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A Bayesian Networks Approach for Dialog Modeling: The Fusion BN

Fernández Martínez, Fernando and Ferreiros López, Javier and Córdoba Herralde, Ricardo de and Montero Martínez, Juan Manuel and San Segundo Hernández, Rubén and Pardo Muñoz, José Manuel (2009) A Bayesian Networks Approach for Dialog Modeling: The Fusion BN. In: IEEE International Conference on Acoustics, Speech, and Signal Processing ICASSP 2009, 19/04/2009 - 24/04/2009, Taipei, Taiwan.

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Item Type:Presentation at Congress or Day (Article)
Authors/Creators:
Creators NameCreators email (if known)
Fernández Martínez, Fernando
Ferreiros López, Javier
Córdoba Herralde, Ricardo de
Montero Martínez, Juan Manuel
San Segundo Hernández, Rubén
Pardo Muñoz, José Manuel
Title:A Bayesian Networks Approach for Dialog Modeling: The Fusion BN
Event Title:IEEE International Conference on Acoustics, Speech, and Signal Processing ICASSP 2009
Event Dates:19/04/2009 - 24/04/2009
Event Location:Taipei, Taiwan
Title of Book:Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing ICASSP 2009
Publisher:IEEE
Date:May 2009
ISBN:978-1-4244-2353-8
Department:Electronic Engineering
Faculty:E.T.S.I. Telecommunication (UPM)
Creative Commons licenses:Recognition - No derivative works - No commercial
Item ID:5579
Subjects:Computer Science
Electronics

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Official URL: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4960702&tag=1

Abstract

Bayesian networks, BNs, are suitable for mixed-initiative dialog modeling allowing a more flexible and natural spoken interaction. This solution can be applied to identify the intention of the user considering the concepts extracted from the last utterance and the dialog context. Subsequently, in order to make a correct decision regarding how the dialog should continue, unnecessary, missing, wrong, optional and required concepts have to be detected according to the inferred goals. This information is useful to properly drive the dialog prompting for missing concepts, clarifying for wrong concepts, ignoring unnecessary concepts and retrieving those required and optional. This paper presents a novel BNs approach where a single BN is obtained from N goal-specific BNs through a fusion process. The new fusion BN enables a single concept analysis which is more consistent with the whole dialog context.

Item Type:Presentation at Congress or Day (Article)
Subjects:Computer Science
Electronics
Código ID:5579
Depositado Por:Memoria Investigacion
Depositado el:22 Dec 2010 11:16
Last Modified:15 Feb 2011 12:04

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