Ziegelwanger Harald, Kreuzer Wolfgang, Majdak Piotr
AIT Austrian Institute of Technology GmbH, Mobility Department, Transportation Infrastructure Technologies, Giefinggasse 2, 1210 Vienna, Austria; Acoustics Research Institute, Austrian Academy of Sciences, Wohllebengasse 12-14, Vienna 1040, Austria.
Acoustics Research Institute, Austrian Academy of Sciences, Wohllebengasse 12-14, Vienna 1040, Austria.
Appl Acoust. 2016 Dec 15;114:99-110. doi: 10.1016/j.apacoust.2016.07.005.
Head-related transfer functions (HRTFs) describe the directional filtering of the incoming sound caused by the morphology of a listener's head and pinnae. When an accurate model of a listener's morphology exists, HRTFs can be calculated numerically with the boundary element method (BEM). However, the general recommendation to model the head and pinnae with at least six elements per wavelength renders the BEM as a time-consuming procedure when calculating HRTFs for the full audible frequency range. In this study, a mesh preprocessing algorithm is proposed, viz., a priori mesh grading, which reduces the computational costs in the HRTF calculation process significantly. The mesh grading algorithm deliberately violates the recommendation of at least six elements per wavelength in certain regions of the head and pinnae and varies the size of elements gradually according to an a priori defined grading function. The evaluation of the algorithm involved HRTFs calculated for various geometric objects including meshes of three human listeners and various grading functions. The numerical accuracy and the predicted sound-localization performance of calculated HRTFs were analyzed. A-priori mesh grading appeared to be suitable for the numerical calculation of HRTFs in the full audible frequency range and outperformed uniform meshes in terms of numerical errors, perception based predictions of sound-localization performance, and computational costs.
头部相关传递函数（HRTFs）描述了由听者头部和耳廓形态引起的传入声音的方向滤波。当存在听者形态的精确模型时，可以使用边界元法（BEM）通过数值计算得出HRTFs。然而，一般建议在每个波长至少用六个单元对头部和耳廓进行建模，这使得在计算全可听频率范围内的HRTFs时，BEM成为一个耗时的过程。在本研究中，提出了一种网格预处理算法，即先验网格分级，它显著降低了HRTF计算过程中的计算成本。网格分级算法在头部和耳廓的某些区域故意违反每个波长至少六个单元的建议，并根据先验定义的分级函数逐渐改变单元大小。该算法的评估涉及为各种几何对象计算的HRTFs，包括三个听众的网格和各种分级函数。分析了计算出的HRTFs的数值精度和预测的声音定位性能。先验网格分级似乎适用于全可听频率范围内HRTFs的数值计算，并且在数值误差、基于感知的声音定位性能预测和计算成本方面优于均匀网格。
