In this paper, we consider mimicking fictional characters as a promising direction for building engaging conversation models. To this end, we present a new practical task where only a few utterances of each fictional character are available to generate responses mimicking them. Furthermore, we propose a new method named Pseudo Dialog Prompting (PDP) that generates responses by leveraging the power of large-scale language models with prompts containing the target character's utterances. To better reflect the style of the character, PDP builds the prompts in the form of dialog that includes the character's utterances as dialog history. Since only utterances of the characters are available in the proposed task, PDP matches each utterance with an appropriate pseudo-context from a predefined set of context candidates using a retrieval model. Through human and automatic evaluation, we show that PDP generates responses that better reflect the style of fictional characters than baseline methods.

本文介绍了一种使用虚构人物作为人工语言生成模型的实现方向，提出了一种名为“Pseudo Dialog Prompting”的新方法，通过大型语言模型结合虚构人物的话语，生成模仿虚构人物风格的回应。研究表明，该方法能够更好地提取虚构人物的风格特点。

模仿小说角色进行开放领域聊天的聊天机器人只需少量话语