations with varying initial laryngeal muscle activation levels leading to the same output. The model can also generate prosodic contours for studying laryngeal motor control in running speech. LaDIVA can expand the understanding of the physiology of human phonation to enable, for the first time, the investigation of causal effects of neural motor control in the fine structure of the vocal signal.Fil: Weerathunge, Hasini R.. Boston University; Estados UnidosFil: Alzamendi, Gabriel Alejandro. Universidad Nacional de Entre Ríos. Instituto de Investigación y Desarrollo en Bioingeniería y Bioinformática - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación y Desarrollo en Bioingeniería y Bioinformática; ArgentinaFil: Cler, Gabriel J.. University of Washington; Estados UnidosFil: Guenther, Frank H.. Boston University; Estados UnidosFil: Stepp, Cara E.. Boston University; Estados UnidosFil: Zañartu, Matías. Universidad Técnica Federico Santa María; Chil

Estimation of Subglottal Pressure, Vocal Fold Collision Pressure, and Intrinsic Laryngeal Muscle Activation From Neck-Surface Vibration Using a Neural Network Framework and a Voice Production Model

The ambulatory assessment of vocal function can be significantly enhanced by having access to physiologically based features that describe underlying pathophysiological mechanisms in individuals with voice disorders. This type of enhancement can improve methods for the prevention, diagnosis, and treatment of behaviorally based voice disorders. Unfortunately, the direct measurement of important vocal features such as subglottal pressure, vocal fold collision pressure, and laryngeal muscle activation is impractical in laboratory and ambulatory settings. In this study, we introduce a method to estimate these features during phonation from a neck-surface vibration signal through a framework that integrates a physiologically relevant model of voice production and machine learning tools. The signal from a neck-surface accelerometer is first processed using subglottal impedance-based inverse filtering to yield an estimate of the unsteady glottal airflow. Seven aerodynamic and acoustic features are extracted from the neck surface accelerometer and an optional microphone signal. A neural network architecture is selected to provide a mapping between the seven input features and subglottal pressure, vocal fold collision pressure, and cricothyroid and thyroarytenoid muscle activation. This non-linear mapping is trained solely with 13,000 Monte Carlo simulations of a voice production model that utilizes a symmetric triangular body-cover model of the vocal folds. The performance of the method was compared against laboratory data from synchronous recordings of oral airflow, intraoral pressure, microphone, and neck-surface vibration in 79 vocally healthy female participants uttering consecutive /pæ/ syllable strings at comfortable, loud, and soft levels. The mean absolute error and root-mean-square error for estimating the mean subglottal pressure were 191 Pa (1.95 cm H2O) and 243 Pa (2.48 cm H2O), respectively, which are comparable with previous studies but with the key advantage of not requiring subject-specific training and yielding more output measures. The validation of vocal fold collision pressure and laryngeal muscle activation was performed with synthetic values as reference. These initial results provide valuable insight for further vocal fold model refinement and constitute a proof of concept that the proposed machine learning method is a feasible option for providing physiologically relevant measures for laboratory and ambulatory assessment of vocal function.Fil: Ibarra, Emiro J.. Universidad Tecnica Federico Santa Maria.; ChileFil: Parra, Jesús A.. Universidad Tecnica Federico Santa Maria.; ChileFil: Alzamendi, Gabriel Alejandro. Universidad Nacional de Entre Ríos. Instituto de Investigación y Desarrollo en Bioingeniería y Bioinformática - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación y Desarrollo en Bioingeniería y Bioinformática; ArgentinaFil: Cortés, Juan P.. Universidad Tecnica Federico Santa Maria.; ChileFil: Espinoza, Víctor M.. Universidad de Chile; ChileFil: Mehta, Daryush D.. Center For Laryngeal Surgery And Voice Rehabilitation; Estados UnidosFil: Hillman, Robert E.. Center For Laryngeal Surgery And Voice Rehabilitation; Estados UnidosFil: Zañartu, Matías. Universidad Tecnica Federico Santa Maria.; Chil

Modeling biomechanical influence of epilaryngeal stricture on the vocal folds: A low-dimensional model of vocal-ventricular coupling

Purpose: Physiological and phonetic studies suggest that, at moderate levels of epilaryngeal stricture, the ventricular folds impinge upon the vocal folds and influence their dynamical behavior, which is thought to be responsible for constricted laryngeal sounds. In this work, the authors examine this hypothesis through biomechanical modeling. Method: The dynamical response of a low-dimensional, lumped-element model of the vocal folds under the influence of vocal-ventricular fold coupling was evaluated. The model was assessed for F0 and cover-mass phase difference. Case studies of simulations of different constricted phonation types and of glottal stop illustrate various additional aspects of model performance. Results: Simulated vocal-ventricular fold coupling lowers F0 and perturbs the mucosal wave. It also appears to reinforce irregular patterns of oscillation, and it can enhance laryngeal closure in glottal stop production. Conclusion: The effects of simulated vocal-ventricular fold coupling are consistent with sounds, such as creaky voice, harsh voice, and glottal stop, that have been observed to involve epilaryngeal stricture and apparent contact between the vocal folds and ventricular folds. This supports the view that vocal-ventricular fold coupling is important in the vibratory dynamics of such sounds and, furthermore, suggests that these sounds may intrinsically require epilaryngeal strictur

Numerical Modeling of Vocal Control and Patient-specific Surgical Planning of Type 1 Thyroplasty

This study aims to develop knowledge about the roles of intrinsic laryngeal muscles on voice control in both healthy and disordered conditions through comprehensive computational models. The phonation simulator was built by combining a three-dimensional high-fidelity MRI-based model of the larynx, active muscle mechanics, and fluid-structure-acoustic interaction model, which enabled the exploration of the underlayer mechanisms of the link between individual and/or group muscles contractions under both symmetric and asymmetric activations, vocal fold posture, vocal fold vibration, and voice outcomes during voice production. The first part of this research extensively investigated the effects of cricothyroid and thyroarytenoid muscle activations on voice characteristics through a parametric study. The role of these intrinsic muscles in the adjustment of geometrical and mechanical properties of vocal fold pre-phonatory posture, glottic flow aerodynamics, and acoustic and how all these components interact were explored. Results were comprehensively validated, and the link between elements of phonation was described in detail. In the next step, due to the model\u27s ability in the individual muscle activations, unilateral vocal fold paralysis was simulated, and the characteristics of disordered voice were analyzed. The voice simulator was then combined with the implant insertion model and genetic algorithm method to build a computational framework for patient-specific surgical planning of type 1 thyroplasty. This surgery is a standard procedure for treating unilateral vocal fold paralysis; however, it is subject to challenges mainly due to the small size of the implant and the high sensitivity of the voice outcome to the implant shape and position. Therefore, although the patient\u27s voice could be improved, the results might not be as satisfying as expected. Despite actual surgery, with very little room for try and error, the ideal implant could be achieved by optimizing the implant based on the patient\u27s desired voice using the presented computational framework. Both healthy and diseased cases and the corrected case using the optimized implant were simulated. Results revealed that the optimized implant could restore the aerodynamic and acoustic features of the disordered voice in producing a sustained vowel utterance. Furthermore, the performance of the implant in the pitch gliding test, which was simulated using temporal activation of the cricothyroid and thyroarytenoid muscles based on the first part of the study, was evaluated. In the final step, a physics-informed neural network-based algorithm was presented to reconstruct the three-dimensional cyclic vibration of vocal fold using two-dimensional sparse experimental data and laws of physics. Key acoustic parameters and vibratory dynamics of vocal folds and other parameters, such as flow rate, pressure distribution, and contact force, which are difficult to measure experimentally, were successfully predicted

A Cervid Vocal Fold Model Suggests Greater Glottal Efficiency in Calling at High Frequencies

Male Rocky Mountain elk (Cervus elaphus nelsoni) produce loud and high fundamental frequency bugles during the mating season, in contrast to the male European Red Deer (Cervus elaphus scoticus) who produces loud and low fundamental frequency roaring calls. A critical step in understanding vocal communication is to relate sound complexity to anatomy and physiology in a causal manner. Experimentation at the sound source, often difficult in vivo in mammals, is simulated here by a finite element model of the larynx and a wave propagation model of the vocal tract, both based on the morphology and biomechanics of the elk. The model can produce a wide range of fundamental frequencies. Low fundamental frequencies require low vocal fold strain, but large lung pressure and large glottal flow if sound intensity level is to exceed 70 dB at 10 m distance. A high-frequency bugle requires both large muscular effort (to strain the vocal ligament) and high lung pressure (to overcome phonation threshold pressure), but at least 10 dB more intensity level can be achieved. Glottal efficiency, the ration of radiated sound power to aerodynamic power at the glottis, is higher in elk, suggesting an advantage of high-pitched signaling. This advantage is based on two aspects; first, the lower airflow required for aerodynamic power and, second, an acoustic radiation advantage at higher frequencies. Both signal types are used by the respective males during the mating season and probably serve as honest signals. The two signal types relate differently to physical qualities of the sender. The low-frequency sound (Red Deer call) relates to overall body size via a strong relationship between acoustic parameters and the size of vocal organs and body size. The high-frequency bugle may signal muscular strength and endurance, via a ‘vocalizing at the edge’ mechanism, for which efficiency is critical

Direct measurement and modeling of intraglottal, subglottal, and vocal fold collision pressures during phonation in an individual with a hemilaryngectomy

The purpose of this paper is to report on the first in vivo application of a recently developed transoral, dual-sensor pressure probe that directly measures intraglottal, subglottal, and vocal fold collision pressures during phonation. Synchronous measurement of intraglottal and subglottal pressures was accomplished using two miniature pressure sensors mounted on the end of the probe and inserted transorally in a 78-year-old male who had previously undergone surgical removal of his right vocal fold for treatment of laryngeal cancer. The endoscopist used one hand to position the custom probe against the surgically medialized scar band that replaced the right vocal fold and used the other hand to position a transoral endoscope to record laryngeal high-speed videoendoscopy of the vibrating left vocal fold contacting the pressure probe. Visualization of the larynx during sustained phonation allowed the endoscopist to place the dual-sensor pressure probe such that the proximal sensor was positioned intraglottally and the distal sensor subglottally. The proximal pressure sensor was verified to be in the strike zone of vocal fold collision during phonation when the intraglottal pressure signal exhibited three characteristics: an impulsive peak at the start of the closed phase, a rounded peak during the open phase, and a minimum value around zero immediately preceding the impulsive peak of the subsequent phonatory cycle. Numerical voice production modeling was applied to validate model-based predictions of vocal fold collision pressure using kinematic vocal fold measures. The results successfully demonstrated feasibility of in vivo measurement of vocal fold collision pressure in an individual with a hemilaryngectomy, motivating ongoing data collection that is designed to aid in the development of vocal dose measures that incorporate vocal fold impact collision and stresses.Fil: Mehta, Daryush D.. Massachusetts General Hospital; Estados UnidosFil: Kobler, James B.. Massachusetts General Hospital; Estados UnidosFil: Zeitels, Steven M.. Harvard Medical School. Department of Medicine. Massachusetts General Hospital; Estados UnidosFil: Zañartu, Matías. Universidad Técnica Federico Santa María; ChileFil: Ibarra, Emiro J.. Universidad Técnica Federico Santa María; ChileFil: Alzamendi, Gabriel Alejandro. Universidad Nacional de Entre Ríos. Instituto de Investigación y Desarrollo en Bioingeniería y Bioinformática - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación y Desarrollo en Bioingeniería y Bioinformática; ArgentinaFil: Manriquez, Rodrigo. Universidad Técnica Federico Santa María; ChileFil: Erath, Byron D.. Clarkson University; Estados UnidosFil: Peterson, Sean D.. University of Waterloo; CanadáFil: Petrillo, Robert H.. Center For Laryngeal Surgery and Voice Rehabilitation; Estados UnidosFil: Hillman, Robert E.. Center For Laryngeal Surgery and Voice Rehabilitation; Estados Unidos. Harvard Medical School. Department of Medicine. Massachusetts General Hospital; Estados Unido