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Data-Driven Methods for Adaptive Spoken Dialogue Systems

Data-Driven Methods for Adaptive Spoken Dialogue Systems

Computational Learning for Conversational Interfaces

by Olivier Pietquin and Oliver Lemon
Hardback
Publication Date: 21/10/2012

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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.
ISBN:
9781461448020
9781461448020
Category:
Natural language & machine translation
Format:
Hardback
Publication Date:
21-10-2012
Language:
English
Publisher:
Springer-Verlag New York Inc.
Country of origin:
United States
Pages:
178
Dimensions (mm):
235x155x15mm
Weight:
0.45kg

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