In the past twenty years, computers and networks have gained a prominent role in supporting human communications. This book presents recent research in multimodal information processing, which demonstrates that computers can achieve more than what telephone calls or videoconferencing can do. The book offers a snapshot of current capabilities for the analysis of human communications in several modalities – audio, speech, language, images, video, and documents – and for accessing this information interactively. The book has a clear application goal, which is the capture, automatic analysis, storage, and retrieval of multimodal signals from human interaction in meetings. This goal provides a controlled experimental framework and helps generating shared data, which is required for methods based on machine learning. This goal has shaped the vision of the contributors to the book and of many other researchers cited in it. It has also received significant long-term support through a series of projects, including the Swiss National Center of Competence in Research (NCCR) in Interactive Multimodal Information Management (IM2), to which the contributors to the book have been connected.

This book provides a synthesis of the multifaceted field of interactive multimodal information management. The subjects treated include spoken language processing, image and video processing, document and handwriting analysis, identity information and interfaces. The book concludes with an overview of the highlights of the progress of the field dur

"This book provides concepts, methodologies, and applications used to design and develop multimodal systems"--Provided by publisher.

The increasing complexity of our world demands new perspectives on the role of technology in human decision making. We need new technology to cope with the increasingly complex and information-rich nature of our modern society. This is particularly true for critical environments such as crisis management and traffic management, where humans need to engage in close collaborations with artificial systems to observe and understand the situation and respond in a sensible way. The book Interactive Collaborative Information Systems addresses techniques that support humans in situations in which complex information handling is required and that facilitate distributed decision-making. The theme integrates research from information technology, artificial intelligence and human sciences to obtain a multidisciplinary foundation from which innovative actor-agent systems for critical environments can emerge. It emphasizes the importance of building actor-agent communities: close collaborations between human and artificial actors that highlight their complementary capabilities in situations where task distribution is flexible and adaptive. This book focuses on the employment of innovative agent technology, advanced machine learning techniques, and cognition-based interface technology for the use in collaborative decision support systems.

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 refereed proceedings of the 5th International Workshop on Machine Learning for Multimodal Interaction, MLMI 2008, held in Utrecht, The Netherlands, in September 2008. The 12 revised full papers and 15 revised poster papers presented together with 5 papers of a special session on user requirements and evaluation of multimodal meeting browsers/assistants were carefully reviewed and selected from 47 submissions. The papers cover a wide range of topics related to human-human communication modeling and processing, as well as to human-computer interaction, using several communication modalities. Special focus is given to the analysis of non-verbal communication cues and social signal processing, the analysis of communicative content, audio-visual scene analysis, speech processing, interactive systems and applications.

This book constitutes the thoroughly refereed post-proceedings of the Third International Workshop on Machine Learning for Multimodal Interaction, MLMI 2006, held in Bethesda, MD, USA, in May 2006. The papers are organized in topical sections on multimodal processing, image and video processing, HCI and applications, discourse and dialogue, speech and audio processing, and NIST meeting recognition evaluation.