Two-Dimension Common Factor Decomposition of Head-Related Impulse Response

In this letter, a Two-Dimension Common Factor Decomposition (2D-CFD) algorithm is proposed to represent the 3D (time, azimuth and elevation) head-related impulse response (HRIR) dataset with two factorized matrices. One matrix is made up of a set of common factor responses extracted from HRIRs with the same azimuth angle and carries azimuthal information contained in original HRIR dataset. The other matrix carries elevation information similarly. By using this dimension reduction, the storage requirement of HRIRs is reduced remarkably. In addition, the common factor responses in the matrix are further modeled with efficient low order IIR filters to reduce the computation complexity in 3D sound synthesis.