SINCA: System for Noun Concepts Acquisition from Utterances about Images

Abstract

For a robot working in an open environment, a task-oriented language ability will not be sufficient. To adapt to the environment, such a robot will have to learn language dynamically. In this paper we propose a system which acquires noun concepts (labels for images) based on an infant vocabulary acquisition model. In order to improve the performance, we have introduced label acquisition rules into this system. The evaluation experiment shows that the rules are effective in extracting noun concepts. We also evaluate user impressions of the system using the rating scale method. The experimental results show that the system leaves a good impression on people.