Gradient ascent paired-comparison subjective quality testing

Abstract

Subjective testing is the most direct means of assessing audio, video, and multimedia quality as experienced by users and maximizing the information gathered while minimizing the number of trials is an important goal. We propose gradient ascent subjective testing (GAST) as an efficient way to locate optimizing sets of coding or transmission parameter values. GAST combines gradient ascent optimization techniques with paired-comparison subjective test trials to efficiently locate parameter values that maximize perceived quality. We used GAST to search a two-dimensional parameter space for the known region of maximal audio quality as proof-of-concept. That point was accurately located and we estimate that conventional testing would have required at least 27 times as many trials to generate the same results.