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Data-Driven Methods for Adaptive Spoken Dialogue Systems

Computational Learning for Conversational Interfaces

Produktform: E-Buch Text Elektronisches Buch in proprietärem

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.weiterlesen

Elektronisches Format: PDF

Sprache(n): Englisch

ISBN: 978-1-4614-4803-7 / 978-1461448037 / 9781461448037

Verlag: Springer US

Erscheinungsdatum: 20.10.2012

Seiten: 178

Herausgegeben von Oliver Lemon, Olivier Pietquin

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