A Case study of Edutainment Robot: Applying Voice Question Answering to Intelligent Robot

Abstract

This paper presents a case study of edutainment robot, which is an intelligent robot for educational use with a voice-QA model applied. The emphatic functions of our robot are: analyzing spoken question from a student, finding an appropriate answer in Korean encyclopedia, and then serving the answer with speech synthesis. We develop the ESTk, which is an Automatic Speech Recognition (ASR) system based on Finite State Network (FSN) for processing Korean spoken questions. For answer extraction, we utilize machine learning techniques and pattern extraction method. With our live-update interaction method, our robot can be extended with new knowledge in real-time. By conducting a quiz game, we show a possibility of our robot as an edutainment robot.