User selection of optimal HRTF sets via holistic comparative evaluation

Rishi Shukla, Rebecca Stewart, Agnieszka Roginska, Mark Sandler

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

If well-matched to a given listener, head-related transfer functions (HRTFs) that have not been individually measured can still present relatively effective auditory scenes compared to renderings from individualised HRTF sets. We present and assess a system for HRTF selection that relies on holistic judgements of users to identify their optimal match through a series of pairwise adversarial comparisons. The mechanism resulted in clear preference for a single HRTF set in a majority of cases. Where this did not occur, randomised selection between equally judged HRTFs did not significantly impact user performance in a subsequent listening task. This approach is shown to be equally effective for both novice and expert listeners in selecting their preferred HRTF set.

Original languageEnglish (US)
Title of host publicationAES International Conference on Audio for Virtual and Augmented Reality 2018
Subtitle of host publicationScience, Technology, Design, and Implementation
PublisherAudio Engineering Society
Pages155-164
Number of pages10
ISBN (Electronic)9781510870390
StatePublished - 2018
EventAES International Conference on Audio for Virtual and Augmented Reality: Science, Technology, Design, and Implementation, AVAR 2018 - Redmond, United States
Duration: Aug 20 2018Aug 22 2018

Publication series

NameProceedings of the AES International Conference
Volume2018-August

Other

OtherAES International Conference on Audio for Virtual and Augmented Reality: Science, Technology, Design, and Implementation, AVAR 2018
Country/TerritoryUnited States
CityRedmond
Period8/20/188/22/18

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Acoustics and Ultrasonics

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