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Introduction to EEG- and Speech-Based Emotion Recognition

  • 1st Edition - March 22, 2016
  • Latest edition
  • Authors: Priyanka A. Abhang, Bharti W. Gawali, Suresh C. Mehrotra
  • Language: English

Introduction to EEG- and Speech-Based Emotion Recognition Methods examines the background, methods, and utility of using electroencephalograms (EEGs) to detect and recognize… Read more

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Description

Introduction to EEG- and Speech-Based Emotion Recognition Methods examines the background, methods, and utility of using electroencephalograms (EEGs) to detect and recognize different emotions. By incorporating these methods in brain-computer interface (BCI), we can achieve more natural, efficient communication between humans and computers. This book discusses how emotional states can be recognized in EEG images, and how this is useful for BCI applications. EEG and speech processing methods are explored, as are the technological basics of how to operate and record EEGs. Finally, the authors include information on EEG-based emotion recognition, classification, and a proposed EEG/speech fusion method for how to most accurately detect emotional states in EEG recordings.

Key features

  • Provides detailed insight on the science of emotion and the brain signals underlying this phenomenon
  • Examines emotions as a multimodal entity, utilizing a bimodal emotion recognition system of EEG and speech data
  • Details the implementation of techniques used for acquiring as well as analyzing EEG and speech signals for emotion recognition

Readership

Neuroscientists, computational neuroscientists, neurologists, engineers, BCI/EEG researchers, graduate students/post-docs in biological and biomedical sciences

Table of contents

  • Preface
  • Acknowledgments
  • Chapter 1. Introduction to Emotion, Electroencephalography, and Speech Processing
    • 1.1. Introduction
    • 1.2. Brain Physiology
    • 1.3. Lobes of the Brain and Their Functions
    • 1.4. Electroencephalography
    • 1.5. Human Auditory System
    • 1.6. Speech Processing
    • 1.7. Organization of the Book
    • 1.8. Conclusion
  • Chapter 2. Technological Basics of EEG Recording and Operation of Apparatus
    • 2.1. Introduction to Electroencephalography
    • 2.2. Modern EEG Equipment
    • 2.3. The EEG 10/20 Electrodes Placement System
    • 2.4. EEG Acquisition Tool
    • 2.5. Artifacts
    • 2.6. Speech Acquisition and Processing
    • 2.7. Computerized Speech Laboratory
    • 2.8. Conclusion
  • Chapter 3. Technical Aspects of Brain Rhythms and Speech Parameters
    • 3.1. Introduction to Brain-Wave Frequencies
    • 3.2. Speech Prosodic Features
    • 3.3. Signal Processing Algorithms
    • 3.4. Conclusion
  • Chapter 4. Time and Frequency Analysis
    • 4.1. Introduction
    • 4.2. Fourier Transformation
    • 4.3. Gabor Transformation (Short-Time Fourier Transformation)
    • 4.4. Short-Time Fourier Transformation
    • 4.5. Wavelet Transformation
    • 4.6. Time Domain Versus Frequency Domain Analysis
    • 4.7. Examples
    • 4.8. Conclusion
  • Chapter 5. Emotion Recognition
    • 5.1. Introduction
    • 5.2. Modalities for Emotion Recognition Systems
    • 5.3. Conclusion
  • Chapter 6. Multimodal Emotion Recognition
    • 6.1. Introduction
    • 6.2. Models and Theories of Emotion
    • 6.3. Pleasure, Arousal, and Dominance Emotional State Model
    • 6.4. Earlier Efforts in Multimodal Emotion Recognition Systems
    • 6.5. Online Databases of Multimodal Emotions
    • 6.6. Advantages of Multimodal Approach
    • 6.7. Challenges for Multimodal Affect Recognition Systems
    • 6.8. Conclusion
  • Chapter 7. Proposed EEG/Speech-Based Emotion Recognition System: A Case Study
    • 7.1. Introduction
    • 7.2. Experimental Database
    • 7.3. Experimental Analysis for EEG Images
    • 7.4. Analysis of Feature Extraction From EEG Images
    • 7.5. Experimental Analysis for Speech Signals
    • 7.6. Correlation of EEG Images and Speech Signals
    • 7.7. Classification Using Linear Discriminate Analysis
    • 7.8. Conclusion
  • Chapter 8. Brain–Computer Interface Systems and Their Applications
    • 8.1. Introduction
    • 8.2. Working of BCI Systems
    • 8.3. Types of BCI
    • 8.4. BCI Applications
    • 8.5. Challenges for BCI
    • 8.6. Conclusion
  • Index

Product details

  • Edition: 1
  • Latest edition
  • Published: March 23, 2016
  • Language: English

About the authors

PA

Priyanka A. Abhang

Ms. Priyanka Abhang has completed her M.Sc. (IT) (2009). She is presently working as a Ph.D. candidate under the guidance of Dr. Bharti Gawali, Professor in Department of Computer Science and Information Technology, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad (MS), India. Research area entitles as “Study and analysis of emotion recognition through EEG images and speech processing.
Affiliations and expertise
Dr. Babasaheb Ambedkar Marathwada University, Maharashtra, India

BG

Bharti W. Gawali

Dr. Bharti W. Gawali has completed M. Sc. Computer science (1998), Ph. D. (2007), SET (2003). She is presently working as a Professor in Department of Computer Science and Information Technology, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad (MS), India. More than 60 research papers in reputed journals. She has successfully completed three major research projects on BCI and Speech Processing. She is associated with various professional bodies like FIETE, FIAENG and FISCA etc. Her field of specification are Data compression, Speech and Speaker Recognition, Human computer Interaction, Emotion Recognition, Signature Recognition, Brain Computer Interface, GIS and remote sensing, Medical Image Processing.
Affiliations and expertise
Dr. Babasaheb Ambedkar Marathwada University, Maharashtra, India

SM

Suresh C. Mehrotra

Dr. Suresh Chandra Mehrotra has completed M. Sc. Physics (1970), Ph.D. (1975), Post Doctorate (Welch Foundation Fellow) (1974-75). Now his designation as Srinivasa Ramanujan Geospatial Chair Professor. He is recipient of Career Award, FOM, Alexander Von Humboldt Fellowship, F.N.A.Sc. He is a fellow and life member of Indian Physics Association (IPA), Indian Laser Association (ILA), Indian Science Congress Association, and IETE. He has also been awarded with Best Teacher Award from Maharashtra (MS) state. More than 239 research papers are published in reputed journals and conferences, and 5 books to his credit. He has organized 7 conferences/workshop and seminar as Chairman/Convener. He has successfully completed Eight Research Project. His fields of specializations are Microwaves Interaction with Matter, Time Domain Spectroscopy Pattern Recognition, Brain Computer Interfacing, Medical Instrumentation, Human Computer Interface, Speech Processing, Signal Processing, Remote sensing and GIS, Hyper Spectral Image Processing.
Affiliations and expertise
Dr. Babasaheb Ambedkar Marathwada University, Maharashtra, India

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