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Headphone Virtualization: Improved Localization and Externalization of Non-Individualized HRTFs by Cluster Analysis

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Research and experimentation is described that aims to prove the hypothesis that by allowing a listener to choose a single non-individualized profile of HRTFs from a subset of maximally different best representative profiles extracted from a database improved localization, and externalization can be achieved for the listener. k-means cluster analysis of entire impulse responses is used to identify the subset of profiles. Experimentation in a controlled environment shows that test subjects who were offered a choice of a preferred HRTF profile were able to consistently discriminate between a front center or rear center virtualized sound source 78.6% of the time, compared with 64.3% in a second group given an arbitrary HRTF profile. Similar results were obtained from virtualizations in uncontrolled environments.

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Permalink: http://www.aes.org/e-lib/browse.cfm?elib=16499

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