Abstract
A novel computational model of localization has been implemented. Using a simplified model of the cochlea filter bank, maximum-likelihood estimates of azimuth and elevation are formed from interaural intensity and phase differences at energy onsets in multiple critical bands. Preliminary results show that the model is capable of resolving front/back confusions and other elevation ambiguities resulting from the ‘‘cones of confusion.’’ The onset sampling strategy is intended to model psychoacoustic phenomena such as the precedence effect and allows the model to deal with multiple sound sources and reverberant environments. Examples of the model’s ability to resolve ambiguous signals will be presented and compared with human performance. [Work supported by NSF.]
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