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Hierarchical Neural Network Structures by Vasquez Daniel (25 results)
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Hierarchical Neural Network Structures for Phoneme Recognition (Signals and Communication Technology)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
US$ 126.22
US$ 15.81 shipping from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: New. In.
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Hierarchical Neural Network Structures for Phoneme Recognition (Signals and Communication Technology)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
US$ 127.92
US$ 15.81 shipping from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: New. In.
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Condition: New.
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Condition: New. pp. 152.
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Hardcover. Condition: Brand New. 2013 edition. 150 pages. 9.25x6.25x0.25 inches. In Stock.
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Taschenbuch. Condition: Neu. Hierarchical Neural Network Structures for Phoneme Recognition | Daniel Vasquez (u. a.) | Taschenbuch | xviii | Englisch | 2014 | Springer | EAN 9783642432101 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Hierarchical Neural Network Structures for Phoneme Recognition
Published by Springer Berlin Heidelberg, Springer Berlin Heidelberg Okt 2012, 2012
ISBN 10: 3642344240 ISBN 13: 9783642344244
Language: English
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Buch. Condition: Neu. Neuware -In this book, hierarchical structures based on neural networks are investigated for automatic speech recognition. These structures are mainly evaluated within the phoneme recognition task under the Hybrid Hidden Markov Model/Artificial Neural Network (HMM/ANN) paradigm. The baseline hierarchical scheme consists of two levels each which is based on a Multilayered Perceptron (MLP). Additionally, the output of the first level is used as an input for the second level. This system can be substantially speeded up by removing the redundant information contained at the output of the first level.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 152 pp. Englisch.
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Paperback. Condition: Brand New. 2013 edition. 152 pages. 9.25x6.10x0.35 inches. In Stock.
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Hierarchical Neural Network Structures for Phoneme Recognition
Published by Springer Berlin Heidelberg, 2014
ISBN 10: 3642432107 ISBN 13: 9783642432101
Language: English
Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - In this book, hierarchical structures based on neural networks are investigated for automatic speech recognition. These structures are mainly evaluated within the phoneme recognition task under the Hybrid Hidden Markov Model/Artificial Neural Network (HMM/ANN) paradigm. The baseline hierarchical scheme consists of two levels each which is based on a Multilayered Perceptron (MLP). Additionally, the output of the first level is used as an input for the second level. This system can be substantially speeded up by removing the redundant information contained at the output of the first level.
-
Hierarchical Neural Network Structures for Phoneme Recognition
Published by Springer Berlin Heidelberg, 2012
ISBN 10: 3642344240 ISBN 13: 9783642344244
Language: English
Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - In this book, hierarchical structures based on neural networks are investigated for automatic speech recognition. These structures are evaluated on the phoneme recognition task where a Hybrid Hidden Markov Model/Artificial Neural Network paradigm is used. The baseline hierarchical scheme consists of two levels each which is based on a Multilayered Perceptron. Additionally, the output of the first level serves as a second level input. The computational speed of the phoneme recognizer can be substantially increased by removing redundant information still contained at the first level output. Several techniques based on temporal and phonetic criteria have been investigated to remove this redundant information. The computational time could be reduced by 57% whilst keeping the system accuracy comparable to the baseline hierarchical approach.
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Hierarchical Neural Network Structures for Phoneme Recognition
Published by Springer Berlin Heidelberg, 2012
ISBN 10: 3642344240 ISBN 13: 9783642344244
Language: English
Condition: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher.
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Hardcover. Condition: Like New. Like New. book.
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Paperback. Condition: Like New. Like New. book.
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Hierarchical Neural Network Structures for Phoneme Recognition
Published by Springer Berlin Heidelberg Nov 2014, 2014
ISBN 10: 3642432107 ISBN 13: 9783642432101
Language: English
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In this book, hierarchical structures based on neural networks are investigated for automatic speech recognition. These structures are mainly evaluated within the phoneme recognition task under the Hybrid Hidden Markov Model/Artificial Neural Network (HMM/ANN) paradigm. The baseline hierarchical scheme consists of two levels each which is based on a Multilayered Perceptron (MLP). Additionally, the output of the first level is used as an input for the second level. This system can be substantially speeded up by removing the redundant information contained at the output of the first level. 152 pp. Englisch.
-
Hierarchical Neural Network Structures for Phoneme Recognition
Published by Springer Berlin Heidelberg Okt 2012, 2012
ISBN 10: 3642344240 ISBN 13: 9783642344244
Language: English
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In this book, hierarchical structures based on neural networks are investigated for automatic speech recognition. These structures are evaluated on the phoneme recognition task where a Hybrid Hidden Markov Model/Artificial Neural Network paradigm is used. The baseline hierarchical scheme consists of two levels each which is based on a Multilayered Perceptron. Additionally, the output of the first level serves as a second level input. The computational speed of the phoneme recognizer can be substantially increased by removing redundant information still contained at the first level output. Several techniques based on temporal and phonetic criteria have been investigated to remove this redundant information. The computational time could be reduced by 57% whilst keeping the system accuracy comparable to the baseline hierarchical approach. 152 pp. Englisch.
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Hierarchical Neural Network Structures for Phoneme Recognition
Published by Springer Berlin Heidelberg, 2014
ISBN 10: 3642432107 ISBN 13: 9783642432101
Language: English
Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Simplifies the analysis in spoken language dialogue systemsInvestigates hierarchical structures based on neural networks for automatic speech recognitionWritten for academic and industrial researchers in speech recognitionIn this bo.
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Hierarchical Neural Network Structures for Phoneme Recognition
Published by Springer Berlin Heidelberg, 2012
ISBN 10: 3642344240 ISBN 13: 9783642344244
Language: English
Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Simplifies the analysis in spoken language dialogue systemsInvestigates hierarchical structures based on neural networks for automatic speech recognitionWritten for academic and industrial researchers in speech recognitionIn this bo.
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Condition: New. Print on Demand.
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Condition: New. Print on Demand pp. 152 49 Illus.
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Condition: New. PRINT ON DEMAND.
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Condition: New. PRINT ON DEMAND pp. 152.
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Hierarchical Neural Network Structures for Phoneme Recognition
Published by Springer-Verlag GmbH, 2012
ISBN 10: 3642344240 ISBN 13: 9783642344244
Language: English
Buch. Condition: Neu. Hierarchical Neural Network Structures for Phoneme Recognition | Daniel Vasquez (u. a.) | Buch | xviii | Englisch | 2012 | Springer-Verlag GmbH | EAN 9783642344244 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.
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Hierarchical Neural Network Structures for Phoneme Recognition
Published by Springer Berlin Heidelberg, Springer Berlin Heidelberg Nov 2014, 2014
ISBN 10: 3642432107 ISBN 13: 9783642432101
Language: English
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -In this book, hierarchical structures based on neural networks are investigated for automatic speech recognition. These structures are mainly evaluated within the phoneme recognition task under the Hybrid Hidden Markov Model/Artificial Neural Network (HMM/ANN) paradigm. The baseline hierarchical scheme consists of two levels each which is based on a Multilayered Perceptron (MLP). Additionally, the output of the first level is used as an input for the second level. This system can be substantially speeded up by removing the redundant information contained at the output of the first level.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 152 pp. Englisch.
