Authors:
Juan Manuel Lucas-Cuesta
;
Fernando Fernández-Martínez
;
G. Dragos Rada
;
Syaheerah L. Lutfi
and
Javier Ferreiros
Affiliation:
Universidad Politécnica de Madrid, Spain
Keyword(s):
Spoken language dialogue systems, User interfaces, Contextual information, User profiles, Natural language processing, Real-user evaluation.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Artificial Intelligence
;
Enterprise Information Systems
;
Human-Computer Interaction
;
Intelligent User Interfaces
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Natural Language Processing
;
Pattern Recognition
;
Symbolic Systems
Abstract:
We present an evaluation of a spoken language dialogue system with a module for the management of user-related information, stored as user preferences and privileges. The flexibility of our dialogue management approach, based on Bayesian Networks (BN), together with a contextual information module, which performs different strategies for handling such information, allows us to include user information as a new level into the Context Manager hierarchy. We propose a set of objective and subjective metrics to measure the relevance of the different contextual information sources. The analysis of our evaluation scenarios shows that the relevance of the short-term information (i.e. the system status) remains pretty stable throughout the dialogue, whereas the dialogue history and the user profile (i.e. the middle-term and the long-term information, respectively) play a complementary role, evolving their usefulness as the dialogue evolves.