Please use this identifier to cite or link to this item: http://localhost:80/handle/Hannan/60771
Title: Acoustic Modeling for Emotion Recognition
Authors: Anne, Koteswara Rao.;Kuchibhotla, Swarna.;Vankayalapati, Hima Deepthi.
subject: Engineering;Computer Science;Computational linguistics.;Acoustics.;Engineering;Signal, Image and Speech Processing.;Computational Linguistics.;User Interfaces and Human Computer Interaction.;Acoustics.;TK7882.S65
Year: 2015
place: Cham
Publisher: Springer International Publishing :.
Imprint: Springer,
Series/Report no.: SpringerBriefs in Electrical and Computer Engineering, 2191-8112.
SpringerBriefs in Electrical and Computer Engineering, 2191-8112.
Abstract:  This book presents state of art research in speech emotion recognition. Readers are first presented with basic research and applications gradually more advance information is provided, giving readers comprehensive guidance for classify emotions through speech. Simulated databases are used and results extensively compared, with the features and the algorithms implemented using MATLAB. Various emotion recognition models like Linear Discriminant Analysis (LDA), Regularized Discriminant Analysis (RDA), Support Vector Machines (SVM) and K-Nearest neighbor (KNN) and are explored in detail using prosody and spectral features, and feature fusion techniques.
Description: Printed edition: 9783319155296.
URI: http://46.100.53.162/handle/Ebook/60771
ISBN: 9783319155302.
9783319155296 (print)
Appears in Collections:مهندسی برق

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Title: Acoustic Modeling for Emotion Recognition
Authors: Anne, Koteswara Rao.;Kuchibhotla, Swarna.;Vankayalapati, Hima Deepthi.
subject: Engineering;Computer Science;Computational linguistics.;Acoustics.;Engineering;Signal, Image and Speech Processing.;Computational Linguistics.;User Interfaces and Human Computer Interaction.;Acoustics.;TK7882.S65
Year: 2015
place: Cham
Publisher: Springer International Publishing :.
Imprint: Springer,
Series/Report no.: SpringerBriefs in Electrical and Computer Engineering, 2191-8112.
SpringerBriefs in Electrical and Computer Engineering, 2191-8112.
Abstract:  This book presents state of art research in speech emotion recognition. Readers are first presented with basic research and applications gradually more advance information is provided, giving readers comprehensive guidance for classify emotions through speech. Simulated databases are used and results extensively compared, with the features and the algorithms implemented using MATLAB. Various emotion recognition models like Linear Discriminant Analysis (LDA), Regularized Discriminant Analysis (RDA), Support Vector Machines (SVM) and K-Nearest neighbor (KNN) and are explored in detail using prosody and spectral features, and feature fusion techniques.
Description: Printed edition: 9783319155296.
URI: http://46.100.53.162/handle/Ebook/60771
ISBN: 9783319155302.
9783319155296 (print)
Appears in Collections:مهندسی برق

Files in This Item:
File Description SizeFormat 
9783319155296.pdf1.52 MBAdobe PDFThumbnail
Preview File
Title: Acoustic Modeling for Emotion Recognition
Authors: Anne, Koteswara Rao.;Kuchibhotla, Swarna.;Vankayalapati, Hima Deepthi.
subject: Engineering;Computer Science;Computational linguistics.;Acoustics.;Engineering;Signal, Image and Speech Processing.;Computational Linguistics.;User Interfaces and Human Computer Interaction.;Acoustics.;TK7882.S65
Year: 2015
place: Cham
Publisher: Springer International Publishing :.
Imprint: Springer,
Series/Report no.: SpringerBriefs in Electrical and Computer Engineering, 2191-8112.
SpringerBriefs in Electrical and Computer Engineering, 2191-8112.
Abstract:  This book presents state of art research in speech emotion recognition. Readers are first presented with basic research and applications gradually more advance information is provided, giving readers comprehensive guidance for classify emotions through speech. Simulated databases are used and results extensively compared, with the features and the algorithms implemented using MATLAB. Various emotion recognition models like Linear Discriminant Analysis (LDA), Regularized Discriminant Analysis (RDA), Support Vector Machines (SVM) and K-Nearest neighbor (KNN) and are explored in detail using prosody and spectral features, and feature fusion techniques.
Description: Printed edition: 9783319155296.
URI: http://46.100.53.162/handle/Ebook/60771
ISBN: 9783319155302.
9783319155296 (print)
Appears in Collections:مهندسی برق

Files in This Item:
File Description SizeFormat 
9783319155296.pdf1.52 MBAdobe PDFThumbnail
Preview File