Suzume-chan: Your Personal Navigator as an Embodied Information Hub

TL;DR

This paper introduces Suzume-chan, an embodied AI agent that enhances knowledge sharing by creating a human-centered, conversational experience using physical interaction and social presence theory.

Contribution

It proposes and develops Suzume-chan, a novel embodied information hub that combines physical form and conversational AI to improve knowledge transfer and social presence.

Findings

Suzume-chan reduces psychological distance in knowledge sharing.

The prototype demonstrates effective spoken explanation learning.

Enhances human-centered communication through physical and conversational interaction.

Abstract

Access to expert knowledge often requires real-time human communication. Digital tools improve access to information but rarely create the sense of connection needed for deep understanding. This study addresses this issue using Social Presence Theory, which explains how a feeling of "being together" enhances communication. An "Embodied Information Hub" is proposed as a new way to share knowledge through physical and conversational interaction. The prototype, Suzume-chan, is a small, soft AI agent running locally with a language model and retrieval-augmented generation (RAG). It learns from spoken explanations and responds through dialogue, reducing psychological distance and making knowledge sharing warmer and more human-centered.