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Japanese Dialogue Corpus of Information Navigation and Attentive Listening Annotated with Extended ISO-24617-2 Dialogue Act Tags

Large-scale dialogue data annotated with dialogue states is necessary to model a natural conversation with machines. However, large-scale conventional dialogue corpora are mainly built for specified tasks (e.g., task-oriented systems for restaurant or bus information navigation) with specially designed dialogue states. Text-chat based dialogue corpora have also been built due to the growth of social communication through the internet; however, most of them do not reflect dialogue behaviors in face-to-face conversation, including backchannelings or interruptions. In this paper, we try to build a corpus that covers a wider range of dialogue tasks than existing task-oriented systems or text-chat systems, by transcribing face-to-face dialogues held in natural conversational situations in tasks of information navigation and attentive listening. The corpus is recorded in Japanese and annotated with an extended ISO-24617-2 dialogue act tag-set, which is defined to see behaviors in natural conversation. The developed data can be used to build a dialogue model based on the ISO-24617-2 dialogue act tags.\\