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Entrainable Neural Conversation Model Based on Reinforcement Learning

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dc.contributor.author KAWANO, SEIYA en
dc.contributor.author MIZUKAMI, MASAHIRO en
dc.contributor.author YOSHINO, KOICHIRO en
dc.contributor.author NAKAMURA, SATOSHI en
dc.date.accessioned 2020-11-26T07:50:30Z en
dc.date.available 2020-11-26T07:50:30Z en
dc.date.issued 2020-10-08 en
dc.identifier.uri http://hdl.handle.net/10061/14161 en
dc.description.abstract The synchronization of words in conversation, called entrainment, is generally observed in human-human conversations. Entrainment has a high correlation with dialogue success, naturalness, and engagement. In this article, we de ne entrainment scores based on the word similarities in semantic space to evaluate the entrainment of system generation.We optimized a neural conversation model to the entrainment scores using reinforcement learning so that the system can control the degree of entrainment of the system response. Experimental results showed that the proposed entrainable neural conversation model generated comparable or more natural responses than conventional models and satisfactorily controlled the degree of entrainment of the generated responses. en
dc.language.iso en en
dc.publisher IEEE en
dc.relation.isreplacedby https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9206588 en
dc.rights This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. For more information, see https://creativecommons.org/licenses/by-nc-nd/4.0/ en
dc.subject Neural conversation model en
dc.subject conditional response generation en
dc.subject entrainment en
dc.subject dialogue evaluation en
dc.subject reinforcement learning en
dc.title Entrainable Neural Conversation Model Based on Reinforcement Learning en
dc.type.nii Journal Article en
dc.contributor.transcription カワノ, セイヤ ja
dc.contributor.transcription ヨシノ, コウイチロウ ja
dc.contributor.transcription ナカムラ, サトシ ja
dc.contributor.alternative 河野, 誠也 ja
dc.contributor.alternative 吉野, 幸一郎 ja
dc.contributor.alternative 中村, 哲 ja
dc.textversion none en
dc.identifier.eissn 2169-3536 en
dc.identifier.jtitle IEEE Access en
dc.identifier.volume 8 en
dc.relation.doi 10.1109/ACCESS.2020.3027099 en
dc.identifier.NAIST-ID 85620920 en
dc.identifier.NAIST-ID 74651712 en
dc.identifier.NAIST-ID 73296626 en


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