Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/597479
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dc.contributor.authorMohammad Hadi Bokaeien_US
dc.contributor.authorHossein Sametien_US
dc.contributor.authorYang Liuen_US
dc.date.accessioned2020-05-20T08:51:25Z-
dc.date.available2020-05-20T08:51:25Z-
dc.date.issued2016en_US
dc.identifier.issn2329-9290en_US
dc.identifier.issn2329-9304en_US
dc.identifier.other10.1109/TASLP.2016.2585859en_US
dc.identifier.urihttp://localhost/handle/Hannan/185293en_US
dc.identifier.urihttp://localhost/handle/Hannan/597479-
dc.description.abstractIn this paper, we aim to improve meeting summarization performance using discourse specific information. Since there are intrinsically different characteristics in utterances in different types of function segments, e.g., Monologue segments versus Discussion ones, we propose a new summarization framework where different summarizers are used for different segment types. For monologue segments, we adopt the integer linear programming-based summarization method; whereas for discussion segments, we use a graph-based method to incorporate speaker information. Performance of our proposed method is evaluated using the standard AMI meeting corpus. Results show a good improvement over previous state-of-the-art algorithms according to various evaluation metrics and different compress ratios.en_US
dc.publisherIEEEen_US
dc.relation.haspart7501601.pdfen_US
dc.subjectfunctional segmentation|multiparty conversation|Extractive summarizationen_US
dc.titleSummarizing Meeting Transcripts Based on Functional Segmentationen_US
dc.typeArticleen_US
dc.journal.volume24en_US
dc.journal.issue10en_US
dc.journal.titleIEEE/ACM Transactions on Audio, Speech, and Language Processingen_US
Appears in Collections:2016

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Full metadata record
DC FieldValueLanguage
dc.contributor.authorMohammad Hadi Bokaeien_US
dc.contributor.authorHossein Sametien_US
dc.contributor.authorYang Liuen_US
dc.date.accessioned2020-05-20T08:51:25Z-
dc.date.available2020-05-20T08:51:25Z-
dc.date.issued2016en_US
dc.identifier.issn2329-9290en_US
dc.identifier.issn2329-9304en_US
dc.identifier.other10.1109/TASLP.2016.2585859en_US
dc.identifier.urihttp://localhost/handle/Hannan/185293en_US
dc.identifier.urihttp://localhost/handle/Hannan/597479-
dc.description.abstractIn this paper, we aim to improve meeting summarization performance using discourse specific information. Since there are intrinsically different characteristics in utterances in different types of function segments, e.g., Monologue segments versus Discussion ones, we propose a new summarization framework where different summarizers are used for different segment types. For monologue segments, we adopt the integer linear programming-based summarization method; whereas for discussion segments, we use a graph-based method to incorporate speaker information. Performance of our proposed method is evaluated using the standard AMI meeting corpus. Results show a good improvement over previous state-of-the-art algorithms according to various evaluation metrics and different compress ratios.en_US
dc.publisherIEEEen_US
dc.relation.haspart7501601.pdfen_US
dc.subjectfunctional segmentation|multiparty conversation|Extractive summarizationen_US
dc.titleSummarizing Meeting Transcripts Based on Functional Segmentationen_US
dc.typeArticleen_US
dc.journal.volume24en_US
dc.journal.issue10en_US
dc.journal.titleIEEE/ACM Transactions on Audio, Speech, and Language Processingen_US
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7501601.pdf865.73 kBAdobe PDFThumbnail
Preview File
Full metadata record
DC FieldValueLanguage
dc.contributor.authorMohammad Hadi Bokaeien_US
dc.contributor.authorHossein Sametien_US
dc.contributor.authorYang Liuen_US
dc.date.accessioned2020-05-20T08:51:25Z-
dc.date.available2020-05-20T08:51:25Z-
dc.date.issued2016en_US
dc.identifier.issn2329-9290en_US
dc.identifier.issn2329-9304en_US
dc.identifier.other10.1109/TASLP.2016.2585859en_US
dc.identifier.urihttp://localhost/handle/Hannan/185293en_US
dc.identifier.urihttp://localhost/handle/Hannan/597479-
dc.description.abstractIn this paper, we aim to improve meeting summarization performance using discourse specific information. Since there are intrinsically different characteristics in utterances in different types of function segments, e.g., Monologue segments versus Discussion ones, we propose a new summarization framework where different summarizers are used for different segment types. For monologue segments, we adopt the integer linear programming-based summarization method; whereas for discussion segments, we use a graph-based method to incorporate speaker information. Performance of our proposed method is evaluated using the standard AMI meeting corpus. Results show a good improvement over previous state-of-the-art algorithms according to various evaluation metrics and different compress ratios.en_US
dc.publisherIEEEen_US
dc.relation.haspart7501601.pdfen_US
dc.subjectfunctional segmentation|multiparty conversation|Extractive summarizationen_US
dc.titleSummarizing Meeting Transcripts Based on Functional Segmentationen_US
dc.typeArticleen_US
dc.journal.volume24en_US
dc.journal.issue10en_US
dc.journal.titleIEEE/ACM Transactions on Audio, Speech, and Language Processingen_US
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7501601.pdf865.73 kBAdobe PDFThumbnail
Preview File