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Item Details
| Title:
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INCORPORATING KNOWLEDGE SOURCES INTO STATISTICAL SPEECH RECOGNITION
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| By: |
Satoshi Nakamura, Sakriani Sakti, Konstantin Markov |
| Format: |
Paperback |
| List price:
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£109.99 |
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We currently do not stock this item, please contact the publisher directly for
further information.
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| ISBN 10: |
1441946764 |
| ISBN 13: |
9781441946768 |
| Publisher: |
SPRINGER-VERLAG NEW YORK INC. |
| Pub. date: |
28 October, 2010 |
| Edition: |
1st ed. Softcover of orig. ed. 2009 |
| Series: |
Lecture Notes in Electrical Engineering 42 |
| Pages: |
196 |
| Description: |
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. |
| Synopsis: |
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. |
| Illustrations: |
100 black & white illustrations, 15 black & white tables, biography |
| Publication: |
US |
| Imprint: |
Springer-Verlag New York Inc. |
| Returns: |
Returnable |
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