title: A Two-Stage Combining Classifier Model for the Development of Adaptive Dialog Systems.
abstract: This paper proposes a statistical framework to develop user-adapted spoken dialog systems. The proposed framework integrates two main models. The first model is used to predict the user's intention during the dialog. The second model uses this prediction and the history of dialog up to the current moment to predict the next system response. This prediction is performed with an ensemble-based classifier trained for each of the tasks considered, so that a better selection of the next system can be attained weighting the outputs of these specialized classifiers. The codification of the information and the definition of data structures to store the data supplied by the user throughout the dialog makes the estimation of the models from the training data and practical domains manageable. We describe our proposal and its application and detailed evaluation in a practical spoken dialog system.
authors.affiliation: 1 Control Learning and Systems Optimization Group, Computer Science Department, Carlos III University of Madrid, Avda. de la Universidad, 30 28911 Leganés, Spain.
authors.forename: David
authors.initials: D
authors.lastname: Griol
authors.affiliation: 1 Control Learning and Systems Optimization Group, Computer Science Department, Carlos III University of Madrid, Avda. de la Universidad, 30 28911 Leganés, Spain.
authors.forename: José Antonio
authors.initials: JA
authors.lastname: Iglesias
authors.affiliation: 1 Control Learning and Systems Optimization Group, Computer Science Department, Carlos III University of Madrid, Avda. de la Universidad, 30 28911 Leganés, Spain.
authors.forename: Agapito
authors.initials: A
authors.lastname: Ledezma
authors.affiliation: 1 Control Learning and Systems Optimization Group, Computer Science Department, Carlos III University of Madrid, Avda. de la Universidad, 30 28911 Leganés, Spain.
authors.forename: Araceli
authors.initials: A
authors.lastname: Sanchis
mesh_terms: D000328:Adult; D000368:Aged; D001185:Artificial Intelligence; D003198:Computer Simulation; D006801:Humans; D008875:Middle Aged; D014584:User-Computer Interface; D055815:Young Adult
keywords: Spoken dialog systems; artificial neural networks; classifier systems; clustering; dialog management; spoken human–machine interaction; user models