Segmentation of spoken discourse into distinct conversational activities has been applied to broadcast news, meetings, monologs, and two-party dialogs. This paper considers the aspectual properties of discourse segments, meaning how they transpire in time. Classifiers were constructed to distinguish between segment boundaries and non-boundaries, where the sizes of utterance spans to represent data instances were varied, and the locations of segment boundaries relative to these instances. Classifier performance was better for representations that included the end of one discourse segment combined with the beginning of the next. In addition, classification accuracy was better for segments in which speakers accomplish goals with distinctive start and end points.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.