Triangular body-cover model of the vocal folds with coordinated activation of the five intrinsic laryngeal muscles

Poor laryngeal muscle coordination that results in abnormal glottal posturing is believed to be a primary etiologic factor in common voice disorders such as non-phonotraumatic vocal hyperfunction. Abnormal activity of antagonistic laryngeal muscles is hypothesized to play a key role in the alteration of normal vocal fold biomechanics that results in the dysphonia associated with such disorders. Current low-order models of the vocal folds are unsatisfactory to test this hypothesis since they do not capture the co-contraction of antagonist laryngeal muscle pairs. To address this limitation, a self-sustained triangular body-cover model with full intrinsic muscle control is introduced. The proposed scheme shows good agreement with prior studies using finite element models, excised larynges, and clinical studies in sustained and time-varying vocal gestures. Simulations of vocal fold posturing obtained with distinct antagonistic muscle activation yield clear differences in kinematic, aerodynamic, and acoustic measures. The proposed tool is deemed sufficiently accurate and flexible for future comprehensive investigations of non-phonotraumatic vocal hyperfunction and other laryngeal motor control disorders.Fil: 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: Peterson, Sean D.. University of Waterloo; CanadáFil: Erath, Byron D.. Clarkson University; Estados UnidosFil: Hillman, Robert E.. Massachusetts General Hospital; Estados UnidosFil: Zañartu, Matías. Universidad Tecnica Federico Santa Maria.; Chil

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

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

Stochastic modeling of phonation and the related biomedical signals. State space methods applied to structural analysis, phonation modeling, and inverse filtering

Fil: Alzamendi, Gabriel Alejandro. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas; Argentina.La voz y las señales relacionadas poseen información que permite caracterizar la fonación. Extraer esta información de forma precisa es beneficioso para la medicina y otras ciencias. En esta Tesis se proponen nuevos métodos para el modelado de la fonación, y sus señales relacionadas, basados en el modelado estocástico y el procesamiento de señales. Primeramente, se investigan las series de períodos y de amplitudes para una vocal sostenida aplicando los conceptos de perturbaciones y fluctuaciones de la voz, y se desarrolla un método novedoso para la síntesis de vocales sostenidas con perturbaciones controladas por dos parámetros acústicos importantes para la medicina. Luego, se propone el modelado estructural en espacio de estados para series de períodos y de amplitudes. Su objetivo es explicar estas señales suponiéndolas compuestas por elementos simples con una interpretación directa, bajo la hipótesis de que son procesos estocásticos no estacionarios. Combinando los modelos estructurales con los métodos en espacio de estados, se implementa el análisis estructural para señales reales. Por otra parte, se investigan nuevos métodos en espacio de estados para realizar el filtrado inverso de la voz. Para ello, se formula una ecuación en diferencias estocástica no estacionaria para la función glótica, y a partir de ésta se construye un modelo de la fonación capaz de representar una voz de forma precisa y flexible. Con este modelo, se implementa un método para la estimación conjunta y precisa de la función glótica y del tracto vocal, denominado filtrado inverso en espacio de estados.The voice and related biomedical signals carry information characterizing the phonation. The accurate extraction of this information becomes beneficial in medicine and other fields. In this Thesis, new methods for modeling the voice production and related biomedical signals, combining the stochastic modeling and digital signal processing, are proposed and evaluated. First, period and amplitude series extracted from sustained vowels are investigated applying the fundamental concepts of voice perturbations and fluctuations, and then a new sustained vowel synthesis method is proposed considering perturbations controlled with two acoustical parameters relevant in voice therapy. Next, state space structural models for studying period and amplitude series are developed. The aim of these models is to represent a signal assuming that it is composed of simple elements with a straightforward interpretation, under the hypothesis that these phenomena behave as non-stationary stochastic processes. Combining the structural models and state space methods, the structural analysis method is successfully implemented. Finally, new state space based methods for phonation modeling and voice inverse filtering are proposed. For that, a stochastic non-stationary difference equation of glottal function is developed, taking into account the perturbations and aperiodicities in this signal. According to this, a phonation model suitable for accurate and flexible vocal sounds representation is formulated. Using this model, a state space based inverse filtering method is proposed allowing the join optimal estimation of the glottal function and the vocal tract filter.Ministerio de Ciencia, Tecnología e Innovación ProductivaConsejo Nacional de Investigaciones Científicas y TécnicasUniversidad Nacional de Entre Río

Modeling and joint estimation of glottal source and vocal tract filter by state-space methods

Accurate estimation of the glottal source from a voiced sound is a difficult blind separation problem in speech signal processing. In this work, state-space methods are investigated to enhance the joint estimation of the glottal source and the vocal tract information. The aim of this paper is twofold. First, a stochastic glottal source is proposed, based on deterministic Liljencrants–Fant model and ruled by a stochastic difference equation. Such a representation allows to accurately capture any perturbation occurring at glottal level in real voices. A state-space voice model is formulated considering the stochastic glottal source. Then, combining this voice model and the state-space framework, an inverse filtering method is developed that allows to jointly estimate both glottal source and vocal tract filter. The performance of this method is studied by means of experiments with voices synthesized by applying both the source-filter theory and a physical based voice model. The method is also test using human voice signals. The results demonstrate that accurate estimates of the glottal source and the vocal tract filter can be obtained over several scenarios. Moreover, the method is shown to be robust with respect to different phonation types.Fil: Alzamendi, Gabriel Alejandro. Universidad Nacional de Entre Ríos. Facultad de Ingeniería. Departamento de Matemática e Informática. Laboratorio de Señales y Dinámicas no Lineales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro de Investigaciones y Transferencia de Entre Ríos. Universidad Nacional de Entre Ríos. Centro de Investigaciones y Transferencia de Entre Ríos; ArgentinaFil: Schlotthauer, Gaston. Universidad Nacional de Entre Ríos. Facultad de Ingeniería. Departamento de Matemática e Informática. Laboratorio de Señales y Dinámicas no Lineales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro de Investigaciones y Transferencia de Entre Ríos. Universidad Nacional de Entre Ríos. Centro de Investigaciones y Transferencia de Entre Ríos; Argentin

State-Space Approach to Structural Representation of Perturbed Pitch Period Sequences in Voice Signals

Objectives: The aim of this study was to propose a state space-based approach to model perturbed pitch period sequences (PPSs), extracted from real sustained vowels, combining the principal features of disturbed real PPSs with structural analysis of stochastic time series and state space methods. Methods: The PPSs were obtained from a database composed of 53 healthy subjects. State space models were developed taking into account different structures and complexity levels. PPS features such as trend, cycle, and irregular structures were considered. Model parameters were calculated using optimization procedures. For each PPS, state estimates were obtained combining the developed models and diffuse initialization with filtering and smoothing methods. Statistical tests were applied to objectively evaluate the performance of this method. Results: Statistical tests demonstrated that the proposed approach correctly represented more than the 75% of the database with a significance value of 0.05. In the analysis, structural estimates suitably characterized the dynamics of the PPSs. Trend estimates proved to properly represent slow long-term dynamics, whereas cycle estimates captured short-term autoregressive dependencies. Conclusions: The present study demonstrated that the proposed approach is suitable for representing and analyzing real perturbed PPSs, also allowing to extract further information related to the phonation process.Fil: Alzamendi, Gabriel Alejandro. Universidad Nacional de Entre Ríos. Facultad de Ingeniería. Departamento de Matemática e Informática. Laboratorio de Señales y Dinámicas no Lineales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Schlotthauer, Gaston. Universidad Nacional de Entre Ríos. Facultad de Ingeniería. Departamento de Matemática e Informática. Laboratorio de Señales y Dinámicas no Lineales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Torres, Maria Eugenia. Universidad Nacional de Entre Ríos. Facultad de Ingeniería. Departamento de Matemática e Informática. Laboratorio de Señales y Dinámicas no Lineales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

Wavelet leader multifractal analysis of period and amplitude sequences from sustained vowels

Irregularities in the amplitude and period are characteristic of both normal and pathological sustained vowels; they are a product of perturbations inherent in the phonation process. Their analysis provides useful diagnostic information for several vocal pathologies, and their accurate modelling has been shown to improve the quality of synthesized voice. In this work, we propose the application of multifractal analysis for the characterization of amplitude and period fluctuations in sustained vowels. Using a combination of high order statistics, this signal processing tool generalizes previous approaches and provides a rich description of the fluctuation in the regularity of the data. Our results suggest that both amplitude and period fluctuations show a multifractal behavior, independent of the gender of the speaker. We also analyze the problem of classification between healthy and nonhealthy speakers as an example to show the usefulness of multifractal attributes. We conclude that amplitude and period sequences of sustained vowels should be analyzed and modelled by the multifractal paradigm.Fil: Leonarduzzi, Roberto Fabio. Universidad Nacional de Entre Ríos. Facultad de Ingeniería. Departamento de Matemática e Informática. Laboratorio de Señales y Dinámicas no Lineales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Alzamendi, Gabriel Alejandro. Universidad Nacional de Entre Ríos. Facultad de Ingeniería. Departamento de Matemática e Informática. Laboratorio de Señales y Dinámicas no Lineales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Schlotthauer, Gaston. Universidad Nacional de Entre Ríos. Facultad de Ingeniería. Departamento de Matemática e Informática. Laboratorio de Señales y Dinámicas no Lineales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Torres, Maria Eugenia. Universidad Nacional de Entre Ríos. Facultad de Ingeniería. Departamento de Matemática e Informática. Laboratorio de Señales y Dinámicas no Lineales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

Kalman Filter Implementation of Subglottal Impedance-Based Inverse Filtering to Estimate Glottal Airflow during Phonation

Subglottal Impedance-Based Inverse Filtering (IBIF) allows for the continuous, non-invasive estimation of glottal airflow from a surface accelerometer placed over the anterior neck skin below the larynx. It has been shown to be advantageous for the ambulatory monitoring of vocal function, specifically in the use of high-order statistics to understand long-term vocal behavior. However, during long-term ambulatory recordings over several days, conditions may drift from the laboratory environment where the IBIF parameters were initially estimated due to sensor positioning, skin attachment, or temperature, among other factors. Observation uncertainties and model mismatch may result in significant deviations in the glottal airflow estimates; unfortunately, they are very difficult to quantify in ambulatory conditions due to a lack of a reference signal. To address this issue, we propose a Kalman filter implementation of the IBIF filter, which allows for both estimating the model uncertainty and adapting the airflow estimates to correct for signal deviations. One-way analysis of variance (ANOVA) results from laboratory experiments using the Rainbow Passage indicate an improvement using the modified Kalman filter on amplitude-based measures for phonotraumatic vocal hyperfunction (PVH) subjects compared to the standard IBIF; the latter showing a statistically difference (p-value =0.02, F=4.1) with respect to a reference glottal volume velocity signal estimated from a single notch filter used here as ground-truth in this work. In contrast, maximum flow declination rates from subjects with vocal phonotrauma exhibit a small but statistically difference between the ground-truth signal and the modified Kalman filter when using one-way ANOVA (p-value =0.04, F=3.3). Other measures did not have significant differences with either the modified Kalman filter or IBIF compared to ground-truth, with the exception of H1-H2, whose performance deteriorates for both methods. Overall, both methods (modified Kalman filter and IBIF) show similar glottal airflow measures, with the advantage of the modified Kalman filter to improve amplitude estimation. Moreover, Kalman filter deviations from the IBIF output airflow might suggest a better representation of some fine details in the ground-truth glottal airflow signal. Other applications may take more advantage from the adaptation offered by the modified Kalman filter implementation