Paper: Gestural Cohesion for Topic Segmentation

ACL ID P08-1097
Title Gestural Cohesion for Topic Segmentation
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2008
Authors

This paper explores the relationship between discourse segmentation and coverbal gesture. Introducing the idea of gestural cohesion, we show that coherent topic segments are char- acterized by homogeneous gestural forms and that changes in the distribution of gestural features predict segment boundaries. Gestu- ral features are extracted automatically from video, and are combined with lexical features in a Bayesian generative model. The resulting multimodal system outperforms text-only seg- mentation on both manual and automatically- recognized speech transcripts.