Multimodal signal processing : theory and applications for human-computer interaction

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書誌事項

Multimodal signal processing : theory and applications for human-computer interaction

Edited by Jean-Philippe Thiran, Ferran Marqués, Hervé Bourlard

（EURASIP and Academic Press Series in Signal and Image Processing）

Academic Press, 2010

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注記

Copyright c2010 by Elsevier

Includes bibliographical references and index

内容説明・目次

内容説明

Multimodal signal processing is an important research and development field that processes signals and combines information from a variety of modalities - speech, vision, language, text - which significantly enhance the understanding, modelling, and performance of human-computer interaction devices or systems enhancing human-human communication. The overarching theme of this book is the application of signal processing and statistical machine learning techniques to problems arising in this multi-disciplinary field. It describes the capabilities and limitations of current technologies, and discusses the technical challenges that must be overcome to develop efficient and user-friendly multimodal interactive systems. With contributions from the leading experts in the field, the present book should serve as a reference in multimodal signal processing for signal processing researchers, graduate students, R&D engineers, and computer engineers who are interested in this emerging field.

目次

  • Statistical Machine Learning for HCI
  • Speech Processing
  • Natural Language and Dialogue Processing
  • Image and Video Processing Tools for HCI
  • Processing of Handwriting and Sketching Dynamics
  • Basic Concepts of Multimodal Analysis
  • Multimodal Information Fusion
  • Modality Integration Methods
  • A Multimodal Recognition Framework for Joint Modality Compensation and Fusion
  • Managing Multimodal Data, Metadata and Annotations: Challenges and Solutions
  • Multimodal Input
  • Multimodal HCI Output: Facial Motion, Gestures and Synthesised Speech Synchronisation
  • Interactive Representations of Multimodal Databases
  • Modelling Interest in Face-to-Face Conversations from Multimodal Nonverbal Behaviour

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