What information should a dialogue system understand?: Collection and analysis of perceived information in chat-oriented dialogue

Abstract

It is important for chat-oriented dialogue systems to be able to understand the various information from user utterances. However, no study has yet clarified the types of information that should be understood by such systems. With this purpose in mind, we collected and clustered information that humans perceive from each utterance (perceived information) in chat-oriented dialogue. We then clarified, i.e., categorized, the types of perceived information. The types were evaluated on the basis of inter-annotator agreement, which showed substantial agreement and demonstrated the validity of our categorization. To the best of our knowledge, this study is the first to clarify the types of information that a chat-oriented dialogue system should understand.