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Lingua: Inglese
Editore: Springer International Publishing AG, CH, 2018
ISBN 10: 3319878492 ISBN 13: 9783319878492
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Aggiungi al carrelloPaperback. Condizione: New. Softcover reprint of the original 1st ed. 2017.
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Editore: Springer-Nature New York Inc, 2018
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Da: moluna, Greven, Germania
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Aggiungi al carrelloKartoniert / Broschiert. Condizione: New. Field of automatic speech recognition has evolved greatly since the introduction of deep learningCovers the state-of-the-art in noise robustness for deep neural-network-based speech recognitionIncludes descrip.
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. New Era for Robust Speech Recognition | Exploiting Deep Learning | Shinji Watanabe (u. a.) | Taschenbuch | xvii | Englisch | 2018 | Springer | EAN 9783319878492 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Lingua: Inglese
Editore: Springer International Publishing, Springer, 2018
ISBN 10: 3319878492 ISBN 13: 9783319878492
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book covers the state-of-the-art in deep neural-network-based methods for noise robustness in distant speech recognition applications. It provides insights and detailed descriptions of some of the new concepts and key technologies in the field, including novel architectures for speech enhancement, microphone arrays, robust features, acoustic model adaptation, training data augmentation, and training criteria. The contributed chapters also include descriptions of real-world applications, benchmark tools and datasets widely used in the field. This book is intended for researchers and practitioners working in the field of speech processing and recognition who are interested in the latest deep learning techniques for noise robustness. It will also be of interest to graduate students in electrical engineering or computer science, who will find it a useful guide to this field of research.
Lingua: Inglese
Editore: Springer International Publishing AG, CH, 2018
ISBN 10: 3319878492 ISBN 13: 9783319878492
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Aggiungi al carrelloGebunden. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Field of automatic speech recognition has evolved greatly since the introduction of deep learningCovers the state-of-the-art in noise robustness for deep neural-network-based speech recognitionIncludes descrip.
Lingua: Inglese
Editore: Springer International Publishing Mai 2018, 2018
ISBN 10: 3319878492 ISBN 13: 9783319878492
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book covers the state-of-the-art in deep neural-network-based methods for noise robustness in distant speech recognition applications. It provides insights and detailed descriptions of some of the new concepts and key technologies in the field, including novel architectures for speech enhancement, microphone arrays, robust features, acoustic model adaptation, training data augmentation, and training criteria. The contributed chapters also include descriptions of real-world applications, benchmark tools and datasets widely used in the field. This book is intended for researchers and practitioners working in the field of speech processing and recognition who are interested in the latest deep learning techniques for noise robustness. It will also be of interest to graduate students in electrical engineering or computer science, who will find it a useful guide to this field of research. 456 pp. Englisch.
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Aggiungi al carrelloCondizione: New. PRINT ON DEMAND.
Lingua: Inglese
Editore: Springer International Publishing, Springer Mai 2018, 2018
ISBN 10: 3319878492 ISBN 13: 9783319878492
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book covers the state-of-the-art in deep neural-network-based methods for noise robustness in distant speech recognition applications. It provides insights and detailed descriptions of some of the new concepts and key technologies in the field, including novel architectures for speech enhancement, microphone arrays, robust features, acoustic model adaptation, training data augmentation, and training criteria. The contributed chapters also include descriptions of real-world applications, benchmark tools and datasets widely used in the field.This book is intended for researchers and practitioners working in the field of speech processing and recognition who are interested in the latest deep learning techniques for noise robustness. It will also be of interest to graduate students in electrical engineering or computer science, who will find it a useful guide to this field of research.Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 456 pp. Englisch.