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Acoustic Metrics of the Strain Dimension of Voice Quality: A Scoping Review
Chia-Hsin Wu1, Lady Catherine Cantor-Cutiva2, Eric J Hunter1
1Department of Communication Sciences and Disorders, University of Iowa, Iowa City, IA.
Background:
Strained voice quality-commonly referred to as vocal strain-is a hallmark of functional voice disorders such as muscle tension dysphonia and is often associated with vocal fatigue and laryngeal hyperfunction. Although listeners describe it as excessive vocal effort, strained voice quality frequently overlaps perceptually with breathiness and roughness, complicating reliable assessment. Despite its clinical relevance, no standardized acoustic definition of strained voice quality has been established.
Purpose:
This review aims to identify and summarize the voice acoustic parameters reported in the literature to quantify the strain dimension of voice quality.
Methods:
A scoping review with systematic elements was conducted using four databases (ScienceDirect, PubMed, Virtual Health Library, and Web of Science) covering 1996 to 2024. Of 311 identified records, 13 met the inclusion criteria. Extracted data included definitions of vocal strain, perceptual assessment tools, acoustic metrics, and methodological details.
Results:
Strain was consistently treated as a perceptual attribute of voice quality, often described as the impression of excessive effort. Common acoustic metrics included cepstral peak prominence (CPP), spectral slope, low-to-high (L/H) spectral ratio, and relative fundamental frequency (RFF). While several measures showed moderate-to-strong correlations with perceptual ratings of strain, methodological variability across studies limited direct comparisons and interpretability.
Conclusion And Recommendations:
Strained voice quality is perceptually complex and acoustically multifaceted. While no single metric reliably captures its full scope, acoustic measures-particularly spectral and cepstral features-can complement perceptual assessments. A multimodal approach that integrates listener-based impressions, acoustic analysis, and, where possible, physiological data is recommended to improve diagnostic consistency and guide future research into strain-sensitive voice assessment tools.
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