Abstract
As one of the core technologies to generate a three-dimensional (3D) virtual sound, Head-Related Transfer Function (HRTF) can be appropriately estimated using a listeneraŕs physical features. In this paper, a weighted correlation method (WCM) was proposed to identify key anthropometric measurements (KAMs) for HRTF individualization. Then, local KAMs (dependent on positions) and global KAMs (independent of positions) were identified by this method. An objective evaluation tool, spectral distortion (SD), was used to evaluate the HRTF estimation errors. No significant differences of SDs when using local and global KAMs were found. They could satisfy rough sound localization at almost all sampled positions. The global KAMs cover measurements of pinna, head, and torso. Compared with using average HRTFs, the SDs when using local and global KAMs could be averagely reduced by 9.4% and 9.7% respectively. The reduction of SD scores is significant at most of the positions of interest (p < 0.05).
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