Comparing training effects associated with two sets of HRTF data on auditory localization performance

Sungyoung Kim, Song Hui Chon, Hiraku Okumura, Shuichi Sakamoto

Research output: Contribution to conferencePaperpeer-review

Abstract

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.

Original languageEnglish
Publication statusPublished - 2020
Event148th Audio Engineering Society International Convention 2020 - Vienna, Virtual, Online, Austria
Duration: 2020 Jun 22020 Jun 5

Conference

Conference148th Audio Engineering Society International Convention 2020
CountryAustria
CityVienna, Virtual, Online
Period20/6/220/6/5

ASJC Scopus subject areas

  • Modelling and Simulation
  • Acoustics and Ultrasonics

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