Abstract
Almost all of existing negotiation systems assume that their interlocutors (the user) are telling the truth. However, in negotiations, participants can tell lies to earn a profit. In this research, we proposed a negotiation dialog management system that detects user’s lies and designed a dialog behavior on how should the system react with. As a typical case, we built a dialog model of doctor-patient conversation on living habits domain. We showed that we can use partially observable Markov decision process (POMDP) to model this conversation and use reinforcement learning to train the system’s policy.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Baltrušaitis T, Robinson P, Morency L-P (2016) Openface: an open source facial behavior analysis toolkit. In: 2016 IEEE winter conference on applications of computer vision (WACV). IEEE, pp 1–10
Bonet B (2002) An e-optimal grid-based algorithm for partially observable markov decision processes. In: Proceedings of the 19th international conference on machine learning (ICML-02)
Efstathiou I, Lemon O (2014) Learning non-cooperative dialogue behaviours. In: Proceedings of the 15th annual meeting of the special interest group on discourse and dialogue (SIGDIAL). Association for Computational Linguistics, Philadelphia, PA, USA, pp 60–68. http://www.aclweb.org/anthology/W14-4308
Eyben F, Wollmer M, Schuller B (2010) Opensmile: the munich versatile and fast open-source audio feature extractor. In: Proceedings of the 18th ACM international conference on Multimedia. ACM, New York, pp 1459–1462
Hirschberg J, Benus S, Brenier JM, Enos F, Friedman S, Gilman S, Girand C, Graciarena M, Kathol A, Michaelis L et al (2005) Distinguishing deceptive from non-deceptive speech. In: Interspeech, pp 1833–1836
Kjellgren KI, Ahlner J, Säljö R (1995) Taking antihypertensive medication controlling or co-operating with patients? Int J Cardiol 47(3):257–268
Pérez-Rosas V, Abouelenien M, Mihalcea R, Burzo M (2015) Deception detection using real-life trial data. In: Proceedings of the 2015 ACM on international conference on multimodal interaction. ACM, New York, pp 59–66
Takuya H, Graham N, Sakriani S, Tomoki T, Satoshi N (2014) Reinforcement learning of cooperative persuasive dialogue policies using framing. In: COLING, pp 1706–1717
Tian L, Moore J, Lai C (2016) Recognizing emotions in spoken dialogue with hierarchically fused acoustic and lexical features. In: 2016 IEEE spoken language technology workshop (SLT). IEEE, pp 565–572
Torning K, Oinas-Kukkonen H (2009) Persuasive system design: state of the art and future directions. In: Proceedings of the 4th international conference on persuasive technology. ACM, New York, p 30
Traum DR (2008) Computational models of noncooperative dialogue
Vourliotakis A, Efstathiou I, Rieser V (2014) Detecting deception in noncooperative dialogue: a smarter adversary cannot be fooled that easily. In: Proceedings of the 18th workshop on the semantics and pragmatics of dialogue (SemDIAL). Edinburgh, Scotland, UK, pp 252–254
Watkins CJCH, Dayan P (1992) Q-learning. Mach Learn 8(3–4):279–292
Yoshino K, Kawahara T (2015) Conversational system for information navigation based on pomdp with user focus tracking. Comput Speech Lang 34(1):275–291
Acknowledgements
Part of this work was supported by JSPS KAKENHI Grant Number JP17H06101.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
The Tung, N., Yoshino, K., Sakti, S., Nakamura, S. (2019). Impact of Deception Information on Negotiation Dialog Management: A Case Study on Doctor-Patient Conversations. In: D'Haro, L., Banchs, R., Li, H. (eds) 9th International Workshop on Spoken Dialogue System Technology. Lecture Notes in Electrical Engineering, vol 579. Springer, Singapore. https://doi.org/10.1007/978-981-13-9443-0_17
Download citation
DOI: https://doi.org/10.1007/978-981-13-9443-0_17
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-9442-3
Online ISBN: 978-981-13-9443-0
eBook Packages: Literature, Cultural and Media StudiesLiterature, Cultural and Media Studies (R0)