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Synopsis
Automatic speech recognition suffers from a lack of robustness with respect to noise, reverberation and interfering speech. The growing field of speech recognition in the presence of missing or uncertain input data seeks to ameliorate those problems by using not only a preprocessed speech signal but also an estimate of its reliability to selectively focus on those segments and features that are most reliable for recognition. This book presents the state of the art in recognition in the presence of uncertainty, offering examples that utilize uncertainty information for noise robustness, reverberation robustness, simultaneous recognition of multiple speech signals, and audiovisual speech recognition.
The book is appropriate for scientists and researchers in the field of speech recognition who will find an overview of the state of the art in robust speech recognition, professionals working in speech recognition who will find strategies for improving recognition results in various conditions of mismatch, and lecturers of advanced courses on speech processing or speech recognition who will find a reference and a comprehensive introduction to the field. The book assumes an understanding of the fundamentals of speech recognition using Hidden Markov Models.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
À propos de l'auteur
Prof. Dr.-Ing. Dorothea Kolossa is a professor at the Institut für Kommunikationsakustik of the Ruhr-Universität Bochum, Germany; her research interests are automatic speech recognition, digital speech signal processing, and blind source separation.
Prof. Dr.-Ing. Reinhold Haeb-Umbach heads the Dept. of Communications Engineering of the University of Paderborn, Germany; his research interest are speech signal processing and automatic speech recognition, statistical learning and pattern recognition, and signal processing for digital communications.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Robust Speech Recognition of Uncertain (eng)
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Robust Speech Recognition of Uncertain or Missing Data
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Springer Berlin Heidelberg, Springer Berlin Heidelberg Jul 2011, 2011
ISBN 10 : 3642213162
ISBN 13 : 9783642213168
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Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Automatic speech recognition suffers from a lack of robustness with respect to noise, reverberation and interfering speech. The growing field of speech recognition in the presence of missing or uncertain input data seeks to ameliorate those problems by using not only a preprocessed speech signal but also an estimate of its reliability to selectively focus on those segments and features that are most reliable for recognition. This book presents the state of the art in recognition in the presence of uncertainty, offering examples that utilize uncertainty information for noise robustness, reverberation robustness, simultaneous recognition of multiple speech signals, and audiovisual speech recognition.The book is appropriate for scientists and researchers in the field of speech recognition who will find an overview of the state of the art in robust speech recognition, professionals working in speech recognition who will find strategies for improving recognition results in various conditions of mismatch, and lecturers of advanced courses on speech processing or speech recognition who will find a reference and a comprehensive introduction to the field. The book assumes an understanding of the fundamentals of speech recognition using Hidden Markov Models. 400 pp. Englisch. N° de réf. du vendeur 9783642213168
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Robust Speech Recognition of Uncertain or Missing Data : Theory and Applications
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Robust Speech Recognition of Uncertain Or Missing Data: Theory and Applications [Hardcover] [Jul 14, 2011] Kolossa, Dorothea and Haeb-Umbach, Reinhold
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Robust Speech Recognition of Uncertain or Missing Data
Edité par
Springer Berlin Heidelberg, 2011
ISBN 10 : 3642213162
ISBN 13 : 9783642213168
Neuf
Couverture rigide
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Scientists and researchers in the field of speech recognition will find an overview of the state of the art in robust speech recognition. Professionals working in speech recognition will find strategies for improving results in various conditions . N° de réf. du vendeur 5052509
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Robust Speech Recognition of Uncertain or Missing Data : Theory and Applications
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Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - Automatic speech recognition suffers from a lack of robustness with respect to noise, reverberation and interfering speech. The growing field of speech recognition in the presence of missing or uncertain input data seeks to ameliorate those problems by using not only a preprocessed speech signal but also an estimate of its reliability to selectively focus on those segments and features that are most reliable for recognition. This book presents the state of the art in recognition in the presence of uncertainty, offering examples that utilize uncertainty information for noise robustness, reverberation robustness, simultaneous recognition of multiple speech signals, and audiovisual speech recognition.The book is appropriate for scientists and researchers in the field of speech recognition who will find an overview of the state of the art in robust speech recognition, professionals working in speech recognition who will find strategies for improving recognition results in various conditions of mismatch, and lecturers of advanced courses on speech processing or speech recognition who will find a reference and a comprehensive introduction to the field. The book assumes an understanding of the fundamentals of speech recognition using Hidden Markov Models. N° de réf. du vendeur 9783642213168
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Robust Speech Recognition of Uncertain or Missing Data
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Robust Speech Recognition of Uncertain or Missing Data
Edité par
Springer, Springer Jul 2011, 2011
ISBN 10 : 3642213162
ISBN 13 : 9783642213168
Neuf
Couverture rigide
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Buch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -Automatic speech recognition suffers from a lack of robustness with respect to noise, reverberation and interfering speech. The growing field of speech recognition in the presence of missing or uncertain input data seeks to ameliorate those problems by using not only a preprocessed speech signal but also an estimate of its reliability to selectively focus on those segments and features that are most reliable for recognition. This book presents the state of the art in recognition in the presence of uncertainty, offering examples that utilize uncertainty information for noise robustness, reverberation robustness, simultaneous recognition of multiple speech signals, and audiovisual speech recognition.The book is appropriate for scientists and researchers in the field of speech recognition who will find an overview of the state of the art in robust speech recognition, professionals working in speech recognition who will find strategies for improving recognition results in various conditions of mismatch, and lecturers of advanced courses on speech processing or speech recognition who will find a reference and a comprehensive introduction to the field. The book assumes an understanding of the fundamentals of speech recognition using Hidden Markov Models.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 400 pp. Englisch. N° de réf. du vendeur 9783642213168
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Robust Speech Recognition of Uncertain or Missing Data: Theory and Applications
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Robust Speech Recognition of Uncertain or Missing Data : Theory and Applications
Edité par
Springer, 2011
ISBN 10 : 3642213162
ISBN 13 : 9783642213168
Ancien ou d'occasion
Couverture rigide
Vendeur : Buchpark, Trebbin, Allemagne
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Etat : Sehr gut. Zustand: Sehr gut | Seiten: 400 | Sprache: Englisch | Produktart: Bücher | Automatic speech recognition suffers from a lack of robustness with respect to noise, reverberation and interfering speech. The growing field of speech recognition in the presence of missing or uncertain input data seeks to ameliorate those problems by using not only a preprocessed speech signal but also an estimate of its reliability to selectively focus on those segments and features that are most reliable for recognition. This book presents the state of the art in recognition in the presence of uncertainty, offering examples that utilize uncertainty information for noise robustness, reverberation robustness, simultaneous recognition of multiple speech signals, and audiovisual speech recognition.The book is appropriate for scientists and researchers in the field of speech recognition who will find an overview of the state of the art in robust speech recognition, professionals working in speech recognition who will find strategies for improving recognition results in various conditions of mismatch, and lecturers of advanced courses on speech processing or speech recognition who will find a reference and a comprehensive introduction to the field. The book assumes an understanding of the fundamentals of speech recognition using Hidden Markov Models. N° de réf. du vendeur 10701273/12
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