One of the various human sensory capabilities is to identify the direction
of perceived sounds. The goal of this work is to study sound source localization
in three dimensions using some of the most important cues the human uses.
Having robotics as a major application, the approach involves a compact
sensor structure that can be placed on a mobile platform. The objective
is to estimate the relative sound source position in three dimensional
space without imposing excessive restrictions on its spatio-temporal characteristics
and the environment structure. Two types of features are considered, interaural
time and level differences. Their relative effectiveness for localization
is studied, as well as a practical way of using these complementary parameters.
A two-stage procedure was used. In the training stage, sound samples are
produced from points with known coordinates and then are stored. In the
recognition stage, unknown sounds are processed by the trained system to
estimate the 3D location of the sound source. Results from the experiments
showed under 3 degrees in average angular error and less than 20% in average
radial distance error.
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1. Microphone array.
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J. Weng and K. Y. Guentchev, ``Three-dimensional
sound localization from a compact noncoplanar array of microphones using
tree-based learning,'' Journal of the Accostic Society of
America, vol. 110, no. 1, pp. 310 - 323, July 2001. Download PDF
file. K. Y. Guentchev and J. Weng, ``Learning-based
three-dimensional sound localization using a compact-coplanar array of
microphones,'' in Proc. 1998 AAAI Spring Symposium Series, Intelligent
Environments Symposium , Stanford University, March 23-25, 1998. Click
here
to down load the paper (PostScript).
To Weng's Home Page: http://web.cps.msu.edu/~weng/