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A priori mesh grading for the numerical calculation of thehead-related transfer functions

机译:先验网格定级用于数值计算头部相关传递函数

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摘要

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 frequencyrange and outperformed uniform meshes in terms of numerical errors, perceptionbased predictions of sound-localization performance, and computationalcosts.
机译:头部相关传递函数(HRTF)描述了由听众的头部和耳廓形态引起的传入声音的定向过滤。如果存在准确的听众形态模型,则可以使用边界元素法(BEM)来数字计算HRTF。但是,一般建议对每个波长至少六个元素的头部和耳廓进行建模,这使得在计算整个可听频率范围的HRTF时,BEM成为一项耗时的过程。在这项研究中,提出了一种网格预处理算法,即先验网格分级,它可以显着降低HRTF计算过程中的计算成本。网格分级算法故意违反了在头部和耳廓的某些区域中每个波长至少六个元素的建议,并根据先验定义的分级功能逐渐改变了元素的大小。该算法的评估涉及为各种几何对象(包括三个人类听众的网格和各种分级函数)计算出的HRTF。分析了计算出的HRTF的数值准确性和预测的声音定位性能。先验网格分级似乎适合于在整个可听频率下对HRTF进行数值计算范围和表现均一的网格在数值误差,感知方面声音定位性能的基础预测和计算费用。

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