A Proposal for the Development of Lifelong Dialog Systems

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 950)


In this paper we describe a proposal that employs Soft Computing techniques for developing intelligent dialog systems that can improve over time. To do this, our proposal merges statistical dialog management methodologies, intentional and emotional information in order to make dialog managers more efficient and adaptive. The prediction of the user intention and emotion is carried out for each user turn in the dialog by means of specific modules that are conceived as an intermediate phase between natural language understanding and dialog management in the architecture of these systems. We have applied and evaluated our method in the UAH system, for which the evaluation results show that merging both sources of information improves system performance as well as its perceived quality.


Conversational interfaces Spoken interaction Evolving classifiers Fuzzy-rule based systems Human-machine interaction 


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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Department of Computer ScienceUniversidad Carlos III de MadridLeganésSpain

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