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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
Data-Driven Methods for Adaptive Spoken Dialogue Systems: Computational Learning for Conversational Interfaces

Data-Driven Methods for Adaptive Spoken Dialogue Systems: Computational Learning for Conversational Interfaces

Pietquin, Olivier
Lemon, Oliver

Hardcover

LinguisticsTechnology & EngineeringGeneral Computers

ISBN10: 1461448026
ISBN13: 9781461448020
Publisher: Springer
Published: Oct 21 2012
Pages: 178
Weight: 1.10
Height: 0.60 Width: 6.10 Depth: 9.30
Language: English
Data driven methods have long been used in Automatic Speech Recognition (ASR) and Text-To-Speech (TTS) synthesis and have more recently been introduced for dialogue management, spoken language understanding, and Natural Language Generation. Machine learning is now present end-to-end in Spoken Dialogue Systems (SDS). However, these techniques require data collection and annotation campaigns, which can be time-consuming and expensive, as well as dataset expansion by simulation. In this book, we provide an overview of the current state of the field and of recent advances, with a specific focus on adaptivity.

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