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Edité par Springer-Verlag New York Inc., New York, NY, 2010
ISBN 10 : 1441946764 ISBN 13 : 9781441946768
Langue: anglais
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Edition originale
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Ajouter au panierPaperback. Etat : new. Paperback. Incorporating Knowledge Sources into Statistical Speech Recognition addresses the problem of developing efficient automatic speech recognition (ASR) systems, which maintain a balance between utilizing a wide knowledge of speech variability, while keeping the training / recognition effort feasible and improving speech recognition performance. The book provides an efficient general framework to incorporate additional knowledge sources into state-of-the-art statistical ASR systems. It can be applied to many existing ASR problems with their respective model-based likelihood functions in flexible ways. Incorporating Knowledge Sources into Statistical Speech Recognition addresses the problem of developing efficient automatic speech recognition (ASR) systems, which maintain a balance between utilizing a wide knowledge of speech variability, while keeping the training / recognition effort feasible and improving speech recognition performance. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Edité par Springer-Verlag New York Inc., New York, NY, 2009
ISBN 10 : 0387858296 ISBN 13 : 9780387858296
Langue: anglais
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Ajouter au panierHardcover. Etat : new. Hardcover. Incorporating Knowledge Sources into Statistical Speech Recognition addresses the problem of developing efficient automatic speech recognition (ASR) systems, which maintain a balance between utilizing a wide knowledge of speech variability, while keeping the training / recognition effort feasible and improving speech recognition performance. The book provides an efficient general framework to incorporate additional knowledge sources into state-of-the-art statistical ASR systems. It can be applied to many existing ASR problems with their respective model-based likelihood functions in flexible ways. Incorporating Knowledge Sources into Statistical Speech Recognition addresses the problem of developing efficient automatic speech recognition (ASR) systems, which maintain a balance between utilizing a wide knowledge of speech variability, while keeping the training / recognition effort feasible and improving speech recognition performance. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Ajouter au panierEtat : New. pp. 220.
Edité par Springer US, Springer US Nov 2010, 2010
ISBN 10 : 1441946764 ISBN 13 : 9781441946768
Langue: anglais
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Ajouter au panierTaschenbuch. Etat : Neu. Neuware -Incorporating Knowledge Sources into Statistical Speech Recognition addresses the problem of developing efficient automatic speech recognition (ASR) systems, which maintain a balance between utilizing a wide knowledge of speech variability, while keeping the training / recognition effort feasible and improving speech recognition performance. The book provides an efficient general framework to incorporate additional knowledge sources into state-of-the-art statistical ASR systems. It can be applied to many existing ASR problems with their respective model-based likelihood functions in flexible ways.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 220 pp. Englisch.
Vendeur : moluna, Greven, Allemagne
EUR 173,76
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Ajouter au panierEtat : New. Provides an efficient general framework to incorporate additional knowledge sources into state-of-the-art statistical ASR systemsDemonstrates applications to existing ASR problems with their respective model-based likelihood functions in flexible .
Edité par Springer US, Springer US, 2010
ISBN 10 : 1441946764 ISBN 13 : 9781441946768
Langue: anglais
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Ajouter au panierTaschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - Incorporating Knowledge Sources into Statistical Speech Recognition addresses the problem of developing efficient automatic speech recognition (ASR) systems, which maintain a balance between utilizing a wide knowledge of speech variability, while keeping the training / recognition effort feasible and improving speech recognition performance. The book provides an efficient general framework to incorporate additional knowledge sources into state-of-the-art statistical ASR systems. It can be applied to many existing ASR problems with their respective model-based likelihood functions in flexible ways.
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Ajouter au panierBuch. Etat : Neu. Neuware - Incorporating Knowledge Sources into Statistical Speech Recognition addresses the problem of developing efficient automatic speech recognition (ASR) systems, which maintain a balance between utilizing a wide knowledge of speech variability, while keeping the training / recognition effort feasible and improving speech recognition performance. The book provides an efficient general framework to incorporate additional knowledge sources into state-of-the-art statistical ASR systems. It can be applied to many existing ASR problems with their respective model-based likelihood functions in flexible ways.
Vendeur : Mispah books, Redhill, SURRE, Royaume-Uni
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Ajouter au panierPaperback. Etat : Like New. Like New. book.
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Ajouter au panierHardcover. Etat : Brand New. 1st edition. 196 pages. 9.50x6.25x0.75 inches. In Stock.
Edité par Springer-Verlag New York Inc., New York, NY, 2010
ISBN 10 : 1441946764 ISBN 13 : 9781441946768
Langue: anglais
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Edition originale
EUR 279,72
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Ajouter au panierPaperback. Etat : new. Paperback. Incorporating Knowledge Sources into Statistical Speech Recognition addresses the problem of developing efficient automatic speech recognition (ASR) systems, which maintain a balance between utilizing a wide knowledge of speech variability, while keeping the training / recognition effort feasible and improving speech recognition performance. The book provides an efficient general framework to incorporate additional knowledge sources into state-of-the-art statistical ASR systems. It can be applied to many existing ASR problems with their respective model-based likelihood functions in flexible ways. Incorporating Knowledge Sources into Statistical Speech Recognition addresses the problem of developing efficient automatic speech recognition (ASR) systems, which maintain a balance between utilizing a wide knowledge of speech variability, while keeping the training / recognition effort feasible and improving speech recognition performance. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Edité par Springer-Verlag New York Inc., 2010
ISBN 10 : 1441946764 ISBN 13 : 9781441946768
Langue: anglais
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EUR 164,78
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Ajouter au panierPaperback / softback. Etat : New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 346.
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
EUR 160,49
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Ajouter au panierTaschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Incorporating Knowledge Sources into Statistical Speech Recognition addresses the problem of developing efficient automatic speech recognition (ASR) systems, which maintain a balance between utilizing a wide knowledge of speech variability, while keeping the training / recognition effort feasible and improving speech recognition performance. The book provides an efficient general framework to incorporate additional knowledge sources into state-of-the-art statistical ASR systems. It can be applied to many existing ASR problems with their respective model-based likelihood functions in flexible ways. 220 pp. Englisch.
Vendeur : moluna, Greven, Allemagne
EUR 136,16
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Ajouter au panierEtat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides an efficient general framework to incorporate additional knowledge sources into state-of-the-art statistical ASR systemsDemonstrates applications to existing ASR problems with their respective model-based likelihood functions in flexible .
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Ajouter au panierEtat : New. Print on Demand pp. 220 100 Illus.
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Ajouter au panierEtat : New. PRINT ON DEMAND pp. 220.