如果红能说话会怎样？使用大语言模型生成动态对话
What if Red Can Talk? Dynamic Dialogue Generation Using Large Language Models
AI总结：
本研究提出一个由知识图谱增强大语言模型的对话填充框架，在《最终幻想7重制版》和《宝可梦》中验证了GPT-4生成动态角色对话的能力，旨在提升RPG玩家沉浸感。
摘要：
角色扮演游戏（RPGs）为玩家提供了一个丰富且可交互的世界以供探索。对话是开发者与玩家之间沟通的主要手段，表现为指南、NPC互动和故事讲述等多种形式。虽然大多数游戏依赖书面剧本来定义主线故事和角色性格，但角色之间的日常互动可以显著提升玩家的沉浸感。随着大语言模型（LLMs）的出现，我们引入了一个对话填充框架，该框架利用由知识图谱增强的LLMs来生成动态且符合语境的角色互动。我们在《最终幻想7重制版》和《宝可梦》的环境中测试了该框架，提供了定性和定量证据，证明了GPT-4能够以设定的性格行动并生成对话。然而，仍存在一些缺陷，例如GPT-4表现得过于积极，或者像成熟这样更微妙的性格，其生成质量往往不如胆怯等更外显的特质。本研究旨在帮助开发者制作更细腻的填充对话，从而丰富玩家的沉浸感并提升整体的RPG体验。
英文摘要：
Role-playing games (RPGs) provide players with a rich, interactive world to explore. Dialogue serves as the primary means of communication between developers and players, manifesting in various forms such as guides, NPC interactions, and storytelling. While most games rely on written scripts to define the main story and character personalities, player immersion can be significantly enhanced through casual interactions between characters. With the advent of large language models (LLMs), we introduce a dialogue filler framework that utilizes LLMs enhanced by knowledge graphs to generate dynamic and contextually appropriate character interactions. We test this framework within the environments of Final Fantasy VII Remake and Pokemon, providing qualitative and quantitative evidence that demonstrates GPT-4's capability to act with defined personalities and generate dialogue. However, some flaws remain, such as GPT-4 being overly positive or more subtle personalities, such as maturity, tend to be of lower quality compared to more overt traits like timidity. This study aims to assist developers in crafting more nuanced filler dialogues, thereby enriching player immersion and enhancing the overall RPG experience.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
