Apprentice of Oz: Human in the Loop System for Conversational Robot Wizard of Oz

Abstract

Conversational robots that exhibit human-level abilities in physical and verbal conversation are widely used in human-robot interaction studies, along with the Wizard of Oz protocol. However, even with the protocol, manipulating the robot to move and talk is cognitively demanding. A preliminary study with a humanoid was conducted to observe difficulties wizards experienced in each of four subtasks: attention, decision, execution, and reflection. Apprentice of Oz is a human-in-the-loop Wizard of Oz system designed to reduce the wizard's cognitive load in each subtask. Each task is co-performed by the wizard and the system. This paper describes the system design from the view of each subtask.