CLIO: A Tour Guide Robot with Co-speech Actions for Visual Attention Guidance and Enhanced User Engagement

TL;DR

CLIO is a tour guide robot that uses co-speech actions like eye contact, head movement, and laser pointing, coordinated by an LLM, to guide visitors' visual attention and improve engagement during guided tours.

Contribution

This paper introduces CLIO, a novel robot system that combines co-speech actions with LLM coordination to enhance visitor engagement and visual attention guidance in exhibition tours.

Findings

CLIO's actions effectively guide visitors' visual attention.

Visitors showed increased engagement with CLIO compared to audio-only guides.

User feedback confirmed the system's engaging and attention-directing capabilities.

Abstract

While audio guides can offer rich information about an exhibit, it is challenging for visitors to focus on specific exhibit details based only on the verbal description. We present \textit{CLIO}, a tour guide robot with co-speech actions to direct visitors' visual attention and thus enhance the overall user engagement in a guided tour. \textit{CLIO} is equipped with designed actions to engage visitors. It builds eye contact with the visitor through tracking a visitor's face and blinking its eyes, or orient their attention by its head movement and laser pointer. We further use a Large Language Model (LLM) to coordinate the designed actions with a given narrative script for exhibition. We conducted a user study to evaluate the \textit{CLIO} system in a mock-up exhibition of historical photographs. We collected feedback from questionnaires and quantitative data from a mobile eye tracker. Experimental results validated that the engaging actions are well designed and demonstrated its efficacy in guiding visual attention of the visitors. It was evidenced that \textit{CLIO} achieved an enhanced engagement compared to the baseline system with only audio guidance.