Disorders of voice quality are one of the most frequent problems seen in patients with voice disorders. Understanding the acoustic bases for dysphonic voice quality and developing tool for its measurement is a critical step in the assessment and treatment of these patients. These changes are often the primary measure of treatment outcome. Knowledge of the relationships between vocal fold physiology, acoustic and the perception of vocal quality are also necessary to guide treatment strategies for these patients. Although the study of voice quality as attracted immense attention in the past several decades, it has been plagued by a number of problems. Subjective approaches to quantify vocal quality are highly inconsistent and lack validity. Objective methods have limited sensitivity, specificity and lack consistency. Therefore, no well-accepted or standardized format for the evaluation of voice quality exists. Our previous research has identified several reasons that contribute to these problems. These include: (1) inadequately controlled perceptual experiments, (2) non-linear mapping between the acoustic stimulus and its perceptual correlate, and, (3) the presence of multiple acoustic cues for each voice quality (which often show trading relationships). We have been able to account for these factors by redesigning perceptual experiments using psychometric principles and through the use of an auditory processing model as a signal processing front-end. In effect, this allows us to study the vocal acoustic signal as it is represented in the auditory system. This "internal" representation of the vocal signal was found to provide measures of breathy voice quality that were as much as 25% better than conventional measures for the same purpose. The proposed research is an extension of this work. We seek to (a) further refine the methods for obtaining precise perceptual judgments of voice quality, (b) use these methods to determine the acoustic cues for roughness and strain, (c) develop computational models to explain the perception of dysphonic voice quality and, (d) evaluate the success of these models to predict the perceptual judgments of voice quality. The findings will then be translated into clinical practice as these can guide treatment strategies and lead to the development of measures to assess treatment outcome.