New era for robust speech recognition : exploiting deep learning /

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Bibliographic Details
Imprint:Cham : Springer, 2017.
Description:1 online resource (XVII, 436 pages) : illustrations
Language:English
Subject:
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/11389321
Hidden Bibliographic Details
Other authors / contributors:Watanabe, Shinji, editor.
Delcroix, Marc, editor.
Metze, Florian, editor.
Hershey, John R., editor.
ISBN:9783319646800
331964680X
3319646796
9783319646794
Digital file characteristics:text file PDF
Notes:Includes bibliographical references.
Summary:This book covers the state-of-the-art in deep neural-network-based methods for noise robustness in distant speech recognition applications. It provides insights and detailed descriptions of some of the new concepts and key technologies in the field, including novel architectures for speech enhancement, microphone arrays, robust features, acoustic model adaptation, training data augmentation, and training criteria. The contributed chapters also include descriptions of real-world applications, benchmark tools and datasets widely used in the field. This book is intended for researchers and practitioners working in the field of speech processing and recognition who are interested in the latest deep learning techniques for noise robustness. It will also be of interest to graduate students in electrical engineering or computer science, who will find it a useful guide to this field of research.
Other form:Printed edition: 9783319646794
Standard no.:10.1007/978-3-319-64680-0
10.1007/978-3-319-64