Head-related transfer function interpolation through multivariate polynomial fitting of principal component weights

Acoustical Science and Technology

Zhe Chen¹  Lin Wang¹  Fuliang Yin¹ 

[1] School of Electronic and Information Engineering, Dalian University of Technology

关键词: Head-related transfer function;    Interpolation;    Principal component analysis;    Multivariate polynomial fitting;   

DOI  :  10.1250/ast.30.395

学科分类：声学和超声波

来源: Acoustical Society of Japan

【 摘 要 】

References(17)Cited-By(2)Head-related transfer function (HRTF) interpolation plays an important role for implementation of 3D sound system because it can not only reduce the number of measurements for HRTFs, but also reduce the data of HRTFs for seamless binaural synthesis. This paper addresses the problem of accurately realizing the interpolation of HRTF for synthesis of virtual auditory space, and proposes a HRTF interpolation method based on principal component analysis. Firstly, the HRTF is decomposed into principal components and corresponding principal component weights, where principal components are direction-independent and principal component weights are direction-dependent; then the directional variation of the principal component weight is multivariate polynomial fitted with a bivariate function of two spatial angulus (azimuth and elevation). Moreover, a sphere-partitioning optimization scheme is employed to improve the approximation precision. Experiment results demonstrate that HRTFs in the entire sphere surface can be interpolated by the proposed method with small distortion, and the proposed method performs better than conventional methods. Therefore the proposed method gives a promising way for HRTF interpolation.

【 授权许可】

Unknown