Book description
To create truly effective human-centric ambient intelligence systems both engineering and computing methods are needed. This is the first book to bridge data processing and intelligent reasoning methods for the creation of human-centered ambient intelligence systems. Interdisciplinary in nature, the book covers topics such as multi-modal interfaces, human-computer interaction, smart environments and pervasive computing, addressing principles, paradigms, methods and applications. This book will be an ideal reference for university researchers, R&D engineers, computer engineers, and graduate students working in signal, speech and video processing, multi-modal interfaces, human-computer interaction and applications of ambient intelligence.
Table of contents
- Front Cover
- Human-Centric Interfaces for Ambient Intelligence
- Copyright Page
- Contents (1/3)
- Contents (2/3)
- Contents (3/3)
- Foreword
- Preface
-
Part 1: Vision and Visual Interfaces
- Chapter 1: Face-to-Face Collaborative Interfaces
- Chapter 2: Computer Vision Interfaces for Interactive Art
- Chapter 3: Ubiquitous Gaze: Using Gaze at the Interface
- Chapter 4: Exploiting Natural Language Generation in Scene Interpretation
-
Chapter 5: The Language of Action: A New Tool for Human-Centric Interfaces
- 5.1 Introduction
- 5.2 Human Action
- 5.3 Learning the Languages of Human Action
- 5.4 Grammars of Visual Human Movement
- 5.5 Grammars of Motoric Human Movement (1/4)
- 5.5 Grammars of Motoric Human Movement (2/4)
- 5.5 Grammars of Motoric Human Movement (3/4)
- 5.5 Grammars of Motoric Human Movement (4/4)
- 5.6 Applications to Health
- 5.7 Applications to Artificial Intelligence and Cognitive Systems
- 5.8 Conclusions
- Acknowledgments
- References
-
Part 2: Speech Processing and Dialogue Management
-
Chapter 6: Robust Speech Recognition Under Noisy Ambient Conditions
- 6.1 Introduction
- 6.2 Speech Recognition Overview
- 6.3 Variability in the Speech Signal
- 6.4 Robust Speech Recognition Techniques (1/3)
- 6.4 Robust Speech Recognition Techniques (2/3)
- 6.4 Robust Speech Recognition Techniques (3/3)
- 6.5 Summary
- References (1/2)
- References (2/2)
-
Chapter 7: Speaker Recognition in Smart Environments
- 7.1 Principles and Applications of Speaker Recognition
- 7.2 Text-Dependent Speaker Recognition Methods
- 7.3 Text-Independent Speaker Recognition Methods
- 7.4 Text-Prompted Speaker Recognition
- 7.5 High-Level Speaker Recognition
- 7.6 Normalization and Adaptation Techniques
- 7.7 ROC and DET Curves
- 7.8 Speaker Diarization
- 7.9 Multimodal Speaker Recognition
- 7.10 Outstanding Issues
- References
-
Chapter 8: Machine Learning Approaches to Spoken Language Understanding for Ambient Intelligence
- 8.1 Introduction
- 8.2 Statistical Spoken Language Understanding
- 8.3 Conditional Random Fields
- 8.4 Efficient Algorithms for Inference and Learning
- 8.5 Transfer Learning for Spoken Language Understanding
- 8.6 Joint Prediction of Dialogue Acts and Named Entities
- 8.7 Multi-Domain Spoken Language Understanding (1/2)
- 8.7 Multi-Domain Spoken Language Understanding (2/2)
- 8.8 Conclusion and Future Direction
- Acknowledgments
- References
-
Chapter 9: The Role of Spoken Dialogue in User-Environment Interaction
- 9.1 Introduction
- 9.2 Types of Interactive Speech Systems
- 9.3 The Components of an Interactive Speech System (1/2)
- 9.3 The Components of an Interactive Speech System (2/2)
- 9.4 Examples of Spoken Dialogue Systems for Ambient Intelligence Environments (1/2)
- 9.4 Examples of Spoken Dialogue Systems for Ambient Intelligence Environments (2/2)
- 9.5 Challenges for Spoken Dialogue Technology in Ambient Intelligence Environments
- 9.6 Conclusions
- References
- Chapter 10: Speech Synthesis Systems in Ambient Intelligence Environments
-
Chapter 6: Robust Speech Recognition Under Noisy Ambient Conditions
-
Part 3: Multimodal Interfaces
- Chapter 11: Tangible Interfaces for Ambient Augmented Reality Applications
-
Chapter 12: Physical Browsing and Selection-Easy Interaction with Ambient Services
- 12.1 Introduction to Physical Browsing
- 12.2 Why Ambient Services Need Physical Browsing Solutions
- 12.3 Physical Selection
- 12.4 Selection as an Interaction Task (1/2)
- 12.4 Selection as an Interaction Task (2/2)
- 12.5 Implementing Physical Selection (1/2)
- 12.5 Implementing Physical Selection (2/2)
- 12.6 Indicating and Negotiating Actions After the Selection Event
- 12.7 Conclusions
- References
- Chapter 13: Nonsymbolic Gestural Interaction for Ambient Intelligence
-
Chapter 14: Evaluation of Multimodal Interfaces for Ambient Intelligence
- 14.1 Introduction
- 14.2 Performance and Quality Taxonomy
- 14.3 Quality Factors
- 14.4 Interaction Performance Aspects
- 14.5 Quality Aspects
- 14.6 Application Examples (1/3)
- 14.6 Application Examples (2/3)
- 14.6 Application Examples (3/3)
- 14.7 Conclusions and Future Work
- Acknowledgment
- References
-
Part 4: Smart Environment Applications
- Chapter 15: New Frontiers in Machine Learning for Predictive User Modeling
-
Chapter 16: Games and Entertainment in Ambient Intelligence Environments
- 16.1 Introduction
- 16.2 Ambient Entertainment Applications
- 16.3 Dimensions in Ambient Entertainment (1/2)
- 16.3 Dimensions in Ambient Entertainment (2/2)
- 16.4 Designing for Ambient Entertainment and Experience (1/2)
- 16.4 Designing for Ambient Entertainment and Experience (2/2)
- 16.5 Conclusions
- Acknowledgments
- References
-
Chapter 17: Natural and Implicit Information-Seeking Cues in Responsive Technology
- 17.1 Introduction
- 17.2 Information Seeking and Indicative Cues
- 17.3 Designing Systems for Natural and Implicit Interaction
- 17.4 Clothes Shopping Support Technologies
- 17.5 Case Study: Responsive Mirror (1/5)
- 17.5 Case Study: Responsive Mirror (2/5)
- 17.5 Case Study: Responsive Mirror (3/5)
- 17.5 Case Study: Responsive Mirror (4/5)
- 17.5 Case Study: Responsive Mirror (5/5)
- 17.6 Lessons for Ambient Intelligence Designs of Natural and Implicit Interaction
- Acknowledgments
- References
-
Chapter 18: Spoken Dialogue Systems for Intelligent Environments
- 18.1 Introduction
- 18.2 Intelligent Environments (1/2)
- 18.2 Intelligent Environments (2/2)
- 18.3 Information Access in Intelligent Environments (1/3)
- 18.3 Information Access in Intelligent Environments (2/3)
- 18.3 Information Access in Intelligent Environments (3/3)
- 18.4 Conclusions
- Acknowledgments
- References
-
Chapter 19: Deploying Context-Aware Health Technology at Home: Human-Centric Challenges
- 19.1 Introduction
- 19.2 The Opportunity: Context-Aware Home Health Applications
- 19.3 Case Study: Context-Aware Medication Adherence
- 19.4 Detecting Context: Twelve Questions to Guide Research (1/3)
- 19.4 Detecting Context: Twelve Questions to Guide Research (2/3)
-
19.4 Detecting Context: Twelve Questions to Guide Research (3/3)
- 19.4.1 Sensor Installation (“Install It”)
- 19.4.2 Activity Model Training (“Customize It”)
-
19.4.3 Activity Model Maintenance (“Fix It”)
- Question 8: Who Will Maintain the System as Activities Change, the Environment Changes, and Sensors Break?
- Question 9: How Does the User Know What Is Broken?
- Question 10: Can the User Make Instantaneous, Nonoscillating Fixes?
- Question 11: What Will Keep the User’s Mental Model in Line with the Algorithmic Model?
- Question 12: How Does a User Add a New Activity to Recognize?
- 19.5 Conclusions
- Acknowledgments
- References
- Epilogue: Challenges and Outlook (1/2)
- Epilogue: Challenges and Outlook (2/2)
- Index
Product information
- Title: Human-Centric Interfaces for Ambient Intelligence
- Author(s):
- Release date: October 2009
- Publisher(s): Academic Press
- ISBN: 9780080878508
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