Paper: Museli: A Multi-Source Evidence Integration Approach To Topic Segmentation Of Spontaneous Dialogue

ACL ID N06-2003
Title Museli: A Multi-Source Evidence Integration Approach To Topic Segmentation Of Spontaneous Dialogue
Venue Human Language Technologies
Session Short Paper
Year 2006
Authors

We introduce a novel topic segmentation approach that combines evidence of topic shifts from lexical cohesion with linguistic evidence such as syntactically distinct fea- tures of segment initial contributions. Our evaluation demonstrates that this hybrid approach outperforms state-of-the-art algo- rithms even when applied to loosely struc- tured, spontaneous dialogue.