Robust automatic speech recognition: a bridge to practical applications
Robust Automatic Speech Recognition: A Bridge to Practical Applications establishes a solid foundation for automatic speech recognition that is robust against acoustic environmental distortion. It provides a thorough overview of classical and modern noise-and reverberation robust techniques that hav...
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Hauptverfasser: | , , , |
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Format: | Elektronisch E-Book |
Sprache: | English |
Veröffentlicht: |
Waltham, MA
Academic Press, an imprint of Elsevier
2016
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Schlagworte: | |
Online-Zugang: | Volltext |
Zusammenfassung: | Robust Automatic Speech Recognition: A Bridge to Practical Applications establishes a solid foundation for automatic speech recognition that is robust against acoustic environmental distortion. It provides a thorough overview of classical and modern noise-and reverberation robust techniques that have been developed over the past thirty years, with an emphasis on practical methods that have been proven to be successful and which are likely to be further developed for future applications. The strengths and weaknesses of robustness-enhancing speech recognition techniques are carefully analyzed. The book covers noise-robust techniques designed for acoustic models which are based on both Gaussian mixture models and deep neural networks. In addition, a guide to selecting the best methods for practical applications is provided. The reader will: Gain a unified, deep and systematic understanding of the state-of-the-art technologies for robust speech recognitionLearn the links and relationship between alternative technologies for robust speech recognition Be able to use the technology analysis and categorization detailed in the book to guide future technology developmentBe able to develop new noise-robust methods in the current era of deep learning for acoustic modeling in speech recognition |
Beschreibung: | Includes bibliographical references and index |
Beschreibung: | 1 online resource |
ISBN: | 9780128023983 9780128026168 0128026162 |
Internformat
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520 | 3 | |a Robust Automatic Speech Recognition: A Bridge to Practical Applications establishes a solid foundation for automatic speech recognition that is robust against acoustic environmental distortion. It provides a thorough overview of classical and modern noise-and reverberation robust techniques that have been developed over the past thirty years, with an emphasis on practical methods that have been proven to be successful and which are likely to be further developed for future applications. The strengths and weaknesses of robustness-enhancing speech recognition techniques are carefully analyzed. The book covers noise-robust techniques designed for acoustic models which are based on both Gaussian mixture models and deep neural networks. In addition, a guide to selecting the best methods for practical applications is provided. The reader will: Gain a unified, deep and systematic understanding of the state-of-the-art technologies for robust speech recognitionLearn the links and relationship between alternative technologies for robust speech recognition Be able to use the technology analysis and categorization detailed in the book to guide future technology developmentBe able to develop new noise-robust methods in the current era of deep learning for acoustic modeling in speech recognition | |
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Datensatz im Suchindex
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---|---|
any_adam_object | |
author | Li, Jinyu Deng, Li Haeb-Umbach, Reinhold Gong, Yifan |
author_facet | Li, Jinyu Deng, Li Haeb-Umbach, Reinhold Gong, Yifan |
author_role | aut aut aut aut |
author_sort | Li, Jinyu |
author_variant | j l jl l d ld r h u rhu y g yg |
building | Verbundindex |
bvnumber | BV043218024 |
collection | ZDB-33-ESD ZDB-33-EBS |
ctrlnum | (OCoLC)952079843 (DE-599)BVBBV043218024 |
dewey-full | 006.54 |
dewey-hundreds | 000 - Computer science, information, general works |
dewey-ones | 006 - Special computer methods |
dewey-raw | 006.54 |
dewey-search | 006.54 |
dewey-sort | 16.54 |
dewey-tens | 000 - Computer science, information, general works |
discipline | Informatik |
format | Electronic eBook |
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id | DE-604.BV043218024 |
illustrated | Not Illustrated |
indexdate | 2024-07-10T07:20:50Z |
institution | BVB |
isbn | 9780128023983 9780128026168 0128026162 |
language | English |
oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-028641006 |
oclc_num | 952079843 |
open_access_boolean | |
owner | DE-706 |
owner_facet | DE-706 |
physical | 1 online resource |
psigel | ZDB-33-ESD ZDB-33-EBS EBOOK-ELS-FL-UBW UBY_PDA_ESDENG_Kauf |
publishDate | 2016 |
publishDateSearch | 2016 |
publishDateSort | 2016 |
publisher | Academic Press, an imprint of Elsevier |
record_format | marc |
spelling | Li, Jinyu Verfasser aut Robust automatic speech recognition a bridge to practical applications Jinyu Li, Li Deng, Reinhold Haeb-Umbach, Yifang Gong Waltham, MA Academic Press, an imprint of Elsevier 2016 1 online resource txt rdacontent c rdamedia cr rdacarrier Includes bibliographical references and index Robust Automatic Speech Recognition: A Bridge to Practical Applications establishes a solid foundation for automatic speech recognition that is robust against acoustic environmental distortion. It provides a thorough overview of classical and modern noise-and reverberation robust techniques that have been developed over the past thirty years, with an emphasis on practical methods that have been proven to be successful and which are likely to be further developed for future applications. The strengths and weaknesses of robustness-enhancing speech recognition techniques are carefully analyzed. The book covers noise-robust techniques designed for acoustic models which are based on both Gaussian mixture models and deep neural networks. In addition, a guide to selecting the best methods for practical applications is provided. The reader will: Gain a unified, deep and systematic understanding of the state-of-the-art technologies for robust speech recognitionLearn the links and relationship between alternative technologies for robust speech recognition Be able to use the technology analysis and categorization detailed in the book to guide future technology developmentBe able to develop new noise-robust methods in the current era of deep learning for acoustic modeling in speech recognition Automatische Spracherkennung (DE-588)4003961-4 gnd rswk-swf Automatic speech recognition Speech processing systems COMPUTERS / General Automatische Spracherkennung (DE-588)4003961-4 s DE-604 Deng, Li aut Haeb-Umbach, Reinhold aut Gong, Yifan aut http://www.sciencedirect.com/science/book/9780128023983 Volltext |
spellingShingle | Li, Jinyu Deng, Li Haeb-Umbach, Reinhold Gong, Yifan Robust automatic speech recognition a bridge to practical applications Automatische Spracherkennung (DE-588)4003961-4 gnd |
subject_GND | (DE-588)4003961-4 |
title | Robust automatic speech recognition a bridge to practical applications |
title_auth | Robust automatic speech recognition a bridge to practical applications |
title_exact_search | Robust automatic speech recognition a bridge to practical applications |
title_full | Robust automatic speech recognition a bridge to practical applications Jinyu Li, Li Deng, Reinhold Haeb-Umbach, Yifang Gong |
title_fullStr | Robust automatic speech recognition a bridge to practical applications Jinyu Li, Li Deng, Reinhold Haeb-Umbach, Yifang Gong |
title_full_unstemmed | Robust automatic speech recognition a bridge to practical applications Jinyu Li, Li Deng, Reinhold Haeb-Umbach, Yifang Gong |
title_short | Robust automatic speech recognition |
title_sort | robust automatic speech recognition a bridge to practical applications |
title_sub | a bridge to practical applications |
topic | Automatische Spracherkennung (DE-588)4003961-4 gnd |
topic_facet | Automatische Spracherkennung |
url | http://www.sciencedirect.com/science/book/9780128023983 |
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