On the forefront of realistic spatial audio is the personalization of binaural auditory input. Specifically, personalized head-related transfer functions (HRTFs) have been shown to improve the quality of binaural spatial audio over generic HRTFs. Here, we approached HRTF personalization from a morphological standpoint by calculating the distance between any two three-dimensional models of the ear. Subsequently, a ranking of ears based on the distances provided a similarity estimate. Using measured HRTFs of these ears, we tested how well listeners performed when localizing sounds in virtual space. We show that performance is closest to that of the individual HRTF when listeners used the best-ranked ear’s HRTF and furthest when listeners used the worst-ranked ear’s HRTF.

Authors: Warnecke, Michaela; Jamison, Sharon; Prepelita, Sebastian; Calamia, Paul; Ithapu, Vamsi Krishna
Affiliation: Reality Labs Research at Meta, Redmond, WA, USA
AES Conference: 2022 AES International Conference on Audio for Virtual and Augmented Reality (August 2022)
Paper Number: 43
Publication Date: August 15, 2022
Subject: Paper

Download Now (17.3 MB)

This paper is Open Access which means you can download it for free.

No AES members have commented on this paper yet.

Subscribe to this discussion

To be notified of new comments on this paper you can subscribe to this RSS feed. Forum users should login to see additional options.

Start a discussion!

If you would like to start a discussion about this paper and are an AES member then you can login here:
Username:
Password:

If you are not yet an AES member and have something important to say about this paper then we urge you to join the AES today and make your voice heard. You can join online today by clicking here.