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.\\
@InProceedings{YOSHINO18.464, author = {Koichiro Yoshino and Hiroki Tanaka and Kyoshiro Sugiyama and Makoto Kondo and Satoshi Nakamura}, title = "{Japanese Dialogue Corpus of Information Navigation and Attentive Listening Annotated with Extended ISO-24617-2 Dialogue Act Tags}", booktitle = {Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)}, year = {2018}, month = {May 7-12, 2018}, address = {Miyazaki, Japan}, editor = {Nicoletta Calzolari (Conference chair) and Khalid Choukri and Christopher Cieri and Thierry Declerck and Sara Goggi and Koiti Hasida and Hitoshi Isahara and Bente Maegaard and Joseph Mariani and Hélène Mazo and Asuncion Moreno and Jan Odijk and Stelios Piperidis and Takenobu Tokunaga}, publisher = {European Language Resources Association (ELRA)}, isbn = {979-10-95546-00-9}, language = {english} }
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