Topic segmentation of dialogue

Authors:
Jaime Arguello;Carolyn Rosé
Affiliations:
Carnegie Mellon University, Pittsburgh, PA;Carnegie Mellon University, Pittsburgh, PA
Venue:
ACTS '09 Proceedings of the HLT-NAACL 2006 Workshop on Analyzing Conversations in Text and Speech
Year:
2006

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Abstract

We introduce a novel topic segmentation approach that combines evidence of topic shifts from lexical cohesion with linguistic evidence such as syntactically distinct features of segment initial and final contributions. Our evaluation shows that this hybrid approach outperforms state-of-the-art algorithms even when applied to loosely structured, spontaneous dialogue. Further analysis reveals that using dialogue exchanges versus dialogue contributions improves topic segmentation quality.