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In this paper, we introduce a new anthropometric-based method for customizing of Head-Related Transfer Functions (HRTF) in the horizontal plane. The method uses Isomap, artificial neural networks (ANN), and a neighborhood-based reconstruction procedure. We first modify Isomap's graph construction step to emphasize the individuality of HRTFs and perform a(More)
We present a new anthropometry-based method to personalize head-related transfer functions (HRTFs) using manifold learning in both azimuth and elevation angles with a single nonlinear regression model. The core element of our approach is a domain-specific nonlinear dimensionality reduction technique, denominated Isomap, over the intraconic component of(More)
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