In this study, we investigated the influence of specific generalized HRTF data on auditory localization in the context of augmented reality (AR). The localization training performance was compared over two weeks between two groups, each of which had received training using a different set of generalized HRTF data. The post-training results showed that training was more effective with one specific HRTF set. In particular, this HRTF set led to better performance in two following aspects: (1) its higher scores in the pre-training test enabling the first-time participants to be more accurate, and (2) its consistency over the entire training period, which demonstrates that the adaptation acquired with this particular set was easier to generalize in a more stable way.

Authors: Kim, Sungyoung; Chon, Song Hui; Okumura, Hiraku; Sakamoto, Shuichi
Affiliations: Rochester Institute of Technology; Belmont University; Yamaha Corporation; Tohoku University(See document for exact affiliation information.)
AES Convention: 148 (May 2020) Paper Number: 10379
Publication Date: May 28, 2020 Import into BibTeX
Subject: Perception
Permalink: https://www.aes.org/e-lib/browse.cfm?elib=20796

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