Year: 2023
Type: article
Abstract: This work proposes a parametric model for just noticeable differences of unilateral differences in head-related transfer functions (HRTFs).For seven generic magnitude-based distance metrics, common trends in their response to inter-individual and intra-individual HRTF differences are analyzed, identifying metric subgroups with pseudo-orthogonal behavior.On the basis of three representative metrics, a three-alternative forced-choice experiment is conducted, and the acquired discrimination probabilities are set in relation with distance metrics via different modeling approaches.A linear model, with coefficients based on principal component analysis and three distance metrics as input, yields the best performance, compared to a simple multi-linear regression approach or to principal component analysis-based models of higher complexity.
Authors: Shaimaa Doma, Cosima A. Ermert, Janina Fels
Language: English
Topic: Speech and Audio Processing
Subfield: Signal Processing
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
Funder: Deutsche Forschungsgemeinschaft
OpenAlex ID: W4366332804