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.
Categories: cs.HC