其他摘要：Individualized head-related impulse responses (HRIRs) to perfectly suit a particular listener remains an open problem in the area of HRIRs modeling. We have modeled the whole range of magnitude of head-related transfer functions (HRTFs) in frequency domain via principal components analysis (PCA), where 37 persons were subjected to sound sources on median plane. We found that a linear combination of only 10 orthonormal basis functions was sufficient to satisfactorily model individual magnitude HRTFs. It was our goal to form multiple linear regressions (MLR) between weights of basis functions acquired from PCA and chosen partial anthropometric measurements in order to individualize a particular listener’s H RTFs with his or her own anthropometries. We proposed a novel individualization method based on MLR of weights of basis functions by employing only 8 out of 27 anthropometric measurements. The experiments’ results showed the proposed method, with mean error of 11.21%, outperformed our previous works on individualizing minimum phase HRIRs (mean error 22.50%) and magnitude HRTFs on horizontal plane (mean error 12.17%) as well as similar researches. The proposed individualization method showed that the individualized magnitude HRTFs could be well estimated as the original ones with a slight error. Thus the eight chosen anthropometric measurements showed their effectiveness in individualizing magnitude HRTFs particularly on median plane.
