Representation of Individual HRTFs Using Weighting Coefficients of SENZI

We have previously proposed a method to realize high-precision sensors of 3D sound-space information for transmission to distant places and for preservation of sound data for the future. This method is named SENZI designated as (Symmetrical object with Enchased Zillion microphones). By using this method, 3D sound-space information recorded at a certain place and time can be accurately reproduced at a distant place at any time after recording. Moreover, the reproduced sound field information can properly reflect the posture of the listener, which is very important for enhancement of the sense of presence. In this method, sound space is represented by a summation of weighting coefficients based on the head-related transfer functions (HRTFs) of a listener. In this study, the feasibility of representing individual HRTFs based on the preliminary characteristics of weighting coefficients given by the method was investigated. Moreover, we investigated the expression method to simplify the distribution of the weighting coefficients of SENZI based on spherical harmonics. The results of the simulation suggest that weighting coefficients have basic tendencies in the distributions of absolute values and phases and these distributions can be converted based on spherical harmonics.