Paper: Automatic Segmentation Of Multiparty Dialogue

ACL ID E06-1035
Title Automatic Segmentation Of Multiparty Dialogue
Venue Annual Meeting of The European Chapter of The Association of Computational Linguistics
Session Main Conference
Year 2006

In this paper, we investigate the prob- lem of automatically predicting segment boundaries in spoken multiparty dialogue. We extend prior work in two ways. We first apply approaches that have been pro- posed for predicting top-level topic shifts to the problem of identifying subtopic boundaries. We then explore the impact on performance of using ASR output as opposed to human transcription. Exam- ination of the effect of features shows that predicting top-level and predicting subtopic boundaries are two distinct tasks: (1) for predicting subtopic boundaries, the lexical cohesion-based approach alone can achieve competitive results, (2) for predicting top-level boundaries, the ma- chine learning approach that combines lexical-cohesion and conversational fea- tures performs best, and (3) con...