Persona-Guided Planning for Controlling the Protagonist’s Persona in Story Generation (2022)

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 .

## introduction stories are important for entertainment. they are made engaging often by portraying animated and believable characters since a story plot unfolds as the characters interact with the object world created in the story @xcite . cognitive psychologists determined that the ability of an audience to comprehend a story is strongly correlated with the characters' believability @xcite . and the believability mostly depends on whether the characters' reaction to what has happened and their deliberate behavior accord with their personas (e.g., weakness, abilities, occupations) @xcite . context: • • • artur boruc, a polish national pilot, was going to get the group infiltrated into the area and prepared for the attack. persona a: @xcite a skilled pilot, trained in operating flight controls on the most common planes. ## related work story generation there have been wide explorations for various story generation tasks, such as story ending generation @xcite , story completion @xcite and story generation from short prompts @xcite , titles @xcite or beginnings @xcite . to improve the coherence of story generation, prior studies usually first predicted intermediate representations as plans and then generated stories conditioned on the plans. the plans could be a series of keywords @xcite , an action sequence @xcite or a keyword distribution @xcite . in terms of character modeling in stories, some studies focused on learning characters' persona as latent variables @xcite or represented characters as learnable embeddings @xcite @xcite . @xcite proposed five types of specific personas for visual story generation. @xcite formulated two new tasks including character description generation and character identification. in contrast, we focus on story generation conditioned on personas in a free form of text to describe one's strengths, weaknesses, abilities, occupations and goals. controllable generation controllable text generation aims to generate texts with specified attributes. for example, @xcite pretrained a language model conditioned on control codes of different attributes (e.g., domains, links). @xcite proposed to combine a pretrained language model with trainable attribute classifiers to increase the likelihood of the target attributes. recent studies in dialogue models focused on controlling through sentence functions @xcite , politeness @xcite and conversation targets @xcite . for storytelling, @xcite incorporated additional phrases to guide the story generation. brahman and chaturvedi (2020) proposed to control the emotional trajectory in a story by regularizing the generation process with reinforcement learning. rashkin et al. (2020) generated stories from outlines of characters and events by tracking the dynamic plot states with a memory network. a similar research to ours is zhang et al. ( 2018 ), which introduced the personachat dataset for endowing the chit-chat dialogue agents with a consis-conper ... artur boruc, a polish national pilot, was going to get the group ... ## methodology we define our task as follows: given a context ## conclusion we present conper, a planning-based model for a new task aiming at controlling the protagonist's persona in story generation. we propose target planning to explicitly model the relations between persona-related events and input personas, and plot planning to learn the keyword transition in a story with the guidance of predicted personarelated events and external commonsense knowledge. extensive experiments show that conper can generate more coherent stories with better consistency with the input personas than strong baselines. further analysis also indicates the better persona-controllability of conper. would cost average one minute for an annotator to finish a comparison.