A mixed-order modeling approach for head-related transfer function in the spherical harmonic domain

Abstract

Head-related transfer function (HRTF) contains all the relevant cues that humans rely on to perceive the direction of a sound source, and its modeling has been widely studied in the past years. Motivated by the different degree of fluctuations in HRTF magnitude spectrum across frequency, in this paper, a mixed-order modeling approach in the spherical harmonic domain is proposed in which HRTF magnitude spectrum with low fluctuation is modeled by the low-order spherical harmonics and that with high fluctuation is modeled by the high-order spherical harmonics. Furthermore, a data-driven optimization approach is presented to determine the transition frequency that separates HRTF magnitude spectrum into two ranges with different degrees of fluctuations. The effectiveness of the proposed mixed-order modeling approach is examined using FABIAN HRTF database through listening tests. Results show that this mixed-order modeling approach enables to reduce the order of spherical harmonics to 8 in the low frequencies and 18 in the high frequencies without perceptual degradation in sound quality and localization.