Evaluation of a system for noun concepts acquisition from utterances about images (SINCA) using daily conversation data

Abstract

For a robot working in an open environment, a task-oriented language capability will not be sufficient. In order to adapt to the environment, such a robot will have to learn language dynamically. We developed a System for Noun Concepts Acquisition from utterances about Images, SINCA in short. It is a language acquisition system without knowledge of grammar and vocabulary, which learns noun concepts from user utterances. We recorded a video of a child’s daily life to collect dialogue data that was spoken to and around him. The child is a member of a family consisting of the parents and his sister. We evaluated the performance of SINCA using the collected data. In this paper, we describe the algorithms of SINCA and an evaluation experiment. We work on Japanese language acquisition, however our method can easily be adapted to other languages.