Compressing Head-Related Transfer Function databases by Eigen decomposition

Abstract

A method to reduce the memory footprint of Head- Related Transfer Functions (HRTFs) is introduced. Based on an Eigen decomposition of HRTFs, the proposed method is capable of reducing a database comprising 6,344 measurements from 36.30 MB to 2.41MB (about a 15:1 compression ratio). Synthetic HRTFs in the compressed database were set to have less than 1dB spectral distortion between 0.1 and 16 kHz. The differences between the compressed measurements with those in the original database do not seem to translate into degradation of perceptual location accuracy. The high degree of compression obtained with this method allows the inclusion of interpolated HRTFs in databases for easing the real-time audio spatialization in Virtual Reality (VR).