Paper: Discourse Cues for Broadcast News Segmentation

ACL ID P98-2135
Title Discourse Cues for Broadcast News Segmentation
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 1998
Authors

This paper describes the design and application of time-enhanced, finite state models of discourse cues to the automated segmentation of broadcast news. We describe our analysis of a broadcast news corpus, the design of a discourse cue based story segmentor that builds upon information extraction techniques, and finally its computational implementation and evaluation in the Broadcast News Navigator (BNN) to support video news browsing, retrieval, and summarization.