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Doust, Richard and Piwek, Paul
(2017).
DOI: https://doi.org/10.18653/v1/W17-3527
URL: https://aclanthology.coli.uni-saarland.de/papers/W...
Abstract
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.
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About
- Item ORO ID
- 51555
- Item Type
- Conference or Workshop Item
- Keywords
- language generation; suspense; narrative;
- Academic Unit or 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)
?? hwpra ?? - Copyright Holders
- © 2017 The Authors
- Related URLs
- Depositing User
- Paul Piwek