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@PHDTHESIS{Heese:674894,
author = {Heese, Florian},
othercontributors = {Vary, Peter and Martin, Rainer},
title = {{S}peech signal enhancement by information combining; 1.
{A}uflage},
volume = {44},
school = {RWTH Aachen University},
type = {Dissertation},
address = {Aachen},
publisher = {Wissenschaftsverlag Mainz},
reportid = {RWTH-2016-09678},
isbn = {978-3-95886-125-1},
series = {Aachener Beiträge zu digitalen Nachrichtensystemen},
pages = {1 Online-Ressource (x, 194 Seiten) : Illustrationen,
Diagramme},
year = {2016},
note = {Auch veröffentlicht auf dem Publikationsserver der RWTH
Aachen University; Dissertation, RWTH Aachen University,
2016},
abstract = {Mobile phones as well as tablets are omnipresent and belong
to everyday life. Today audiovisual communication takes
place at different locations and in a large variety of
acoustic environments. In consequence, the intelligibility
as well as the quality of speech may significantly be
degraded by ambient background noise. In order to improve
speech intelligibility and to ensure a convenient
communication with high audio quality, speech enhancement
techniques are required. In this thesis all critical
components contributing to the enhancement of the up-link
signal are addressed: • signal capturing at the acoustic
front-end with a new near field beam former, • new
codebook based speech and noise estimation procedure
generating and exploiting reliability information, and •
actual noise reduction exploiting spectral dependencies of
human speech. For the acoustic front-end of the digital
processing chain a novel concept for the filter optimization
of a near field beamformer is introduced. The optimization
scheme allows to closely approximate a predefined reception
characteristic which can be freely chosen according to the
application. The output of the beamformer provides a
pre-enhanced signal with improved SNR for subsequent
single-microphone based speech enhancement.
Single-microphone noise reduction usually relies on
statistical properties of speech and noise. In general, the
noise is assumed to be stationary or only slightly
time-varying, which is in practice often not fulfilled. Due
to imprecise noise estimation, single-microphone systems are
prone to unpleasant artifacts that are called musical tones.
In this context different Information Combining methods,
merging various estimates, are presented which address
specifically the problem of non-stationary noise signals,
leading to a significant improved estimation accuracy. On
the one hand, the proposed Information Combining is used
with respect to spectral dependencies of human speech. On
the other hand, it merges the best of several speech and
noise estimates depending on their reliability. The
necessary estimates are provided by a new statistical noise
estimator as well as a codebook driven speech and noise
estimation algorithm. The achieved estimation quality opens
up the possibility to close the gap between the conflicting
goals of high noise attenuation, low speech distortion, and
the prevention of undesired musical tone artifacts. Finally,
the practical aspects of the proposed enhancement systems
are considered and discussed with two implemented real-time
demonstrators.},
cin = {613310},
ddc = {621.3},
cid = {$I:(DE-82)613310_20140620$},
typ = {PUB:(DE-HGF)11 / PUB:(DE-HGF)3},
urn = {urn:nbn:de:hbz:82-rwth-2016-096782},
url = {https://publications.rwth-aachen.de/record/674894},
}
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