Title :
Kernel regression for Head-Related Transfer Function interpolation and spectral extrema extraction
Author :
Yuancheng Luo ; Zotkin, Dmitry N. ; Daume, Hal ; Duraiswami, Ramani
Author_Institution :
Dept. of Comput. Sci., Univ. of Maryland, College Park, MD, USA
Abstract :
Head-Related Transfer Function (HRTF) representation and interpolation is an important problem in spatial audio. We present a kernel regression method based on Gaussian process (GP) modeling of the joint spatial-frequency relationship between HRTF measurements and obtain a smooth non-linear representation based on data measured over both arbitrary and structured spherical measurement grids. This representation is further extended to the problem of extracting spectral extrema (notches and peaks). We perform HRTF interpolation and spectral extrema extraction using freely available CIPIC HRTF data. Experimental results are shown.
Keywords :
Gaussian processes; signal representation; transfer functions; Gaussian process modeling; Kernel regression; head-related transfer function interpolation; nonlinear representation; spatial audio; spectral extrema extraction; Frequency measurement; Ground penetrating radar; Harmonic analysis; Interpolation; Joints; Noise; Transfer functions; Gaussian Process Regression; Head-Related Transfer Function; Interpolation; Spectral Extrema;
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on
Conference_Location :
Vancouver, BC
DOI :
10.1109/ICASSP.2013.6637648
