A localization model to localize multiple sources using Bayesian inference

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Authors
Dunham, M. Joshua Rolv
Issue Date
2014-08
Type
Electronic thesis
Thesis
Language
ENG
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Architectural sciences
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Abstract
Accurate localization of a sound source in a room setting is important in both psychoacoustics and architectural acoustics. Binaural models have been proposed to explain how the brain processes and utilizes the interaural time differences (ITDs) and interaural level differences (ILDs) of sound waves arriving at the ears of a listener in determining source location. Recent work shows that applying Bayesian methods to this problem is proving fruitful. In this thesis, pink noise samples are convolved with head-related transfer functions (HRTFs) and compared to combinations of one and two anechoic speech signals convolved with different HRTFs or binaural room impulse responses (BRIRs) to simulate room positions. Through exhaustive calculation of Bayesian posterior probabilities and using a maximal likelihood approach, model selection will determine the number of sources present, and parameter estimation will result in azimuthal direction of the source(s).
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August 2014
School of Architecture
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Rensselaer Polytechnic Institute, Troy, NY
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