Abstract
This paper presents a chat-like conversational system, and that generates a reply by selecting an appropriate reply generating module. Such modules consist in selecting a sentence from an article of Web news, retrieving a definition sentence in Wikipedia, question-answering, and so on. A dialogue strategy corresponds to which reply generating module should be chosen according to a user input and the dialogue history, and is learned in the MDP framework. User evaluations showed that our system could learn an appropriate dialogue strategy, and perform natural dialogues.
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References
Bellman R (1957) A markov decision process. J Math Mech 6(679–684):2
Kaelbling L, Littman M, Cassandra A (1998) Planning and acting in partially observable stochastic domains. Artif Intell 101(1–2):99–134
Levin E, Pieraccini R, Eckert W (1998) Using markov decision process for learning dialogue strategies. In: Proceedings of the 1998 IEEE international conference on acoustics, speech and signal processing. IEEE, pp 201–204
Meguro T, Higashinaka R, Minami Y, Dohsaka K (2010) Controlling listening-oriented dialogue using partially observable markov decision processes. In: Proceedings of the 23rd international conference on computational linguistics, pp 761–769
Nakano M, Funakoshi K, Hasegawa Y, Tsujino H (2008) A framework for building conversational agents based on a multi-expert model. In: Proceedings of the 9th SIGdial workshop on discourse and dialogue, pp 88–91
Weizenbaum J (1966) Eliza—a computer program for the study of natural language communication between man and machine. Commun ACM 9(1):36–45
Yoshino K, Mori S, Kawahara T (2011) Spoken dialogue system based on information extraction using similarity of predicate argument structures. In: Proceedings of the SIGDIAL 2011 Conference, pp 59–66
Young S, Gasic M, Keizer S, Mairesse F, Schatzmann J, Thomson B, Yu K (2010) The hidden information state model: a practical framework for pomdp-based spoken dialogue management. Comput Speech Lang 24(2):150–174
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© 2016 Springer International Publishing Switzerland
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Shibata, T., Egashira, Y., Kurohashi, S. (2016). Chat-Like Conversational System Based on Selection of Reply Generating Module with Reinforcement Learning. In: Rudnicky, A., Raux, A., Lane, I., Misu, T. (eds) Situated Dialog in Speech-Based Human-Computer Interaction. Signals and Communication Technology. Springer, Cham. https://doi.org/10.1007/978-3-319-21834-2_6
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DOI: https://doi.org/10.1007/978-3-319-21834-2_6
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