Psychology-guided Controllable Story Generation
Yuqiang Xie, Yue Hu, Yunpeng Li, Guanqun Bi, Luxi Xing, Wei Peng

TL;DR
This paper introduces a novel system that generates more controllable and psychologically consistent stories by integrating the protagonist's needs and emotions, guided by psychological theories, into the story creation process.
Contribution
It proposes a new framework that incorporates global psychological state chains and local psychological state tracking to improve controllability and psychological consistency in story generation.
Findings
PICS outperforms baseline models in automatic evaluations.
Stories generated by PICS show more consistent psychological changes.
The system effectively integrates psychological states into story planning.
Abstract
Controllable story generation is a challenging task in the field of NLP, which has attracted increasing research interest in recent years. However, most existing works generate a whole story conditioned on the appointed keywords or emotions, ignoring the psychological changes of the protagonist. Inspired by psychology theories, we introduce global psychological state chains, which include the needs and emotions of the protagonists, to help a story generation system create more controllable and well-planned stories. In this paper, we propose a Psychology-guIded Controllable Story Generation System (PICS) to generate stories that adhere to the given leading context and desired psychological state chains for the protagonist. Specifically, psychological state trackers are employed to memorize the protagonist's local psychological states to capture their inner temporal relationships. In…
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Taxonomy
TopicsTopic Modeling · Advanced Text Analysis Techniques · Artificial Intelligence in Games
