Model adaptation for dialog act tagging

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dc.authorid0000-0002-4597-0954
dc.authorid0000-0001-5246-2117
dc.contributor.authorTür, Gökhanen_US
dc.contributor.authorGüz, Ümiten_US
dc.contributor.authorHakkani Tür, Dileken_US
dc.date.accessioned2019-08-31T12:10:23Z
dc.date.accessioned2019-08-05T16:05:02Z
dc.date.available2019-08-31T12:10:23Z
dc.date.available2019-08-05T16:05:02Z
dc.date.issued2006
dc.departmentIşık Üniversitesi, Mühendislik Fakültesi, Elektrik-Elektronik Mühendisliği Bölümüen_US
dc.departmentIşık University, Faculty of Engineering, Department of Electrical-Electronics Engineeringen_US
dc.description.abstractIn this paper, we analyze the effect of model adaptation for dialog act tagging. The goal of adaptation is to improve the performance of the tagger using out-of-domain data or models. Dialog act tagging aims to provide a basis for further discourse analysis and understanding in conversational speech. In this study we used the ICSI meeting corpus with high-level meeting recognition dialog act (MRDA) tags, that is, question, statement, backchannel, disruptions, and floor grabbers/holders. We performed controlled adaptation experiments using the Switchboard (SWBD) corpus with SWBD-DAMSL tags as the out-of-domain corpus. Our results indicate that we can achieve significantly better dialog act tagging by automatically selecting a subset of the Switchboard corpus and combining the confidences obtained by both in-domain and out-of-domain models via logistic regression, especially when the in-domain data is limited.en_US
dc.description.sponsorshipThis material is based upon work supported by the Scientific and Technological Research Council of Turkey (TUBITAK) and Defense Advanced Research Projects Agency (DARPA) GALE (HR0011-06-C- 0023) and CALO (NBCHD-030010) funding at ICSI and SRI, respectively. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of DARPA. We thank Andreas Stolcke and Elizabeth Shriberg for many helpful discussionsen_US
dc.description.versionPublisher's Versionen_US
dc.identifier.citationTür, G., Güz, Ü. & Hakkani Tür, D. (2006). Model adaptation for dialog act tagging. Paper presented at the 2006 IEEE ACL Spoken Language Technology Workshop, SLT 2006, Proceedings, 94-97. doi:10.1109/SLT.2006.326825en_US
dc.identifier.doi10.1109/SLT.2006.326825
dc.identifier.endpage97
dc.identifier.isbn1424408733
dc.identifier.isbn9781424408733
dc.identifier.isbn1424408725
dc.identifier.isbn9781424408726
dc.identifier.issn2639-5479
dc.identifier.scopus2-s2.0-48749111525
dc.identifier.scopusqualityN/A
dc.identifier.startpage94
dc.identifier.urihttps://hdl.handle.net/11729/2005
dc.identifier.urihttps://dx.doi.org/10.1109/SLT.2006.326825
dc.identifier.wosWOS:000245891500023
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakConference Proceedings Citation Index – Science (CPCI-S)en_US
dc.institutionauthorGüz, Ümiten_US
dc.institutionauthorid0000-0002-4597-0954
dc.language.isoenen_US
dc.peerreviewedYesen_US
dc.publicationstatusPublisheden_US
dc.publisherIEEEen_US
dc.relation.ispartof2006 IEEE ACL Spoken Language Technology Workshop, SLT 2006, Proceedingsen_US
dc.relation.ispartofseriesIEEE Workshop on Spoken Language Technologyen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectAdaptation modelen_US
dc.subjectAutomatic controlen_US
dc.subjectComputer scienceen_US
dc.subjectConversational speechen_US
dc.subjectDialog act taggingen_US
dc.subjectDialogue policyen_US
dc.subjectDiscourse analysisen_US
dc.subjectDomain modelingen_US
dc.subjectElectric switchboardsen_US
dc.subjectFloorsen_US
dc.subjectFood processingen_US
dc.subjectHigh-level meeting recognition dialog acten_US
dc.subjectHumansen_US
dc.subjectICSI meeting corpusen_US
dc.subjectInteractive systemsen_US
dc.subjectInterpolationen_US
dc.subjectLinguisticsen_US
dc.subjectLogistic regressionen_US
dc.subjectLogistic regression (LR)en_US
dc.subjectLogisticsen_US
dc.subjectMaterials handlingen_US
dc.subjectMeeting recognitionen_US
dc.subjectModel adaptationen_US
dc.subjectModelsen_US
dc.subjectNatural language processingen_US
dc.subjectNatural languagesen_US
dc.subjectOut-of-domain dataen_US
dc.subjectQuery languagesen_US
dc.subjectSpeech analysisen_US
dc.subjectSpeech processingen_US
dc.subjectSpeech recognitionen_US
dc.subjectSpoken languagesen_US
dc.subjectSWBD-DAMSL tagsen_US
dc.subjectSwitchboard corpusen_US
dc.subjectTaggingen_US
dc.titleModel adaptation for dialog act taggingen_US
dc.typeConference Objecten_US
dspace.entity.typePublication

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