Deep throat as a source of information

Heldner M, Wagner P, Włodarczak M. Deep throat as a source of information. In: Abelin Å, Nagano-Madsen Y, eds. Proceedings FONETIK 2018. Göteborg: University of Gothenburg, Department of Languages and Literatures Department of Philosophy, Linguistics and Theory of Science; 2018

Procesamiento, análisis y modelado de señales biomédicas: un enfoque integrador

Este proyecto se centra en el estudio, desarrollo y aplicación de técnicas de procesamiento, modelado y análisis de señales que permitan abordar los casos de señales biomédicas. Abordaremos métodos adaptativos de análisis de señales, principalmente la descomposición empírica en modos y sus variantes. Se avanzará en el desarrollo de modelos de las señales relacionadas con el aparato fonador. Se continuará el estudio de modelos en espacio de estados que permiten extraer información sobre el estado instantáneo del tracto vocal y de la fuente glótica. Se estudiará la factibilidad de extraer nuevos parámetros acústicos de utilidad clínica. Investigaremos técnicas y herramientas provenientes de la teoría de la información estudiando medidas basadas en la integral de correlación asistida por ruido y la integral de correlación U, propuestas por nuestro grupo, para la estimación de los invariantes dimensión, entropía y ruido, en sistemas simulados y reales de variadas dimensiones. Finalmente, se continuará con la formación de recursos humanos, a través de la realización de becas postdoctorales y doctorales CONICET, y el fortalecimiento de un grupo de investigación en el área de las TICs en el procesamiento de señales biomédicas, en el contexto del Instituto de Bioinformática y Bioingeniería en vías de creación. ARK/CAICYT: http://id.caicyt.gov.ar/ark:/s22504559/rd18ww2h

Using Ambulatory Voice Monitoring to Investigate Common Voice Disorders: Research Update

Many common voice disorders are chronic or recurring conditions that are likely to result from inefficient and/or abusive patterns of vocal behavior, referred to as vocal hyperfunction. The clinical management of hyperfunctional voice disorders would be greatly enhanced by the ability to monitor and quantify detrimental vocal behaviors during an individual’s activities of daily life. This paper provides an update on ongoing work that uses a miniature accelerometer on the neck surface below the larynx to collect a large set of ambulatory data on patients with hyperfunctional voice disorders (before and after treatment) and matched-control subjects. Three types of analysis approaches are being employed in an effort to identify the best set of measures for differentiating among hyperfunctional and normal patterns of vocal behavior: (1) ambulatory measures of voice use that include vocal dose and voice quality correlates, (2) aerodynamic measures based on glottal airflow estimates extracted from the accelerometer signal using subject-specific vocal system models, and (3) classification based on machine learning and pattern recognition approaches that have been used successfully in analyzing long-term recordings of other physiological signals. Preliminary results demonstrate the potential for ambulatory voice monitoring to improve the diagnosis and treatment of common hyperfunctional voice disorders

Accelerator-Based Vocal Tract Measurements

Clinical research seeks a voice monitoring device for everyday situations. This thesis in- vestigates the extraction of vocal tract information (VTI) from a portable, lightweight, and wireless voice accelerometer (ACC). An experiment recorded participants’ speech using two ACCs placed on the neck and cheek, comparing them to an acoustic microphone. The analysis focused on formant frequencies (FFs), inter-annotator agreement (IAA) for voice onset time (VOT), resistance to environmental noise, and accuracy of transcriptions using automatic speech recognition (ASR). FF extraction yielded unreliable and non-canonical vowel distributions. IAA showed agreement in voice onset between ACC and acoustic signal, but less for VOT start time and duration. Both placements resisted noise up to 85 dBA. However, ACC signals had a high Word error rate (WER), indicating poor recogni- tion. These findings suggest limited VTI extraction from ACC signals, requiring further improvements before reliable VTI recording devices can be developed

The relationships among physiological, acoustical, and perceptual measures of vocal effort

The purpose of this work was to explore the physiological mechanisms of vocal effort, the acoustical manifestation of vocal effort, and the perceptual interpretation of vocal effort by speakers and listeners. The first study evaluated four proposed mechanisms of vocal effort specific to the larynx: intrinsic laryngeal tension, extrinsic laryngeal tension, supraglottal compression, and subglottal pressure. Twenty-six healthy adults produced modulations of vocal effort (mild, moderate, maximal) and rate (slow, typical, fast), followed by self-ratings of vocal effort on a visual analog scale. Ten physiological measures across the four hypothesized mechanisms were captured via high-speed flexible laryngoscopy, surface electromyography, and neck-surface accelerometry. A mixed-effects backward stepwise regression analysis revealed that estimated subglottal pressure, mediolateral supraglottal compression, and a normalized percent activation of extrinsic suprahyoid muscles significantly increased as ratings of vocal effort increased (R2 = .60). The second study had twenty inexperienced listeners rate vocal effort on the speech recordings from the first study (typical, mild, moderate, and maximal effort) via a visual sort-and-rate method. A set of acoustical measures were calculated, including amplitude-, time-, spectral-, and cepstral-based measures. Two separate mixed-effects regression models determined the relationship between the acoustical predictors and speaker and listener ratings. Results indicated that mean sound pressure level, low-to-high spectral ratio, and harmonic-to-noise ratio significantly predicted speaker and listener ratings. Mean fundamental frequency (measured as change in semitones from typical productions) and relative fundamental frequency offset cycle 10 were also significant predictors of listener ratings. The acoustical predictors accounted for 72% and 82% of the variance in speaker and listener ratings, respectively. Speaker and listener ratings were also highly correlated (average r = .86). From these two studies, we determined that vocal effort is a complex physiological process that is mediated by changes in laryngeal configuration and subglottal pressure. The self-perception of vocal effort is related to the acoustical properties underlying these physiological changes. Listeners appear to rely on the same acoustical manifestations as speakers, yet incorporate additional time-based acoustical cues during perceptual judgments. Future work should explore the physiological, acoustical, and perceptual measures identified here in speakers with voice disorders.2019-07-06T00:00:00

The quantitative assessment of laryngeal physiology

Current clinical voice assessment uses a range of metrics, many of which lack objectivity and/or specificity. Two populations that are negatively impacted from insufficiencies in current voice assessment are individuals with vocal hyperfunction and transmasculine individuals. The following dissertation details four projects that investigated and validated quantitative measures of laryngeal function in order to improve clinical voice assessment in these two populations. Project 1 observed voice onset time (VOT) during modulations of vocal effort, vocal strain, and fundamental frequency (fo) in individuals with typical voices. VOT mean decreased when fo increased, but not during increases in effort or strain, indicating that the individuals with typical voices likely use different musculature when increasing fo than when increasing vocal effort and vocal strain, despite potential increases in laryngeal tension in all instances. VOT variance did not increase when vocal effort and vocal strain increased, suggesting that previous increases in VOT variance observed in individuals with vocal hyperfunction may be inherent to the voice disorder. Project 2 developed automated algorithms to calculate relative fundamental frequency (RFF) from ambulatory accelerometer signals. Average mean bias errors supported that these algorithms could be used to reliably calculate RFF during ecological momentary assessment. Project 3 developed a novel method for calculating RFF based on the end of vocal fold contact observed from laryngeal imaging during voicing offset. Statistically significant decreases in RFF variability with this novel method suggest that decreases in RFF offset patterns are directly driven by a decrease in vocal fold collision forces during abduction. Project 4 explored the development of a resynthesis algorithm to explore how quantitative features of acoustic signals recorded pre- and post- hormone replacement therapy with exogenous testosterone (HRT) affect speech-based gender perception in transmasculine speakers. Listener ratings suggest that mean fo is the single acoustic feature that drives the greatest changes in speech-based gender perception as a result of HRT. The results of these four projects advance the development of quantitative voice assessment and improve understanding of the underlying laryngeal physiology