Learning to Tell Tales: A Data-driven Approach to Story Generation

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• Ekaterina Shutova (University of Cambridge)
• Monday 26 April 2010, 12:30-13:30
• GS15, Computer Laboratory.

If you have a question about this talk, please contact Diarmuid Ó Séaghdha.

At this session of the NLIP Reading Group we’ll be discussing the following paper:

Neil McIntyre and Mirella Lapata. 2009. Learning to Tell Tales: A Data-driven Approach to Story Generation. In Proceedings of ACL -IJCNLP-09.

Abstract: Computational story telling has sparked great interest in artificial intelligence, partly because of its relevance to educational and gaming applications. Traditionally, story generators rely on a large repository of background knowledge containing information about the story plot and its characters. This information is detailed and usually hand crafted. In this paper we propose a data-driven approach for generating short children’s stories that does not require extensive manual involvement. We create an end-to-end system that realizes the various components of the generation pipeline stochastically. Our system follows a generate-and-and-rank approach where the space of multiple candidate stories is pruned by considering whether they are plausible, interesting, and coherent.

This talk is part of the Natural Language Processing Reading Group series.

This talk is included in these lists:

• Cambridge Forum of Science and Humanities
• Cambridge Language Sciences
• Chris Davis' list
• GS15, Computer Laboratory
• Guy Emerson's list
• Natural Language Processing Reading Group

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