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Abstract:
This paper examines the role of biological constraints in the
human auditory localization process. A psychophysical and neural
system modeling approach was undertaken in which performance
comparisons between competing models and the human subject provided
the foundation for understanding the relevant biologically
plausible"realism constraints". The directional acoustical cues,
upon which sound localization is based, were derived from the human
subject's head-related transfer functions (HRTFs). Sound stimuli
were generated by convolving bandpass noise with the HRTFs and were
presented to both the subject and the model. The input stimuli to
the model was processed using the Auditory Image Model of cochlear
processing. The cochlear data was then analyzed by a time-delay
neural network which integrated temporal and spectral information
to determine the spatial location of the sound source. The combined
cochlear model and neural network provided a system model of the
sound localization process in which measurable human-like
localization performance was achieved in relationship to frequency
division or tonotopicity, sound level variations, band-pass sounds
with restricted frequencies, and "natural" listening conditions
with variable training sounds.
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