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Acoustic modeling for emotion recogn...
~
Anne, Koteswara Rao.
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Acoustic modeling for emotion recognition
Record Type:
Electronic resources : Monograph/item
Title/Author:
Acoustic modeling for emotion recognition/ by Koteswara Rao Anne, Swarna Kuchibhotla, Hima Deepthi Vankayalapati.
Author:
Anne, Koteswara Rao.
other author:
Kuchibhotla, Swarna.
Published:
Cham :Springer International Publishing : : 2015.,
Description:
vii, 66 p. :ill., digital ;24 cm.
[NT 15003449]:
Introduction -- Emotion Recognition using Prosodic features -- Emotion Recognition using Spectral features -- Emotional Speech Corpora -- Classification Models -- Comparative Analysis of Classifiers in emotion recognition -- Summary and Conclusions.
Contained By:
Springer eBooks
Subject:
Acoustic models. -
Online resource:
http://dx.doi.org/10.1007/978-3-319-15530-2
ISBN:
9783319155302 (electronic bk.)
Acoustic modeling for emotion recognition
Anne, Koteswara Rao.
Acoustic modeling for emotion recognition
[electronic resource] /by Koteswara Rao Anne, Swarna Kuchibhotla, Hima Deepthi Vankayalapati. - Cham :Springer International Publishing :2015. - vii, 66 p. :ill., digital ;24 cm. - SpringerBriefs in electrical and computer engineering,2191-8112. - SpringerBriefs in electrical and computer engineering..
Introduction -- Emotion Recognition using Prosodic features -- Emotion Recognition using Spectral features -- Emotional Speech Corpora -- Classification Models -- Comparative Analysis of Classifiers in emotion recognition -- Summary and Conclusions.
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.
ISBN: 9783319155302 (electronic bk.)
Standard No.: 10.1007/978-3-319-15530-2doiSubjects--Topical Terms:
2139379
Acoustic models.
LC Class. No.: QC243
Dewey Class. No.: 534
Acoustic modeling for emotion recognition
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Introduction -- Emotion Recognition using Prosodic features -- Emotion Recognition using Spectral features -- Emotional Speech Corpora -- Classification Models -- Comparative Analysis of Classifiers in emotion recognition -- Summary and Conclusions.
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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.
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EB QC243 .A613 2015
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