Localization and externalization in binaural reproduction with sparse HRTF measurement grids

Abstract

High-quality spatial sound reproduction is important for many applications of virtual and augmented reality. A key component in spatial audio reproduction is the head-related transfer function (HRTF). To achieve a realistic spatial audio experience, in terms of sound localization and externalization, high resolution individualized HRTFs are necessary. However, these are typically unavailable as they require specialized equipment and a large number of measurements, which motivates the use of sparsely measured HRTFs. Reducing the number of measurement points requires spatial interpolation, and may lead to spatial aliasing error. Previous studies suggested the use of spherical-harmonics (SH) decomposition for the interpolation. With a sparse grid, the SH representation is order-limited, leading to a constrained spatial resolution due to the truncation error. In this study, the effect of sparse measurement grids on the reproduced binaural signal is perceptually evaluated, through localization and externalization tests under varying conditions of aliasing and truncation. Preliminary results indicate relatively large effect of SH order on these attributes, while smaller effect is observed due to aliasing error.