Talk With Socrates: Relation Between Perceived Agent Personality and User Personality in LLM-Based Natural Language Dialogue Using Virtual Reality

Large Language Models (LLMs) offer almost immediate human-like quality responses to user queries. Conversational agent systems support natural language dialogues utilizing LLM backends in combination with Text-to-Speech (TTS) and Automatic Speech Recognition (ASR) technologies, enabling life-like characters in virtual environments. This study investigates the relationship between user personality and perceived agent personality in LLM-based natural language dialogue. We adopt a Virtual Reality (VR) setting where the user can talk with the agent that assumes the role of Socrates, the famous philosopher. To this end, we utilize a three-dimensional (3D) avatar model resembling Socrates and use specific LLM prompts to get stylistic answers from OpenAI's Chat Completions Application Programming Interface (API). Our user study measures the agent's personality and the system's ease of use, quality, realism, and immersion concerning the user's self-reported personality. The results suggest that the user's conscientiousness, extraversion, and emotional stability have a moderate effect on certain personality factors and system qualities. User conscientiousness affects the perceived ease of use, quality, and realism, while user extraversion affects perceived agent conscientiousness, system realism, and immersion. Additionally, the user's emotional stability correlates with perceived extraversion and agreeableness.