國立高雄大學圖資館 |

語系: 繁體中文

說明(常見問題)

圖資館首頁

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Canonical correlation analysis in sp...

Benesty, Jacob.

Canonical correlation analysis in speech enhancement

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Canonical correlation analysis in speech enhancementby Jacob Benesty, Israel Cohen.
作者:	Benesty, Jacob.
其他作者:	Cohen, Israel.
出版者:	Cham :Springer International Publishing :2018.
面頁冊數:	ix, 121 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
標題:	Speech processing systems.
電子資源:	http://dx.doi.org/10.1007/978-3-319-67020-1
ISBN:	9783319670201$q(electronic bk.)

Canonical correlation analysis in speech enhancement
Benesty, Jacob.

Canonical correlation analysis in speech enhancement[electronic resource] /by Jacob Benesty, Israel Cohen. - Cham :Springer International Publishing :2018. - ix, 121 p. :ill., digital ;24 cm. - SpringerBriefs in electrical and computer engineering,2191-8112. - SpringerBriefs in electrical and computer engineering..

Introduction -- Canonical Correlation Analysis -- Single-Channel Speech Enhancement in the Time Domain -- Single-Channel Speech Enhancement in the STFT Domain -- Multichannel Speech Enhancement in the Time Domain -- Multichannel Speech Enhancement in the Time Domain -- Adaptive Beamforming.

This book focuses on the application of canonical correlation analysis (CCA) to speech enhancement using the filtering approach. The authors explain how to derive different classes of time-domain and time-frequency-domain noise reduction filters, which are optimal from the CCA perspective for both single-channel and multichannel speech enhancement. Enhancement of noisy speech has been a challenging problem for many researchers over the past few decades and remains an active research area. Typically, speech enhancement algorithms operate in the short-time Fourier transform (STFT) domain, where the clean speech spectral coefficients are estimated using a multiplicative gain function. A filtering approach, which can be performed in the time domain or in the subband domain, obtains an estimate of the clean speech sample at every time instant or time-frequency bin by applying a filtering vector to the noisy speech vector. Compared to the multiplicative gain approach, the filtering approach more naturally takes into account the correlation of the speech signal in adjacent time frames. In this study, the authors pursue the filtering approach and show how to apply CCA to the speech enhancement problem. They also address the problem of adaptive beamforming from the CCA perspective, and show that the well-known Wiener and minimum variance distortionless response (MVDR) beamformers are particular cases of a general class of CCA-based adaptive beamformers.

ISBN: 9783319670201$q(electronic bk.)

Standard No.: 10.1007/978-3-319-67020-1doiSubjects--Topical Terms:

184755
Speech processing systems.

LC Class. No.: TK7882.S65

Dewey Class. No.: 006.454

Canonical correlation analysis in speech enhancement
LDR:02841nmm a2200349 a 4500 001 528248
003 DE-He213
005 20180604113940.0
006 m d
007 cr nn 008maaau
008 181024s2018 gw s 0 eng d
020 $a 9783319670201$q(electronic bk.)
020 $a 9783319670195$q(paper)
024 7 $a 10.1007/978-3-319-67020-1 $2 doi
035 $a 978-3-319-67020-1
040 $a GP $c GP
041 0 $a eng
050 4 $a TK7882.S65
072 7 $a TTBM $2 bicssc
072 7 $a UYS $2 bicssc
072 7 $a TEC008000 $2 bisacsh
072 7 $a COM073000 $2 bisacsh
082 0 4 $a 006.454 $2 23
090 $a TK7882.S65 $b B465 2018
100 1 $a Benesty, Jacob. $3 237920
245 1 0 $a Canonical correlation analysis in speech enhancement $h [electronic resource] / $c by Jacob Benesty, Israel Cohen.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2018.
300 $a ix, 121 p. : $b ill., digital ; $c 24 cm.
490 1 $a SpringerBriefs in electrical and computer engineering, $x 2191-8112
505 0 $a Introduction -- Canonical Correlation Analysis -- Single-Channel Speech Enhancement in the Time Domain -- Single-Channel Speech Enhancement in the STFT Domain -- Multichannel Speech Enhancement in the Time Domain -- Multichannel Speech Enhancement in the Time Domain -- Adaptive Beamforming.
520 $a This book focuses on the application of canonical correlation analysis (CCA) to speech enhancement using the filtering approach. The authors explain how to derive different classes of time-domain and time-frequency-domain noise reduction filters, which are optimal from the CCA perspective for both single-channel and multichannel speech enhancement. Enhancement of noisy speech has been a challenging problem for many researchers over the past few decades and remains an active research area. Typically, speech enhancement algorithms operate in the short-time Fourier transform (STFT) domain, where the clean speech spectral coefficients are estimated using a multiplicative gain function. A filtering approach, which can be performed in the time domain or in the subband domain, obtains an estimate of the clean speech sample at every time instant or time-frequency bin by applying a filtering vector to the noisy speech vector. Compared to the multiplicative gain approach, the filtering approach more naturally takes into account the correlation of the speech signal in adjacent time frames. In this study, the authors pursue the filtering approach and show how to apply CCA to the speech enhancement problem. They also address the problem of adaptive beamforming from the CCA perspective, and show that the well-known Wiener and minimum variance distortionless response (MVDR) beamformers are particular cases of a general class of CCA-based adaptive beamformers.
650 0 $a Speech processing systems. $3 184755
650 1 4 $a Engineering. $3 210888
650 2 4 $a Signal, Image and Speech Processing. $3 273768
700 1 $a Cohen, Israel. $3 455968
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer eBooks
830 0 $a SpringerBriefs in electrical and computer engineering. $3 557682
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-67020-1
950 $a Engineering (Springer-11647)