Compressing Head-Related Transfer Function databases by Eigen decomposition

Camilo Arévalo, J. Villegas
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引用次数: 3

Abstract

A method to reduce the memory footprint of Head- Related Transfer Functions (HRTFs) is introduced. Based on an Eigen decomposition of HRTFs, the proposed method is capable of reducing a database comprising 6,344 measurements from 36.30 MB to 2.41MB (about a 15:1 compression ratio). Synthetic HRTFs in the compressed database were set to have less than 1dB spectral distortion between 0.1 and 16 kHz. The differences between the compressed measurements with those in the original database do not seem to translate into degradation of perceptual location accuracy. The high degree of compression obtained with this method allows the inclusion of interpolated HRTFs in databases for easing the real-time audio spatialization in Virtual Reality (VR).
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基于特征分解的头部相关传递函数数据库压缩
介绍了一种减少头部相关传递函数(hrtf)内存占用的方法。基于hrtf的特征分解,该方法能够将包含6344个测量值的数据库从36.30 MB减少到2.41MB(约15:1的压缩比)。将压缩数据库中的合成hrtf设置为在0.1和16 kHz之间具有小于1dB的频谱失真。压缩测量值与原始数据库中的测量值之间的差异似乎不会转化为感知定位精度的降低。该方法获得的高压缩度允许在数据库中包含插值的hrtf,以缓解虚拟现实(VR)中的实时音频空间化。
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