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A model of suspense for narrative generation

Doust, Richard and Piwek, Paul (2017). A model of suspense for narrative generation. In: Proceedings of the 10th International Conference on Natural Language Generation (Alonso, Jose M.; Bugarín, Alberto and Reiter, Ehud eds.), Association for Computational Linguistics, pp. 178–187.

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Most work on automatic generation of narratives, and more specifically suspenseful narrative, has focused on detailed domain-specific modelling of character psychology and plot structure. Recent work on the automatic learning of narrative schemas suggests an alternative approach that exploits such schemas for modelling and measuring suspense. We propose a domain-independent model for tracking suspense in a story which can be used to predict the audience’s suspense response on a sentence-by-sentence basis at the content determination stage of narrative generation. The model lends itself as the theoretical foundation for a suspense module that is compatible with alternative narrative generation theories. The proposal is evaluated by human judges’ normalised average scores correlate strongly with predicted values.

Item Type: Conference or Workshop Item
Copyright Holders: 2017 The Authors
Keywords: language generation; suspense; narrative;
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Research Group: Centre for Research in Computing (CRC)
Health and Wellbeing PRA (Priority Research Area)
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Item ID: 51555
Depositing User: Paul Piwek
Date Deposited: 16 Oct 2017 09:36
Last Modified: 12 Jun 2020 10:10
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