CHAE: Fine-Grained Controllable Story Generation with Characters, Actions and Emotions

Xinpeng Wang, Han Jiang, Zhihua Wei, Shanlin Zhou


Abstract
Story generation has emerged as an interesting yet challenging NLP task in recent years. Some existing studies aim at generating fluent and coherent stories from keywords and outlines; while others attempt to control the global features of the story, such as emotion, style and topic. However, these works focus on coarse-grained control on the story, neglecting control on the details of the story, which is also crucial for the task. To fill the gap, this paper proposes a model for fine-grained control on the story, which allows the generation of customized stories with characters, corresponding actions and emotions arbitrarily assigned. Extensive experimental results on both automatic and human manual evaluations show the superiority of our method. It has strong controllability to generate stories according to the fine-grained personalized guidance, unveiling the effectiveness of our methodology. Our code is available at https://github.com/victorup/CHAE.
Anthology ID:
2022.coling-1.559
Volume:
Proceedings of the 29th International Conference on Computational Linguistics
Month:
October
Year:
2022
Address:
Gyeongju, Republic of Korea
Venue:
COLING
SIG:
Publisher:
International Committee on Computational Linguistics
Note:
Pages:
6426–6435
Language:
URL:
https://aclanthology.org/2022.coling-1.559
DOI:
Bibkey:
Cite (ACL):
Xinpeng Wang, Han Jiang, Zhihua Wei, and Shanlin Zhou. 2022. CHAE: Fine-Grained Controllable Story Generation with Characters, Actions and Emotions. In Proceedings of the 29th International Conference on Computational Linguistics, pages 6426–6435, Gyeongju, Republic of Korea. International Committee on Computational Linguistics.
Cite (Informal):
CHAE: Fine-Grained Controllable Story Generation with Characters, Actions and Emotions (Wang et al., COLING 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.coling-1.559.pdf
Code
 victorup/chae
Data
Story Commonsense