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Verlag: Springer US, Springer US Nov 2010, 2010
ISBN 10: 1441946764 ISBN 13: 9781441946768
Sprache: Englisch
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In den WarenkorbTaschenbuch. Zustand: 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.
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In den WarenkorbBuch. Zustand: 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.
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In den WarenkorbTaschenbuch. Zustand: 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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In den WarenkorbZustand: 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 .
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Verlag: Springer-Verlag New York Inc., 2010
ISBN 10: 1441946764 ISBN 13: 9781441946768
Sprache: Englisch
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In den WarenkorbZustand: New. The authors address the problem of developing efficient automatic speech recognition systems that maintain a balance between utilizing a wide knowledge of speech variability, while keeping the training manageable and improving speech recognition performance. Series: Lecture Notes in Electrical Engineering. Num Pages: 220 pages, 100 black & white illustrations, 15 black & white tables, biography. BIC Classification: PHDS; THR; TJK; TTBM; UKN. Category: (P) Professional & Vocational. Dimension: 234 x 156 x 11. Weight in Grams: 343. . 2010. 1st ed. Softcover of orig. ed. 2009. Paperback. . . . .
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ISBN 10: 1441946764 ISBN 13: 9781441946768
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In den WarenkorbPaperback. Zustand: 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.
Verlag: Springer-Verlag New York Inc., New York, NY, 2009
ISBN 10: 0387858296 ISBN 13: 9780387858296
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In den WarenkorbHardcover. Zustand: 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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ISBN 10: 1441946764 ISBN 13: 9781441946768
Sprache: Englisch
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In den WarenkorbZustand: New. The authors address the problem of developing efficient automatic speech recognition systems that maintain a balance between utilizing a wide knowledge of speech variability, while keeping the training manageable and improving speech recognition performance. Series: Lecture Notes in Electrical Engineering. Num Pages: 220 pages, 100 black & white illustrations, 15 black & white tables, biography. BIC Classification: PHDS; THR; TJK; TTBM; UKN. Category: (P) Professional & Vocational. Dimension: 234 x 156 x 11. Weight in Grams: 343. . 2010. 1st ed. Softcover of orig. ed. 2009. Paperback. . . . . Books ship from the US and Ireland.
Verlag: Springer-Verlag New York Inc., New York, NY, 2010
ISBN 10: 1441946764 ISBN 13: 9781441946768
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In den WarenkorbPaperback. Zustand: 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.
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In den WarenkorbZustand: 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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In den WarenkorbTaschenbuch. Zustand: 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.
Verlag: Springer-Verlag New York Inc., 2010
ISBN 10: 1441946764 ISBN 13: 9781441946768
Sprache: Englisch
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In den WarenkorbZustand: New. Print on Demand pp. 220 100 Illus.
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In den WarenkorbZustand: New. PRINT ON DEMAND pp. 220.