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This research focuses on sound localization experiments in which subjects report the position of an active sound source by turning toward it. A statistical framework for the analysis of the data is presented together with a case study from a large-scale listening experiment. The statistical framework is based on a model that is robust to the presence of front/back confusions and random errors. Closed-form natural estimators are derived, and one-sample and two-sample statistical tests are described. The framework is used to analyze the data of an auralized experiment undertaken by nearly nine hundred subjects. The objective was to explore localization performance in the horizontal plane in an informal setting and with little training, which are conditions that are similar to those typically encountered in consumer applications of binaural audio. Results show that responses had a rightward bias and that speech was harder to localize than percussion sounds, which are results consistent with the literature. Results also show that it was harder to localize sound in a simulated room with a high ceiling despite having a higher direct-to-reverberant ratio than other simulated rooms.
Sena, Enzo De; Brookes, Mike; Naylor, Patrick A.; Waterschoot, Toon van
Affiliations: University of Surrey, Institute of Sound Recording, Guildford, UK; Imperial College London, Electrical and Electronic Engineering Department, Communications and Signal Processing Group, London, UK; KU Leuven, Dept. of Electrical Engineering (ESAT-STADIUS/ETC), Leuven, Belgium(See document for exact affiliation information.)
JAES Volume 65 Issue 12 pp. 982-996; December 2017
Publication Date: December 22, 2017
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