Title
Dialogue-Based Management Of User Feedback In An Autonomous Preference Learning System
Abstract
We present an enhanced method for user feedback in an autonomous learning system that includes a spoken dialogue system to manage the interactions between the users and the system. By means of a rule-based natural language understanding module and a state-based dialogue manager we allow the users to update the preferences learnt by the system from the data obtained from different sensors. The design of the dialogue together with the storage of context information (the previous dialogue turns and the current state of the dialogue) ensures highly natural interactions, reducing the number of dialogue turns and making it possible to use complex linguistic constructions instead of isolated commands.
Year
Venue
Keywords
2010
ICAART 2010: PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON AGENTS AND ARTIFICIAL INTELLIGENCE, VOL 1: ARTIFICIAL INTELLIGENCE
Spoken dialogue systems, Autonomous preference learning, User feedback, Human-computer interaction
Field
DocType
Citations 
Computer science,Knowledge management,Human–computer interaction,Natural language understanding,Preference learning,Artificial intelligence,Machine learning,Autonomous learning
Conference
0
PageRank 
References 
Authors
0.34
2
5
Name
Order
Citations
PageRank
Juan Manuel Lucas-Cuesta1354.37
Javier Ferreiros200.34
Asier Aztiria318113.88
Juan Carlos Augusto41344145.59
Michael F. McTear536738.16