Optimally truncating head-related impulse response by dynamic programming with its applications

We propose a method to optimally truncate the head-related impulse responses (HRIRs) in this paper. The truncated HRIR consists of a portion of the original HRIR and a flat line. An algorithm based on dynamic programming is used to optimally select the portions of the original HRIRs and the constants of the flat lines to minimize the modeling errors. The truncated HRIRs can be used to reproduce multi-channel sound for headphones with a significantly lower computational cost. The proposed method is compared with another approximation method, the CAPZ (Common-Acoustical-Pole and Zero) approach. The experimental results show that the proposed method yields lower composition as well as modeling errors for the same amount of computation. Compared with the direct implementation, the proposed approach requires about 35 % of the computational cost while maintaining acceptable composition errors.

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