This work aims at deriving a minimum required resolution for optimization of head-related transfer functions (HRTFs). It builds on existing metrics, used to numerically evaluate HRTF differences, as well as on a model estimating just noticeable differences (JNDs) for uni-lateral variation of HRTFs. Integrating this model, as well as descriptors for both monaural and binaural cue differences, a three-alternative forced choice experiment is set up to investigate JNDs for bi-lateral variation of HRTF sets. Rather than introducing manual changes to the spectra, an exchange between magnitude spectra of generic HRTF sets is employed, while controlling for multiple conditions related to the descriptors. The probability of distinguishing between the stimulus pairs is linearly modeled using different subsets of numerical descriptors. A model integrating two monaural descriptors, ‘issd’ and ‘mfcd’, achieves the best performance, compared to the rest. It shows a tendency for slight improvement when combined with an estimate of the detectability of changes in interaural cross-correlation.

Authors: Doma, Shaimaa; Fels, Janina
Affiliations: RWTH, Aachen University, Germany; RWTH, Aachen University, Germany(See document for exact affiliation information.)
AES Convention: 154 (May 2023) Paper Number: 10654
Publication Date: May 13, 2023
Subject: HRTFs

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