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Automatic speech recognition: a deep learning approach

This book summarizes the recent advancement in the field of automatic speech recognition with a focus on discriminative and hierarchical models. This will be the first automatic speech recognition book to include a comprehensive coverage of recent developments such as conditional random field and de...

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Detalles Bibliográficos
Autores principales: Yu, Dong, Deng, Li
Lenguaje:eng
Publicado: Springer 2015
Materias:
Acceso en línea:https://dx.doi.org/10.1007/978-1-4471-5779-3
http://cds.cern.ch/record/1973389
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author Yu, Dong
Deng, Li
author_facet Yu, Dong
Deng, Li
author_sort Yu, Dong
collection CERN
description This book summarizes the recent advancement in the field of automatic speech recognition with a focus on discriminative and hierarchical models. This will be the first automatic speech recognition book to include a comprehensive coverage of recent developments such as conditional random field and deep learning techniques. It presents insights and theoretical foundation of a series of recent models such as conditional random field, semi-Markov and hidden conditional random field, deep neural network, deep belief network, and deep stacking models for sequential learning. It also discusses practical considerations of using these models in both acoustic and language modeling for continuous speech recognition.
id cern-1973389
institution Organización Europea para la Investigación Nuclear
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publishDate 2015
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spelling cern-19733892021-04-21T20:42:22Zdoi:10.1007/978-1-4471-5779-3http://cds.cern.ch/record/1973389engYu, DongDeng, LiAutomatic speech recognition: a deep learning approachEngineeringThis book summarizes the recent advancement in the field of automatic speech recognition with a focus on discriminative and hierarchical models. This will be the first automatic speech recognition book to include a comprehensive coverage of recent developments such as conditional random field and deep learning techniques. It presents insights and theoretical foundation of a series of recent models such as conditional random field, semi-Markov and hidden conditional random field, deep neural network, deep belief network, and deep stacking models for sequential learning. It also discusses practical considerations of using these models in both acoustic and language modeling for continuous speech recognition.Springeroai:cds.cern.ch:19733892015
spellingShingle Engineering
Yu, Dong
Deng, Li
Automatic speech recognition: a deep learning approach
title Automatic speech recognition: a deep learning approach
title_full Automatic speech recognition: a deep learning approach
title_fullStr Automatic speech recognition: a deep learning approach
title_full_unstemmed Automatic speech recognition: a deep learning approach
title_short Automatic speech recognition: a deep learning approach
title_sort automatic speech recognition: a deep learning approach
topic Engineering
url https://dx.doi.org/10.1007/978-1-4471-5779-3
http://cds.cern.ch/record/1973389
work_keys_str_mv AT yudong automaticspeechrecognitionadeeplearningapproach
AT dengli automaticspeechrecognitionadeeplearningapproach