Emotion Recognition using Speech Features

K. Sreenivasa Rao, Shashidhar G. Koolagudi

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English

Springer-Verlag New York Inc.
07 November 2012

Computational linguistics; Imaging systems & technology; Speech recognition; User interface design & usability

Series: SpringerBriefs in Speech Technology

“Emotion Recognition Using Speech Features” provides coverage of emotion-specific features present in speech. The author also discusses suitable models for capturing emotion-specific information for distinguishing different emotions. The content of this book is important for designing and developing natural and sophisticated speech systems.

In this Brief, Drs. Rao and Koolagudi lead a discussion of how emotion-specific information is embedded in speech and how to acquire emotion-specific knowledge using appropriate statistical models. Additionally, the authors provide information about exploiting multiple evidences derived from various features and models. The acquired emotion-specific knowledge is useful for synthesizing emotions. Features includes discussion of: • Global and local prosodic features at syllable, word and phrase levels, helpful for capturing emotion-discriminative information;

• Exploiting complementary evidences obtained from excitation sources, vocal tract systems and prosodic features in order to enhance the emotion recognition performance;

• Proposed multi-stage and hybrid models for improving the emotion recognition performance.

This brief is for researchers working in areas related to speech-based products such as mobile phone manufacturing companies, automobile companies, and entertainment products as well as researchers involved in basic and applied speech processing research.

By: K. Sreenivasa Rao, Shashidhar G. Koolagudi
Imprint: Springer-Verlag New York Inc.
Country of Publication: United States [Currently unable to ship to USA: see Shipping Info]
Edition: 2013 ed.
Dimensions: Height: 235mm, Width: 155mm, Spine: 10mm
Weight: 2.175kg
ISBN: 9781461451426
ISBN 10: 1461451426
Series: SpringerBriefs in Speech Technology
Pages: 124
Publication Date: 07 November 2012
Audience: College/higher education , Further / Higher Education
Format: Paperback
Publisher's Status: Active

Introduction.- Speech Emotion Recognition: A Review.- Emotion Recognition Using Excitation Source Information.- Emotion Recognition Using Vocal Tract Information.- Emotion Recognition Using Prosodic Information.- Summary and Conclusions.- Linear Prediction Analysis of Speech.- MFCC Features.- Gaussian Mixture Model (GMM)

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