Emotion-Oriented Systems

Table of contents

1. Cover
2. Title Page
3. Copyright
4. Preface
5. PART 1: Foundations
   1. Chapter 1: Contemporary Theories and Concepts in the Psychology of Emotions
      1. 1.1. Introduction
      2. 1.2. Emergence of a scientific approach to emotions
         1. 1.2.1. The emotional sequence: James-Lange versus Cannon-Bard
         2. 1.2.2. Schachter’s two-factor theory
      3. 1.3. Basic emotions theories
         1. 1.3.1. Premises of basic emotions theories
         2. 1.3.2. Characteristics of basic emotions
         3. 1.3.3. Criticisms of basic emotions theories
      4. 1.4. Bi-dimensional theories of emotion
         1. 1.4.1. Premises of bi-dimensional theories of emotion
         2. 1.4.2. Criticisms of bi-dimensional theories of emotion
      5. 1.5. Appraisal theories of emotions
         1. 1.5.1. Premises of appraisal theories of emotion
         2. 1.5.2. Specific models of this theoretical trend
         3. 1.5.3. Criticisms of appraisal theories of emotion
      6. 1.6. Conclusion
      7. 1.7. Glossary
      8. 1.8. Bibliography
   2. Chapter 2: Emotion and the Brain
      1. 2.1. Introduction
         1. 2.1.1. Emotions and the brain: the emergence of affective neuroscience as an independent discipline
      2. 2.2. The major role of affective neuroscience in understanding emotions
         1. 2.2.1. Emotion and the brain: from a unitary entity to processing, from structure to neural networks
         2. 2.2.2. Levels of processing in emotional processes
         3. 2.2.3. Emotion and cognition
      3. 2.3. The historical and conceptual legacy of early conceptions of emotions and the brain
         1. 2.3.1. Forerunners of affective neuroscience
            1. 2.3.1.1. Charles Darwin
            2. 2.3.1.2. The James-Lange peripheralist theory
      4. 2.4. Initial neuro-anatomical emotion theories
         1. 2.4.1. Canon-Bard’s centralist theory
         2. 2.4.2. Papez’s circuit
         3. 2.4.3. MacLean’s limbic theory
      5. 2.5. Structures in the brain and their functions in emotional processes
         1. 2.5.1. Amygdala
         2. 2.5.2. Amygdala and emotional learning processes
            1. 2.5.2.1. Amygdala and classical conditioning
            2. 2.5.2.2. The amygdala: a structure with two processing streams
         3. 2.5.3. The amygdala and emotional perception: hypotheses around the specificity of processing within the amygdala
            1. 2.5.3.1. The amygdala as a fear module
            2. 2.5.3.2. The amygdala and arousal
            3. 2.5.3.3. The amygdala as a relevance detector
         4. 2.5.4. The amygdala and memory processing
      6. 2.6. The prefrontal cortex
         1. 2.6.1. The prefrontal cortex and bodily signals
         2. 2.6.2. The prefrontal cortex and the top-down regulation of behavior
         3. 2.6.3. The prefrontal cortex and the motivational component of emotion
      7. 2.7. The anterior cingulate cortex
      8. 2.8. The role of the insula in disgust
      9. 2.9. Temporal dynamic of brain processes in emotional genesis
      10. 2.10. Functional connectivity
          1. 2.10.1. Investigations of the connectivity using brain imaging techniques (MRI)
          2. 2.10.2. Investigations into connectivity using electroencephalographic (EEG) techniques
          3. 2.10.3. Benefits of brain connectivity studies
      11. 2.11. Conclusion
      12. 2.12. Bibliography
6. PART 2: Non-verbal behavior
   1. Chapter 3: Emotional Corpora: from Acquisition to Modeling
      1. 3.1. Introduction
      2. 3.2. Building corpora: “acted”, “induced” and real-life emotions
         1. 3.2.1. Acted data
         2. 3.2.2. Induced data
         3. 3.2.3. Real-life data
         4. 3.2.4. Comparison of different types of data
      3. 3.3. Current emotional corpora
      4. 3.4. Coding schemes
         1. 3.4.1. Emotional annotation protocols
            1. 3.4.1.1. Definitions of annotated features
            2. 3.4.1.2. Annotation
         2. 3.4.2. Annotating context
            1. 3.4.2.1. Validation
      5. 3.5. Complex emotions in spontaneous data
      6. 3.6. Applications for corpora
         1. 3.6.1. Detecting and deciphering emotions in speech
         2. 3.6.2. Designing an expressive agent from corpora
      7. 3.7. Conclusion
      8. 3.8. Bibliography
   2. Chapter 4: Visual Emotion Recognition: Status and Key Issues
      1. 4.1. Introduction
      2. 4.2. What is a facial expression?
         1. 4.2.1. Definition
         2. 4.2.2. Description
         3. 4.2.3. Ekman’s universal expressions
         4. 4.2.4. An ideal system
      3. 4.3. Overview of facial expression recognition methods
         1. 4.3.1. Databases
         2. 4.3.2. Preprocessing: extracting the face
         3. 4.3.3. Extracting facial characteristics
         4. 4.3.4. Classification
         5. 4.3.5. Performance
      4. 4.4. Spontaneous facial expressions
         1. 4.4.1. Position of the problem
         2. 4.4.2. Databases
         3. 4.4.3. Recognizing spontaneous expressions
      5. 4.5. Expression intensity
      6. 4.6. Dynamic analysis
      7. 4.7. Multimodality
      8. 4.8. Conclusion
      9. 4.9. Bibliography
   3. Chapter 5: Recognition of Acoustic Emotion
      1. 5.1. Introduction
      2. 5.2. Principles of automatic emotion-recognition systems
      3. 5.3. Acoustic descriptors
         1. 5.3.1. Voiced versus unvoiced content
         2. 5.3.2. A temporal unit for emotional analysis
         3. 5.3.3. Prosodic descriptors
            1. 5.3.3.1. Fundamental frequency (pitch)
            2. 5.3.3.2. Intensity
            3. 5.3.3.3. Rhythm descriptors
         4. 5.3.4. Voice quality descriptors
            1. 5.3.4.1. Normalized amplitude quotient
            2. 5.3.4.2. Frequency modulation (jitter)
            3. 5.3.4.3. Amplitude modulation (shimmer)
            4. 5.3.4.4. Rate of unvoiced windows
            5. 5.3.4.5. Harmonic to noise ration
         5. 5.3.5. Cepstral and spectral descriptors
            1. 5.3.5.1. Formant parameters
            2. 5.3.5.2. Mel-frequency cepstral coefficients
            3. 5.3.5.3. Bark band energy
            4. 5.3.5.4. Spectral centroide
      4. 5.4. Automatic emotion classification
         1. 5.4.1. Choosing descriptors
            1. 5.4.1.1. Normalizing descriptors
            2. 5.4.1.2. Reduction in data representation space
         2. 5.4.2. Learning algorithms
            1. 5.4.2.1. Separators with vast margin
            2. 5.4.2.2. Gaussian mixture models
      5. 5.5. Performance and assessment
         1. 5.5.1. First factor: data and classes of emotions
         2. 5.5.2. Second factor: the problem of “ground truths”
         3. 5.5.3. Third factor: manual preprocessing
         4. 5.5.4. Fourth factor: learning algorithms
         5. 5.5.5. Fifth factor: learning conditions
      6. 5.6. Conclusion
      7. 5.7. Bibliography
   4. Chapter 6: Modeling Facial Expressions of Emotions
      1. 6.1. Expressive conversational agents
      2. 6.2. Expressions and their emotional states
         1. 6.2.1. Expressing discrete emotions
         2. 6.2.2. Dimensional approaches to emotional expression
         3. 6.2.3. Componential expression of emotions
      3. 6.3. Computational models for facial expressions of emotions
         1. 6.3.1. A discrete representation of facial expressions
         2. 6.3.2. Dimensional representation of facial expressions
         3. 6.3.3. Componential approaches to facial expressions
         4. 6.3.4. Mixtures of emotions and social constraints
         5. 6.3.5. Sequences of emotional expressions
      4. 6.4. Conclusion
      5. 6.5. Acknowledgements
      6. 6.6. Bibliography
   5. Chapter 7: Emotion Perception and Recognition
      1. 7.1. Introduction
      2. 7.2. Perception in vocal communication of emotion
      3. 7.3. Experimental paradigms and emotion-oriented automatic systems
         1. 7.3.1. Experiments validating emotional content and/or annotation strategies
            1. 7.3.1.1. Experimental design and stimuli
            2. 7.3.1.2. Test populations
            3. 7.3.1.3. Perceptual categorization into emotional classes
            4. 7.3.1.4. Choosing emotional labels
            5. 7.3.1.5. Discussion
         2. 7.3.2. Tests for validating measurable parameters of emotional information
            1. 7.3.2.1. Discussion
         3. 7.3.3. Tests comparing human and automated emotion recognition
            1. 7.3.3.1. Discussion
      4. 7.4. Conclusion
      5. 7.5. Bibliography
7. PART 3: Functions
   1. Chapter 8: The Role of Emotions in Human−Machine Interaction
      1. 8.1. Introduction
      2. 8.2. Interactive information and assistance systems
         1. 8.2.1. Uses of emotions in interactive systems
         2. 8.2.2. Current research and tools
            1. 8.2.2.1. Collecting and annotating expressions of emotions
            2. 8.2.2.2. Automatic emotion recognition
            3. 8.2.2.3. Interface expressivity
               1. 8.2.2.3.1. Expressing emotions in ECAs
               2. 8.2.2.3.2. The Impact of emotional virtual agents on interaction
      3. 8.3. Video games
         1. 8.3.1. The importance of emotions in video games
            1. 8.3.1.1. Emotions in gaming systems
            2. 8.3.1.2. Player emotions
         2. 8.3.2. Current research and tools
            1. 8.3.2.1. Towards believable emotional virtual characters
            2. 8.3.2.2. Towards games that account for player emotions
      4. 8.4. Intelligent tutoring systems (ITS)
         1. 8.4.1. The importance of emotions in ITS
            1. 8.4.1.1. The learner’s emotions
            2. 8.4.1.2. Emotions in ITS
         2. 8.4.2. Current research and tools
      5. 8.5. Discussion and research perspectives
      6. 8.6. Bibliography
   2. Chapter 9: Music and Emotions
      1. 9.1. The growing importance of music in society
      2. 9.2. Recognizing emotions and structural characteristics in music
         1. 9.2.1. Understanding listeners’ emotional reactions
         2. 9.2.2. A categorical or dimensional approach?
      3. 9.3. Rules for modeling musical expression of emotions
      4. 9.4. Towards a continuous measure of emotional reactions to music
      5. 9.5. Multimodality in musical experience
         1. 9.5.1. A multimodal research platform for musical expression
            1. 9.5.1.1. Level 1
            2. 9.5.1.2. Level 2
            3. 9.5.1.3. Level 3
            4. 9.5.1.4. Level 4
            5. 9.5.1.5. Overview
      6. 9.6. Multimodal emotional synthesis in a musical context
      7. 9.7. The social active listening paradigm: the collective aspect of emotion
         1. 9.7.1. Example: Mappe per Affetti Erranti
      8. 9.8. Conclusion and perspectives
      9. 9.9. Bibliography
   3. Chapter 10: Literary Feelings in Interactive Fiction
      1. 10.1. Introduction: emotions and feelings
      2. 10.2. French novels and the representation of feelings
      3. 10.3. Madame Bovary: plot and scenes
      4. 10.4. Interactive fiction and emotional planning
      5. 10.5. Linguistic interaction and emotions
      6. 10.6. Emma Bovary’s virtuality
      7. 10.7. Conclusion
      8. 10.8. Bibliography
   4. Chapter 11: The Design of Emotions: How the Digital is Making Us More Emotional
      1. 11.1. Representing, interpreting and evoking emotions
      2. 11.2. Emotion, mimicry and technical devices
         1. 11.2.1. Representing emotions and catharsis
      3. 11.3. Devices as an alternate source of emotion: photography
      4. 11.4. Art and computers: formal beginnings
      5. 11.5. The human behind the mechanics and the mechanics behind the human
      6. 11.6. Mirror interaction as an emotional vehicle
      7. 11.7. Trompe l’œil versus explicit expression
      8. 11.8. Three-dimensional universes: an empathetic experience
      9. 11.9. Empathy and identifying emotions
         1. 11.9.1. From empathy to shared emotions
      10. 11.10. Making human−machine interaction and dialog effective
      11. 11.11. Conclusion: “revenge of the emotions”
      12. 11.11. Bibliography
8. List of Authors
9. Index