Connectionist Speech Recognition: A Hybrid Approach (The Springer International Series in Engineering and Computer Science)

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9780792393962: Connectionist Speech Recognition: A Hybrid Approach (The Springer International Series in Engineering and Computer Science)

Connectionist Speech Recognition: A Hybrid Approach describes the theory and implementation of a method to incorporate neural network approaches into state of the art continuous speech recognition systems based on hidden Markov models (HMMs) to improve their performance. In this framework, neural networks (and in particular, multilayer perceptrons or MLPs) have been restricted to well-defined subtasks of the whole system, i.e. HMM emission probability estimation and feature extraction.
The book describes a successful five-year international collaboration between the authors. The lessons learned form a case study that demonstrates how hybrid systems can be developed to combine neural networks with more traditional statistical approaches. The book illustrates both the advantages and limitations of neural networks in the framework of a statistical systems.
Using standard databases and comparison with some conventional approaches, it is shown that MLP probability estimation can improve recognition performance. Other approaches are discussed, though there is no such unequivocal experimental result for these methods.
Connectionist Speech Recognition is of use to anyone intending to use neural networks for speech recognition or within the framework provided by an existing successful statistical approach. This includes research and development groups working in the field of speech recognition, both with standard and neural network approaches, as well as other pattern recognition and/or neural network researchers. The book is also suitable as a text for advanced courses on neural networks or speech processing.

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1.

Hervé Bourlard, Nelson Morgan
Editorial: Springer, Netherlands (1994)
ISBN 10: 0792393961 ISBN 13: 9780792393962
Nuevos Tapa dura Cantidad: 10
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Descripción Springer, Netherlands, 1994. Hardback. Estado de conservación: New. 1994 ed.. Language: English . This book usually ship within 10-15 business days and we will endeavor to dispatch orders quicker than this where possible. Brand New Book. Connectionist Speech Recognition: A Hybrid Approach describes the theory and implementation of a method to incorporate neural network approaches into state of the art continuous speech recognition systems based on hidden Markov models (HMMs) to improve their performance. In this framework, neural networks (and in particular, multilayer perceptrons or MLPs) have been restricted to well-defined subtasks of the whole system, i.e. HMM emission probability estimation and feature extraction. The book describes a successful five-year international collaboration between the authors. The lessons learned form a case study that demonstrates how hybrid systems can be developed to combine neural networks with more traditional statistical approaches. The book illustrates both the advantages and limitations of neural networks in the framework of a statistical systems. Using standard databases and comparison with some conventional approaches, it is shown that MLP probability estimation can improve recognition performance. Other approaches are discussed, though there is no such unequivocal experimental result for these methods. Connectionist Speech Recognition is of use to anyone intending to use neural networks for speech recognition or within the framework provided by an existing successful statistical approach. This includes research and development groups working in the field of speech recognition, both with standard and neural network approaches, as well as other pattern recognition and/or neural network researchers. The book is also suitable as a text for advanced courses on neural networks or speech processing. Nº de ref. de la librería LIE9780792393962

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HERVÇ A. BOURLARD
Editorial: Springer (1993)
ISBN 10: 0792393961 ISBN 13: 9780792393962
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Descripción Springer, 1993. Hardback. Estado de conservación: NEW. 9780792393962 This listing is a new book, a title currently in-print which we order directly and immediately from the publisher. For all enquiries, please contact Herb Tandree Philosophy Books directly - customer service is our primary goal. Nº de ref. de la librería HTANDREE0284767

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Hervé A. Bourlard; Nelson Morgan
Editorial: Springer (1993)
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Descripción Springer, 1993. Estado de conservación: New. This item is printed on demand for shipment within 3 working days. Nº de ref. de la librería LP9780792393962

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Bourlard, Hervé A.
Editorial: Kluwer Academic Publishers (1993)
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Descripción Kluwer Academic Publishers, 1993. HRD. Estado de conservación: New. New Book. Delivered from our US warehouse in 10 to 14 business days. THIS BOOK IS PRINTED ON DEMAND.Established seller since 2000. Nº de ref. de la librería IP-9780792393962

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Bourlard, Hervà A.
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Descripción Springer, 2016. Paperback. Estado de conservación: New. PRINT ON DEMAND Book; New; Publication Year 2016; Not Signed; Fast Shipping from the UK. No. book. Nº de ref. de la librería ria9780792393962_lsuk

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Bourlard, Herv? A.; Morgan, Nelson
Editorial: Springer (1993)
ISBN 10: 0792393961 ISBN 13: 9780792393962
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Descripción Springer, 1993. Hardcover. Estado de conservación: New. Nº de ref. de la librería INGM9780792393962

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Hervé Bourlard, Nelson Morgan
Editorial: Springer, Netherlands (1994)
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Descripción Springer, Netherlands, 1994. Hardback. Estado de conservación: New. 1994 ed.. Language: English . Brand New Book ***** Print on Demand *****. Connectionist Speech Recognition: A Hybrid Approach describes the theory and implementation of a method to incorporate neural network approaches into state of the art continuous speech recognition systems based on hidden Markov models (HMMs) to improve their performance. In this framework, neural networks (and in particular, multilayer perceptrons or MLPs) have been restricted to well-defined subtasks of the whole system, i.e. HMM emission probability estimation and feature extraction. The book describes a successful five-year international collaboration between the authors. The lessons learned form a case study that demonstrates how hybrid systems can be developed to combine neural networks with more traditional statistical approaches. The book illustrates both the advantages and limitations of neural networks in the framework of a statistical systems. Using standard databases and comparison with some conventional approaches, it is shown that MLP probability estimation can improve recognition performance. Other approaches are discussed, though there is no such unequivocal experimental result for these methods. Connectionist Speech Recognition is of use to anyone intending to use neural networks for speech recognition or within the framework provided by an existing successful statistical approach. This includes research and development groups working in the field of speech recognition, both with standard and neural network approaches, as well as other pattern recognition and/or neural network researchers. The book is also suitable as a text for advanced courses on neural networks or speech processing. Nº de ref. de la librería APC9780792393962

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8.

Hervé Bourlard, Nelson Morgan
Editorial: Springer, Netherlands (1994)
ISBN 10: 0792393961 ISBN 13: 9780792393962
Nuevos Tapa dura Cantidad: 10
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Descripción Springer, Netherlands, 1994. Hardback. Estado de conservación: New. 1994 ed.. Language: English . Brand New Book ***** Print on Demand *****.Connectionist Speech Recognition: A Hybrid Approach describes the theory and implementation of a method to incorporate neural network approaches into state of the art continuous speech recognition systems based on hidden Markov models (HMMs) to improve their performance. In this framework, neural networks (and in particular, multilayer perceptrons or MLPs) have been restricted to well-defined subtasks of the whole system, i.e. HMM emission probability estimation and feature extraction. The book describes a successful five-year international collaboration between the authors. The lessons learned form a case study that demonstrates how hybrid systems can be developed to combine neural networks with more traditional statistical approaches. The book illustrates both the advantages and limitations of neural networks in the framework of a statistical systems. Using standard databases and comparison with some conventional approaches, it is shown that MLP probability estimation can improve recognition performance. Other approaches are discussed, though there is no such unequivocal experimental result for these methods. Connectionist Speech Recognition is of use to anyone intending to use neural networks for speech recognition or within the framework provided by an existing successful statistical approach. This includes research and development groups working in the field of speech recognition, both with standard and neural network approaches, as well as other pattern recognition and/or neural network researchers. The book is also suitable as a text for advanced courses on neural networks or speech processing. Nº de ref. de la librería APC9780792393962

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Herve Bourlard
Editorial: Kluwer Academic Publishers (1993)
ISBN 10: 0792393961 ISBN 13: 9780792393962
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Descripción Kluwer Academic Publishers, 1993. HRD. Estado de conservación: New. New Book.Shipped from US within 10 to 14 business days.THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Nº de ref. de la librería IP-9780792393962

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10.

Hervé A. Bourlard; Nelson Morgan
Editorial: Springer (1993)
ISBN 10: 0792393961 ISBN 13: 9780792393962
Nuevos Tapa dura Cantidad: 1
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Irish Booksellers
(Rumford, ME, Estados Unidos de America)
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Descripción Springer, 1993. Hardcover. Estado de conservación: New. book. Nº de ref. de la librería M0792393961

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