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Managing Multi-task Dialogs by Means of a Statistical Dialog Management Technique

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Increasing Naturalness and Flexibility in Spoken Dialogue Interaction

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 714))

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Abstract

One of the most demanding tasks when developing a dialog system consists of deciding the next system response considering the user’s actions and the dialog history, which is the fundamental responsibility related to dialog management. A statistical dialog management technique is proposed 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 for which the dialog system has been designed. The practical application of the proposed technique to develop a dialog system for a travel-planning domain shows that the use of task-specific dialog models increases the quality and number of successful interactions with the system in comparison with developing a single dialog model for the complete domain.

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Acknowledgements

The research leading to these results has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 823907 (MENHIR project:https://menhir-project.eu) and the CAVIAR project (MINECO, TEC2017-84593-C2-1-R, AEI/FEDER, UE).

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Authors and Affiliations

  1. Department of Languages and Computer Systems, University of Granada, Granada, Spain

    David Griol & Zoraida Callejas

  2. Department of Computer Science and Artificial Intelligence, University of Seville, Seville, Spain

    Jose F. Quesada

Authors
  1. David Griol
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  2. Zoraida Callejas
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  3. Jose F. Quesada
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Corresponding author

Correspondence to David Griol .

Editor information

Editors and Affiliations

  1. Apple, Cupertino, CA, USA

    Erik Marchi

  2. Kore University of Enna, Enna, Italy

    Sabato Marco Siniscalchi

  3. Polytechnic University of Turin, Torino, Italy

    Sandro Cumani

  4. Kore University of Enna, Enna, Italy

    Valerio Mario Salerno

  5. National University of Singapore, Singapore, Singapore

    Haizhou Li

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Griol, D., Callejas, Z., Quesada, J.F. (2021). Managing Multi-task Dialogs by Means of a Statistical Dialog Management Technique. In: Marchi, E., Siniscalchi, S.M., Cumani, S., Salerno, V.M., Li, H. (eds) Increasing Naturalness and Flexibility in Spoken Dialogue Interaction. Lecture Notes in Electrical Engineering, vol 714. Springer, Singapore. https://doi.org/10.1007/978-981-15-9323-9_6

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  • DOI: https://doi.org/10.1007/978-981-15-9323-9_6

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-9322-2

  • Online ISBN: 978-981-15-9323-9

  • eBook Packages: EngineeringEngineering (R0)

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