Building dialogue POMDPs from expert dialogues [electronic resource] : an end-to-end approach / Hamidreza Chinaei, Brahim Chaib-draa.
2016
QA76.9.N38
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Title
Building dialogue POMDPs from expert dialogues [electronic resource] : an end-to-end approach / Hamidreza Chinaei, Brahim Chaib-draa.
Author
Chinaei, Hamiza, author.
ISBN
9783319262000 (electronic book)
3319262009 (electronic book)
9783319261980
3319262009 (electronic book)
9783319261980
Published
Cham : Springer, 2016.
Language
English
Description
1 online resource.
Item Number
10.1007/978-3-319-26200-0 doi
Call Number
QA76.9.N38
Dewey Decimal Classification
006.35
Summary
This book discusses the Partially Observable Markov Decision Process (POMDP) framework applied in dialogue systems. It presents POMDP as a formal framework to represent uncertainty explicitly while supporting automated policy solving. The authors propose and implement an end-to-end learning approach for dialogue POMDP model components. Starting from scratch, they present the state, the transition model, the observation model and then finally the reward model from unannotated and noisy dialogues. These altogether form a significant set of contributions that can potentially inspire substantial further work. This concise manuscript is written in a simple language, full of illustrative examples, figures, and tables. Provides insights on building dialogue systems to be applied in real domain Illustrates learning dialogue POMDP model components from unannotated dialogues in a concise format Introduces an end-to-end approach that makes use of unannotated and noisy dialogue for learning each component of dialogue POMDPs.
Bibliography, etc. Note
Includes bibliographical references.
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Access limited to authorized users.
Source of Description
Online resource; title from PDF title page (viewed February 15, 2016)
Added Author
Chaib-draa, Brahim, author.
Series
SpringerBriefs in electrical and computer engineering. Speech technology.
Available in Other Form
Print version: 9783319261980
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Table of Contents
1 Introduction
2 A few words on topic modeling
3 Sequential decision making in spoken dialog management
4 Learning the dialog POMDP model components
5 Learning the reward function
6 Application on healthcare dialog management
7 Conclusions and future work.
2 A few words on topic modeling
3 Sequential decision making in spoken dialog management
4 Learning the dialog POMDP model components
5 Learning the reward function
6 Application on healthcare dialog management
7 Conclusions and future work.