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160 pages. German language. 8.66x5.91x0.37 inches. In Stock. Bestandsnummer des Verkäufers 383810191X
Due to the growing need for security applications,speaker recognition as the biometric task ofauthenticating a claimant by voice has currentlybecome a focus of interest.In this book we present new approaches to integratediscriminative classifiers like Support VectorMachines (SVMs) and Sparse Kernel Logistic Regression(SKLR) into speaker recognition systems that aretraditionally based on generative classifiers likeGaussian Mixture Models (GMMs).In a first approach for limited training data thediscriminative classifiers are applied directly onfeature vectors from parameterized speech frames andit is shown that both, SVM as well as SKLR outperformtraditional methods.In the second approach a state-of-the-art speakerrecognition system for large amount of training datais designed that combines Gaussian Mixture Modelswith discriminative classifiers.Furthermore, we investigate different featureextraction methods for speaker recognition on largeamount of training data and it is shown that theapplication of fusion schemes that combine thesesubsystems yield a significant improvement of therecognition performance in comparison to theapplication of single subsystems.
Über die Autorin bzw. den Autor: Marcel Katz studied Electrical Engineering in Duesseldorf andreceived his PhD for his works in the fields of speech andspeaker recognition in 2008 from the University of Magdeburg,Germany. He successfully participated in several speakerrecognition evaluations and is currently working as a speechrecognition specialist in Cambridge, UK.
Titel: Discriminative Classifiers For Speaker ...
Verlag: Südwestdeutscher Verlag Für Hochschulschriften
Erscheinungsdatum: 2009
Einband: Paperback
Zustand: Brand New
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Due to the growing need for security applications, speaker recognition as the biometric task of authenticating a claimant by voice has currently become a focus of interest. In this book we present new approaches to integrate discriminative classifiers like Support Vector Machines (SVMs) and Sparse Kernel Logistic Regression (SKLR) into speaker recognition systems that are traditionally based on generative classifiers like Gaussian Mixture Models (GMMs). In a first approach for limited training data the discriminative classifiers are applied directly on feature vectors from parameterized speech frames and it is shown that both, SVM as well as SKLR outperform traditional methods. In the second approach a state-of-the-art speaker recognition system for large amount of training data is designed that combines Gaussian Mixture Models with discriminative classifiers. Furthermore, we investigate different feature extraction methods for speaker recognition on large amount of training data and it is shown that the application of fusion schemes that combine these subsystems yield a significant improvement of the recognition performance in comparison to the application of single subsystems. Bestandsnummer des Verkäufers 9783838101910
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Anbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Due to the growing need for security applications, speaker recognition as the biometric task of authenticating a claimant by voice has currently become a focus of interest. In this book we present new approaches to integrate discriminative classifiers like Support Vector Machines (SVMs) and Sparse Kernel Logistic Regression (SKLR) into speaker recognition systems that are traditionally based on generative classifiers like Gaussian Mixture Models (GMMs). In a first approach for limited training data the discriminative classifiers are applied directly on feature vectors from parameterized speech frames and it is shown that both, SVM as well as SKLR outperform traditional methods. In the second approach a state-of-the-art speaker recognition system for large amount of training data is designed that combines Gaussian Mixture Models with discriminative classifiers. Furthermore, we investigate different feature extraction methods for speaker recognition on large amount of training data and it is shown that the application of fusion schemes that combine these subsystems yield a significant improvement of the recognition performance in comparison to the application of single subsystems. 164 pp. Deutsch. Bestandsnummer des Verkäufers 9783838101910
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Anbieter: preigu, Osnabrück, Deutschland
Taschenbuch. Zustand: Neu. Discriminative Classifiers for Speaker Recognition | Marcel Katz | Taschenbuch | 164 S. | Deutsch | 2015 | Südwestdeutscher Verlag für Hochschulschriften | EAN 9783838101910 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Bestandsnummer des Verkäufers 101662129
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Due to the growing need for security applications, speaker recognition as the biometric task of authenticating a claimant by voice has currently become a focus of interest. In this book we present new approaches to integrate discriminative classifiers like Support Vector Machines (SVMs) and Sparse Kernel Logistic Regression (SKLR) into speaker recognition systems that are traditionally based on generative classifiers like Gaussian Mixture Models (GMMs). In a first approach for limited training data the discriminative classifiers are applied directly on feature vectors from parameterized speech frames and it is shown that both, SVM as well as SKLR outperform traditional methods. In the second approach a state-of-the-art speaker recognition system for large amount of training data is designed that combines Gaussian Mixture Models with discriminative classifiers. Furthermore, we investigate different feature extraction methods for speaker recognition on large amount of training data and it is shown that the application of fusion schemes that combine these subsystems yield a significant improvement of the recognition performance in comparison to the application of single subsystems.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 164 pp. Deutsch. Bestandsnummer des Verkäufers 9783838101910
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Due to the growing need for security applications, speaker recognition as the biometric task of authenticating a claimant by voice has currently become a focus of interest. In this book we present new approaches to integrate discriminative classifiers like . Bestandsnummer des Verkäufers 5404587
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Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
Paperback. Zustand: Brand New. 160 pages. German language. 8.66x5.91x0.37 inches. In Stock. Bestandsnummer des Verkäufers __383810191X
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