Paper Info
Title
Optimizing Dialog Strategies for Conversational Agents Interacting in AmI Environments.
Abstract
In this paper, we describe a conversational agent which provides academic information. The dialog model of this agent has been developed by means of a statistical methodology that automatically explores the dialog space and allows learning new enhanced dialog strategies from a dialog corpus. A dialog simulation technique has been applied to acquire data required to train the dialog model and then explore the new dialog strategies. A set of measures has also been defined to evaluate the dialog strategy. The results of the evaluation show how the dialog model deviates from the initially predefined strategy, allowing the conversational agent to tackle new situations and generate new coherent answers for the situations already present in the initial corpus. The proposed technique can be used not only to develop new dialog managers but also to explore new enhanced dialog strategies focused on user adaptation required to interact in AmI environments.
Year
DOI
Venue
2012
10.1007/978-3-642-28783-1_12
AMBIENT INTELLIGENCE - SOFTWARE AND APPLICATIONS
Keywords
Field
DocType
Conversational Agents,Speech Interaction,Agent & Multiagent Systems for AmI,Statistical Methodologies
Dialog box,Computer science,Speech interaction,Human–computer interaction,Dialog system
Conference
Volume
ISSN
Citations 
153
1867-5662
0
PageRank 
References 
Authors
0.34
6
3
Name
Order
Citations
PageRank
David Griol122349.82
Javier Carbó218220.85
José Manuel Molina3546.24