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Internet Technol."],"published-print":{"date-parts":[[2021,11,30]]},"abstract":"<jats:p>In an open-domain dialogue system, recognition and expression of emotions are the key factors for success. Most of the existing research related to Chinese dialogue systems aims at improving the quality of content but ignores the expression of human emotions. In this article, we propose a Chinese emotional dialogue response generation algorithm based on reinforcement learning that can generate responses not only according to content but also according to emotion. In the proposed method, a multi-emotion classification model is first used to add emotion labels to the corpus of post-response pairs. Then, with the help of reinforcement learning, the reward function is constructed based on two aspects, namely, emotion and content. Among the generated candidates, the system selects the one with long-term success as the best reply. At the same time, to avoid safe responses and diversify dialogue, a diversity beam search algorithm is applied in the decoding process. The comparative experiments demonstrate that the proposed model achieves satisfactory results according to both automatic and human evaluations.<\/jats:p>","DOI":"10.1145\/3446390","type":"journal-article","created":{"date-parts":[[2021,7,22]],"date-time":"2021-07-22T14:32:41Z","timestamp":1626964361000},"page":"1-17","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":5,"title":["Chinese Emotional Dialogue Response Generation via Reinforcement Learning"],"prefix":"10.1145","volume":"21","author":[{"given":"Rushi","family":"Lan","sequence":"first","affiliation":[{"name":"Guangxi Key Laboratory of Image and Graphic Intelligent Processing, Guilin University of Electronic Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jing","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Information Security, Guilin University of Electronic Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenming","family":"Huang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Information Security, Guilin University of Electronic Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhenrong","family":"Deng","sequence":"additional","affiliation":[{"name":"School of Computer Science and Information Security, Guilin University of Electronic Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiyan","family":"Sun","sequence":"additional","affiliation":[{"name":"National Local Joint Engineering Research Center of Satellite Navigation and Location Service, Guilin University of Electronic Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhuo","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering, The University of British Columbia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaonan","family":"Luo","sequence":"additional","affiliation":[{"name":"National and Local Joint Engineering Research Center of Satellite Navigation and Location Service, Guilin University of Electronic Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2021,7,22]]},"reference":[{"doi-asserted-by":"publisher","key":"e_1_2_1_1_1","DOI":"10.21437\/Interspeech.2016-1175"},{"volume-title":"3rd International Conference on Learning Representations (ICLR\u201915)","year":"2015","author":"Bahdanau Dzmitry","key":"e_1_2_1_2_1"},{"doi-asserted-by":"publisher","key":"e_1_2_1_3_1","DOI":"10.1109\/TII.2019.2911697"},{"doi-asserted-by":"publisher","key":"e_1_2_1_4_1","DOI":"10.1145\/1961189.1961199"},{"doi-asserted-by":"publisher","key":"e_1_2_1_5_1","DOI":"10.1142\/S0218488501001125"},{"doi-asserted-by":"publisher","key":"e_1_2_1_6_1","DOI":"10.1109\/ICIEA.2018.8398173"},{"doi-asserted-by":"publisher","key":"e_1_2_1_7_1","DOI":"10.1016\/j.neucom.2020.02.102"},{"doi-asserted-by":"publisher","key":"e_1_2_1_8_1","DOI":"10.18653\/v1\/W17-3207"},{"doi-asserted-by":"publisher","key":"e_1_2_1_9_1","DOI":"10.1109\/SLT.2014.7078634"},{"volume-title":"Generating text with deep reinforcement learning. 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