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In den WarenkorbZustand: New. In.
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
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In den WarenkorbZustand: New. In.
Sprache: Englisch
Verlag: Springer-Verlag New York Inc, 2014
ISBN 10: 1489992839 ISBN 13: 9781489992833
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In den WarenkorbPaperback. Zustand: Brand New. 188 pages. 9.25x6.10x0.45 inches. In Stock.
Sprache: Englisch
Verlag: Springer-Verlag New York Inc, 2012
ISBN 10: 1461448026 ISBN 13: 9781461448020
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In den WarenkorbHardcover. Zustand: Brand New. 2012 edition. 186 pages. 9.00x8.25x0.50 inches. In Stock.
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Taschenbuch. Zustand: Neu. Data-Driven Methods for Adaptive Spoken Dialogue Systems | Computational Learning for Conversational Interfaces | Oliver Lemon (u. a.) | Taschenbuch | x | Englisch | 2014 | Humana | EAN 9781489992833 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Sprache: Englisch
Verlag: Springer New York, Springer US, 2012
ISBN 10: 1461448026 ISBN 13: 9781461448020
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.