The effectiveness of binaural reproductions depends on the accuracy of those spatialization cues that are unique to an individual’s personal physiology. These cues are embedded in the Head-Related Transfer Functions (HRTFs), which guide sound from a given source direction to a listener’s ears. This report discusses the design and evaluation of a HRTF database matching system that pairs users to premeasured HRTF sets created from a sparse set of individualized acoustic measurements. The utilized spatial grid, which was derived from an LDA classifier, consisted of 68 filters nonuniformly distributed across 5 elevations from -30° and +30°. A binaural localization study confirmed the original hypothesis that the similarity between subsets of binaural filters can be generalized to represent the relationship of the HRTFs of origin. Analysis of the participant responses provided strong evidence that HRTF database matching is useful. The designed implementation was successful in providing users with alternative HRTF datasets when the similarity of the matched data to the search query was above a certain similarity threshold. It was also shown that low-similarity HRTFs can lead to decreased spatial localization accuracy.
本文讨论了一种用于稀疏测量头部相关传递函数的数据库匹配方法。这个方法用精心选择的测试程序将数据采集时间减至最少，同时通过从已有知识库中为用户提供最佳拟合的稠密测量HRTFs来保证空间精度。我们用线性判别分析来选定稀疏声学测量的坐标，以最具区分性的方式来展现与众不同的空间特性。稀疏测量头部相关传递函数子集由从-30度到30度的5个仰角经不均匀取样的68个位置测量而得。所设计的数据库匹配系统通过双耳定位研究来评估。结果证明，只要测量和匹配数据之间的客观相似性高于目标门限，这个系统在对预先测得了HRTFs的用户进行匹配上是成功的。
https://www.aes.org/e-lib/browse.cfm?elib=19171
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