Sixth International Conference on Spoken Language Processing
October 16-20, 2000
Dominant Subspace Analysis for Auditory Spectrum
Xugang Lu, Gang Li, Lipo Wang
Nanyang Technological University , School of EEE, Workstation Resource Lab,
In hearing perception theory, spectral structure is a most
important feature for speech perception, this spectral
structure is not easy to be masked in noisy condition. So
if this structure is extracted and enhanced, the
representation will be much more robust. In this paper,
we propose a new statistical dominant subspace analysis
method for auditory spectrum based on SVD(Singular
Values Decomposition) and signal subspace analysis
method. The auditory spectrum can be decomposed into
two subspaces, one is a dominant subspace, which is
expanded by useful speech auditory spectrum , another
subspace is sub-dominant subspace, which there is only
noise information. So we analyze the auditory spectrum
in the dominant subspace, the SNR will be increased.
Thus this representation is much more robust.
Lu, Xugang / Li, Gang / Wang, Lipo (2000):
"Dominant subspace analysis for auditory spectrum",
In ICSLP-2000, vol.3, 59-62.