Audio classification and localization for incongruent event detection

Abstract

A method is presented that detects unexpected acoustic events, i.e., occurrence of acoustic objects that do not belong to any of the learned classes but nevertheless appear to constitutemeaningful acoustic events. Building on the framework [Weinshall et al.], general and specific acoustic classifiers are implemented and combined for detection of events in which they respond in an incongruous way, indicating an unexpected event. Subsequent identification of events is performed by estimation of source direction, for which a novel classification-based approach is outlined. Performance, evaluated in dependence of signal-to-noise ratio (SNR) and type of unexpected event, indicates decent performance at SNRs better than 5 dB. © 2012 Springer-Verlag Berlin Heidelberg.