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IMPROVEMENT OF NOISE ROBUST SPEAKER IDENTIFICATION: PERFORMANCE IMPROVEMENT OF REAL TIME SPEAKER IDENTIFICATION SYSTEM UNDER NOISY TALKING CONDITION - Softcover
Synopsis
In this book, an improved strategy to the improvement of an automated text dependent speaker identification system as a biometrically-based technology has been studied and it is concerned with the close set text dependent speaker identification process using genetically optimized Hidden Markov Model with cepstral based features. At first, speech is taken by using microphone. Then some speech pre-processing techniques such as start and end points detection, silence part removal, pre-emphasis filtering, speech segmentation, windowing etc techniques have been applied. After pre-processing, features are extracted by different techniques to optimize the performance of the identification. RCC, MFCC, ?MFCC, ??MFCC, LPC and LPCC have been used to extract the features. To design the codebook, Genetic Algorithm has been used. Finally, HMM is used in the learning and identification phases. To remove the background noise, Wiener filter has been used. To measure the performance, a standard speech corpus NOIZEUS has been used. The experimental result shows the superiority of this proposed GA-HMM based close-set real time speaker identification system.
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IMPROVEMENT OF NOISE ROBUST SPEAKER IDENTIFICATION
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LAP LAMBERT Academic Publishing Mai 2010, 2010
ISBN 10: 3838364155
ISBN 13: 9783838364155
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Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In this book, an improved strategy to the improvement of an automated text dependent speaker identification system as a biometrically-based technology has been studied and it is concerned with the close set text dependent speaker identification process using genetically optimized Hidden Markov Model with cepstral based features. At first, speech is taken by using microphone. Then some speech pre-processing techniques such as start and end points detection, silence part removal, pre-emphasis filtering, speech segmentation, windowing etc techniques have been applied. After pre-processing, features are extracted by different techniques to optimize the performance of the identification. RCC, MFCC, ¿MFCC, ¿¿MFCC, LPC and LPCC have been used to extract the features. To design the codebook, Genetic Algorithm has been used. Finally, HMM is used in the learning and identification phases. To remove the background noise, Wiener filter has been used. To measure the performance, a standard speech corpus NOIZEUS has been used. The experimental result shows the superiority of this proposed GA-HMM based close-set real time speaker identification system. 88 pp. Englisch. Seller Inventory # 9783838364155
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IMPROVEMENT OF NOISE ROBUST SPEAKER IDENTIFICATION
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LAP LAMBERT Academic Publishing, 2010
ISBN 10: 3838364155
ISBN 13: 9783838364155
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Seller: moluna, Greven, Germany
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Condition: 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 & Engineering at Rajshahi University of Engineering & Technology. His research interests include bio-informatics, human-computer interac. Seller Inventory # 5416756
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IMPROVEMENT OF NOISE ROBUST SPEAKER IDENTIFICATION
Published by
LAP LAMBERT Academic Publishing Mai 2010, 2010
ISBN 10: 3838364155
ISBN 13: 9783838364155
New
Taschenbuch
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -In this book, an improved strategy to the improvement of an automated text dependent speaker identification system as a biometrically-based technology has been studied and it is concerned with the close set text dependent speaker identification process using genetically optimized Hidden Markov Model with cepstral based features. At first, speech is taken by using microphone. Then some speech pre-processing techniques such as start and end points detection, silence part removal, pre-emphasis filtering, speech segmentation, windowing etc techniques have been applied. After pre-processing, features are extracted by different techniques to optimize the performance of the identification. RCC, MFCC, ¿MFCC, ¿¿MFCC, LPC and LPCC have been used to extract the features. To design the codebook, Genetic Algorithm has been used. Finally, HMM is used in the learning and identification phases. To remove the background noise, Wiener filter has been used. To measure the performance, a standard speech corpus NOIZEUS has been used. The experimental result shows the superiority of this proposed GA-HMM based close-set real time speaker identification system.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 88 pp. Englisch. Seller Inventory # 9783838364155
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IMPROVEMENT OF NOISE ROBUST SPEAKER IDENTIFICATION : PERFORMANCE IMPROVEMENT OF REAL TIME SPEAKER IDENTIFICATION SYSTEM UNDER NOISY TALKING CONDITION
Published by
LAP LAMBERT Academic Publishing, 2010
ISBN 10: 3838364155
ISBN 13: 9783838364155
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In this book, an improved strategy to the improvement of an automated text dependent speaker identification system as a biometrically-based technology has been studied and it is concerned with the close set text dependent speaker identification process using genetically optimized Hidden Markov Model with cepstral based features. At first, speech is taken by using microphone. Then some speech pre-processing techniques such as start and end points detection, silence part removal, pre-emphasis filtering, speech segmentation, windowing etc techniques have been applied. After pre-processing, features are extracted by different techniques to optimize the performance of the identification. RCC, MFCC, ¿MFCC, ¿¿MFCC, LPC and LPCC have been used to extract the features. To design the codebook, Genetic Algorithm has been used. Finally, HMM is used in the learning and identification phases. To remove the background noise, Wiener filter has been used. To measure the performance, a standard speech corpus NOIZEUS has been used. The experimental result shows the superiority of this proposed GA-HMM based close-set real time speaker identification system. Seller Inventory # 9783838364155
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IMPROVEMENT OF NOISE ROBUST SPEAKER IDENTIFICATION | PERFORMANCE IMPROVEMENT OF REAL TIME SPEAKER IDENTIFICATION SYSTEM UNDER NOISY TALKING CONDITION
Published by
LAP LAMBERT Academic Publishing, 2010
ISBN 10: 3838364155
ISBN 13: 9783838364155
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Taschenbuch
Seller: preigu, Osnabrück, Germany
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Taschenbuch. Condition: Neu. IMPROVEMENT OF NOISE ROBUST SPEAKER IDENTIFICATION | PERFORMANCE IMPROVEMENT OF REAL TIME SPEAKER IDENTIFICATION SYSTEM UNDER NOISY TALKING CONDITION | Md. Rabiul Islam (u. a.) | Taschenbuch | 88 S. | Englisch | 2010 | LAP LAMBERT Academic Publishing | EAN 9783838364155 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu Print on Demand. Seller Inventory # 101106111