Abstract
One of the most demanding tasks when developing conversational agents consists of designing the dialog manager, which decides the next system response considering the user’s actions and the dialog history. A previously developed statistical dialog management technique is adapted in this work to reduce the effort and time required to design the dialog manager. This technique allows not only an easy adaptation to new domains, but also to deal with the different subtasks by means of specific dialog models adapted to each dialog objective in the domain of a multiagent system. The practical application of the proposed technique to develop a conversational agent providing railway information shows that the use of these specific dialog models increases the quality and number of successful interactions with the agent in comparison with developing a single dialog model for the complete domain.
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References
Pieraccini, R.: The Voice in the Machine: Building Computers that Understand Speech. The MIT Press (2012)
López-Cózar, R., Araki, M.: Spoken, Multilingual and Multimodal Dialogue Systems. John Wiley & Sons Publishers (2005)
Hempel, T.: Usability of Speech Dialog Systems: Listening to the Target Audience. Springer (2008)
Heinroth, T., Minker, W.: Introducing Spoken Dialogue Systems into Intelligent Environments. Kluwer Academic Publishers (2012)
Rodríguez, S., de Paz, Y., Bajo, J., Corchado, J.M.: Social-based Planning Model for Multi-agent Systems. Expert Systems with Applications 38(10), 13005–13023 (2011)
Corchado, J., Tapia, D., Bajo, J.: A multi-agent architecture for distributed services and applications. Computational Intelligence 24(2), 77–107 (2008)
Vipperla, R., Wolters, M., Renals, S.: Spoken dialogue interfaces for older people, pp. 118–137. IOS Press (2012)
Rojas-Barahona, L., Giorgino, T.: Adaptable dialog architecture and runtime engine (adarte): A framework for rapid prototyping of health dialog systems. International Journal of Medical Informatics 78, 56–68 (2009)
Schatzmann, J., Weilhammer, K., Stuttle, M., Young, S.: A Survey of Statistical User Simulation Techniques for Reinforcement-Learning of Dialogue Management Strategies. Knowledge Engineering Review 21(2), 97–126 (2006)
Griol, D., Molina, J.M., Callejas, Z.: Bringing together commercial and academic perspectives for the development of intelligent AmI interfaces. Journal of Ambient Intelligence and Smart Environments 4, 183–207 (2012)
Paek, T., Pieraccini, R.: Automating spoken dialogue management design using machine learning: An industry perspective. Speech Communication 50(8-9), 716–729 (2008)
Levin, E., Pieraccini, R., Eckert, W.: A stochastic model of human-machine interaction for learning dialog strategies. IEEE Transactions on Speech and Audio Processing 8(1), 11–23 (2000)
Young, S., Schatzmann, J., Weilhammer, K., Ye, H.: The Hidden Information State Approach to Dialogue Management. In: Proc. ICASSP 2007, pp. 149–152 (2007)
Griol, D., Carbó, J., Molina, J.: An Automatic Dialog Simulation Technique to Develop and Evaluate Interactive Conversational Agents. Applied Artificial Intelligence 27(9), 759–780 (2013)
Borrajo, M., Baruque, B., Corchado, E., Bajo, J., Corchado, J.: Hybrid neural intelligent system to predict business failure in small-to-medium-size enterprises. International Journal of Neural Systems 21(4), 277–296 (2011)
Griol, D., Hurtado, L., Segarra, E., Sanchis, E.: A Statistical Approach to Spoken Dialog Systems Design and Evaluation. Speech Communication 50(8-9), 666–682 (2008)
Minsky, M.: A Framework for Representing Knowledge. McGraw-Hill (1975)
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Griol, D., Molina, J.M., Sanchis de Miguel, A. (2014). Domain and Subtask-Adaptive Conversational Agents to Provide an Enhanced Human-Agent Interaction. In: Demazeau, Y., Zambonelli, F., Corchado, J.M., Bajo, J. (eds) Advances in Practical Applications of Heterogeneous Multi-Agent Systems. The PAAMS Collection. PAAMS 2014. Lecture Notes in Computer Science(), vol 8473. Springer, Cham. https://doi.org/10.1007/978-3-319-07551-8_12
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DOI: https://doi.org/10.1007/978-3-319-07551-8_12
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