HRTF personalization using anthropometric measurements

Abstract

Individualized head related transfer functions (HRTFs) are needed for accurate rendering of spatial audio, which is important in many applications. Since these are relatively tedious to acquire, they may not be acceptable for some applications. A number of studies have sought to perform simple customization of the HRTF. We propose and test a strategy for HRTF personalization, based on matching certain anthropometric ear parameters with the HRTF database, and the incorporation of a low-frequency "head-and-torso" model. We present preliminary tests aimed at evaluation of this customization. Results show that the approach improves both the accuracy of the localization and subjective perception of the virtual auditory scene.