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Conversation System Based on Computational Intelligence for Robot Partner Using Smart Phone

Jinseok Woo, Naoyuki Kubota

Year
2013
Citations
21

Abstract

This paper proposes a conversation system based on multimodal perception for verbal communication between a human and a robot partner using various types of sensors. First, we describe the control structure of the robot partner and explain the architecture of the robot system. Next, evolutionary robot vision is applied to human and object detection. Next, a conversation system based on information ally structured space is proposed. Furthermore, we propose a method of conversation learning based on the flow of human utterance patterns and its related perceptual information. Finally, we show experimental results of the proposed method, and discuss the future direction on this research.

Keywords

ConversationComputer scienceRobotUtteranceHuman–computer interactionPerceptionArtificial intelligenceObject (grammar)Social robotRobot learning

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