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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.
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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
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Hierarchical Neural Network Structures for Phoneme Recognition (Signals and Communication Technology)
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Hierarchical Neural Network Structures for Phoneme Recognition (Hardcover)
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Hardcover. Condizione: new. Hardcover. 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. In this book, hierarchical structures based on neural networks are investigated for automatic speech recognition. Additionally, the output of the first level is used as an input for the second level. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Codice articolo 9783642344244
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Hierarchical Neural Network Structures for Phoneme Recognition
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Springer Berlin Heidelberg Okt 2012, 2012
ISBN 10: 3642344240
ISBN 13: 9783642344244
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Buch. Condizione: 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. Codice articolo 9783642344244
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Hierarchical Neural Network Structures for Phoneme Recognition
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Condizione: 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. Codice articolo 5057608
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Hierarchical Neural Network Structures for Phoneme Recognition
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Hierarchical Neural Network Structures for Phoneme Recognition
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Buch. Condizione: 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. Codice articolo 9783642344244
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Hierarchical Neural Network Structures for Phoneme Recognition
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Buch. Condizione: 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. Codice articolo 9783642344244
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