Building Dialogue POMDPs from Expert Dialogues

An end-to-end approach de

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Éditeur :

Springer


Collection :

SpringerBriefs in Speech Technology

Paru le : 2016-02-08

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Description

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.
Pages
119 pages
Collection
SpringerBriefs in Speech Technology
Parution
2016-02-08
Marque
Springer
EAN papier
9783319261980
EAN PDF
9783319262000

Informations sur l'ebook
Nombre pages copiables
1
Nombre pages imprimables
11
Taille du fichier
2017 Ko
Prix
52,74 €
EAN EPUB
9783319262000

Informations sur l'ebook
Nombre pages copiables
1
Nombre pages imprimables
11
Taille du fichier
1505 Ko
Prix
52,74 €