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Inter-frequency dependency in MMSE speech enhancement

Li, CJ and Andersen, Sören Vang LU (2004) 6th Nordic Signal Processing Symposium (NORSIG 2004) In NORSIG 2004: PROCEEDINGS OF THE 6TH NORDIC SIGNAL PROCESSING SYMPOSIUM 46. p.200-203
Abstract
In this paper an MMSE estimator of the complex shortime spectrum is considered for optimum noise reduction of speech. The correlation between frequency components is exploited to improve the estimation, especially of those components with low local SNR. Furthermore, by making use of both spectral envelope and time envelope, the estimator is able to suppress noise power infrequency domain and lime domain simultaneously. The performance of the resulting estimator is found to be superior to the non-causal IN Wiener filter The enhanced signal suffers less spectral distortion, while achieving a lower mean squared error than the Wiener filter.
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author
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
in
NORSIG 2004: PROCEEDINGS OF THE 6TH NORDIC SIGNAL PROCESSING SYMPOSIUM
volume
46
pages
200 - 203
publisher
HELSINKI UNIVERSITY TECHNOLOGY
conference name
6th Nordic Signal Processing Symposium (NORSIG 2004)
external identifiers
  • wos:000225463400051
  • scopus:12144283194
ISSN
1458-6401
language
English
LU publication?
no
id
28b7f3f0-0154-428b-8af6-43c2d3e60b49 (old id 4092545)
date added to LUP
2013-10-17 10:43:17
date last changed
2017-06-11 04:32:19
@inproceedings{28b7f3f0-0154-428b-8af6-43c2d3e60b49,
  abstract     = {In this paper an MMSE estimator of the complex shortime spectrum is considered for optimum noise reduction of speech. The correlation between frequency components is exploited to improve the estimation, especially of those components with low local SNR. Furthermore, by making use of both spectral envelope and time envelope, the estimator is able to suppress noise power infrequency domain and lime domain simultaneously. The performance of the resulting estimator is found to be superior to the non-causal IN Wiener filter The enhanced signal suffers less spectral distortion, while achieving a lower mean squared error than the Wiener filter.},
  author       = {Li, CJ and Andersen, Sören Vang},
  booktitle    = {NORSIG 2004: PROCEEDINGS OF THE 6TH NORDIC SIGNAL PROCESSING SYMPOSIUM},
  issn         = {1458-6401},
  language     = {eng},
  pages        = {200--203},
  publisher    = {HELSINKI UNIVERSITY TECHNOLOGY},
  title        = {Inter-frequency dependency in MMSE speech enhancement},
  volume       = {46},
  year         = {2004},
}