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Multimodal Signal Processing : Theory and Applications for Human-Computer Interaction

ISBN: 9780123748256 | 0123748259
Format: Hardcover
Publisher: Academic Pr
Pub. Date: 11/17/2009

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SummaryTable of ContentsAuthor Biography
Presents state-of-the art methods for multimodal signal processing, analysis, and modelling
Prefacep. xiii
Introductionp. 1
Signal Processing, Modelling and Related Mathematical Toolsp. 5
Statistical Machine Learning for HCIp. 7
Introductionp. 7
Introduction to Statistical Learningp. 8
Types of Problemp. 8
Function Spacep. 9
Loss Functionsp. 10
Expected Risk and Empirical Riskp. 10... MORE
Statistical Learning Theoryp. 11
Support Vector Machines for Binary Classificationp. 13
Hidden Markov Models for Speech Recognitionp. 16
Speech Recognitionp. 17
Markovian Processesp. 17
Hidden Markov Modelsp. 18
Inference and Learning with HMMsp. 20
HMMs for Speech Recognitionp. 22
Conclusionp. 22
Referencesp. 23
Speech Processingp. 25
Introductionp. 26
Speech Recognitionp. 28
Feature Extractionp. 28
Acoustic Modellingp. 30
Language Modellingp. 33
Decodingp. 34
Multiple Sensorsp. 35
Confidence Measuresp. 37
Robustnessp. 38
Speaker Recognitionp. 40
Overviewp. 40
Robustnessp. 43
Text-to-Speech Synthesisp. 44
Natural Language Processing for Speech Synthesisp. 44
Concatenative Synthesis with a Fixed Inventoryp. 46
Unit Selection-Based Synthesisp. 50
Statistical Parametric Synthesisp. 53
Conclusionsp. 56
Referencesp. 57
Natural Language and Dialogue Processingp. 63
Introductionp. 63
Natural Language Understandingp. 64
Syntactic Parsingp. 64
Semantic Parsingp. 68
Contextual Interpretationp. 70
Natural Language Generationp. 71
Document Planningp. 72
Microplanningp. 73
Surface Realisationp. 73
Dialogue Processingp. 74
Discourse Modellingp. 74
Dialogue Managementp. 77
Degrees of Initiativep. 80
Evaluationp. 81
Conclusionp. 85
Referencesp. 85
Image and Video Processing Tools for HCIp. 93
Introductionp. 93
Face Analysesp. 94
Face Detectionp. 95
Face Trackingp. 96
Facial Feature Detection and Trackingp. 98
Gaze Analysisp. 100
Face Recognitionp. 101
Facial Expression Recognitionp. 103
Hand-Gesture Analysisp. 104
Head Orientation Analysis and FoA Estimationp. 106
Head Orientation Analysisp. 106
Focus of Attention Estimationp. 107
Body Gesture Analysisp. 109
Conclusionsp. 112
Referencesp. 112
Processing of Handwriting and Sketching Dynamicsp. 119
Introductionp. 119
History of Handwriting Modality and the Acquisition of Online Handwriting Signalsp. 121
Basics in Acquisition, Examples for Sensorsp. 123
Analysis of Online Handwriting and Sketching Signalsp. 124
Overview of Recognition Goals in HCIp. 125
Sketch Recognition for User Interface Designp. 128
Similarity Search in Digital Inkp. 133
Summary and Perspectives for Handwriting and Sketching in HCIp. 138
Referencesp. 139
Multimodal Signal Processing and Modellingp. 143
Basic Concepts of Multimodal Analysisp. 143
Defining Multimodalityp. 145
Advantages of Multimodal Analysisp. 148
Conclusionp. 151
Referencesp. 152
Multimodal Information Fusionp. 153
Introductionp. 153
Levels of Fusionp. 156
Adaptive versus Non-Adaptive Fusionp. 158
Other Design Issuesp. 162
Conclusionsp. 165
Referencesp. 165
Modality Integration Methodsp. 171
Introductionp. 171
Multimodal Fusion for AVSRp. 172
Types of Fusionp. 172
Multistream HMMsp. 174
Stream Reliability Estimatesp. 174
Multimodal Speaker Localisationp. 178
Conclusionp. 181
Referencesp. 181
A Multimodal Recognition Framework for Joint Modality Compensation and Fusionp. 185
Introductionp. 186
Joint Modality Recognition and Applicationsp. 188
A New Joint Modality Recognition Schemep. 191
Conceptp. 191
Theoretical Backgroundp. 191
Joint Modality Audio-Visual Speech Recognitionp. 194
Signature Extraction Stagep. 196
Recognition Stagep. 197
Joint Modality Recognition in Biometricsp. 198
Overviewp. 198
Resultsp. 199
Conclusionsp. 203
References 204
Managing Multimodal Data, Metadata and Annotations: Challenges and Solutionsp. 207
Introductionp. 208
Setting the Stage: Concepts and Projectsp. 208
Metadate-versusAnnotationsp. 209
Examples of Large Multimodal Collectionsp. 210
Capturing and Recording Multimodal Datap. 211
Capture Devicesp. 211
Synchronisationp. 212
Activity Types in Multimodal Corporap. 213
Examples of Set-ups and Raw Datap. 213
Reference Metadata and Annotationsp. 214
Gathering Metadata: Methodsp. 215
Metadata for the AMI Corpusp. 216
Reference Annotations: Procedure and Toolsp. 217
Data Storage and Accessp. 219
Exchange Formats for Metadata and Annotationsp. 219
Data Serversp. 221
Accessing Annotated Multimodal Datap. 222
Conclusions and Perspectivesp. 223
Referencesp. 224
Multimodal Human-Computer and Human-to-Human Interactionp. 229
Multimodal Inputp. 231
Introductionp. 231
Advantages of Multimodal Input Interfacesp. 232
State-of-the-Art Multimodal Input Systemsp. 234
Multimodality, Cognition and Performancep. 237
Multimodal Perception and Cognitionp. 237
Cognitive Load and Performancep. 238
Understanding Multimodal Input Behaviourp. 239
Theoretical Frameworksp. 240
Interpretation of Multimodal Input Patternsp. 243
Adaptive Multimodal Interfacesp. 245
Designing Multimodal Interfaces that Manage Users' Cognitive Loadp. 246
Designing Low-Load Multimodal Interfaces for Educationp. 248
Conclusions and Future Directionsp. 250
Referencesp. 251
MuItimodal Output: Facial Motion, Gestures and Synthesised Speech Synchronisationp. 257
Introductionp. 257
Basic AV Speech Synthesisp. 258
The Animation Systemp. 260
Coarticulationp. 263
Extended AV Speech Synthesisp. 264
Data-Driven Approachesp. 267
Rule-Based Approachesp. 269
Embodied Conversational Agentsp. 270
TTS Timing Issuesp. 272
On-the-Fly Synchronisationp. 272
A Priori Synchronisationp. 273
Conclusionp. 274
Referencesp. 274
Interactive Representations of Multimodal Databasesp. 279
Introductionp. 279
Multimodal Data Representationp. 280
Multimodal Data Accessp. 283
Browsing as Extension of the Query Formulation Mechanismp. 283
Browsing for the Exploration of the Content Spacep. 287
Alternative Representationsp. 292
Evaluationp. 292
Commercial Impactp. 293
Gaining Semantic from User Interactionp. 294
Multimodal Interactive Retrievalp. 294
Crowdsourcingp. 295
Conclusion and Discussionp. 298
Referencesp. 299
Modelling Interest in Face-to-Face Conversations from Multimodal Nonverbal Behaviourp. 309
Introductionp. 309
Perspectives on Interest Modellingp. 311
Computing Interest from Audio Cuesp. 315
Computing interest from Multimodal Cuesp. 318
Other Concepts Related to Interestp. 320
Concluding Remarksp. 322
Referencesp. 323
Indexp. 327
Table of Contents provided by Ingram. All Rights Reserved.
Jean-Philippe Thiran received his PhD from the Universit Catholique de Louvain (UCL) in 1997. He is Assistant Professor at the Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland, responsible for the image analysis group. Dr Thiran's current scientific interests include image segmentation, multimodal signal processing and medical image analysis. Ferran Marqus is Full Professor in the TSC Department of Universitat Polytcnica di Catalunya (UPC) where he is lecturing on the area of digital signal and image processing. He has previously held posts at EPFL and the University of Southern California. He received his PhD from UPC in December 1992. Herv Bourlard is Director of the Idiap Research Institute, Full Professor at the Swiss Federal Institute of Technology at Lausanne(EPFL), and Director of a National Centre of Competence in Research on 'Interactive Multimodal Information Management. His current interests mainly include statistical pattern classification, signal processing, multi-channel processing, artificial neural networks, and applied mathematics.


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