Multidimensional scaling of sound quality

Multidimensional scaling is a technique that is based on dissimilarity data and yields, via statistical modeling, an optimal, low-dimensional vector space. The dimensions of this space can be interpreted as signifying relevant attributes underlying the dissimilarity judgments. This technology was applied to a heterogeneous set of environmental sounds, in order to investigate, in which way their perceptual (dis-)similarity could be represented, and which psychoacoustic, and other parameters, played a role in the representation. Moreover, the degree towhich individuals corresponded in their judgments was assessed. An experimental set-up for automated stimulus presentation and response collection was developed and implemented, and data were collected on 79subjects. The analysis revealed a three-dimensional solution; using linear regression, these three dimensions could be associated with instrumental measures of loudness (RSQ = .83) and sharpness (RSQ = .83), and with the subjectively measured unpleasantness (RSQ = .69). Further results indicate that the subjects employed largely the same criteria for their judgments. (Center contract)