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Insights into Head Related Transfer Function: Spatial Dimensionality and Continuous Representation
 

Summary: Insights into Head Related Transfer Function: Spatial Dimensionality
and Continuous Representation
Wen Zhang, Thushara D. Abhayapala, and Rodney A. Kennedy
Department of Information Engineering, Research School of Information Sciences and Engineering, College of
Engineering and Computer Science, The Australian National University, Canberra ACT 0200, Australiaa)
and Ramani Duraiswami
Perceptual Interfaces and Reality Laboratory, Institute for Advanced Computer Studies, University of Maryland,
College Park, Maryland 20742, United Statesb)
(Dated: Jan. 2010)
This paper studies HRTF sampling and synthesis in a three-dimensional auditory scene based on a
general modal decomposition of the HRTF in all frequency-range-angle domains. The main finding
is the HRTF decomposition with the derived spatial basis function modes can be well approximated
by a finite number, which is defined as the spatial dimensionality of the HRTF. The dimension-
ality determines the minimum number of parameters to represent the HRTF corresponding to all
directions and also the required spatial resolution in HRTF measurement. The general model is
further developed to a continuous HRTF representation, in which, the normalized spatial modes
can achieve HRTF near-field and far-field representations in one formulation. The remaining HRTF
spectral components are compactly represented using Fourier Spherical Bessel (FSB) series, where
the aim is to generate the HRTF with much higher spectral resolution in fewer parameters from
typical measurements which usually have limited spectral resolution constrained by sampling condi-

  

Source: Abhayapala, Thushara D. - Department of Information Engineering, Australian National University

 

Collections: Computer Technologies and Information Sciences