Stories Animated: A Framework for Personalized Interactive Narratives using Filtering of Story Characteristics

Hui-Yin Wu 1 Marc Christie 2 Tsai-Yen Li 1
1 IMLab
IMLab - Intelligent Media Lab [Taïwan]
2 MIMETIC - Analysis-Synthesis Approach for Virtual Human Simulation
UR2 - Université de Rennes 2, Inria Rennes – Bretagne Atlantique , IRISA-D6 - MEDIA ET INTERACTIONS
Abstract : Interactive storytelling opens exciting possibilities to personalized narrative creation, providing a more compelling and immersive experience than traditional narratives. In this work we propose a creative framework in which the author can specify story characteristics (such as genre or complexity) on a story structure in order to generate interactive stories tailored to personalized constraints. The story generation model combines a branching story structure with a planning algorithm that filters and recombines story fragments based on characteristics, generating a high-level interactive scenario that satisfies all authorial constraints, and provides sufficient abstraction from the technical implementation. The scenario is then simulated in a real-time storytelling system, featuring autonomous characters and camera control. As a demonstration of our approach, we have authored an interactive narrative based on the Brothers Grimm fairytale "Godfather Death."
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https://hal.inria.fr/hal-00854390
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Hui-Yin Wu, Marc Christie, Tsai-Yen Li. Stories Animated: A Framework for Personalized Interactive Narratives using Filtering of Story Characteristics. CASA - Computer Animation and Social Agents, May 2013, Istanbul, Turkey. ⟨hal-00854390⟩

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