The ChatBot Feels You - A Counseling Service Using Emotional Response Generation

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dc.contributor.authorLee, Dongkeonko
dc.contributor.authorOh, Kyo-Joongko
dc.contributor.authorChoi, Ho-Jinko
dc.date.accessioned2018-01-23T01:16:00Z-
dc.date.available2018-01-23T01:16:00Z-
dc.date.created2017-12-28-
dc.date.created2017-12-28-
dc.date.issued2017-02-13-
dc.identifier.citationIEEE International Conference on Big Data and Smart Computing (BigComp), pp.437 - 440-
dc.identifier.issn2375-933X-
dc.identifier.urihttp://hdl.handle.net/10203/237786-
dc.description.abstractEarly study tries to use chatbot for counseling services. They changed drinking habit of who being consulted by leading them via intervene chatbot. However, the application did not concerned about psychiatric status through continuous conversation with user monitoring. Furthermore, they had no ethical judgment method that about the intervention of the chatbot. We argue that more reasonable and continuous emotion recognition will make better mental healthcare experiment. It will be more proper clinical psychiatric consolation in ethical view as well. This paper suggests a introduce a novel chatbot system for psychiatric counseling service. Our system understands content of conversation based on recent natural language processing (NLP) methods with emotion recognition. It senses emotional flow through the continuous observation of conversation. Also, we generate personalized counseling response from user input, to do this, we use additional constrains to generation model for the proper response generation which can detect conversational context, user emotion and expected reaction.-
dc.languageEnglish-
dc.publisherInstitute of Electrical and Electronics Engineers Inc.-
dc.titleThe ChatBot Feels You - A Counseling Service Using Emotional Response Generation-
dc.typeConference-
dc.identifier.wosid000403390900076-
dc.identifier.scopusid2-s2.0-85017666234-
dc.type.rimsCONF-
dc.citation.beginningpage437-
dc.citation.endingpage440-
dc.citation.publicationnameIEEE International Conference on Big Data and Smart Computing (BigComp)-
dc.identifier.conferencecountryKO-
dc.identifier.conferencelocationMaison Glad Jeju-
dc.identifier.doi10.1109/BIGCOMP.2017.7881752-
dc.contributor.localauthorChoi, Ho-Jin-
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CS-Conference Papers(학술회의논문)
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