16th Annual Conference of the International Speech Communication Association

Dresden, Germany
September 6-10, 2015

Extractive Meeting Summarization Through Speaker Zone Detection

Mohammad Hadi Bokaei (1), Hossein Sameti (1), Yang Liu (2)

(1) Sharif University of Technology, Iran
(2) University of Texas at Dallas, USA

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.

Full Paper

Bibliographic reference.  Bokaei, Mohammad Hadi / Sameti, Hossein / Liu, Yang (2015): "Extractive meeting summarization through speaker zone detection", In INTERSPEECH-2015, 2724-2728.