Suspenser: A Story Generation System for Suspense
Yun-Gyung Cheong, R. Michael Young · IEEE Transactions on Computational Intelligence and AI in Games · 2014
Interactive storytelling has been receiving a growing attention from AI and game communities and a number of computational approaches have shown promises in generating stories for games. However, there has been little research on stories evoking specific cognitive and affective responses. The goal of the work we describe here is to develop a system that produces a narrative designed specifically to arouse suspense from its reader. Our approach attempts to create stories that manipulate the reader's suspense level by elaborating on the story structure that can influence the reader's narrative comprehension at a specific point in her reading. Adapting theories developed by cognitive psychologists, our approach uses a plan-based model of narrative comprehension to determine the final content of the story in order to manipulate the reader's suspense. In this paper, we describe our system implementation and empirical evaluations to test the efficacy of this system.