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dc.contributor.authorDielmann, Alfred
dc.contributor.authorRenals, Steve
dc.date.accessioned2007-09-18T10:02:22Z
dc.date.available2007-09-18T10:02:22Z
dc.date.issued2007
dc.identifier.citationA. Dielmann and S. Renals. DBN based joint dialogue act recognition of multiparty meetings. In Proc. IEEE ICASSP, volume 4, pages 133-136, April 2007.en
dc.identifier.urihttp://hdl.handle.net/1842/2001
dc.description.abstractJoint Dialogue Act segmentation and classification of the new AMI meeting corpus has been performed through an integrated framework based on a switching dynamic Bayesian network and a set of continuous features and language models. The recognition process is based on a dictionary of 15 DA classes tailored for group decision-making. Experimental results show that a novel interpolated Factored Language Model results in a low error rate on the automatic segmentation task, and thus good recognition results can be achieved on AMI multiparty conversational speech.en
dc.format.extent75416 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.subjectspeech technologyen
dc.titleDBN based joint dialogue act recognition of multiparty meetingsen
dc.typeConference Paperen


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