A. S. Fryd, J. H. Van Stan, R. E. Hillman, and D. D. Mehta, “Estimating subglottal pressure from neck-surface acceleration during normal voice production,” Journal of Speech, Language, and Hearing Research, vol. 59, no. 6, pp. 1335-1345, 2016. Publisher's VersionAbstract

Purpose The purpose of this study was to evaluate the potential for estimating subglottal air pressure using a neck-surface accelerometer and to compare the accuracy of predicting subglottal air pressure relative to predicting acoustic sound pressure level (SPL).

Method Indirect estimates of subglottal pressure (Psg′) were obtained from 10 vocally healthy speakers during loud-to-soft repetitions of 3 different /p/–vowel gestures (/pa/, /pi/, /pu/) at 3 pitch levels in the modal register. Intraoral air pressure, neck-surface acceleration, and radiated acoustic pressure were recorded, and the root-mean-square amplitude of the acceleration signal was correlated with Psg′ and SPL.

Results The coefficient of determination between accelerometer level and Psg′ was high when data were pooled from all vowel and pitch contexts for each participant (r 2 = .68–.93). These relationships were stronger than corresponding relationships between accelerometer level and SPL (r 2 = .46–.81). The average 95% prediction interval for estimating Psg′ using accelerometer level was ±2.53 cm H2O, ranging from ±1.70 to ±3.74 cm H2O across participants.

Conclusions Accelerometer signal amplitude correlated more strongly with Psg′ than with SPL. Future work is warranted to investigate the robustness of the relationship in nonmodal voice qualities, individuals with voice disorders, and accelerometer-based ambulatory monitoring of subglottal pressure.

O. Murton, et al., “Impact of congestive heart failure on voice and speech production: A pilot study,” Proceedings of the Annual Scientific Meeting of the Heart Failure Society of America, 2016. Poster
R. E. Hillman, D. Mehta, C. Stepp, J. Van Stan, and M. Zanartu, “Objective assessment of vocal hyperfunction,” Proceedings of The Journal of the Acoustical Society of America, vol. 139, pp. 2193-2194, 2016.
R. L. Horwitz-Martin, et al., “Relation of automatically extracted formant trajectories with intelligibility loss and speaking rate decline in amyotrophic lateral sclerosis,” Proceedings of InterSpeech, pp. 1205-1209, 2016. Paper
D. Mehta, J. Van Stan, and R. Hillman, “Relationships between vocal function measures derived from an acoustic microphone and a subglottal neck-surface accelerometer,” IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 24, no. 4, pp. 659-668, 2016. Publisher's VersionAbstract

Monitoring subglottal neck-surface acceleration has received renewed attention due to the ability of low-profile accelerometers to confidentially and noninvasively track properties related to normal and disordered voice characteristics and behavior. This study investigated the ability of subglottal necksurface acceleration to yield vocal function measures traditionally derived from the acoustic voice signal and help guide the development of clinically functional accelerometer-based measures from a physiological perspective. Results are reported for 82 adult speakers with voice disorders and 52 adult speakers with normal voices who produced the sustained vowels /A/, /i/, and /u/ at a comfortable pitch and loudness during the simultaneous recording of radiated acoustic pressure and subglottal necksurface acceleration. As expected, timing-related measures of jitter exhibited the strongest correlation between acoustic and necksurface acceleration waveforms (r 0:99), whereas amplitudebased measures of shimmer correlated less strongly (r 0:74). Additionally, weaker correlations were exhibited by spectral measures of harmonics-to-noise ratio (r 0:69) and tilt (r 0:57), whereas the cepstral peak prominence correlated more strongly (r 0:90). These empirical relationships provide evidence to support the use of accelerometers as effective complements to acoustic recordings in the assessment and monitoring of vocal function in the laboratory, clinic, and during an individual’s daily activities.

M. Ghassemi, Z. Syed, D. D. Mehta, J. H. Van Stan, R. E. Hillman, and J. V. Guttag, “Uncovering voice misuse using symbolic mismatch,” JMLR (Journal of Machine Learning Research): Workshop and Conference Proceedings, pp. 1-14, 2016. Paper
H. Aljehani, J. H. Van Stan, C. W. Haynes, and D. D. Mehta, “Ambulatory voice monitoring of a Muslim imam during Ramadan,” Proceedings of the Voice Foundation Symposium, 2015. Poster
J. H. Van Stan, D. D. Mehta, S. M. Zeitels, J. A. Burns, A. M. Barbu, and R. E. Hillman, “Average ambulatory measures of sound pressure level, fundamental frequency, and vocal dose do not differ between adult females with phonotraumatic lesions and matched control subjects,” Annals of Otology, Rhinology, and Laryngology, vol. 124, pp. 864-874, 2015.Abstract

Objectives: Clinical management of phonotraumatic vocal fold lesions (nodules, polyps) is based largely on assumptions that abnormalities in habitual levels of sound pressure level (SPL), fundamental frequency (f0), and/or amount of voice use play a major role in lesion development and chronic persistence. This study used ambulatory voice monitoring to evaluate if significant differences in voice use exist between patients with phonotraumatic lesions and normal matched controls.Methods: Subjects were 70 adult females: 35 with vocal fold nodules or polyps and 35 age-, sex-, and occupation-matched normal individuals. Weeklong summary statistics of voice use were computed from anterior neck surface acceleration recorded using a smartphone-based ambulatory voice monitor.Results: Paired t tests and Kolmogorov-Smirnov tests resulted in no statistically significant differences between patients and matched controls regarding average measures of SPL, f0, vocal dose measures, and voicing/voice rest periods. Paired t tests comparing f0 variability between the groups resulted in statistically significant differences with moderate effect sizes.Conclusions: Individuals with phonotraumatic lesions did not exhibit differences in average ambulatory measures of vocal behavior when compared with matched controls. More refined characterizations of underlying phonatory mechanisms and other potentially contributing causes are warranted to better understand risk factors associated with phonotraumatic lesions.

M. Ghassemi, et al., “Corrections to "Learning to detect vocal hyperfunction from ambulatory neck-surface acceleration features: Initial results for vocal fold nodules,” IEEE Transactions on Biomedical Engineering, vol. 62, no. 10, pp. 2544-2544, 2015. Publisher's VersionAbstract

In, the third sentence of the second paragraph in Section III-D should have read as follows: “We first divided data using leave-one-out cross validation (LOOCV) to generate 12 subject subsets, where each subject subset consisted of randomly selected data across the 12 pairs. For each test subset, all windows from the 11 other subsets were then subdivided using fivefold cross validation (1/5th validation and 4/5th training in each fold).”

G. Maguluri, E. Chang, N. Iftimia, D. Mehta, and J. Kobler, “Dynamic vocal fold imaging by integrating optical coherence tomography with laryngeal high-speed video endoscopy,” Proceedings of the Conference on Lasers and Electro-Optics (CLEO), pp. 1-2, 2015.Abstract

We demonstrate three-dimensional vocal fold imaging during phonation by integrating optical coherence tomography with high-speed videoendoscopy. Results from ex vivo larynx experiments yield reconstructed vocal fold surface contours for ten phases of periodic motion.

J. H. Van Stan, D. D. Mehta, and R. E. Hillman, “The effect of voice ambulatory biofeedback on the daily performance and retention of a modified vocal motor behavior in participants with normal voices,” Journal of Speech, Language, and Hearing Research, vol. 58, no. 3, pp. 713-721, 2015. Publisher's VersionAbstract

Purpose Ambulatory biofeedback has potential to improve carryover of newly established vocal motor behaviors into daily life outside of the clinic and warrants systematic research that is lacking in the literature. This proof-of-concept study was designed to establish an empirical basis for future work in this area by formally assessing whether ambulatory biofeedback reduces daily vocal intensity (performance) and the extent to which this change remains after biofeedback removal (retention). Method Six participants with normal voices wore the KayPENTAX Ambulatory Phonation Monitor for 3 baseline days followed by 4 days with biofeedback provided on odd days. Results Compared to baseline days, participants exhibited a statistically significant decrease in mean vocal intensity (4.4 dB) and an increase in compliance (16.8 percentage points) when biofeedback was provided above a participant-specific intensity threshold. After biofeedback removal, mean vocal intensity and compliance reverted back to baseline levels. Conclusions These findings suggest that although current ambulatory biofeedback approaches have potential to modify a vocal motor behavior, the modified behavior may not be retained after biofeedback removal. Future work calls for the testing of more innovative ambulatory biofeedback approaches on the basis of motor control and learning theories to improve retention of a desired vocal motor behavior.

A. S. Fryd, J. H. Van Stan, R. E. Hillman, and D. D. Mehta, “Estimating subglottal pressure during phonation with a neck-surface accelerometer sensor,” Proceedings of the Annual Convention of the American Speech-Language-Hearing Association, 2015. Poster
Jón Guðnason, D. D. Mehta, and T. F. Quatieri, “Evaluation of speech inverse filtering techniques using a physiologically-based synthesizer,” Proceedings of the International Conference on Acoustics, Speech, and Signal Processing, 2015. Paper
D. D. Mehta, D. D. Deliyski, S. M. Zeitels, M. Zañartu, and R. E. Hillman, “Integration of transnasal fiberoptic high-speed videoendoscopy with time-synchronized recordings of vocal function”, K. Izdebski, Y. Yan, R. R. Ward, B. J. F. Wong, and R. M. Cruz, Ed. San Francisco: Pacific Voice & Speech Foundation, 2015, pp. 105-114. Publisher's Version
D. D. Deliyski, R. E. Hillman, and D. D. Mehta, “Laryngeal high-speed videoendoscopy: Rationale and recommendation for accurate and consistent terminology,” Journal of Speech, Language, and Hearing Research, vol. 58, no. 5, pp. 1488-1492, 2015. Publisher's VersionAbstract

Abstract Purpose: The authors discuss the rationale behind the term laryngeal high-speed videoendoscopy to describe the application of high-speed endoscopic imaging techniques to the visualization of vocal fold vibration. Method: Commentary on the advantages of using accurate and consistent terminology in the field of voice research is provided. Specific justification is described for each component of the term high-speed videoendoscopy, which is compared and contrasted with alternative terminologies in the literature. Results: In addition to the ubiquitous high-speed descriptor, the term endoscopy is necessary to specify the appropriate imaging technology and distinguish among modalities such as ultrasound, magnetic resonance imaging, and nonendoscopic optical imaging. Furthermore, the term video critically indicates the electronic recording of a sequence of optical still images representing scenes in motion, in contrast to strobed images using high-speed photography and non-optical high-speed magnetic resonance imaging. High-speed videoendoscopy thus concisely describes the technology and can be appended by the desired anatomical nomenclature such as laryngeal. Conclusions: Laryngeal high-speed videoendoscopy strikes a balance between conciseness and specificity when referring to the typical high-speed imaging method performed on human participants. Guidance for the creation of future terminology provides clarity and context for current and future experiments and the dissemination of results among researchers.

A. F. Llico, et al., “Real-time estimation of aerodynamic features for ambulatory voice biofeedback,” The Journal of the Acoustical Society of America, vol. 138, no. 1, pp. EL14-EL19, 2015. Publisher's Version Paper
J. R. Williamson, T. F. Quatieri, B. S. Helfer, G. Ciccarelli, and D. D. Mehta, “Segment-dependent dynamics in predicting Parkinson’s disease,” Proceedings of InterSpeech, pp. 518-522, 2015. Paper
D. D. Mehta and P. J. Wolfe, “Statistical properties of linear prediction analysis underlying the challenge of formant bandwidth estimation,” The Journal of the Acoustical Society of America, vol. 137, no. 2, pp. 944-950, 2015. Publisher's Version Paper
G. Luegmair, D. D. Mehta, J. B. Kobler, and M. Döllinger, “Three-dimensional optical reconstruction of vocal fold kinematics using high-speed video with a laser projection system,” IEEE Transactions on Medical Imaging, vol. 34, no. 12, pp. 2572-2582, 2015. Publisher's Version Paper
D. D. Mehta, et al., “Using ambulatory voice monitoring to investigate common voice disorders: Research update,” Frontiers in Bioengineering and Biotechnology, vol. 3, no. 155, pp. 1-14, 2015. Publisher's VersionAbstract

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.