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Emotion Recognition using Speech Features

  • Book
  • © 2013

Overview

Authors:
  1. K. Sreenivasa Rao

    1. , School of Information Technology, Indian Institute of Technology, Kharagpur, India

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  2. Shashidhar G. Koolagudi

    1. , School of Information Technology, Indian Institute of Technology, Kharagpur, India

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    You can also search for this author in PubMed   Google Scholar

  • Discusses complete state-of -art features, models and databases in the context of emotion recognition
  • Explores implicit and explicit excitation source features for discriminating the emotions
  • Proposes pitch synchronous and sub-syllabic spectral features, in addition to conventional spectral features, for characterizing emotions
  • Includes supplementary material: sn.pub/extras

Part of the book series: SpringerBriefs in Speech Technology (BRIEFSSPEECHTECH)

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Table of contents (6 chapters)

  1. Front Matter

    Pages i-xii
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  2. Introduction

    • Sreenivasa Rao Krothapalli, Shashidhar G. Koolagudi
    Pages 1-14

  3. Speech Emotion Recognition: A Review

    • Sreenivasa Rao Krothapalli, Shashidhar G. Koolagudi
    Pages 15-34

  4. Emotion Recognition Using Excitation Source Information

    • Sreenivasa Rao Krothapalli, Shashidhar G. Koolagudi
    Pages 35-66

  5. Emotion Recognition Using Vocal Tract Information

    • Sreenivasa Rao Krothapalli, Shashidhar G. Koolagudi
    Pages 67-78

  6. Emotion Recognition Using Prosodic Information

    • Sreenivasa Rao Krothapalli, Shashidhar G. Koolagudi
    Pages 79-91

  7. Summary and Conclusions

    • Sreenivasa Rao Krothapalli, Shashidhar G. Koolagudi
    Pages 93-98

  8. Back Matter

    Pages 99-124
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Keywords

About this book

“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.

Authors and Affiliations

  • , School of Information Technology, Indian Institute of Technology, Kharagpur, India

    K. Sreenivasa Rao, Shashidhar G. Koolagudi

About the authors

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

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