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Measuring vocal quality with speech synthesis.

Abstract

Much previous research has demonstrated that listeners do not agree well when using traditional rating scales to measure pathological voice quality. Although these findings may indicate that listeners are inherently unable to agree in their perception of such complex auditory stimuli, another explanation implicates the particular measurement method-rating scale judgments-as the culprit. An alternative method of assessing quality-listener-mediated analysis-synthesis-was devised to assess this possibility. In this new approach, listeners explicitly compare synthetic and natural voice samples, and adjust speech synthesizer parameters to create auditory matches to voice stimuli. This method is designed to replace unstable internal standards for qualities like breathiness and roughness with externally presented stimuli, to overcome major hypothetical sources of disagreement in rating scale judgments. In a preliminary test of the reliability of this method, listeners were asked to adjust the signal-to-noise ratio for 12 synthetic pathological voices so that the resulting stimuli matched the natural target voices as well as possible For comparison to the synthesis judgments, listeners also judged the noisiness of the natural stimuli in a separate task using a traditional visual-analog rating scale. For 9 of the 12 voices, agreement among listeners was significantly (and substantially) greater for the synthesis task than for the rating scale task. Response variances for the two tasks did not differ for the remaining three voices. However, a second experiment showed that the synthesis settings that listeners selected for these three voices were within a difference limen, and therefore observed differences were perceptually insignificant. These results indicate that listeners can in fact agree in their perceptual assessments of voice quality, and that analysis-synthesis can measure perception reliably.

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BibTeXRIS

B R Gerratt, J Kreiman. 2001. Measuring vocal quality with speech synthesis.. https://doi.org/10.1121/1.1409969

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