{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,23]],"date-time":"2024-09-23T13:10:23Z","timestamp":1727097023012},"reference-count":21,"publisher":"Institute of Electronics, Information and Communications Engineers (IEICE)","issue":"5","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEICE Trans. Inf. & Syst."],"published-print":{"date-parts":[[2022,5,1]]},"DOI":"10.1587\/transinf.2021dap0008","type":"journal-article","created":{"date-parts":[[2022,4,30]],"date-time":"2022-04-30T22:17:12Z","timestamp":1651357032000},"page":"928-935","source":"Crossref","is-referenced-by-count":0,"title":["Toward Generating Robot-Robot Natural Counseling Dialogue"],"prefix":"10.1587","volume":"E105.D","author":[{"given":"Tomoya","family":"HASHIGUCHI","sequence":"first","affiliation":[{"name":"Graduate School of Applied Informatics, University of Hyogo"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Takehiro","family":"YAMAMOTO","sequence":"additional","affiliation":[{"name":"School of Social Information Science, University of Hyogo"},{"name":"Graduate School of Information Science, University of Hyogo"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sumio","family":"FUJITA","sequence":"additional","affiliation":[{"name":"Yahoo Japan Corporation"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hiroaki","family":"OHSHIMA","sequence":"additional","affiliation":[{"name":"Graduate School of Applied Informatics, University of Hyogo"},{"name":"School of Social Information Science, University of Hyogo"},{"name":"Graduate School of Information Science, University of Hyogo"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"532","reference":[{"key":"1","doi-asserted-by":"crossref","unstructured":"[1] K. Hayashi, D. Sakamoto, T. Kanda, M. Shiomi, S. Koizumi, H. Ishiguro, T. Ogasawara, and N. Hagita, \u201cHumanoid robots as a passive-social medium: a field experiment at a train station,\u201d Proc. HRI'07, pp.137-144, March 2007. 10.1145\/1228716.1228735","DOI":"10.1145\/1228716.1228735"},{"key":"2","doi-asserted-by":"publisher","unstructured":"[2] K. Hayashi, T. Kanda, T. Miyashita, H. Ishiguro, and N. Hagita, \u201cRobot manzai: Robot conversation as a passive-social medium,\u201d Int. J. Humanoid Robotics, vol.5, no.1, pp.67-86, 2008. 10.1142\/S0219843608001315","DOI":"10.1142\/S0219843608001315"},{"key":"3","doi-asserted-by":"crossref","unstructured":"[3] T. Wolf, V. Sanh, J. Chaumond, and C. Delangue, \u201cTransferTransfo: A Transfer learning approach for neural network based conversational agents,\u201d Proc. NIPS'18, pp.1-6, 2018.","DOI":"10.18653\/v1\/P18-2001"},{"key":"4","doi-asserted-by":"crossref","unstructured":"[4] Y. Zhang, S. Sun, M. Galley, Y.C. Chen, C. Brockett, X. Gao, J. Gao, J. Liu, and B. Dolan, \u201cDialoGPT: Large-scale generative pre-training for conversational response generation,\u201d Proc. ACL'2020 system demonstration, pp.270-279, 2020. 10.18653\/v1\/2020.acl-demos.30","DOI":"10.18653\/v1\/2020.acl-demos.30"},{"key":"5","doi-asserted-by":"crossref","unstructured":"[5] H. Rashkin, E.M. Smith, M. Li, and Y.L. Boureau, \u201cTowards empathetic open-domain conversation models: A new benchmark and dataset,\u201d Proc. ACL'19, pp.5370-5381, 2019. 10.18653\/v1\/P19-1534","DOI":"10.18653\/v1\/P19-1534"},{"key":"6","doi-asserted-by":"crossref","unstructured":"[6] P. Zhong, Y. Zhu, Y. Liu, C. Zhang, H. Wang, Z. Nie, and C. Miao, \u201cTowards persona-based empathetic conversational models,\u201d Proc. EMNLP'20, pp.6556-6566, 2020. 10.18653\/v1\/2020.emnlp-main.531","DOI":"10.18653\/v1\/2020.emnlp-main.531"},{"key":"7","doi-asserted-by":"publisher","unstructured":"[7] W. Levinson, R. Gorawara-Bhat, and J. Lamb, \u201cA Study of patient clues and physician responses in primary care and surgical settings,\u201d JAMA, vol.284, no.8, pp.1021-1027, 2000. 10.1001\/jama.284.8.1021","DOI":"10.1001\/jama.284.8.1021"},{"key":"8","doi-asserted-by":"publisher","unstructured":"[8] K. Wentzel, \u201cStudent motivation in middle school: The role of perceived pedagogical caring.,\u201d J. Educational Psychology, vol.89, no.3, pp.411-419, 1997. 10.1037\/0022-0663.89.3.411","DOI":"10.1037\/0022-0663.89.3.411"},{"key":"9","doi-asserted-by":"crossref","unstructured":"[9] T. Kim, M. Ruensuk, and H. Hong, \u201cIn helping a vulnerable bot, you help yourself: Designing a social bot as a care-receiver to promote mental health and reduce stigma,\u201d Proc. CHI'20, pp.1-13, April 2020. 10.1145\/3313831.3376743","DOI":"10.1145\/3313831.3376743"},{"key":"10","doi-asserted-by":"crossref","unstructured":"[10] K. Cho, B. van Merri\u00ebnboer, C. Gulcehre, D. Bahdanau, F. Bougares, H. Schwenk, and Y. Bengio, \u201cLearning phrase representations using RNN encoder-decoder for statistical machine translation,\u201d Proc. EMNLP'14, pp.1724-1734, Oct. 2014. 10.3115\/v1\/D14-1179","DOI":"10.3115\/v1\/D14-1179"},{"key":"11","unstructured":"[11] I. Sutskever, O. Vinyals, and Q.V. Le, \u201cSequence to sequence learning with neural networks,\u201d Proc. NIPS'14, pp.3104-3112, Dec. 2014."},{"key":"12","unstructured":"[12] O. Vinyals and Q. Le, \u201cA neural conversational model,\u201d Proc. ICML'15 Deep Learning Workshop, pp.1-7, 2015."},{"key":"13","doi-asserted-by":"crossref","unstructured":"[13] A. Sordoni, Y. Bengio, H. Vahabi, C. Lioma, J. Grue Simonsen, and J.Y. Nie, \u201cA hierarchical recurrent encoder-decoder for generative context-aware query suggestion,\u201d Proc. CIKM'15, pp.553-562, Oct. 2015. 10.1145\/2806416.2806493","DOI":"10.1145\/2806416.2806493"},{"key":"14","unstructured":"[14] I.V. Serban, A. Sordoni, R. Lowe, L. Charlin, J. Pineau, A. Courville, and Y. Bengio, \u201cA hierarchical latent variable encoder-decoder model for generating dialogues,\u201d Proc. AAAI'17, pp.3295-3301, Feb. 2017."},{"key":"15","unstructured":"[15] A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A.N. Gomez, u. Kaiser, and I. Polosukhin, \u201cAttention is all you need,\u201d Proc. NIPS'17, pp.6000-6010, 2017."},{"key":"16","unstructured":"[16] A. Radford, K. Narasimhan, T. Salimans, and I. Sutskever, \u201cImproving language understanding by generative pre-training,\u201d pp.1-12, 2018."},{"key":"17","unstructured":"[17] J. Devlin, M.W. Chang, K. Lee, and K. Toutanova, \u201cBERT: Pre-training of deep bidirectional transformers for language understanding,\u201d Proc. NAACL'19, pp.4171-4186, 2019. 10.18653\/v1\/N19-1423"},{"key":"18","unstructured":"[18] K. Jaidka, I. Singh, J. Lu, N. Chhaya, and L. Ungar, \u201cA report of the CL-Aff OffMyChest Shared Task: Modeling supportiveness and disclosure,\u201d Proc. AAAI'20 Workshop on Affective Content Analysis, pp.1-12, 2020."},{"key":"19","doi-asserted-by":"crossref","unstructured":"[19] Q. Li, H. Chen, Z. Ren, P. Ren, Z. Tu, and Z. Chen, \u201cEmpDG: Multi-resolution interactive empathetic dialogue generation,\u201d Proc. COLING'2020, pp.4454-4466, Dec. 2020. 10.18653\/v1\/2020.coling-main.394","DOI":"10.18653\/v1\/2020.coling-main.394"},{"key":"20","unstructured":"[20] S. Roller, Y.L. Boureau, J. Weston, A. Bordes, E. Dinan, A. Fan, D. Gunning, D. Ju, M. Li, S. Poff, P. Ringshia, K. Shuster, E.M. Smith, A.D. Szlam, J. Urbanek, and M. Williamson, \u201cOpen-domain conversational agents: Current progress, open problems, and future directions,\u201d arXiv:2006.12442, 2020."},{"key":"21","doi-asserted-by":"publisher","unstructured":"[21] J. Deriu, A. Rodrigo, A. Otegi, G. Echegoyen, S. Rosset, E. Agirre, and M. Cieliebak, \u201cSurvey on evaluation methods for dialogue systems,\u201d Artificial Intelligence Review, vol.54, pp.755-810, 2020. 10.1007\/s10462-020-09866-x","DOI":"10.1007\/s10462-020-09866-x"}],"container-title":["IEICE Transactions on Information and Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.jstage.jst.go.jp\/article\/transinf\/E105.D\/5\/E105.D_2021DAP0008\/_pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,23]],"date-time":"2024-09-23T12:49:50Z","timestamp":1727095790000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.jstage.jst.go.jp\/article\/transinf\/E105.D\/5\/E105.D_2021DAP0008\/_article"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,5,1]]},"references-count":21,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2022]]}},"URL":"https:\/\/doi.org\/10.1587\/transinf.2021dap0008","relation":{},"ISSN":["0916-8532","1745-1361"],"issn-type":[{"type":"print","value":"0916-8532"},{"type":"electronic","value":"1745-1361"}],"subject":[],"published":{"date-parts":[[2022,5,1]]},"article-number":"2021DAP0008"}}