Factors Influencing Human Perception of Robots During Communication Initiated by Task-Indeterminate Robots

Abstract

This study examines how failures in robot speech affect human acceptance of robots. The analysis focuses on conversations between humans and robots that engage in casual conversation, rather than performing specific tasks like industrial robots. The robot used in this study combines M5Stack, a speech synthesis server, a speech recognition server, and Chat-GPT. The method involves measuring acceptance of the robot through a questionnaire survey before the conversation. Then, a robot-initiated conversation lasting about 15 minutes is conducted, during which intentional mishearing by the robot is introduced. After the conversation, acceptance of the robot is measured again through a questionnaire survey. The study integrates the changes in acceptance measured by the questionnaire with the analysis of human actions towards the robot during the conversation, focusing mainly on speech, gaze, and facial orientation.