N2 - Principal components analysis (PCA) is frequently used for modelling the
magnitude of the head-related transfer functions (HRTFs). Assuming that
the HRTFs are minimum phase systems, the phase is obtained from the
Hilbert transform of the log-magnitude. In recent years, the PCA applied
to HRTFs is also used to model individual HRTFs relating the PCA weights
with anthropometric measurements of the head, torso and pinnae. The HRTF
log-magnitude is the most used format of input data to the PCA, but it has
been shown that if the input data is HRTF linear magnitude, the cumulative
variance converges faster, and the mean square error (MSE) is smaller.
This study demonstrates that PCA applied directly on HRTF complex values
is even better than the two formats mentioned above, that is, the MSE is
the smallest and the cumulative variance converges faster after the 8th
principal component. Different objective experiments around all the median
plane put in evidence the differences which, although small, seem to be
perceptually detectable. To elucidate this point, psychoacoustic
discrimination tests are done between measured and reconstructed HRTFs
from the three types of input data mentioned, in the median plane between
-45°. and +9°.
JO - Archives of Acoustics
L1 - http://rhis.czasopisma.pan.pl/Content/101474/PDF/05_paper.pdf
L2 - http://rhis.czasopisma.pan.pl/Content/101474
IS - No 4
EP - 482
KW - HRTF
KW - PCA
KW - binaural audition
KW - auditory perception
ER -
A1 - Ramos, Oscar Alberto
A1 - Tommasini, Fabián Carlos
PB - Committee on Acoustics PAS, PAS Institute of Fundamental Technological Research, Polish Acoustical Society
VL - vol. 39
JF - Archives of Acoustics
SP - 477
T1 - Magnitude Modelling of HRTF Using Principal Component Analysis Applied to Complex Values
UR - http://rhis.czasopisma.pan.pl/dlibra/docmetadata?id=101474
DOI - 10.2478/aoa-2014-0051