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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Building Dialogue Pomdps from Expert Dialogues: An End-To-End Approach

Building Dialogue Pomdps from Expert Dialogues: An End-To-End Approach

Chinaei, Hamidreza
Chaib-Draa, Brahim

Paperback

Series: Springerbriefs in Speech Technology

Technology & EngineeringGeneral Computers

ISBN10: 3319261983
ISBN13: 9783319261980
Publisher: Springer Nature
Published: Feb 16 2016
Pages: 119
Weight: 0.42
Height: 0.27 Width: 6.14 Depth: 9.21
Language: English

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.

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