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E-grāmata: Emotion-Oriented Systems

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  • Formāts: EPUB+DRM
  • Izdošanas datums: 07-Feb-2013
  • Izdevniecība: ISTE Ltd and John Wiley & Sons Inc
  • Valoda: eng
  • ISBN-13: 9781118603321
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Emotion-Oriented SystemsPalielināt
  • Formāts: EPUB+DRM
  • Izdošanas datums: 07-Feb-2013
  • Izdevniecība: ISTE Ltd and John Wiley & Sons Inc
  • Valoda: eng
  • ISBN-13: 9781118603321
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"The Affective Computing domain, term coined by Rosalind Picard in 1997, gathers several scientific areas such as computer science, cognitive science, psychology, design and art. The humane-machine interaction systems are no longer solely fast and efficient. They aim to offer to users affective experiences: user's affective state is detected and considered within the interaction; the system displays affective state; it can reason about their implication to achieve a task or resolve a problem. In this book, we have chosen to cover various domains of research in emotion-oriented systems. Our aim is also to highlight the importance to base the computational model on theoretical foundations and on natural data"--



Preface xiii
Part 1 Foundations
1(76)
Chapter 1 Contemporary Theories and Concepts in the Psychology of Emotions
3(30)
Geraldine Coppin
David Sander
1.1 Introduction
3(1)
1.2 Emergence of a scientific approach to emotions
4(3)
1.2.1 The emotional sequence: James-Lange versus Cannon-Bard
4(2)
1.2.2 Schachter's two-factor theory
6(1)
1.3 Basic emotions theories
7(4)
1.3.1 Premises of basic emotions theories
7(1)
1.3.2 Characteristics of basic emotions
8(2)
1.3.3 Criticisms of basic emotions theories
10(1)
1.4 Bi-dimensional theories of emotion
11(3)
1.4.1 Premises of bi-dimensional theories of emotion
11(1)
1.4.2 Criticisms of bi-dimensional theories of emotion
12(2)
1.5 Appraisal theories of emotions
14(5)
1.5.1 Premises of appraisal theories of emotion
14(1)
1.5.2 Specific models of this theoretical trend
15(3)
1.5.3 Criticisms of appraisal theories of emotion
18(1)
1.6 Conclusion
19(1)
1.7 Glossary
20(1)
1.8 Bibliography
21(12)
Chapter 2 Emotion and the Brain
33(44)
Andy Christen
Didier Grandjean
2.1 Introduction
33(2)
2.1.1 Emotions and the brain: the emergence of affective neuroscience as an independent discipline
34(1)
2.2 The major role of affective neuroscience in understanding emotions
35(5)
2.2.1 Emotion and the brain: from a unitary entity to processing, from structure to neural networks
36(2)
2.2.2 Levels of processing in emotional processes
38(1)
2.2.3 Emotion and cognition
39(1)
2.3 The historical and conceptual legacy of early conceptions of emotions and the brain
40(1)
2.3.1 Forerunners of affective neuroscience
40(1)
2.3.1.1 Charles Darwin
40(1)
2.3.1.2 The James-Lange peripheralist theory
41(1)
2.4 Initial neuro-anatomical emotion theories
41(3)
2.4.1 Canon-Bard's centralist theory
41(1)
2.4.2 Papez's circuit
42(1)
2.4.3 MacLean's limbic theory
43(1)
2.5 Structures in the brain and their functions in emotional processes
44(9)
2.5.1 Amygdala
44(1)
2.5.2 Amygdala and emotional learning processes
45(1)
2.5.2.1 Amygdala and classical conditioning
45(1)
2.5.2.2 The amygdala: a structure with two processing streams
46(2)
2.5.3 The amygdala and emotional perception: hypotheses around the specificity of processing within the amygdala
48(1)
2.5.3.1 The amygdala as a fear module
48(2)
2.5.3.2 The amygdala and arousal
50(1)
2.5.3.3 The amygdala as a relevance detector
51(1)
2.5.4 The amygdala and memory processing
52(1)
2.6 The prefrontal cortex
53(5)
2.6.1 The prefrontal cortex and bodily signals
55(1)
2.6.2 The prefrontal cortex and the top-down regulation of behavior
56(1)
2.6.3 The prefrontal cortex and the motivational component of emotion
57(1)
2.7 The anterior cingulate cortex
58(1)
2.8 The role of the insula in disgust
58(1)
2.9 Temporal dynamic of brain processes in emotional genesis
59(1)
2.10 Functional connectivity
60(3)
2.10.1 Investigations of the connectivity using brain imaging techniques (MRI)
60(1)
2.10.2 Investigations into connectivity using electroencephalographic (EEG) techniques
61(1)
2.10.3 Benefits of brain connectivity studies
62(1)
2.11 Conclusion
63(1)
2.12 Bibliography
64(13)
Part 2 Non-Verbal Behavior
77(138)
Chapter 3 Emotional Corpora: from Acquisition to Modeling
79(28)
Laurence Devillers
Jean-Claude Martin
3.1 Introduction
79(2)
3.2 Building corpora: "acted", "induced" and real-life emotions
81(5)
3.2.1 Acted data
82(1)
3.2.2 Induced data
83(1)
3.2.3 Real-life data
84(1)
3.2.4 Comparison of different types of data
85(1)
3.3 Current emotional corpora
86(1)
3.4 Coding schemes
86(7)
3.4.1 Emotional annotation protocols
89(1)
3.4.1.1 Definitions of annotated features
89(1)
3.4.1.2 Annotation
90(1)
3.4.2 Annotating context
91(1)
3.4.2.1 Validation
92(1)
3.5 Complex emotions in spontaneous data
93(4)
3.6 Applications for corpora
97(3)
3.6.1 Detecting and deciphering emotions in speech
97(1)
3.6.2 Designing an expressive agent from corpora
98(2)
3.7 Conclusion
100(1)
3.8 Bibliography
101(6)
Chapter 4 Visual Emotion Recognition: Status and Key Issues
107(32)
Alice Caplier
4.1 Introduction
107(2)
4.2 What is a facial expression?
109(3)
4.2.1 Definition
109(1)
4.2.2 Description
109(2)
4.2.3 Ekman's universal expressions
111(1)
4.2.4 An ideal system
112(1)
4.3 Overview of facial expression recognition methods
112(6)
4.3.1 Databases
112(2)
4.3.2 Preprocessing: extracting the face
114(1)
4.3.3 Extracting facial characteristics
115(2)
4.3.4 Classification
117(1)
4.3.5 Performance
117(1)
4.4 Spontaneous facial expressions
118(6)
4.4.1 Position of the problem
118(1)
4.4.2 Databases
119(3)
4.4.3 Recognizing spontaneous expressions
122(2)
4.5 Expression intensity
124(2)
4.6 Dynamic analysis
126(2)
4.7 Multimodality
128(3)
4.8 Conclusion
131(1)
4.9 Bibliography
132(7)
Chapter 5 Recognition of Acoustic Emotion
139(30)
Chloe Clavel
Gael Richard
5.1 Introduction
139(1)
5.2 Principles of automatic emotion-recognition systems
140(1)
5.3 Acoustic descriptors
141(10)
5.3.1 Voiced versus unvoiced content
142(1)
5.3.2 A temporal unit for emotional analysis
143(1)
5.3.3 Prosodic descriptors
143(1)
5.3.3.1 Fundamental frequency (pitch)
144(1)
5.3.3.2 Intensity
145(1)
5.3.3.3 Rhythm descriptors
146(1)
5.3.4 Voice quality descriptors
146(1)
5.3.4.1 Normalized amplitude quotient
147(1)
5.3.4.2 Frequency modulation (jitter)
147(1)
5.3.4.3 Amplitude modulation (shimmer)
148(1)
5.3.4.4 Rate of unvoiced windows
148(1)
5.3.4.5 Harmonic to noise ration
148(1)
5.3.5 Cepstral and spectral descriptors
149(1)
5.3.5.1 Formant parameters
149(1)
5.3.5.2 Mel-frequency cepstral coefficients
149(1)
5.3.5.3 Bark band energy
150(1)
5.3.5.4 Spectral centroide
151(1)
5.4 Automatic emotion classification
151(6)
5.4.1 Choosing descriptors
152(1)
5.4.1.1 Normalizing descriptors
152(1)
5.4.1.2 Reduction in data representation space
152(2)
5.4.2 Learning algorithms
154(1)
5.4.2.1 Separators with vast margin
154(1)
5.4.2.2 Gaussian mixture models
155(2)
5.5 Performance and assessment
157(4)
5.5.1 First factor: data and classes of emotions
157(2)
5.5.2 Second factor: the problem of "ground truths"
159(1)
5.5.3 Third factor: manual preprocessing
160(1)
5.5.4 Fourth factor: learning algorithms
160(1)
5.5.5 Fifth factor: learning conditions
161(1)
5.6 Conclusion
161(2)
5.7 Bibliography
163(6)
Chapter 6 Modeling Facial Expressions of Emotions
169(22)
Sylwia Julia Hyniewska
Radostaw Niewiadomski
Catherine Pelachaud
6.1 Expressive conversational agents
169(1)
6.2 Expressions and their emotional states
170(4)
6.2.1 Expressing discrete emotions
171(1)
6.2.2 Dimensional approaches to emotional expression
171(2)
6.2.3 Componential expression of emotions
173(1)
6.3 Computational models for facial expressions of emotions
174(9)
6.3.1 A discrete representation of facial expressions
174(1)
6.3.2 Dimensional representation of facial expressions
174(2)
6.3.3 Componential approaches to facial expressions
176(2)
6.3.4 Mixtures of emotions and social constraints
178(3)
6.3.5 Sequences of emotional expressions
181(2)
6.4 Conclusion
183(1)
6.5 Acknowledgements
184(1)
6.6 Bibliography
184(7)
Chapter 7 Emotion Perception and Recognition
191(24)
Ioana Vasilescu
7.1 Introduction
191(2)
7.2 Perception in vocal communication of emotion
193(1)
7.3 Experimental paradigms and emotion-oriented automatic systems
194(14)
7.3.1 Experiments validating emotional content and/or annotation strategies
195(1)
7.3.1.1 Experimental design and stimuli
195(1)
7.3.1.2 Test populations
196(1)
7.3.1.3 Perceptual categorization into emotional classes
196(1)
7.3.1.4 Choosing emotional labels
197(2)
7.3.1.5 Discussion
199(3)
7.3.2 Tests for validating measurable parameters of emotional information
202(3)
7.3.2.1 Discussion
205(1)
7.3.3 Tests comparing human and automated emotion recognition
205(3)
7.3.3.1 Discussion
208(1)
7.4 Conclusion
208(1)
7.5 Bibliography
209(6)
Part 3 Functions
215(106)
Chapter 8 The Role of Emotions in Human-Machine Interaction
217(30)
Valerie Maffiolo
Magalie Ochs
8.1 Introduction
217(2)
8.2 Interactive information and assistance systems
219(8)
8.2.1 Uses of emotions in interactive systems
220(1)
8.2.2 Current research and tools
220(1)
8.2.2.1 Collecting and annotating expressions of emotions
221(1)
8.2.2.2 Automatic emotion recognition
222(1)
8.2.2.3 Interface expressivity
223(4)
8.3 Video games
227(8)
8.3.1 The importance of emotions in video games
228(1)
8.3.1.1 Emotions in gaming systems
228(1)
8.3.1.2 Player emotions
229(2)
8.3.2 Current research and tools
231(1)
8.3.2.1 Towards believable emotional virtual characters
231(2)
8.3.2.2 Towards games that account for player emotions
233(2)
8.4 Intelligent tutoring systems (ITS)
235(2)
8.4.1 The importance of emotions in ITS
235(1)
8.4.1.1 The learner's emotions
235(1)
8.4.1.2 Emotions in ITS
235(1)
8.4.2 Current research and tools
235(2)
8.5 Discussion and research perspectives
237(1)
8.6 Bibliography
238(9)
Chapter 9 Music and Emotions
247(24)
Donald Glowinski
Antonio Camurri
9.1 The growing importance of music in society
247(2)
9.2 Recognizing emotions and structural characteristics in music
249(2)
9.2.1 Understanding listeners' emotional reactions
249(1)
9.2.2 A categorical or dimensional approach?
250(1)
9.3 Rules for modeling musical expression of emotions
251(1)
9.4 Towards a continuous measure of emotional reactions to music
252(1)
9.5 Multimodality in musical experience
253(7)
9.5.1 A multimodal research platform for musical expression
255(2)
9.5.1.1 Level 1
257(1)
9.5.1.2 Level 2
258(1)
9.5.1.3 Level 3
259(1)
9.5.1.4 Level 4
259(1)
9.5.1.5 Overview
259(1)
9.6 Multimodal emotional synthesis in a musical context
260(2)
9.7 The social active listening paradigm: the collective aspect of emotion
262(1)
9.7.1 Example: Mappe per Affetti Erranti
262(1)
9.8 Conclusion and perspectives
263(1)
9.9 Bibliography
263(8)
Chapter 10 Literary Feelings in Interactive Fiction
271(28)
Marc Cavazza
David Pizzi
10.1 Introduction: emotions and feelings
271(2)
10.2 French novels and the representation of feelings
273(2)
10.3 Madame Bovary: plot and scenes
275(5)
10.4 Interactive fiction and emotional planning
280(4)
10.5 Linguistic interaction and emotions
284(6)
10.6 Emma Bovary's virtuality
290(4)
10.7 Conclusion
294(1)
10.8 Bibliography
295(4)
Chapter 11 The Design of Emotions: How the Digital is Making Us More Emotional
299(22)
Annie Gentes
11.1 Representing, interpreting and evoking emotions
299(2)
11.2 Emotion, mimicry and technical devices
301(1)
11.2.1 Representing emotions and catharsis
301(1)
11.3 Devices as an alternate source of emotion: photography
301(2)
11.4 Art and computers: formal beginnings
303(2)
11.5 The human behind the mechanics and the mechanics behind the human
305(2)
11.6 Mirror interaction as an emotional vehicle
307(2)
11.7 Trompe l'œil versus explicit expression
309(2)
11.8 Three-dimensional universes: an empathetic experience
311(4)
11.9 Empathy and identifying emotions
315(2)
11.9.1 From empathy to shared emotions
315(2)
11.10 Making human-machine interaction and dialog effective
317(1)
11.11 Conclusion: "revenge of the emotions"
318(1)
11.12 Bibliography
318(3)
List of Authors 321(4)
Index 325
Catherine Pelachaud is the author of Emotion-Oriented Systems, published by Wiley.
Biežāk uzdotie jautājumi par e-grāmatām Biežāk uzdotie jautājumi par e-grāmatām
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