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Capturing the Intraspeaker Heterogeneity of Vocal Hyperfunction Using Spatiotemporal Indices of Relative Fundamental Frequency.

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Title: Capturing the Intraspeaker Heterogeneity of Vocal Hyperfunction Using Spatiotemporal Indices of Relative Fundamental Frequency.
Authors: Vojtech, Jenny1 jmvo@bu.edu, Toles, Laura E.2, Buckley, Daniel P.1,3, Steppa, Cara E.1,3,4
Source: Journal of Speech, Language & Hearing Research. Sep2025, Vol. 68 Issue 9, p4220-4235. 16p.
Subject Terms: *Predictive tests, *Data analysis, *Voice disorders, *Speech evaluation, *Comparative studies, Cross-sectional method, Receiver operating characteristic curves, Laryngeal muscles, Research funding, Logistic regression analysis, Signal processing, Descriptive statistics, Multivariate analysis, Physiological aspects of speech, Analysis of variance, Statistics, Human voice, Acoustic stimulation, Data analysis software, Nonparametric statistics, Sensitivity & specificity (Statistics)
Abstract: Purpose: Hyperfunctional voice disorders are highly prevalent yet difficult to characterize objectively. Relative fundamental frequency (RFF) has the potential to characterize these disorders but faces limited clinical use due to intersubject variability in mean RFF values. This study examined whether RFF variability offers insights beyond traditional mean measures. Method: Speech samples were collected from 132 adults: individuals with phonotraumatic vocal hyperfunction (PVH; n = 44), nonphonotraumatic vocal hyperfunction (NPVH; n = 44), and typical voices (controls; n = 44). Two measures of RFF variability--standard deviation and spatiotemporal index (STI)--were calculated along with mean RFF values. While standard deviation captures variability in magnitude, STI incorporates variability in time and magnitude. Permutational analyses of variance were conducted to assess relationships between group (PVH/NPVH/control) and the mean, standard deviation, and STI measures. Significant measures were entered along with demographic parameters into hierarchical multinomial logistic regression models using a training set (n = 102). Final model equations were then applied to an independent test set (n = 30) to predict group membership. Results: Mean and STI measures showed significant group differences, whereas standard deviation did not. Both mean and STI measures improved model performance after adjusting for demographics. Receiver operating characteristic analysis on the test set yielded acceptable classification (area under curve = 0.78) for group membership. Conclusions: Variability in RFF, especially when considering both time and magnitude, captures subtle features of vocal hyperfunction that may be overlooked by traditional mean measures. These findings underscore the clinical value of advanced RFF variability metrics in characterizing vocal hyperfunction. Supplemental Material: https://doi.org/10.23641/asha.29903054 [ABSTRACT FROM AUTHOR]
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Database: Education Research Complete
Description
Abstract:Purpose: Hyperfunctional voice disorders are highly prevalent yet difficult to characterize objectively. Relative fundamental frequency (RFF) has the potential to characterize these disorders but faces limited clinical use due to intersubject variability in mean RFF values. This study examined whether RFF variability offers insights beyond traditional mean measures. Method: Speech samples were collected from 132 adults: individuals with phonotraumatic vocal hyperfunction (PVH; n = 44), nonphonotraumatic vocal hyperfunction (NPVH; n = 44), and typical voices (controls; n = 44). Two measures of RFF variability--standard deviation and spatiotemporal index (STI)--were calculated along with mean RFF values. While standard deviation captures variability in magnitude, STI incorporates variability in time and magnitude. Permutational analyses of variance were conducted to assess relationships between group (PVH/NPVH/control) and the mean, standard deviation, and STI measures. Significant measures were entered along with demographic parameters into hierarchical multinomial logistic regression models using a training set (n = 102). Final model equations were then applied to an independent test set (n = 30) to predict group membership. Results: Mean and STI measures showed significant group differences, whereas standard deviation did not. Both mean and STI measures improved model performance after adjusting for demographics. Receiver operating characteristic analysis on the test set yielded acceptable classification (area under curve = 0.78) for group membership. Conclusions: Variability in RFF, especially when considering both time and magnitude, captures subtle features of vocal hyperfunction that may be overlooked by traditional mean measures. These findings underscore the clinical value of advanced RFF variability metrics in characterizing vocal hyperfunction. Supplemental Material: https://doi.org/10.23641/asha.29903054 [ABSTRACT FROM AUTHOR]
ISSN:10924388
DOI:10.1044/2025_JSLHR-25-00138