Adaptive Psychological Distance in J apanese Spoken Human-Agent Dialogue: A Politeness-Based Management Model (2025)

Abstract: While existing spoken dialogue systems can adapt various aspects of interaction, systematic management of psychological distance through verbal politeness remains underexplored. Current approaches typically maintain fixed levels of formality and social distance, limiting naturalness in long-term human-agent interactions. We propose a novel dialogue management model that dynamically adjusts verbal politeness levels in Japanese based on user preferences. We evaluated the model using two pseudo-users with distinct distance preferences in daily conversations. Human observers (n=20) assessed the interactions, with 70% successfully distinguishing the intended social distance variations. The results demonstrate that systematic modulation of verbal politeness can create perceptibly different levels of psychological distance in spoken dialogue, with implications for culturally appropriate human-agent interaction in Japanese contexts.

## introduction the advancement of communication robots designed for frequent human interaction has accelerated significantly in recent years. by integrating human-like traits, these robots or agents are expected to become more approachable and relatable, facilitating broader adoption @xcite . with the advent of generative ai, robots can now understand and respond to human speech more effectively. however, understanding implied meaning, which is a cornerstone of human communication, remains challenging for ai. a critical yet understudied aspect of implied meaning is psychological distance, which plays a fundamental role in relationship development and maintenance. this concept has been extensively studied in psychological research, particularly through the lenses of personal space and politeness theory @xcite . although previous studies have explored personal space and politeness in robot interactions, there has been limited investigation into robots' active management of psychological distance during ongoing conversations @xcite @xcite , especially in japanese language contexts where politeness levels are deeply embedded in linguistic structures. traditional approaches to politeness have primarily relied on @xcite framework, which conceptualizes politeness as strategies to mitigate face-threatening acts. however, more recent theoretical developments by @xcite have shifted focus toward "relational work", emphasizing the dynamic and contextual nature of politeness rather than inherent linguistic features. similarly, @xcite contributions to understanding impoliteness have broadened the theoretical landscape. our work integrates these perspectives while addressing the specific linguistic features of japanese politeness. therefore, the present study addresses this gap by designing and implementing an internal model that enables robots to modulate psychological distance through linguistics behaviors grounded in an integrated politeness theory framework, with specific application to japanese language interaction. ## proposed system our system enables robots to converse at the psychological distance preferred by users through an internal state variable d that governs the selection of conversation strategies based on politeness theory. this value evolves through extended interactions, triggering corresponding adjustments in conversational approaches. the system maintains individual d values for each user, allowing for personalized distance calibration in japanese dialogue contexts. given the complexity of accurately inferring users' preferred psychological distance in realtime, we initially validate our approach using pseudo-users with predetermined distance preferences. this controlled setup enables systematic evaluation of the model's effectiveness. ## conclusion this work introduces an adaptive politenessbased model for managing psychological distance in human-agent dialogue. our experimental evaluation through simulated cohabitation scenarios demonstrates the model's effectiveness in maintaining natural conversation while creating perceptible variations in psychological distance. the results validate both the technical feasibility of our approach and its ability to accommodate diverse user preferences for social distance in dialogue interactions. future research will focus on enhancing realtime psychological distance estimation, validating the model with human users in naturalistic settings, and implementing the system in physical robot platforms. these advances will contribute to the development of more sophisticated and socially aware dialogue systems that can sustain meaningful long-term interactions with users.