Hearing the Robot's Mind: Sonification for Explicit Feedback in Human-Robot Interaction

TL;DR

This paper investigates using sonification to provide explicit auditory feedback from social robots, aiming to improve mutual understanding and communication effectiveness in human-robot interaction.

Contribution

It introduces a novel sonification method to convey the robot's internal states related to perception and intentions, evaluated through user studies.

Findings

Sonification enhances robot expressivity and communication effectiveness.

Participants found auditory cues useful but uninteresting and unpleasant.

Design refinement is needed for better user experience.

Abstract

Social robots are required not only to understand human intentions but also to effectively communicate their intentions or own internal states to users. This study explores the use of sonification to provide explicit auditory feedback, enhancing mutual understanding in HRI. We introduce a novel sonification approach that conveys the robot's internal state, linked to its perception of nearby individuals and their interaction intentions. The approach is evaluated through a two-fold user study: an online video-based survey with $26$ participants and live experiments with $10$ participants. Results indicate that while sonification improves the robot's expressivity and communication effectiveness, the design of the auditory feedback needs refinement to enhance user experience. Participants found the auditory cues useful but described the sounds as uninteresting and unpleasant. These findings underscore the importance of carefully designed auditory feedback in developing more effective and engaging HRI systems.