Learning to judge distance of nearby sounds in reverberant and anechoic environments

pantgrievousAI and Robotics

Nov 30, 2013 (4 years and 7 months ago)


Learning to judge distance of nearby sounds in
reverberant and anechoic environments

Norbert Kop
Matt Schoolmaster
, and Barbara Shinn

Hearing Research Center, Boston University, Boston, MA, USA

Dept. of Cybernetics & AI, Technical Uni
, Košice, Slovakia

Previous studies have shown that accuracy of distance judgments for nearby sources
improves over time when the listener is in a reverberant environment, but not in an
anechoic space. The improvement observed in rooms may be the r
esult of the listener
learning (through experience) how to interpret reverberation cues and map these cues to
different distances in a particular room. The present study evaluates whether such “room
learning” is disrupted when reverberation cues vary over
the course of the experiment.
Results of two auditory distance perception experiments are reported. In the first study,
perceived distance was measured for listeners whose position in a real room was varied
from session to session. In the second study, dis
tance perception was studied using virtual
auditory space (VAS) techniques to simulate sounds for different listener locations in a
reverberant room and in anechoic space. In the real room, listeners appeared to get better
at judging source distance despi
te the fact that their location in the room varied from
session to session. However, in the VAS study, intermingling sounds simulated in a room
with sounds simulated in anechoic space led to a dramatic reduction in performance
overall as well as a reductio
n in the amount of improvement observed with experience. In
the limit, when the simulated room was varied on a trial
trial basis, no learning was
observed. These results suggest that listeners can generalize “room learning” across
different listener locations within a single room, but not across dramatically different
acoustic environments.