Extractive Meeting Summarization Through Speaker Zone Detection

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Extractive Meeting Summarization Through Speaker Zone Detection

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Title: Extractive Meeting Summarization Through Speaker Zone Detection
Author(s):
Bokaei, M. H.;
Sameti, H.;
Liu, Yang (UT Dallas)
Item Type: article
Keywords: Show Keywords
Abstract: In 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.
Publisher: International Speech and Communication Association
ISSN: 2308-457X (ISSN)
Persistent Link: http://hdl.handle.net/10735
Bibliographic Citation: Bokaei, 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.
Terms of Use: ©2015 ISCA

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