Perceptual structure of everyday sounds: A multidimensional scaling approach

Abstract

The present study was designed to provide insight into the perceptual structure of everyday sounds. A large stimulus set of 74 sounds was used to gather sorting data, attribute ratings, and acoustic measurements for analysis using multidimensional scaling solutions (MDS). Correlations between and among the acoustic measurements and attribute ratings were as expected. The resulting MDS solution with regressed vectors for attribute ratings and acoustic measurements reveals a well-defined 3- dimensional perceptual structure for this stimulus set. Dimension 1 is defined by 5 perceptual attributes and 3 acoustic measures; Dimension 2 is explained by 1 perceptual attribute and 1 acoustic measure; and finally Dimension 3 is characterized by 3 perceptual attributes and 1 acoustic measurement. Information about perceptual structure can be used by researchers to increase basic knowledge about how people perceive the relationships among everyday sounds as well as by designers of virtual reality environments to assist in developing algorithms for realistic synthesized sounds.