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Related Experiment Videos

Multiparametric evaluation of dysphonic severity.

Estella P-M Ma1, Edwin M-L Yiu

  • 1Division of Speech Pathology, The University of Queensland, Brisbane, Queensland, Australia. estella.ma@shrs.uq.edu.au

Journal of Voice : Official Journal of the Voice Foundation
|September 28, 2005
PubMed
Summary

Predicting voice quality severity is possible using a few key measures. Maximum phonation time, peak intraoral pressure, voice range profile area, and acoustic jitter accurately predicted overall severity in dysphonic individuals.

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Area of Science:

  • Speech and Hearing Sciences
  • Otolaryngology
  • Acoustics

Background:

  • The multiparametric approach is increasingly used for voice quality assessment.
  • Accurate prediction of perceived voice severity is crucial for clinical diagnosis and treatment planning.

Purpose of the Study:

  • To evaluate the accuracy of a minimal set of aerodynamic, voice range profile (phonetogram), and acoustic perturbation measures in predicting perceived overall voice quality severity.
  • To identify the most effective instrumental measures for discriminating between dysphonic and normal voices and correlating with perceptual severity ratings.

Main Methods:

  • Involved 112 individuals with dysphonia and 41 healthy controls.
  • Perceptual severity was rated using the G (overall grade) parameter of the GRBAS scale by four listeners.

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  • A minimal set of instrumental measures was selected based on discriminative ability and correlation with perceived severity.
  • Main Results:

    • Maximum phonation time, peak intraoral pressure, voice range profile area, and acoustic jitter were identified as key predictors.
    • These four measures in combination correctly predicted 67.3% of perceived overall severity levels using discriminant function analysis.

    Conclusions:

    • A minimal set of aerodynamic, voice range profile, and acoustic measures can accurately predict perceived voice quality severity.
    • This finding supports the use of a focused, multiparametric approach for efficient and reliable voice assessment.