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dc.contributor.authorJin, Craig
dc.date.accessioned2006-12-18
dc.date.available2006-12-18
dc.date.issued2001-06-01
dc.identifier.urihttp://hdl.handle.net/2123/1342
dc.description.abstractThis dissertation provides an overview of my research over the last five years into the spectral analysis involved in human sound localization. The work involved conducting psychophysical tests of human auditory localization performance and then applying analytical techniques to analyze and explain the data. It is a fundamental thesis of this work that human auditory localization response directions are primarily driven by the auditory localization cues associated with the acoustic filtering properties of the external auditory periphery, i.e., the head, torso, shoulder, neck, and external ears. This work can be considered as composed of three parts. In the first part of this work, I compared the auditory localization performance of a human subject and a time-delay neural network model under three sound conditions: broadband, high-pass, and low-pass. A “black-box” modeling paradigm was applied. The modeling results indicated that training the network to localize sounds of varying center-frequency and bandwidth could degrade localization performance results in a manner demonstrating some similarity to human auditory localization performance. As the data collected during the network modeling showed that humans demonstrate striking localization errors when tested using bandlimited sound stimuli, the second part of this work focused on human sound localization of bandpass filtered noise stimuli. Localization data was collected from 5 subjects and for 7 sound conditions: 300 Hz to 5 kHz, 300 Hz to 7 kHz, 300 Hz to 10 kHz, 300 Hz to 14 kHz, 3 to 8 kHz, 4 to 9 kHz, and 7 to 14 kHz. The localization results were analyzed using the method of cue similarity indices developed by Middlebrooks (1992). The data indicated that the energy level in relatively wide frequency bands could be driving the localization response directions, just as in Butler’s covert peak area model (see Butler and Musicant, 1993). The question was then raised as to whether the energy levels in the various frequency bands, as described above, are most likely analyzed by the human auditory localization system on a monaural or an interaural basis. In the third part of this work, an experiment was conducted using virtual auditory space sound stimuli in which the monaural spectral cues for auditory localization were disrupted, but the interaural spectral difference cue was preserved. The results from this work showed that the human auditory localization system relies primarily on a monaural analysis of spectral shape information for its discrimination of directions on the cone of confusion. The work described in the three parts lead to the suggestion that a spectral contrast model based on overlapping frequency bands of varying bandwidth and perhaps multiple frequency scales can provide a reasonable algorithm for explaining much of the current psychophysical and neurophysiological data related to human auditory localization.en
dc.format.extent13853351 bytes
dc.format.extent13830558 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypeapplication/pdf
dc.language.isoen_AU
dc.rightsThe author retains copyright of this thesis
dc.rights.urihttp://www.library.usyd.edu.au/copyright.html
dc.subjecthuman sound localizationen
dc.subjectspectral analysisen
dc.subjecthead related transfer functionsen
dc.subjectvirtual auditory spaceen
dc.titleSpectral analysis and resolving spatial ambiguities in human sound localizationen
dc.typeThesisen
dc.date.valid2001-01-01en
dc.type.thesisDoctor of Philosophyen
usyd.facultyFaculty of Engineering and Information Technologies, School of Electrical and Information Engineeringen
usyd.degreeDoctor of Philosophy Ph.D.en
usyd.awardinginstThe University of Sydneyen


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