Persona-Guided Planning for Controlling the Protagonist’s Persona in Story Generation

Zhexin Zhang, Jiaxin Wen, Jian Guan, Minlie Huang


Abstract
Endowing the protagonist with a specific personality is essential for writing an engaging story. In this paper, we aim to control the protagonist’s persona in story generation, i.e., generating a story from a leading context and a persona description, where the protagonist should exhibit the specified personality through a coherent event sequence. Considering that personas are usually embodied implicitly and sparsely in stories, we propose a planning-based generation model named ConPer to explicitly model the relationship between personas and events. ConPer first plans events of the protagonist’s behavior which are motivated by the specified persona through predicting one target sentence, then plans the plot as a sequence of keywords with the guidance of the predicted persona-related events and commonsense knowledge, and finally generates the whole story. Both automatic and manual evaluation results demonstrate that ConPer outperforms state-of-the-art baselines for generating more coherent and persona-controllable stories. Our code is available at https://github.com/thu-coai/ConPer.
Anthology ID:
2022.naacl-main.245
Volume:
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Month:
July
Year:
2022
Address:
Seattle, United States
Editors:
Marine Carpuat, Marie-Catherine de Marneffe, Ivan Vladimir Meza Ruiz
Venue:
NAACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
3346–3361
Language:
URL:
https://aclanthology.org/2022.naacl-main.245
DOI:
10.18653/v1/2022.naacl-main.245
Bibkey:
Cite (ACL):
Zhexin Zhang, Jiaxin Wen, Jian Guan, and Minlie Huang. 2022. Persona-Guided Planning for Controlling the Protagonist’s Persona in Story Generation. In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 3346–3361, Seattle, United States. Association for Computational Linguistics.
Cite (Informal):
Persona-Guided Planning for Controlling the Protagonist’s Persona in Story Generation (Zhang et al., NAACL 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.naacl-main.245.pdf
Software:
 2022.naacl-main.245.software.zip
Video:
 https://aclanthology.org/2022.naacl-main.245.mp4
Code
 thu-coai/conper
Data
ConceptNet