Extractive Meeting Summarization Through Speaker Zone Detection

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dc.contributor.authorBokaei, M. H.en_US
dc.contributor.authorSameti, H.en_US
dc.contributor.authorLiu, Yangen_US
dc.contributor.utdAuthorLiu, Yang
dc.date.accessioned2017-03-31T19:52:41Z
dc.date.available2017-03-31T19:52:41Z
dc.date.created2015-09
dc.description.abstractIn this paper we investigate the role of discourse analysis in extractive meeting summarization task. Specifically our proposed method comprises of two distinct steps. First we use a meeting segmentation algorithm in order to detect various functional parts of the input meeting. Afterwards, a two level scoring mechanism in a graph-based framework is used to score each dialogue act in order to extract the most valuable ones and include them in the extracted summary. We evaluate our proposed method on AMI and ICSI corpora and compare it with other state-of-the-art graph based algorithms according to various evaluation metrics. The experimental results show that our algorithm outperforms the other state-of-the-art ones according to most of the metrics and on both datasets.en_US
dc.identifier.bibliographicCitationBokaei, M. H., H. Sameti, and Y. Liu. 2015. "Extractive meeting summarization through speaker zone detection." INTERSPEECH (16th Annual Conference of the International Speech Communication Association) 2015, 2724-2728.en_US
dc.identifier.issn2308-457Xen_US
dc.identifier.urihttp://hdl.handle.net/10735.1/5349
dc.identifier.volume2015en_US
dc.language.isoenen_US
dc.publisherInternational Speech and Communication Associationen_US
dc.rights©2015 ISCAen_US
dc.source.journal16th Annual Conference of the International Speech Communication Association, Interspeech 2015en_US
dc.subjectDiscourse analysisen_US
dc.subjectAlgorithmsen_US
dc.subjectOral communicationen_US
dc.subjectDialoguesen_US
dc.subjectMeetingsen_US
dc.subjectConversation analysisen_US
dc.subjectInternational Computer Science Instituteen_US
dc.subjectAmbient intelligenceen_US
dc.titleExtractive Meeting Summarization Through Speaker Zone Detectionen_US
dc.type.genrearticleen_US

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