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Developing Clinically Relevant Scales of Breathy and Rough Voice Quality
David A Eddins1, Supraja Anand1, Arianna Lang2
1Department of Communication Sciences and Disorders, University of South Florida, Tampa, Florida.
Abstract:
The most common measurement tools used in the perceptual evaluation of voice quality yield ordinal data and thus do not support the establishment of mathematical relationships among different measurement values. This makes their interpretation challenging. Among the many desirable features of any psychophysical measurement tool is the ability to quantify the difference between two or more measurements and the ability to interpret the measurements in a manner that is related to the experience of the observer. The former allows one to compare among measurements using simple mathematics, while the latter allows that comparison to be interpreted in constructive ways. In this paper we describe the development of standard measurement scales for two dimensions of voice quality, following an approach that has been applied successfully to the perception of loudness. The scales follow step-by-step procedures used to develop the sone scale of loudness, which ties physical units to the perceptual estimates of loudness magnitude. Goals of the current work include development of analogous scales for the perception of breathy and rough voice qualities. First, the relationship between perceived voice quality and physical units were established using single-variable matching tasks. Second, the relationship between a change in physical units from the single-variable matching tasks and perceived voice quality magnitude were established using magnitude estimation tasks. Third, single reference points were identified on breathy and rough continuums. Finally, all points on the newly established voice quality continuums were rescaled relative to these arbitrary reference points. The proposed breathiness and roughness scales result in ratio-level data with standard measurement units that support quantitative comparisons of perceptual judgments. Such judgments can be used, for example, to compare magnitude of change pre- and post-treatment.
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