Beyond Machines: The Impact of Robot Dialogue Types and Acoustic Parameters on Perceived Personality in Different Application Fields

This study investigates how dialogue types and acoustic parameters shape social robot personality perception. Grounded in the CASA paradigm, two experiments manipulated dialogue type (task-oriented vs. non-task-oriented), voice gender, pitch, and speech rate. Study 1 (educational robots) revealed that low-pitched male voices enhanced agreeableness and conscientiousness in task-oriented contexts. Study 2 (companion robots) showed that high-pitched female voices with slow speech rates increased acceptance and extraversion among older adults. We propose the Social Robot Acoustic Parameters Configuration Model (SRAPCM), situating contexts within a sociability–competence framework. These findings offer practical guidelines for context-aware vocal design. This research underscores the synergistic effect of semantic and acoustic channels in personality attribution and provides a structured approach to vocal design in human-robot interaction.