Robust Emotion Recognition using Spectral and Prosodic Features

Author:   K. Sreenivasa Rao ,  Shashidhar G. Koolagudi
Publisher:   Springer-Verlag New York Inc.
Edition:   2013 ed.
ISBN:  

9781461463597


Pages:   118
Publication Date:   12 January 2013
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Robust Emotion Recognition using Spectral and Prosodic Features


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Overview

In this brief, the authors discuss recently explored spectral (sub-segmental and pitch synchronous) and prosodic (global and local features at word and syllable levels in different parts of the utterance) features for discerning emotions in a robust manner. The authors also delve into the complementary evidences obtained from excitation source, vocal tract system and prosodic features for the purpose of enhancing emotion recognition performance. Features based on speaking rate characteristics are explored with the help of multi-stage and hybrid models for further improving emotion recognition performance. Proposed spectral and prosodic features are evaluated on real life emotional speech corpus.

Full Product Details

Author:   K. Sreenivasa Rao ,  Shashidhar G. Koolagudi
Publisher:   Springer-Verlag New York Inc.
Imprint:   Springer-Verlag New York Inc.
Edition:   2013 ed.
Dimensions:   Width: 15.50cm , Height: 1.30cm , Length: 23.50cm
Weight:   2.117kg
ISBN:  

9781461463597


ISBN 10:   1461463599
Pages:   118
Publication Date:   12 January 2013
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Introduction.- Robust Emotion Recognition using Pitch Synchronous and Sub-syllabic Spectral Features.- Robust Emotion Recognition using Word and Syllable Level Prosodic Features.- Robust Emotion Recognition using Combination of Excitation Source, Spectral and Prosodic Features.- Robust Emotion Recognition using Speaking Rate Features.- Emotion Recognition on Real Life Emotions.- Summary and Conclusions.- MFCC Features.- Gaussian Mixture Model (GMM).

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Author Information

K. Sreenivasa Rao is at Indian Institute of Technology, Kharagpur, India. Shashidhar G, Koolagudi is at Graphic Era University, Dehradun, India.

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