View source for Publications:Synergy of lip motion and acoustic features in biometric speech and speaker recognition

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{{PublicationSetupTemplate|Author=Maycel Faraj, Josef Bigun
|PID=239276
|Name=Faraj, Maycel [mafa] (Högskolan i Halmstad [2804], Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE) [3905], Halmstad Embedded and Intelligent Systems Research (EIS) [3938]);Bigun, Josef [josef] (Högskolan i Halmstad [2804], Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE) [3905], Halmstad Embedded and Intelligent Systems Research (EIS) [3938])
|Title=Synergy of lip motion and acoustic features in biometric speech and speaker recognition
|PublicationType=Journal Paper
|ContentType=Refereegranskat
|Language=eng
|Journal=IEEE transactions on computers (Print)
|JournalISSN=0018-9340
|Status=published
|Volume=56
|Issue=9
|HostPublication=
|Conference=
|StartPage=1169
|EndPage=1175
|Year=2007
|Edition=
|Pages=
|City=New York
|Publisher=IEEE Press
|Series=
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|DOI=http://dx.doi.org/10.1109/TC.2007.1074
|ISI=000248208300003
|PMID=
|ScopusId=2-s2.0-34548205797
|NBN=urn:nbn:se:hh:diva-2058
|LocalId=2082/2453
|ArchiveNumber=
|Keywords=GMM;SVM;Speech recognition;biometrics;Lip motion;Lip reading;Motion estimation;Normal image flow;normal image velocity;Speaker recognition
|Categories=Teknik och teknologier (2)
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|Projects=
|Notes=<p>©2007 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.</p>
|Abstract=<p>This paper presents the scheme and evaluation of a robust audio-visual digit-and-speaker-recognition system using lip motion and speech biometrics. Moreover, a liveness verification barrier based on a person's lip movement is added to the system to guard against advanced spoofing attempts such as replayed videos. The acoustic and visual features are integrated at the feature level and evaluated first by a support vector machine for digit and speaker identification and, then, by a Gaussian mixture model for speaker verification. Based on ap300 different personal identities, this paper represents, to our knowledge, the first extensive study investigating the added value of lip motion features for speaker and speech-recognition applications. Digit recognition and person-identification and verification experiments are conducted on the publicly available XM2VTS database showing favorable results (speaker verification is 98 percent, speaker identification is 100 percent, and digit identification is 83 percent to 100 percent).</p>
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|CreatedDate=2008-10-17
|PublicationDate=2008-10-17
|LastUpdated=2012-09-19
|diva=http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:239276}}
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