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Speech recognition using articulatory and excitation source features

This book discusses the contribution of articulatory and excitation source information in discriminating sound units. The authors focus on excitation source component of speech -- and the dynamics of various articulators during speech production -- for enhancement of speech recognition (SR) performa...

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Detalles Bibliográficos
Autores principales: Rao, K Sreenivasa, K E, Manjunath
Lenguaje:eng
Publicado: Springer 2017
Materias:
Acceso en línea:https://dx.doi.org/10.1007/978-3-319-49220-9
http://cds.cern.ch/record/2243799
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author Rao, K Sreenivasa
K E, Manjunath
author_facet Rao, K Sreenivasa
K E, Manjunath
author_sort Rao, K Sreenivasa
collection CERN
description This book discusses the contribution of articulatory and excitation source information in discriminating sound units. The authors focus on excitation source component of speech -- and the dynamics of various articulators during speech production -- for enhancement of speech recognition (SR) performance. Speech recognition is analyzed for read, extempore, and conversation modes of speech. Five groups of articulatory features (AFs) are explored for speech recognition, in addition to conventional spectral features. Each chapter provides the motivation for exploring the specific feature for SR task, discusses the methods to extract those features, and finally suggests appropriate models to capture the sound unit specific knowledge from the proposed features. The authors close by discussing various combinations of spectral, articulatory and source features, and the desired models to enhance the performance of SR systems.
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institution Organización Europea para la Investigación Nuclear
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spelling cern-22437992021-04-21T19:21:41Zdoi:10.1007/978-3-319-49220-9http://cds.cern.ch/record/2243799engRao, K SreenivasaK E, ManjunathSpeech recognition using articulatory and excitation source featuresEngineeringThis book discusses the contribution of articulatory and excitation source information in discriminating sound units. The authors focus on excitation source component of speech -- and the dynamics of various articulators during speech production -- for enhancement of speech recognition (SR) performance. Speech recognition is analyzed for read, extempore, and conversation modes of speech. Five groups of articulatory features (AFs) are explored for speech recognition, in addition to conventional spectral features. Each chapter provides the motivation for exploring the specific feature for SR task, discusses the methods to extract those features, and finally suggests appropriate models to capture the sound unit specific knowledge from the proposed features. The authors close by discussing various combinations of spectral, articulatory and source features, and the desired models to enhance the performance of SR systems.Springeroai:cds.cern.ch:22437992017
spellingShingle Engineering
Rao, K Sreenivasa
K E, Manjunath
Speech recognition using articulatory and excitation source features
title Speech recognition using articulatory and excitation source features
title_full Speech recognition using articulatory and excitation source features
title_fullStr Speech recognition using articulatory and excitation source features
title_full_unstemmed Speech recognition using articulatory and excitation source features
title_short Speech recognition using articulatory and excitation source features
title_sort speech recognition using articulatory and excitation source features
topic Engineering
url https://dx.doi.org/10.1007/978-3-319-49220-9
http://cds.cern.ch/record/2243799
work_keys_str_mv AT raoksreenivasa speechrecognitionusingarticulatoryandexcitationsourcefeatures
AT kemanjunath speechrecognitionusingarticulatoryandexcitationsourcefeatures