Stylized Story Generation with Style-Guided Planning
Xiangzhe Kong, Jialiang Huang, Ziquan Tung, Jian Guan, Minlie Huang

TL;DR
This paper introduces a new task of stylized story generation with style-guided planning, proposing a model that first plans style keywords and then generates stories, demonstrating controllable generation of emotion- and event-driven stories.
Contribution
The paper presents a novel generation model that incorporates style-guided planning for controllable story generation, along with automatic metrics for style consistency evaluation.
Findings
Model effectively controls story style based on specified keywords.
Experiments show successful generation of emotion- and event-driven stories.
Provides insights for future research in stylized story generation.
Abstract
Current storytelling systems focus more ongenerating stories with coherent plots regard-less of the narration style, which is impor-tant for controllable text generation. There-fore, we propose a new task, stylized story gen-eration, namely generating stories with speci-fied style given a leading context. To tacklethe problem, we propose a novel generationmodel that first plans the stylized keywordsand then generates the whole story with theguidance of the keywords. Besides, we pro-pose two automatic metrics to evaluate theconsistency between the generated story andthe specified style. Experiments demonstratesthat our model can controllably generateemo-tion-driven orevent-driven stories based onthe ROCStories dataset (Mostafazadeh et al.,2016). Our study presents insights for stylizedstory generation in further research.
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Taxonomy
TopicsTopic Modeling · Natural Language Processing Techniques · Artificial Intelligence in Games
