Movie Script Summarization as Graph-based Scene Extraction

Philip John Gorinski, Mirella Lapata

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

In this paper we study the task of movie script summarization, which we argue could enhance script browsing, give readers a rough idea of the script’s plotline, and speed up reading time. We formalize the process of generating a shorter version of a screenplay as the task of finding an optimal chain of scenes. We develop a graph-based model that selects a chain by jointly optimizing its logical progression, diversity, and importance. Human evaluation based on a question-answering task shows that our model produces summaries which are more informative compared to competitive baselines.
Original languageEnglish
Title of host publicationProceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Place of PublicationDenver, Colorado
PublisherAssociation for Computational Linguistics
Pages1066-1076
Number of pages11
Publication statusPublished - 1 May 2015

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