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Estimation of individualized head-related transfer function based on principal component analysis

机译:基于主成分分析的个体化头部相关传递函数估计

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摘要

In binaural reproduction providing spatial sound by means of convolving sound sources and head-related transfer functions (HRTFs), it is important to approximate the listener’s own HRTFs with a high degree of accuracy. HRTF measurement, however, typically requires a great deal of labor, time, and expense. In this paper, a method for estimating such individualized HRTFs that uses principal component analysis (PCA) is introduced. In this method, the orthogonal bases of a set of HRTFs are computed and partially measured HRTFs are interpolated from the weighted sum of the bases. The validity of the method was verified in objective and subjective experiments in which the required approximation accuracy of HRTFs was evaluated.
机译:在通过卷积声源和与头部相关的传递函数(HRTF)来提供空间声音的双耳再现中,非常重要的一点是要以较高的准确度估算听众自己的HRTF。然而,HRTF测量通常需要大量的人工,时间和费用。本文介绍了一种使用主成分分析(PCA)估算此类个性化HRTF的方法。在此方法中,将计算一组HRTF的正交基,并从这些基的加权总和内插部分测得的HRTF。在客观和主观实验中验证了该方法的有效性,在该实验中评估了所需的HRTF近似精度。

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