E. S. Schwenker and G. D. Romigh, “An Evolutionary Algorithm Approach to Customization of Non-Individualized Head Related Transfer Functions,” in Proc. AES Convention 137, Oct. 2014, Paper 9153. [Online]. Available: https://aes.org/publications/elibrary-page/?id=17476
Schwenker ES, Romigh GD. An Evolutionary Algorithm Approach to Customization of Non-Individualized Head Related Transfer Functions. In: AES Convention 137. Audio Engineering Society; 2014. Paper 9153. Available from: https://aes.org/publications/elibrary-page/?id=17476
@inproceedings{Schwenker2014_17476,
author = {Schwenker, Eric S. and Romigh, Griffin D.},
title = {{An Evolutionary Algorithm Approach to Customization of Non-Individualized Head Related Transfer Functions}},
booktitle = {AES Convention 137},
note = {Paper 9153},
year = {2014},
month = oct,
publisher = {Audio Engineering Society},
url = {https://aes.org/publications/elibrary-page/?id=17476}
}
TY - CPAPER
TI - An Evolutionary Algorithm Approach to Customization of Non-Individualized Head Related Transfer Functions
AU - Schwenker, Eric S.
AU - Romigh, Griffin D.
T2 - AES Convention 137
M1 - Paper 9153
PY - 2014
DA - 2014/10/06
UR - https://aes.org/publications/elibrary-page/?id=17476
PB - Audio Engineering Society
LA - en
AB - Currently, the commercialization of high-quality virtual auditory display technology is limited by the costly and time-consuming methods required for obtaining listener-specific head-related transfer functions (HRTFs), directionally-dependent filters that encode spatial information. As such, there is an increased interest in the estimation of individualized HRTFs based on non-acoustic data. This study highlights the capabilities of an evolutionary algorithm method applied to the complex parameter optimization problem that arises when HRTFs are fit to individuals (or populations), rather than acoustically measured. Results suggest the algorithm may be capable of providing HRTFs that improve localization through both personalization of generic HRTFs and the generation of an optimized set of generic HRTFs.
ER -