Toward Generalizable Machine Learning Models in Speech, Language, and Hearing Sciences: Estimating Sample Size and Reducing Overfitting

PURPOSE: Many studies using machine learning (ML) in speech, language, and hearing sciences rely upon cross-validations with single data splitting. This study\u27s first purpose is to provide quantitative evidence that would incentivize researchers to instead use the more robust data splitting method of nested METHOD: First, the significant impact of different cross-validations on ML outcomes was demonstrated using real-world clinical data. Then, Monte Carlo simulations were used to quantify the interactions among the employed cross-validation method, the discriminative power of features, the dimensionality of the feature space, the dimensionality of the model, and the sample size. Four different cross-validation methods (single holdout, 10-fold, train-validation-test, and nested 10-fold) were compared based on the statistical power and confidence of the resulting ML models. Distributions of the null and alternative hypotheses were used to determine the minimum required sample size for obtaining a statistically significant outcome (5% significance) with 80% power. Statistical confidence of the model was defined as the probability of correct features being selected for inclusion in the final model. RESULTS: ML models generated based on the single holdout method had very low statistical power and confidence, leading to overestimation of classification accuracy. Conversely, the nested 10-fold cross-validation method resulted in the highest statistical confidence and power while also providing an unbiased estimate of accuracy. The required sample size using the single holdout method could be 50% higher than what would be needed if nested CONCLUSION: The adoption of neste

Toward Generalizable Machine Learning Models in Speech, Language, and Hearing Sciences: Power Analysis and Sample Size Estimation

This study's first purpose is to provide quantitative evidence that would incentivize researchers to instead use the more robust method of nested cross-validation. The second purpose is to present methods and MATLAB codes for doing power analysis for ML-based analysis during the design of a study. Monte Carlo simulations were used to quantify the interactions between the employed cross-validation method, the discriminative power of features, the dimensionality of the feature space, and the dimensionality of the model. Four different cross-validations (single holdout, 10-fold, train-validation-test, and nested 10-fold) were compared based on the statistical power and statistical confidence of the ML models. Distributions of the null and alternative hypotheses were used to determine the minimum required sample size for obtaining a statistically significant outcome ({\alpha}=0.05, 1-\b{eta}=0.8). Statistical confidence of the model was defined as the probability of correct features being selected and hence being included in the final model. Our analysis showed that the model generated based on the single holdout method had very low statistical power and statistical confidence and that it significantly overestimated the accuracy. Conversely, the nested 10-fold cross-validation resulted in the highest statistical confidence and the highest statistical power, while providing an unbiased estimate of the accuracy. The required sample size with a single holdout could be 50% higher than what would be needed if nested cross-validation were used. Confidence in the model based on nested cross-validation was as much as four times higher than the confidence in the single holdout-based model. A computational model, MATLAB codes, and lookup tables are provided to assist researchers with estimating the sample size during the design of their future studies.Comment: Under review at JSLH

Quantifying the Occupational Voice Use of Teachers

PURPOSE: The teaching profession is a high-voice use occupation at elevated risk for developing voice disorders. Continued research on teachers\u27 vocal demands is necessary to advocate for and establish vocal health programs. This study quantified ambulatory vocal dose measures for teachers during both on- and off-work periods, comparing their occupational voice use to that in other studies that have reported percent phonation ranging from 17% to 30%. METHOD: Participants included 26 full-time, female school teachers between 23 and 55 years of age across multiple grades and subjects, including individuals with and without a voice disorder. Ambulatory voice data were collected from weeklong voice monitoring that recorded phonatory activity through anterior neck-surface vibration. Three vocal dose measures-time, cycle, and distance doses-were computed for each participant for three time periods: on-work weekdays, off-work weekdays, and off-work weekend days. RESULTS: The teachers\u27 average percent phonation was 16.2% on-work weekdays, 8.4% off-work weekdays, and 8.0% off-work weekend days. No statistically significant differences for vocal dose measures were found between off-work weekdays and weekend days. Overall, all vocal dose measures were approximately 2 times higher during work relative to off-work time periods. CONCLUSIONS: This study provides values for vocal dose measures for school teachers using ambulatory voice-monitoring technology. The vocal demands of this particular teacher sample and voice activity detection algorithm are potential factors contributing to percent phonation values on the lower end of the range reported in the literature. Future work is needed to continue to understand occupational voice use and its associated risks related to voice health, with the ultimate goal of preventing and managing voice disorders in individuals engaged in high-risk occupations

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

Novel DNA methylation profiles associated with key gene regulation and transcription pathways in blood and placenta of growth-restricted neonates

BB/H012494/1/ Biotechnology and Biological Sciences Research Counci

Histopathologic and Biochemical Responses in Arctic Marine Bivalve Molluscs Exposed to Experimentally Spilled Oil

Following two experimental spills of chemically dispersed and undispersed crude oil in shallow bays on the northwest coast of Baffin Island, Canadian Arctic, the bivalve molluscs Mya truncata and Macoma calcarea accumulated significant amounts of petroleum hydrocarbons in bays receiving dispersed oil and in those receiving crude oil alone (Boehm et all., 1987). Following the spills, Mya released accumulated hydrocarbons more rapidly than Macoma. ... The results of the biochemical analyses indicate that Mya from the four bays were not severely stressed by either dispersed oil or oil alone. Immediately after the spill, clams from the dispersal oil bays were nearly normal, while those from the bay receiving oil alone appeared stressed. These results seem to corroborate results from analytical chemistry and histopathology: that the acute effects of dispersed oil are greater than those of undispersed oil, but effects of undispersed oil on infaunal molluscs develop more slowly and persist longer than those from dispersed oil.Key words: oil spill, dispersant, Mya truncata, Macoma calcarea, histopathology, biochemistry, neoplasia, free amino acids, glycogen, parasitesMots clés: marée noire, agent de dispersion, Mya truncata, Macoma calcarea, histopathologie, biochimie, néoplasme, acides aminés libres, glycogène, parasite

Effect of Nodule Size and Stiffness on Phonation Threshold and Collision Pressures in a Synthetic Hemilaryngeal Vocal Fold Model

Synthetic vocal fold (VF) replicas were used to explore the role of nodule size and stiffness on kinematic, aerodynamic, and acoustic measures of voiced speech production. Emphasis was placed on determining how changes in collision pressure may contribute to the development of phonotrauma. This was performed by adding spherical beads with different sizes and moduli of elasticity at the middle of the medial surface of synthetic silicone VF models, representing nodules of varying size and stiffness. The VF models were incorporated into a hemilaryngeal flow facility. For each case, self-sustained oscillations were investigated at the phonation threshold pressure. It was found that increasing the nodule diameter increased the open quotient, phonation threshold pressure, and phonation threshold flow rate. However, these values did not change considerably as a function of the modulus of elasticity of the nodule. Nevertheless, the ratio of collision pressure to subglottal pressure increased significantly for both increasing nodule size and stiffness. This suggests that over time, both growth in size and fibrosis of nodules will lead to an increasing cycle of compensatory vocal hyperfunction that accelerates phonotrauma

Acoustic Voice and Speech Biomarkers of Treatment Status during Hospitalization for Acute Decompensated Heart Failure

This study investigates acoustic voice and speech features as biomarkers for acute decompensated heart failure (ADHF), a serious escalation of heart failure symptoms including breathlessness and fatigue. ADHF-related systemic fluid accumulation in the lungs and laryngeal tissues is hypothesized to affect phonation and respiration for speech. A set of daily spoken recordings from 52 patients undergoing inpatient ADHF treatment was analyzed to identify voice and speech biomarkers for ADHF and to examine the trajectory of biomarkers during treatment. Results indicated that speakers produce more stable phonation, a more creaky voice, faster speech rates, and longer phrases after ADHF treatment compared to their pre-treatment voices. This project builds on work to develop a method of monitoring ADHF using speech biomarkers and presents a more detailed understanding of relevant voice and speech features