Anthropometric-based customization of head-related transfer functions using Isomap in the horizontal plane

Felipe Grijalva, Luiz Martini, Siome Goldenstein, and Dinei Florencio

Abstract

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 emphasizes the individuality of HRTFs and perform a customized nonlinear dimensionality reduction of the HTRFs. We then use an ANN to model the nonlinear relationship between anthropometric features and our low-dimensional HRTFs. Finally, we use a neighborhood-based reconstruction approach to reconstruct the HRTF from the estimated low-dimensional version. Simulations show that our approach performs better than PCA and confirm that Isomap is capable of discovering the underlying nonlinear relationships of sound perception.

Details

Publication typeInproceedings
Published inICASSP'14
PublisherIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
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