Editore: LAP LAMBERT Academic Publishing Jun 2010, 2010
ISBN 10: 3838368916 ISBN 13: 9783838368917
Lingua: Inglese
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
EUR 49,00
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Neuware -Automatic Speech Recognition (ASR) has progressed considerably over the past several decades, but still has not achieved the potential imagined at its very beginning. Almost all of the existing applications of ASR systems are PC based. This work is an attempt to develop a speech recognition system that is independent of any PC support and is small enough in size to be used in a daily use consumer appliance. The proposed system would recognize isolated word utterances from a limited vocabulary, provide speaker independence, require less memory and be cost-efficient compared to present ASR systems. In this system, isolated word recognition is performed by using Vector Quantization (VQ) and Mel-Frequency Cepstral Coefficient (MFCC). The final system has been implemented on a vero board with an ATMEGA32 microcontroller. Learning and recognition algorithm have been used to recognize the speech utterances.Books on Demand GmbH, Überseering 33, 22297 Hamburg 80 pp. Englisch.
Editore: LAP LAMBERT Academic Publishing, 2010
ISBN 10: 3838368916 ISBN 13: 9783838368917
Lingua: Inglese
Da: Mispah books, Redhill, SURRE, Regno Unito
EUR 113,90
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Aggiungi al carrelloPaperback. Condizione: Like New. Like New. book.
Editore: LAP LAMBERT Academic Publishing Jun 2010, 2010
ISBN 10: 3838368916 ISBN 13: 9783838368917
Lingua: Inglese
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 49,00
Convertire valutaQuantità: 2 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Automatic Speech Recognition (ASR) has progressed considerably over the past several decades, but still has not achieved the potential imagined at its very beginning. Almost all of the existing applications of ASR systems are PC based. This work is an attempt to develop a speech recognition system that is independent of any PC support and is small enough in size to be used in a daily use consumer appliance. The proposed system would recognize isolated word utterances from a limited vocabulary, provide speaker independence, require less memory and be cost-efficient compared to present ASR systems. In this system, isolated word recognition is performed by using Vector Quantization (VQ) and Mel-Frequency Cepstral Coefficient (MFCC). The final system has been implemented on a vero board with an ATMEGA32 microcontroller. Learning and recognition algorithm have been used to recognize the speech utterances. 80 pp. Englisch.
Editore: LAP LAMBERT Academic Publishing, 2010
ISBN 10: 3838368916 ISBN 13: 9783838368917
Lingua: Inglese
Da: moluna, Greven, Germania
EUR 41,05
Convertire valutaQuantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Islam Md. RabiulMd. Rabiul Islam is an Assistant Professor in the Department of Computer Science and Engineering at Rajshahi University of Engineering and Technology. His research interests include bio-informatics, human-computer int.
Editore: LAP LAMBERT Academic Publishing, 2010
ISBN 10: 3838368916 ISBN 13: 9783838368917
Lingua: Inglese
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 49,00
Convertire valutaQuantità: 1 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Automatic Speech Recognition (ASR) has progressed considerably over the past several decades, but still has not achieved the potential imagined at its very beginning. Almost all of the existing applications of ASR systems are PC based. This work is an attempt to develop a speech recognition system that is independent of any PC support and is small enough in size to be used in a daily use consumer appliance. The proposed system would recognize isolated word utterances from a limited vocabulary, provide speaker independence, require less memory and be cost-efficient compared to present ASR systems. In this system, isolated word recognition is performed by using Vector Quantization (VQ) and Mel-Frequency Cepstral Coefficient (MFCC). The final system has been implemented on a vero board with an ATMEGA32 microcontroller. Learning and recognition algorithm have been used to recognize the speech utterances.