https://scholars.lib.ntu.edu.tw/handle/123456789/580911
標題: | Personalized dialogue response generation learned from monologues | 作者: | Su F.-G Hsu A.R Tuan Y.-L HUNG-YI LEE |
公開日期: | 2019 | 卷: | 2019-September | 起(迄)頁: | 4160-4164 | 來源出版物: | Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH | 摘要: | Personalized responses are essential for having an informative and human-like conversation. Because it is difficult to collect a large amount of dialogues involved with specific speakers, it is desirable that chatbot can learn to generate personalized responses simply from monologues of individuals. In this paper, we propose a novel personalized dialogue generation method which reduces the training data requirement to dialogues without speaker information and monologues of every target speaker. In the proposed approach, a generative adversarial network ensures the responses containing recognizable personal characteristics of the target speaker, and a backward SEQ2SEQ model reconstructs the input message for keeping the coherence of the generated responses. The proposed model demonstrates its flexibility to respond to open-domain conversations, and the experimental results show that the proposed method performs favorably against prior work in coherence, personality classification, and human evaluation. Copyright ? 2019 ISCA |
URI: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85094428911&doi=10.21437%2fInterspeech.2019-1696&partnerID=40&md5=ddc3bf4d0aae0cbbd1bebb49b2798889 https://scholars.lib.ntu.edu.tw/handle/123456789/580911 |
ISSN: | 2308457X | DOI: | 10.21437/Interspeech.2019-1696 |
顯示於: | 電機工程學系 |
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