Prioritizing foreground selection of natural chirp sounds by tempo and spectral centroid

Abstract

Salience shapes the involuntary perception of a sound scene into foreground and background. Auditory interfaces, such as those used in continuous process monitoring, rely on the prominence of those sounds that are perceived as foreground. We propose to distinguish between the salience of sound events and that of streams, and introduce a paradigm to study the latter using repetitive patterns of natural chirps. Since streams are the sound objects populating the auditory scene, we suggest the use of global descriptors of perceptual dimensions to predict their salience, and hence, the organization of the objects into foreground and background. However, there are many possible independent features that can be used to describe sounds. Based on the results of two experiments, we suggest a parsimonious interpretation of the rules guiding foreground formation: after loudness, tempo and brightness are the dimensions that have higher priority. Our data show that, under equal-loudness conditions, patterns with fast tempo and lower brightness tend to emerge and that the interaction between tempo and brightness in foreground selection seems to increase with task difficulty. We propose to use the relations we uncovered as the underpinnings for a computational model of foreground selection, and also, as design guidelines for stream-based sonification applications.