Noise Reduction in the Time Domain using Joint Diagonalization

Sidsel Marie Nørholm, Jacob Benesty, Jesper Rindom Jensen, Mads Græsbøll Christensen

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Abstract

A new filter design based on joint diagonalization of the clean
speech and noise covariance matrices is proposed. First, an
estimate of the noise is found by filtering the observed signal.
The filter for this is generated by a weighted sum of the eigenvectors
from the joint diagonalization. Second, an estimate of
the desired signal is found by subtraction of the noise estimate
from the observed signal. The filter can be designed to
obtain a desired trade-off between noise reduction and signal
distortion, depending on the number of eigenvectors included
in the filter design. This is explored through simulations using
a speech signal corrupted by car noise, and the results confirm
that the output signal-to-noise ratio and speech distortion index
both increase when more eigenvectors are included in the
filter design.
OriginalsprogEngelsk
Titel2014 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
ForlagIEEE
Publikationsdato2014
Sider7058-7062
ISBN (Trykt)978-1-4799-2892-7, 9781479928941
DOI
StatusUdgivet - 2014
Begivenhed2014 IEEE International Conference on Acoustics, Speech and Signal Processing - Firenze, Italien
Varighed: 4 maj 20149 maj 2014
Konferencens nummer: 18874

Konference

Konference2014 IEEE International Conference on Acoustics, Speech and Signal Processing
Nummer18874
Land/OmrådeItalien
ByFirenze
Periode04/05/201409/05/2014

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