
Because Knetbooks knows college students. Our rental program is designed to save you time and money. Whether you need a textbook for a semester, quarter or even a summer session, we have an option for you. Simply select a rental period, enter your information and your book will be on its way!
| Preface | p. xiii |
| Introduction | p. 1 |
| Signal Processing, Modelling and Related Mathematical Tools | p. 5 |
| Statistical Machine Learning for HCI | p. 7 |
| Introduction | p. 7 |
| Introduction to Statistical Learning | p. 8 |
| Types of Problem | p. 8 |
| Function Space | p. 9 |
| Loss Functions | p. 10 |
| Expected Risk and Empirical Risk | p. 10... MORE |
| Statistical Learning Theory | p. 11 |
| Support Vector Machines for Binary Classification | p. 13 |
| Hidden Markov Models for Speech Recognition | p. 16 |
| Speech Recognition | p. 17 |
| Markovian Processes | p. 17 |
| Hidden Markov Models | p. 18 |
| Inference and Learning with HMMs | p. 20 |
| HMMs for Speech Recognition | p. 22 |
| Conclusion | p. 22 |
| References | p. 23 |
| Speech Processing | p. 25 |
| Introduction | p. 26 |
| Speech Recognition | p. 28 |
| Feature Extraction | p. 28 |
| Acoustic Modelling | p. 30 |
| Language Modelling | p. 33 |
| Decoding | p. 34 |
| Multiple Sensors | p. 35 |
| Confidence Measures | p. 37 |
| Robustness | p. 38 |
| Speaker Recognition | p. 40 |
| Overview | p. 40 |
| Robustness | p. 43 |
| Text-to-Speech Synthesis | p. 44 |
| Natural Language Processing for Speech Synthesis | p. 44 |
| Concatenative Synthesis with a Fixed Inventory | p. 46 |
| Unit Selection-Based Synthesis | p. 50 |
| Statistical Parametric Synthesis | p. 53 |
| Conclusions | p. 56 |
| References | p. 57 |
| Natural Language and Dialogue Processing | p. 63 |
| Introduction | p. 63 |
| Natural Language Understanding | p. 64 |
| Syntactic Parsing | p. 64 |
| Semantic Parsing | p. 68 |
| Contextual Interpretation | p. 70 |
| Natural Language Generation | p. 71 |
| Document Planning | p. 72 |
| Microplanning | p. 73 |
| Surface Realisation | p. 73 |
| Dialogue Processing | p. 74 |
| Discourse Modelling | p. 74 |
| Dialogue Management | p. 77 |
| Degrees of Initiative | p. 80 |
| Evaluation | p. 81 |
| Conclusion | p. 85 |
| References | p. 85 |
| Image and Video Processing Tools for HCI | p. 93 |
| Introduction | p. 93 |
| Face Analyses | p. 94 |
| Face Detection | p. 95 |
| Face Tracking | p. 96 |
| Facial Feature Detection and Tracking | p. 98 |
| Gaze Analysis | p. 100 |
| Face Recognition | p. 101 |
| Facial Expression Recognition | p. 103 |
| Hand-Gesture Analysis | p. 104 |
| Head Orientation Analysis and FoA Estimation | p. 106 |
| Head Orientation Analysis | p. 106 |
| Focus of Attention Estimation | p. 107 |
| Body Gesture Analysis | p. 109 |
| Conclusions | p. 112 |
| References | p. 112 |
| Processing of Handwriting and Sketching Dynamics | p. 119 |
| Introduction | p. 119 |
| History of Handwriting Modality and the Acquisition of Online Handwriting Signals | p. 121 |
| Basics in Acquisition, Examples for Sensors | p. 123 |
| Analysis of Online Handwriting and Sketching Signals | p. 124 |
| Overview of Recognition Goals in HCI | p. 125 |
| Sketch Recognition for User Interface Design | p. 128 |
| Similarity Search in Digital Ink | p. 133 |
| Summary and Perspectives for Handwriting and Sketching in HCI | p. 138 |
| References | p. 139 |
| Multimodal Signal Processing and Modelling | p. 143 |
| Basic Concepts of Multimodal Analysis | p. 143 |
| Defining Multimodality | p. 145 |
| Advantages of Multimodal Analysis | p. 148 |
| Conclusion | p. 151 |
| References | p. 152 |
| Multimodal Information Fusion | p. 153 |
| Introduction | p. 153 |
| Levels of Fusion | p. 156 |
| Adaptive versus Non-Adaptive Fusion | p. 158 |
| Other Design Issues | p. 162 |
| Conclusions | p. 165 |
| References | p. 165 |
| Modality Integration Methods | p. 171 |
| Introduction | p. 171 |
| Multimodal Fusion for AVSR | p. 172 |
| Types of Fusion | p. 172 |
| Multistream HMMs | p. 174 |
| Stream Reliability Estimates | p. 174 |
| Multimodal Speaker Localisation | p. 178 |
| Conclusion | p. 181 |
| References | p. 181 |
| A Multimodal Recognition Framework for Joint Modality Compensation and Fusion | p. 185 |
| Introduction | p. 186 |
| Joint Modality Recognition and Applications | p. 188 |
| A New Joint Modality Recognition Scheme | p. 191 |
| Concept | p. 191 |
| Theoretical Background | p. 191 |
| Joint Modality Audio-Visual Speech Recognition | p. 194 |
| Signature Extraction Stage | p. 196 |
| Recognition Stage | p. 197 |
| Joint Modality Recognition in Biometrics | p. 198 |
| Overview | p. 198 |
| Results | p. 199 |
| Conclusions | p. 203 |
| References 204 | |
| Managing Multimodal Data, Metadata and Annotations: Challenges and Solutions | p. 207 |
| Introduction | p. 208 |
| Setting the Stage: Concepts and Projects | p. 208 |
| Metadate-versusAnnotations | p. 209 |
| Examples of Large Multimodal Collections | p. 210 |
| Capturing and Recording Multimodal Data | p. 211 |
| Capture Devices | p. 211 |
| Synchronisation | p. 212 |
| Activity Types in Multimodal Corpora | p. 213 |
| Examples of Set-ups and Raw Data | p. 213 |
| Reference Metadata and Annotations | p. 214 |
| Gathering Metadata: Methods | p. 215 |
| Metadata for the AMI Corpus | p. 216 |
| Reference Annotations: Procedure and Tools | p. 217 |
| Data Storage and Access | p. 219 |
| Exchange Formats for Metadata and Annotations | p. 219 |
| Data Servers | p. 221 |
| Accessing Annotated Multimodal Data | p. 222 |
| Conclusions and Perspectives | p. 223 |
| References | p. 224 |
| Multimodal Human-Computer and Human-to-Human Interaction | p. 229 |
| Multimodal Input | p. 231 |
| Introduction | p. 231 |
| Advantages of Multimodal Input Interfaces | p. 232 |
| State-of-the-Art Multimodal Input Systems | p. 234 |
| Multimodality, Cognition and Performance | p. 237 |
| Multimodal Perception and Cognition | p. 237 |
| Cognitive Load and Performance | p. 238 |
| Understanding Multimodal Input Behaviour | p. 239 |
| Theoretical Frameworks | p. 240 |
| Interpretation of Multimodal Input Patterns | p. 243 |
| Adaptive Multimodal Interfaces | p. 245 |
| Designing Multimodal Interfaces that Manage Users' Cognitive Load | p. 246 |
| Designing Low-Load Multimodal Interfaces for Education | p. 248 |
| Conclusions and Future Directions | p. 250 |
| References | p. 251 |
| MuItimodal Output: Facial Motion, Gestures and Synthesised Speech Synchronisation | p. 257 |
| Introduction | p. 257 |
| Basic AV Speech Synthesis | p. 258 |
| The Animation System | p. 260 |
| Coarticulation | p. 263 |
| Extended AV Speech Synthesis | p. 264 |
| Data-Driven Approaches | p. 267 |
| Rule-Based Approaches | p. 269 |
| Embodied Conversational Agents | p. 270 |
| TTS Timing Issues | p. 272 |
| On-the-Fly Synchronisation | p. 272 |
| A Priori Synchronisation | p. 273 |
| Conclusion | p. 274 |
| References | p. 274 |
| Interactive Representations of Multimodal Databases | p. 279 |
| Introduction | p. 279 |
| Multimodal Data Representation | p. 280 |
| Multimodal Data Access | p. 283 |
| Browsing as Extension of the Query Formulation Mechanism | p. 283 |
| Browsing for the Exploration of the Content Space | p. 287 |
| Alternative Representations | p. 292 |
| Evaluation | p. 292 |
| Commercial Impact | p. 293 |
| Gaining Semantic from User Interaction | p. 294 |
| Multimodal Interactive Retrieval | p. 294 |
| Crowdsourcing | p. 295 |
| Conclusion and Discussion | p. 298 |
| References | p. 299 |
| Modelling Interest in Face-to-Face Conversations from Multimodal Nonverbal Behaviour | p. 309 |
| Introduction | p. 309 |
| Perspectives on Interest Modelling | p. 311 |
| Computing Interest from Audio Cues | p. 315 |
| Computing interest from Multimodal Cues | p. 318 |
| Other Concepts Related to Interest | p. 320 |
| Concluding Remarks | p. 322 |
| References | p. 323 |
| Index | p. 327 |
| Table of Contents provided by Ingram. All Rights Reserved. |