Constraints on computational models of auditory scene analysis, as derived from human perception.

Abstract

Auditory scene analysis (ASA) groups the sensory evidence derived from a mixture of sound sources and derives separate descriptions of the individual sources. There are two possible ways of doing this:(a) using knowledge of the properties of certain classes of sounds, such as speech, in a top-down fashion;(b) using, in a bottom-up manner, those properties in the input (such as harmonic relations) that are typically found when two or more sound sources (e.g., voice and footsteps) affect the input at the same time. Some properties of the ASA done by humans are discussed and proposed as specifications for a computational model: the adding up of evidence, the coherence of the ASA system, the combining of top-down and bottom-up constraints, as illustrated in the duplex perception of speech, and the propagation of influences across the auditory field.