TY - JOUR
T1 - Towards optimal functional representation of head-related transfer functions in the horizontal plane
AU - Zhang, Wen
AU - Abhayapala, Thushara D.
AU - Kennedy, Rodney A.
AU - Zhang, Mengqiu
PY - 2013
Y1 - 2013
N2 - Head-related transfer function (HRTF) individualization using principle component analysis (PCA) modelling rely on the empirical data to reduce HRTF dimensionality for an optimal representation and to achieve HRTF personalization by tuning the model weights with the subject anthropometric parameters. However, for these representations, the basis is discrete and data dependent which can limit its usefulness in universal HRTF representation. This paper studies the optimal functional representation of magnitude HRTF of 45 subjects for sound sources in the horizontal plane. We firstly use circular harmonics to extract the subject-independent HRTF angular dependence. The remaining spectral components of 45 subjects are then modelled by PCA and two standard functions, i.e., Fourier series and Fourier Bessel series. The metric to evaluate the model efficiency is the expansion weights cumulative variance. We identify that individual magnitude HRTFs over 20 kHz range could be modelled adequately well by a linear combination of only 19 Fourier Bessel series; this is a near optimal representation in comparison with the statistical PCA model. Further analysis of the model weights with subjective anthropometric measurements will provide a promising method for HRTF individualization, especially considering the nature of data independent continuous basis functions employed in the proposed functional representation.
AB - Head-related transfer function (HRTF) individualization using principle component analysis (PCA) modelling rely on the empirical data to reduce HRTF dimensionality for an optimal representation and to achieve HRTF personalization by tuning the model weights with the subject anthropometric parameters. However, for these representations, the basis is discrete and data dependent which can limit its usefulness in universal HRTF representation. This paper studies the optimal functional representation of magnitude HRTF of 45 subjects for sound sources in the horizontal plane. We firstly use circular harmonics to extract the subject-independent HRTF angular dependence. The remaining spectral components of 45 subjects are then modelled by PCA and two standard functions, i.e., Fourier series and Fourier Bessel series. The metric to evaluate the model efficiency is the expansion weights cumulative variance. We identify that individual magnitude HRTFs over 20 kHz range could be modelled adequately well by a linear combination of only 19 Fourier Bessel series; this is a near optimal representation in comparison with the statistical PCA model. Further analysis of the model weights with subjective anthropometric measurements will provide a promising method for HRTF individualization, especially considering the nature of data independent continuous basis functions employed in the proposed functional representation.
UR - http://www.scopus.com/inward/record.url?scp=84878981673&partnerID=8YFLogxK
U2 - 10.1121/1.4799560
DO - 10.1121/1.4799560
M3 - Conference article
AN - SCOPUS:84878981673
SN - 1939-800X
VL - 19
JO - Proceedings of Meetings on Acoustics
JF - Proceedings of Meetings on Acoustics
M1 - 050012
T2 - 21st International Congress on Acoustics, ICA 2013 - 165th Meeting of the Acoustical Society of America
Y2 - 2 June 2013 through 7 June 2013
ER -