A method for estimating sound source distance in dynamic
auditory „scenes‟ using binaural data is presented. The technique
requires little prior knowledge of the acoustic environment.
It consists of feature extraction for two dynamic distance
cues, motion parallax and acoustic τ, coupled with an inference
framework for distance estimation. Sequential and nonsequential
models are evaluated using simulated anechoic and
reverberant spaces. Sequential approaches based on particle
filtering more than half the distance estimation error in all conditions
relative to the non-sequential models. These results
confirm the value of active behaviour and probabilistic reasoning
in auditorily-inspired models of distance perception.