基于个体张量分解与模态的头相关传输函数重构

远场头相关传输函数(HRTF)随声源方向、频率以及个体变化。完整HRTF的数据量很大,且测量或计算每个人的高方向分辨率HRTF是很困难的。本文提出一种从少量方向的测量或计算重构高方向分辨率HRTF的方法。基于HRTF张量分解,远场HRTF可分解为方向模态、频率模态和少量个体模态的张量组合。通过对已有的基线HRTF数据库进行统计分析,可得到与个体无关的方向模态矩阵和频率模态矩阵。而对于任何新的个体,只要少量方向的测量或计算HRTF即可估计出个体模态的变化,并重构出高方向分辨率的HRTF数据。对两个HRTF数据库的计算表明,采用11个个体模态即可表示超过98%的个体相关的HRTF能量变化,并从大约30个方向的测量或计算HRTF重构出高方向分辨率的HRTF幅度。心理声学实验验证了提出的方法。该方法可用于简化个性化HRTF的测量或计算。

Reconstruction head-related transfer function from individualized

Far-field Head-Related Transfer Functions (HRTFs) vary with source direction, frequency and individual. Correspondingly, the dimensionality of a full set of HRTFs is huge and measurement or calculation of individualized HRTFs with high directional resolution could be difficult. A method to construct HRTFs with high directional resolution from a small set of directional measurements or calculations is proposed in present paper. Based on tensor decomposition of HRTFs, far-field HRTFs are decomposed into a combination of directional modes, frequency modes and a few of individual modes. The individual-independent matrices of directional modes and frequency modes are derived by statistical analysis on a known base-line HRTF database. For arbitrary new individual, the individual mode can be estimated from measured or calculated HRTFs at a small set of directions, then the HRTFs with high directional resolution are reconstructed. Calculation from two base-line HRTF databases indicates that 11 individual modes account for more than 98% individual-related energy variation of HRTFs; and HRTFs with high directional resolution can be reconstructed from about 30 directional measurements or calculation. A psychoacoustic experiment validates the analysis. The present method is applicable to simplify individualized HRTF measurement or calculation.