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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. - Presents state-of-art methods for multimodal signal processing, analysis, and modeling - Contains numerous examples of systems with different modalities combined - Describes advanced applications in multimodal Human-Computer Interaction (HCI) as well as in computer-based analysis and modelling of multimodal human-human communication scenes.
This book constitutes the thoroughly refereed post-proceedings of the First International Workshop on Machine Learning for Multimodal Interaction, MLMI 2004, held in Martigny, Switzerland in June 2004. The 30 revised full papers presented were carefully selected during two rounds of reviewing and revision. The papers are organized in topical sections on HCI and applications, structuring and interaction, multimodal processing, speech processing, dialogue management, and vision and emotion.
This book constitutes the thoroughly refereed post-conference proceedings of the COST Action 2102 and euCognition supported international school on Multimodal Signals: "Cognitive and Algorithmic Issues" held in Vietri sul Mare, Italy, in April 2008. The 34 revised full papers presented were carefully reviewed and selected from participants’ contributions and invited lectures given at the workshop. The volume is organized in two parts; the first on Interactive and Unsupervised Multimodal Systems contains 14 papers. The papers deal with the theoretical and computational issue of defining algorithms, programming languages, and determinist models to recognize and synthesize multimodal signals. These are facial and vocal expressions of emotions, tones of voice, gestures, eye contact, spatial arrangements, patterns of touch, expressive movements, writing patterns, and cultural differences, in anticipation of the implementation of intelligent avatars and interactive dialogue systems that could be exploited to improve user access to future telecommunication services. The second part of the volume, on Verbal and Nonverbal Communication Signals, presents 20 original studies devoted to the modeling of timing synchronisation between speech production, gestures, facial and head movements in human communicative expressions and on their mutual contribution for an effective communication.
A timely book containing foundations and current research directions on emotion recognition by facial expression, voice, gesture and biopotential signals This book provides a comprehensive examination of the research methodology of different modalities of emotion recognition. Key topics of discussion include facial expression, voice and biopotential signal-based emotion recognition. Special emphasis is given to feature selection, feature reduction, classifier design and multi-modal fusion to improve performance of emotion-classifiers. Written by several experts, the book includes several tools and techniques, including dynamic Bayesian networks, neural nets, hidden Markov model, rough sets, type-2 fuzzy sets, support vector machines and their applications in emotion recognition by different modalities. The book ends with a discussion on emotion recognition in automotive fields to determine stress and anger of the drivers, responsible for degradation of their performance and driving-ability. There is an increasing demand of emotion recognition in diverse fields, including psycho-therapy, bio-medicine and security in government, public and private agencies. The importance of emotion recognition has been given priority by industries including Hewlett Packard in the design and development of the next generation human-computer interface (HCI) systems. Emotion Recognition: A Pattern Analysis Approach would be of great interest to researchers, graduate students and practitioners, as the book Offers both foundations and advances on emotion recognition in a single volume Provides a thorough and insightful introduction to the subject by utilizing computational tools of diverse domains Inspires young researchers to prepare themselves for their own research Demonstrates direction of future research through new technologies, such as Microsoft Kinect, EEG systems etc.
"This book introduces the readers to the various aspects of visual speech recognitions, including lip segmentation from video sequence, lip feature extraction and modeling, feature fusion and classifier design for visual speech recognition and speaker verification" résumé de l'éditeur.
More than 30 leading experts from around the world provide comprehensive coverage of various branches of face image analysis, making this text a valuable asset for students, researchers, and practitioners engaged in the study, research, and development of face image analysis techniques.
This latest volume in the series, Socio-Affective Computing, presents a set of novel approaches to analyze opinionated videos and to extract sentiments and emotions. Textual sentiment analysis framework as discussed in this book contains a novel way of doing sentiment analysis by merging linguistics with machine learning. Fusing textual information with audio and visual cues is found to be extremely useful which improves text, audio and visual based unimodal sentiment analyzer. This volume covers the three main topics of: textual preprocessing and sentiment analysis methods; frameworks to process audio and visual data; and methods of textual, audio and visual features fusion. The inclusion of key visualization and case studies will enable readers to understand better these approaches. Aimed at the Natural Language Processing, Affective Computing and Artificial Intelligence audiences, this comprehensive volume will appeal to a wide readership and will help readers to understand key details on multimodal sentiment analysis.
tionship indicates how multimodal medical image processing can be unified to a large extent, e. g. multi-channel segmentation and image registration, and extend information theoretic registration to other features than image intensities. The framework is not at all restricted to medical images though and this is illustrated by applying it to multimedia sequences as well. In Chapter 4, the main results from the developments in plastic UIs and mul- modal UIs are brought together using a theoretic and conceptual perspective as a unifying approach. It is aimed at defining models useful to support UI plasticity by relying on multimodality, at introducing and discussing basic principles that can drive the development of such UIs, and at describing some techniques as proof-of-concept of the aforementioned models and principles. In Chapter 4, the authors introduce running examples that serve as illustration throughout the d- cussion of the use of multimodality to support plasticity.
Embodied agents play an increasingly important role in cognitive interaction technology. The two main types of embodied agents are virtual humans inhabiting simulated environments and humanoid robots inhabiting the real world. So far research on embodied communicative agents has mainly explored their potential for practical applications. However, the design of communicative artificial agents can also be of great heuristic value for the scientific study of communication. It allows researchers to isolate, implement, and test essential properties of inter-agent communications in operational models. Modeling communication with robots and virtual humans thus involves the vision of using communicative machines as research tools. Artificial systems that reproduce certain aspects of natural, multimodal communication help to elucidate the internal mechanisms that give rise to different aspects of communication. In short, constructing embodied agents who are able to communicate may help us to understand the principles of human communication. As a comprehensive theme, “Embodied Communication in Humans and Machines” was taken up by an international research group hosted by Bielefeld University’s Center for Interdisciplinary Research (ZiF – Zentrum für interdisziplinäre Forschung) from October 2005 through September 2006. The overarching goal of this research year was to develop an integrated perspective of embodiment in communication, establishing bridges between lower-level, sensorimotor functions and a range of higher-level, communicative functions involving language and bodily action. The present volume grew out of a workshop that took place during April 5–8, 2006 at the ZiF as a part of the research year on embodied communication.
Welcome to the second IEEE Pacific Rim Conference on Multimedia (IEEE PCM 2001) held in Zhongguanchun, Beijing, China, October 22 24, 2001. Building upon the success of the inaugural IEEE PCM 2000 in Sydney in December 2000, the second PCM again brought together the researchers, developers, practitioners, and educators of multimedia in the Pacific area. Theoretical breakthroughs and practical systems were presented at this conference, thanks to the sponsorship by the IEEE Circuit and Systems Society, IEEE Signal Processing Society, China Computer Foundation, China Society of Image and Graphics, National Natural Science Foundation of China, Tsinghua University, and Microsoft Research, China. IEEE PCM 2001 featured a comprehensive program including keynote talks, regular paper presentations, posters, demos, and special sessions. We received 244 papers and accepted only 104 of them as regular papers, and 53 as poster papers. Our special session chairs, Shin'ichi Satoh and Mohan Kankanhalli, organized 6 special sessions. We acknowledge the great contribution from our program committee members and paper reviewers who spent many hours reviewing submitted papers and providing valuable comments for the authors. The conference would not have been successful without the help of so many people. We greatly appreciated the support of our honorary chairs: Prof. Sun Yuan Kung of Princeton University, Dr. Ya Qin Zhang of Microsoft Research China, and Prof.