The Handbook of Multimodal-Multisensor Interfaces, Volume 2 : Signal Processing, Architectures, and Detection of Emotion and Cognition

Sharon Oviatt

ISBN 10: 1970001712 / ISBN 13: 9781970001716

Edité par Association For Computing Machinery, 2018

A propos de cet article

nach der Bestellung gedruckt Neuware - Printed after ordering - The Handbook of Multimodal-Multisensor Interfaces provides the first authoritative resource on what has become the dominant paradigm for new computer interfaces: user input involving new media (speech, multi-touch, hand and body gestures, facial expressions, writing) embedded in multimodal-multisensor interfaces that often include biosignals. This edited collection is written by international experts and pioneers in the field. It provides a textbook, reference, and technology roadmap for professionals working in this and related areas. This second volume of the handbook begins with multimodal signal processing, architectures, and machine learning. It includes recent deep learning approaches for processing multisensorial and multimodal user data and interaction, as well as context-sensitivity. A further highlight is processing of information about users' states and traits, an exciting emerging capability in next-generation user interfaces. These chapters discuss real-time multimodal analysis of emotion and social signals from various modalities, and perception of affective expression by users. Further chapters discuss multimodal processing of cognitive state using behavioral and physiological signals to detect cognitive load, domain expertise, deception, and depression. This collection of chapters provides walk-through examples of system design and processing, information on tools and practical resources for developing and evaluating new systems, and terminology and tutorial support for mastering this rapidly expanding field. In the final section of this volume, experts exchange views on the timely and controversial challenge topic of multimodal deep learning. The discussion focuses on how multimodal-multisensor interfaces are most likely to advance human performance during the next decade.

N° de réf. du vendeur 9781970001716

Détails bibliographiques

• Titre: The Handbook of Multimodal-Multisensor Interfaces, Volume 2 : Signal Processing, Architectures, and Detection of Emotion and Cognition
• Éditeur: Association For Computing Machinery
• Date de parution: 2018
• Langue: anglais
• ISBN à 10 chiffres: 1970001712
• ISBN à 13 chiffres: 9781970001716
• Reliure: Buch
• État de l'article: Neu
• Dimensions: 241 L x 196 H x 34 P (en millimètres) 241 millimètres de largeur par 196 millimètres de hauteur par 34 millimètres de profondeur
• Poids: 1219 grammes

A propos de ce titre

Synopsis

The Handbook of Multimodal-Multisensor Interfaces provides the first authoritative resource on what has become the dominant paradigm for new computer interfaces: user input involving new media (speech, multi-touch, hand and body gestures, facial expressions, writing) embedded in multimodal-multisensor interfaces that often include biosignals. This edited collection is written by international experts and pioneers in the field. It provides a textbook, reference, and technology roadmap for professionals working in this and related areas. This second volume of the handbook begins with multimodal signal processing, architectures, and machine learning. It includes recent deep learning approaches for processing multisensorial and multimodal user data and interaction, as well as context-sensitivity. A further highlight is processing of information about users' states and traits, an exciting emerging capability in next-generation user interfaces. These chapters discuss real-time multimodal analysis of emotion and social signals from various modalities, and perception of affective expression by users. Further chapters discuss multimodal processing of cognitive state using behavioral and physiological signals to detect cognitive load, domain expertise, deception, and depression. This collection of chapters provides walk-through examples of system design and processing, information on tools and practical resources for developing and evaluating new systems, and terminology and tutorial support for mastering this rapidly expanding field. In the final section of this volume, experts exchange views on the timely and controversial challenge topic of multimodal deep learning. The discussion focuses on how multimodal-multisensor interfaces are most likely to advance human performance during the next decade.

À propos des auteurs

Sharon Oviatt (Incaa Designs) is internationally known for her multidisciplinary work on multimodal and mobile interfaces, human-centered interfaces, educational interfaces and learning analytics. She has been recipient of the inaugural ACM-ICMI Sustained Accomplishment Award, National Science Foundation Special Creativity Award, and ACM-SIGCHI CHI Academy award. She has published over 160 scientific articles in a wide range of venues, and is an Associate Editor of the main journals and edited book collections in the field of human-centered interfaces. Her other books include The Design of Future Educational Interfaces (2013, Routledge) and The Paradigm Shift to Multimodality in Contemporary Computer Interfaces (2015, Morgan Claypool).

Björn Schuller (University of Passau and Imperial College London) is currently Chair of Complex and Intelligent Systems at University of Passau and Reader in Machine Learning at Imperial College. He is best known for his work on multisensorial/multimodal intelligent signal processing for affective, behavioral, and human-centered computing. In 2015 and 2016, he was honored by the World Economic Forum as one of 40/50 extraordinary scientists under age 40. His further awards include the CHiME, MediaEval, and MIREX competitions. He has published over 500 peer-reviewed scientific contributions across a range of disciplines and venues, and is Editor-in-Chief of IEEE Transactions on Affective Computing. His books include Intelligent Audio Analysis (2013, Springer) and Computational Paralinguistics (2013, Wiley).

Philip Cohen (VoiceBox Technologies) is Senior Vice President and Chief Scientist for Artificial Intelligence, whose research interests include multimodal interaction, human-computer dialogue, and multi-agent systems. He is a Fellow of the American Association for Artificial Intelligence, past President of the Association for Computational Linguistics, and recipient (with Hector Levesque) of an Inaugural Influential Paper Award by the International Foundation for Autonomous Agents and Multi-Agent Systems. He was the Founder of Adapx, Professor and Co-Director of the Center for Human-Computer Communication in Computer Science at Oregon Health and Science University, and Director of Natural Language in the Artificial Intelligence Center at SRI International.