Toward standardizing perceptual voice quality measures

University Of California Los Angeles, Los Angeles CA

Investigators

Linked publications & trials

Abstract

DESCRIPTION (provided by applicant): Perception of pathological voice quality is centrally important in clinical voice evaluation, but adequately quantifying the sound of a person's voice remains problematic. Data from studies completed during the previous funding period indicate that many difficulties associated with current measures of voice quality derive from the way in which quality is defined and measured. We propose the development of a psychoacoustic model of overall voice quality as an alternative to traditional ratings and acoustic analysis protocols. This psychoacoustic model will specify a set of perceptually-important acoustic parameters that combine to replicate and thereby quantify the overall, integral quality of a voice. We will first determine the minimal set of acoustic parameters required to produce a synthetic copy of any voice, such that listeners judge that the synthetic copy matches the quality of the original voice. This set will constitute a preliminary psychoacoustic model of voice quality. We will then refine and validate this psychoacoustic model by synthesizing copies of natural voices using only these model parameters. To the extent that listeners judge that the natural and synthetic tokens match exactly, the psychoacoustic model will be considered valid. Mismatches will be analyzed to determine what parameters should be added to or subtracted from the model. We will assess the relationship between changes in acoustic values and changes in the extent to which a voice deviates from normal. This will provide an explanatory model specifying how acoustic parameters combine and interact perceptually to determine the location of any voice sample along a continuum from better to worse. Finally, we will investigate the link between perceptually-important acoustic, spectral changes and the associated alterations in glottal configuration. Such knowledge could identify targets for remediation that have the highest likelihood of producing vocal improvement during treatment.