@inproceedings{zhang-etal-2022-persona,
title = "Persona-Guided Planning for Controlling the Protagonist{'}s Persona in Story Generation",
author = "Zhang, Zhexin and
Wen, Jiaxin and
Guan, Jian and
Huang, Minlie",
editor = "Carpuat, Marine and
de Marneffe, Marie-Catherine and
Meza Ruiz, Ivan Vladimir",
booktitle = "Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies",
month = jul,
year = "2022",
address = "Seattle, United States",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.naacl-main.245",
doi = "10.18653/v1/2022.naacl-main.245",
pages = "3346--3361",
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 \url{https://github.com/thu-coai/ConPer}.",
}
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<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.</abstract>
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%0 Conference Proceedings
%T Persona-Guided Planning for Controlling the Protagonist’s Persona in Story Generation
%A Zhang, Zhexin
%A Wen, Jiaxin
%A Guan, Jian
%A Huang, Minlie
%Y Carpuat, Marine
%Y de Marneffe, Marie-Catherine
%Y Meza Ruiz, Ivan Vladimir
%S Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
%D 2022
%8 July
%I Association for Computational Linguistics
%C Seattle, United States
%F zhang-etal-2022-persona
%X 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.
%R 10.18653/v1/2022.naacl-main.245
%U https://aclanthology.org/2022.naacl-main.245
%U https://doi.org/10.18653/v1/2022.naacl-main.245
%P 3346-3361
Markdown (Informal)
[Persona-Guided Planning for Controlling the Protagonist’s Persona in Story Generation](https://aclanthology.org/2022.naacl-main.245) (Zhang et al., NAACL 2022)
ACL