Quantifying Localization Potential using Interaural Transfer Function

Mathew JD, Januszkiewicz L, Pensko M, Hertensteiner M, Audfray R. Quantifying Localization Potential using Interaural Transfer Function. In: AES Convention 151. Audio Engineering Society; 2021. Paper 648. Available from: https://aes.org/publications/elibrary-page/?id=21571

@inproceedings{Mathew2021_21571,
  author = {Mathew, Justin D and Januszkiewicz, Lukasz and Pensko, Maria and Hertensteiner, Mark and Audfray, Rémi},
  title = {{Quantifying Localization Potential using Interaural Transfer Function}},
  booktitle = {AES Convention 151},
  note = {Paper 648},
  year = {2021},
  month = oct,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=21571}
}

TY  - CPAPER
TI  - Quantifying Localization Potential using Interaural Transfer Function
AU  - Mathew, Justin D
AU  - Januszkiewicz, Lukasz
AU  - Pensko, Maria
AU  - Hertensteiner, Mark
AU  - Audfray, Rémi
T2  - AES Convention 151
M1  - Paper 648
PY  - 2021
DA  - 2021/10/06
UR  - https://aes.org/publications/elibrary-page/?id=21571
PB  - Audio Engineering Society
LA  - en
AB  - The ability to generate appropriate auditory localization cues is an important requisite of spatial audio rendering technology that contributes to the plausibility of virtual sounds presented to a user, especially in XR applications (VR/AR/MR). Algorithmic approaches have been proposed to quantify such technologies’ ability to reproduce interaural level difference (ILD) cues through regression and statistical methods, providing a useful standardization and automation method to estimate the localization accuracy potential of a given spatial audio rendering engine. Previous approaches are extended to include interaural time difference (ITD) cues as part the perceptual transform through the use of the interaural transfer function (ITF). The extended algorithmic approach of quantifying localization accuracy may provide an adequate substitute for critical listening studies as an evaluation method. However, this approach has not yet been validated through comparison with localization listening studies. A review of listening tests are reviewed in conclusion to increase confidence in presented methods of algorithmically quantifying localization accuracy potential of a spatial audio rendering engine.
ER  -