Second order impropriety based complex-valued algorithm for frequency-domain blind separation of convolutive speech mixtures

The performance of the complex-valued blind source separation (BSS) is studied in the frequency domain approach to separate convolutive speech mixtures. In this context, the strong uncorrelating transform (SUT) and complex maximization of non-Gaussianity (CMN) do not produce satisfactory separation...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:2011 IEEE International Workshop on Machine Learning for Signal Processing S. 1 - 6
Hauptverfasser: Fengyu Cong, Qiu-Hua Lin, Peng Jia, Xizhi Shi, Ristaniemi, T.
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 01.09.2011
Schlagworte:
complex-valued BSS
convolutive speech
Correlation
frequency domain
improper
second order
Source separation
Speech
Time domain analysis
Time frequency analysis
Vectors
ISBN:1457716216, 9781457716218
ISSN:1551-2541
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Abstract The performance of the complex-valued blind source separation (BSS) is studied in the frequency domain approach to separate convolutive speech mixtures. In this context, the strong uncorrelating transform (SUT) and complex maximization of non-Gaussianity (CMN) do not produce satisfactory separation results since their assumptions about the independence among the frequency-domain complex-valued sources and the different diagonal elements of the pseudo-covariance of those sources are not met at each frequency bin. The proposed strong second order statistics (SSOS) algorithm exploits the second order impropriety of the frequency-domain complex-valued sources with the assumption that the complex-valued sources are improper and uncorrelated, and can well separate the mixtures at about 50% of frequency bins, outperforming SUT and CMN. Thus, it is promising to recover the time-domain speech sources by combing SSOS and the following indeterminacy correction in the frequency domain approach to separate convolutive speech mixtures.
AbstractList The performance of the complex-valued blind source separation (BSS) is studied in the frequency domain approach to separate convolutive speech mixtures. In this context, the strong uncorrelating transform (SUT) and complex maximization of non-Gaussianity (CMN) do not produce satisfactory separation results since their assumptions about the independence among the frequency-domain complex-valued sources and the different diagonal elements of the pseudo-covariance of those sources are not met at each frequency bin. The proposed strong second order statistics (SSOS) algorithm exploits the second order impropriety of the frequency-domain complex-valued sources with the assumption that the complex-valued sources are improper and uncorrelated, and can well separate the mixtures at about 50% of frequency bins, outperforming SUT and CMN. Thus, it is promising to recover the time-domain speech sources by combing SSOS and the following indeterminacy correction in the frequency domain approach to separate convolutive speech mixtures.
Author Qiu-Hua Lin
Peng Jia
Ristaniemi, T.
Fengyu Cong
Xizhi Shi
Author_xml – sequence: 1
  surname: Fengyu Cong
  fullname: Fengyu Cong
  organization: Dept. of Math. Inf. Technol., Univ. of Jyvaskyla, Jyvaskyla, Finland
– sequence: 2
  surname: Qiu-Hua Lin
  fullname: Qiu-Hua Lin
  organization: Sch. of Inf. & Commun. Eng., Dalian Univ. of Technol., Dalian, China
– sequence: 3
  surname: Peng Jia
  fullname: Peng Jia
  organization: NERC for Mobile Satellite Commun., Nanjing, China
– sequence: 4
  surname: Xizhi Shi
  fullname: Xizhi Shi
  organization: Mech. Eng. Sch., Shanghai Jiao Tong Univ., Shanghai, China
– sequence: 5
  givenname: T.
  surname: Ristaniemi
  fullname: Ristaniemi, T.
  organization: Dept. of Math. Inf. Technol., Univ. of Jyvaskyla, Jyvaskyla, Finland
BookMark eNo1kN1KwzAcxSNOcJt7APEmL9CZNB9NL2X4BROF6fVI2n9cpE1q0o4NfHgLzptzOHD4wTkzNPHBA0LXlCwpJeXty3rztswJpUtJJBeqPEOLslCUi6KgMmf5OZr9ByonaEqFoFkuOL1Es5S-COE5o3SKfjZQBV_jEGuI2LVdDF100B-x0QlqXIW2a-CQ7XUzjFE3nyG6ftdiGyK2Eb4H8NUxq0OrncemcSMrQaej7l3wONiR4PehGXq3B5w6gGqHW3fohwjpCl1Y3SRYnHyOPh7u31dP2fr18Xl1t84cLUSfmZxbooBpRgouixoMV7WqgMtKWsaYUVoVGmxp6tIIa6USFoTJx0o1CmFzdPPHdQCwHfe1Oh63p-fYL46VZmo
ContentType Conference Proceeding
DBID 6IE
6IL
CBEJK
RIE
RIL
DOI 10.1109/MLSP.2011.6064589
DatabaseName IEEE Electronic Library (IEL) Conference Proceedings
IEEE Xplore POP ALL
IEEE Xplore All Conference Proceedings
IEEE Electronic Library (IEL)
IEEE Proceedings Order Plans (POP All) 1998-Present
DatabaseTitleList
Database_xml – sequence: 1
  dbid: RIE
  name: IEEE Electronic Library
  url: https://ieeexplore.ieee.org/
  sourceTypes: Publisher
DeliveryMethod fulltext_linktorsrc
Discipline Computer Science
EISBN 9781457716232
1457716232
1457716224
9781457716225
EndPage 6
ExternalDocumentID 6064589
Genre orig-research
GroupedDBID 29M
6IE
6IF
6IH
6IK
6IL
6IN
AAJGR
AAWTH
ACGFS
ADZIZ
ALMA_UNASSIGNED_HOLDINGS
BEFXN
BFFAM
BGNUA
BKEBE
BPEOZ
CBEJK
CHZPO
IPLJI
M43
OCL
RIE
RIL
RNS
ID FETCH-LOGICAL-i175t-b24f08e3a307467deb48d8ce46c6f333b8a87aef9bd9b5ff685fe5b28cec28c03
IEDL.DBID RIE
ISBN 1457716216
9781457716218
ISICitedReferencesCount 0
ISICitedReferencesURI http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000298259900044&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN 1551-2541
IngestDate Wed Aug 27 02:59:31 EDT 2025
IsPeerReviewed false
IsScholarly true
Language English
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-i175t-b24f08e3a307467deb48d8ce46c6f333b8a87aef9bd9b5ff685fe5b28cec28c03
PageCount 6
ParticipantIDs ieee_primary_6064589
PublicationCentury 2000
PublicationDate 2011-Sept.
PublicationDateYYYYMMDD 2011-09-01
PublicationDate_xml – month: 09
  year: 2011
  text: 2011-Sept.
PublicationDecade 2010
PublicationTitle 2011 IEEE International Workshop on Machine Learning for Signal Processing
PublicationTitleAbbrev MLSP
PublicationYear 2011
Publisher IEEE
Publisher_xml – name: IEEE
SSID ssj0042311
ssj0000669903
Score 1.807072
Snippet The performance of the complex-valued blind source separation (BSS) is studied in the frequency domain approach to separate convolutive speech mixtures. In...
SourceID ieee
SourceType Publisher
StartPage 1
SubjectTerms complex-valued BSS
convolutive speech
Correlation
frequency domain
improper
second order
Source separation
Speech
Time domain analysis
Time frequency analysis
Vectors
Title Second order impropriety based complex-valued algorithm for frequency-domain blind separation of convolutive speech mixtures
URI https://ieeexplore.ieee.org/document/6064589
WOSCitedRecordID wos000298259900044&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3NS8MwFA_b8ODJj038JgeP1q1Lk6ZncXiYYzCF3UaavLiCa0fbjQn-8SZpVxG8eClJKaSE5H3-3u8hdGeUHuc24Q6UKi_wJbF3DjzOAl9r2w5JOJ7ZcTiZ8Pk8mrbQfVMLAwAOfAYPduhy-SqTGxsq6zNLrsajNmqHIatqtZp4ilGdRrA2UthYCX7FlUp9zzhBvivqoqElTPLZnuupnvM63ekPov7LeDatmD3r1X61XXFaZ3T0v_89Rr2f8j08bRTTCWpBeoqO9v0bcH2du-hrZr1hhR39Jk5seGGdWwwntrpNYQc3h51nCcHNVHy8Z3lSLlfYGLpY5xUI-9NT2UokKY6NwapwARWZeJbiTGOLaXdnewu4WAPIJV4lO5u0KHrobfT0-vjs1d0YvMSYGKUXDwM94EAEcS1KFMQBV1xCwCTThJCYCx4K0FGsophqzTjVQOOh-USax4CcoU6apXCOMA80KMKMd0xZAIIIqakUUmkjfsCH-AJ17WYu1hXhxqLex8u_X1-hwyrQa4Ff16hT5hu4QQdyWyZFfutOyTf92LrY
linkProvider IEEE
linkToHtml http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3NS8MwFA9zCnqauonf5uDRunVJuvQsjonbGGzCbiNNXlzBtaP7YIJ_vEnaTQQvXkpSCikheZ-_93sI3Rulx7lNuANjyqO-JPbOgccD6mtt2yEJxzPbbfX7fDwOByX0sKuFAQAHPoNHO3S5fJXKlQ2V1QNLrsbDPbTPKG028mqtXUTFKE8jWndy2NgJfs6WynzPuEG-K-tiLUuZ5AdbtqdizouEp98I673ucJBzexbr_Wq84vROu_K_Pz5GtZ8CPjzYqaYTVILkFFW2HRxwcaGr6Gto_WGFHQEnjm2AYZ5ZFCe22k1hBziHjWcpwc1UfLynWbyczrAxdbHOchj2p6fSmYgTHBmTVeEF5HTiaYJTjS2q3Z3uNeDFHEBO8Sze2LTFoobe2s-jp45X9GPwYmNkLL2oSXWDAxHENSlREFGuuAQayEATQiIueEuADiMVRkzrgDMNLGqaT6R5NMgZKidpAucIc6pBkcD4xyygIIiQmkkhlTYCCHyILlDVbuZknlNuTIp9vPz79R067Ix63Un3pf96hY7ysK-FgV2j8jJbwQ06kOtlvMhu3Yn5BuDovh8
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=proceeding&rft.title=2011+IEEE+International+Workshop+on+Machine+Learning+for+Signal+Processing&rft.atitle=Second+order+impropriety+based+complex-valued+algorithm+for+frequency-domain+blind+separation+of+convolutive+speech+mixtures&rft.au=Fengyu+Cong&rft.au=Qiu-Hua+Lin&rft.au=Peng+Jia&rft.au=Xizhi+Shi&rft.date=2011-09-01&rft.pub=IEEE&rft.isbn=9781457716218&rft.issn=1551-2541&rft.spage=1&rft.epage=6&rft_id=info:doi/10.1109%2FMLSP.2011.6064589&rft.externalDocID=6064589
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1551-2541&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1551-2541&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1551-2541&client=summon