Abstract
In this paper, we test the applicability of a statistical user modeling technique to develop a simulated user agent that generates dialogs which are similar to real human-machine spoken interactions. The proposed user simulation technique decides the next response of the agent taking into account the previous user turns, the last system answer and the objective of the dialog. In our contribution, we present the results of the comparison between a corpus acquired from real interactions of users with a conversational agent and a corpus acquired by means of the proposed user simulation technique. To do so, we describe the practical application of our proposal for a conversational agent providing tourist information in natural language, employing a comprehensive set of measures for its evaluation.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Macal C, North M (2010) Tutorial on agent-based modelling and simulation. J Simul 4:151–162
Heath B, Hill R, Ciarallo F (2009) A survey of agent-based modeling practices (January 1998 to July 2008). JASSS 12(4)
Wilensky U, Rand W (2015) An introduction to agent-based modeling: modeling natural, social and engineered complex systems with NetLogo. MIT Press
North M, Collier N, Vos J (2006) Experiences creating three implementations of the repast agent modeling toolkit. ACM Trans Model Comput Simul 16:1–25
Klgl F, Herrler R, Oechslein C (2003) From simulated to real environments: how to use SeSam for software development. LNCS 2831:13–24
Barnard E, Halberstadt A, Kotelly C, Phillips M (1999) A consistent approach to designing spoken-dialog systems. In: Proceedings of the ASRU, pp 1173–1176
Pieraccini R, Huerta J (2005) Where do we go from here? research and commercial spoken dialog systems. In: Proceedings of the SIGdial, pp 1–10
Williams J (2009) The best of both worlds: unifying conventional dialog systems and pomdps. In: Proceedings of the InterSpeech, pp 1173–1176
Cohen M, Giangola J, Balough J (2004) Voice user interface design. Addison Wesley
Paek T, Pieraccini R (2008) Automating spoken dialogue management design using machine learning: an industry perspective. Speech Commun 50(8–9):716–729
Möller S, Englert R, Engelbrecht K, Hafner V, Jameson A, Oulasvirta A, Raake A, Reithinger N (2006) MeMo: towards automatic usability evaluation of spoken dialogue services by user error simulations. In: Proceedings of the Interspeech, pp 1786–1789
Schatzmann J, Weilhammer K, Stuttle M, Young S (2006) A survey of statistical user simulation techniques for reinforcement-learning of dialogue management strategies. Knowl Eng Rev 21(2):97–126
Schatzmann J, Georgila K, Young S (2005) Quantitative evaluation of user simulation techniques for spoken dialogue systems. In: Proceedings of the SIGdial, pp 45–54
Ai H, Raux A, Bohus D, Eskenazi M, Litman D (2007) Comparing spoken dialog corpora collected with recruited subjects versus real users. In: Proceedings of the SIGdial, pp 124–131
Griol D, Callejas Z, López-Cózar R, Riccardi G (2014) A domain-independent statistical methodology for dialog management in spoken dialog systems. Comput Speech Lang 28(3)
Schatzmann J, Thomson B, Weilhammer K, Ye H, Young S (2007) Agenda-based user simulation for bootstrapping a pomdp dialogue system. In: Proceedings of the HLT/NAACL, pp 149–152
Griol D, Molina J, Callejas Z (2012) Bringing together commercial and academic perspectives for the development of intelligent Am I interfaces. JAISE 4(3):183–207
Acknowledgments
This work was supported in part by Projects MINECO TEC2012-37832-C02-01, CICYT TEC2011-28626-C02-02, CAM CONTEXTS (S2009/TIC-1485).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Griol, D., Molina, J.M. (2015). User Modeling Optimization for the Conversational Human-Machine Interfaces. In: Herrero, Á., Sedano, J., Baruque, B., Quintián, H., Corchado, E. (eds) 10th International Conference on Soft Computing Models in Industrial and Environmental Applications. Advances in Intelligent Systems and Computing, vol 368. Springer, Cham. https://doi.org/10.1007/978-3-319-19719-7_1
Download citation
DOI: https://doi.org/10.1007/978-3-319-19719-7_1
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-19718-0
Online ISBN: 978-3-319-19719-7
eBook Packages: EngineeringEngineering (R0)