Multimodal Affective Computing Affective Information Representation Modelling And Analysis

Author : Gyanendra K. Verma
Publisher : Bentham Science Publishers
ISBN 13 : 9815124463
Total Pages : 167 pages
Book Rating : 4.60/5 ( download)

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Download or read book Multimodal Affective Computing: Affective Information Representation, Modelling, and Analysis written by Gyanendra K. Verma and published by Bentham Science Publishers. This book was released on 2023-03-21 with total page 167 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer Assistive Technologies for Physically and Cognitively Challenged Users focuses on the technologies and devices that assist individuals with physical and cognitive disabilities. These technologies facilitate independent activity and participation, serving to improve daily functional capabilities. The book features nine chapters that cover a wide range of computer assistive technologies that give readers an indepth understanding of the available resources to help the elderly or individuals with disabilities. The topics covered in the book include 1) The category and ontology of assistive devices, 2) Web accessibility and ICT accessibility for persons with disability (PWD), 3) Assistive technologies for blind and visually impaired people, 4) Assistive technologies for home comfort and care, 5) Assistive technologies for hearing impaired people using Indian sign language synthetic animations, 6) Augmentative and alternative communication/hearing impairments, 7) Accessibility innovations to help physically disabled users, 8) Adhesive tactile walking surface indicators for elderly and visually impaired people mobility, 9) future of assistive technologies This book serves as a textbook resource for students undertaking modular courses that require learning material on computer assistive technology. It also serves as a reference for graduate level courses in disability studies, humancomputer interaction, gerontology and rehabilitation engineering. Researchers working in the allied fields intersecting computer science, medicine and psychology will also benefit from the information provided in the book.

Author : Ramón Zatarain Cabada
Publisher : Springer Nature
ISBN 13 : 3031325427
Total Pages : 211 pages
Book Rating : 4.27/5 ( download)

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Download or read book Multimodal Affective Computing written by Ramón Zatarain Cabada and published by Springer Nature. This book was released on 2023-06-26 with total page 211 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores AI methodologies for the implementation of affective states in intelligent learning environments. Divided into four parts, Multimodal Affective Computing: Technologies and Applications in Learning Environments begins with an overview of Affective Computing and Intelligent Learning Environments, from their fundamentals and essential theoretical support up to their fusion and some successful practical applications. The basic concepts of Affective Computing, Machine Learning, and Pattern Recognition in Affective Computing, and Affective Learning Environments are presented in a comprehensive and easy-to-read manner. In the second part, a review on the emerging field of Sentiment Analysis for Learning Environments is introduced, including a systematic descriptive tour through topics such as building resources for sentiment detection, methods for data representation, designing and testing the classification models, and model integration into a learning system. The methodologies corresponding to Multimodal Recognition of Learning-Oriented Emotions are presented in the third part of the book, where topics such as building resources for emotion detection, methods for data representation, multimodal recognition systems, and multimodal emotion recognition in learning environments are presented. The fourth and last part of the book is devoted to a wide application field of the combination of methodologies, such as Automatic Personality Recognition, dealing with issues such as building resources for personality recognition, methods for data representation, personality recognition models, and multimodal personality recognition for affective computing. This book can be very useful not only for beginners who are interested in affective computing and intelligent learning environments, but also for advanced and experts in the practice and developments of the field. It complies an end-to-end treatment on these subjects, especially with educational applications, making it easy for researchers and students to get on track with fundamentals, established methodologies, conventional evaluation protocols, and the latest progress on these subjects.

Author : Jianhua Tao
Publisher : Springer Science & Business Media
ISBN 13 : 1848003064
Total Pages : 347 pages
Book Rating : 4.64/5 ( download)

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Download or read book Affective Information Processing written by Jianhua Tao and published by Springer Science & Business Media. This book was released on 2008-12-02 with total page 347 pages. Available in PDF, EPUB and Kindle. Book excerpt: Affective information processing assigns computers the human-like capabilities of observation, interpretation and generation of affect features. It is an important topic for harmonious human-computer interaction, by increasing the quality of human-computer communication and improving the intelligence of the computer. Discussing state of art of the research in affective information processing, this book summarises key technologies researched, such as facial expression recognition, face animation, emotional speech synthesis, intelligent agent, and virtual reality. The detailed discussion covers a wide range of topics including hot topics which look to challenge and improve current research work. Written to provide an opportunity for scientists, engineers and graduate students to learn problems, solutions and technologies in the topic area, this book will provide insight and prove a valuable reference tool.

Author : Hua Xu
Publisher : Springer Nature
ISBN 13 : 9819957761
Total Pages : 278 pages
Book Rating : 4.67/5 ( download)

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Download or read book Multi-Modal Sentiment Analysis written by Hua Xu and published by Springer Nature. This book was released on 2023-11-26 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: The natural interaction ability between human and machine mainly involves human-machine dialogue ability, multi-modal sentiment analysis ability, human-machine cooperation ability, and so on. To enable intelligent computers to have multi-modal sentiment analysis ability, it is necessary to equip them with a strong multi-modal sentiment analysis ability during the process of human-computer interaction. This is one of the key technologies for efficient and intelligent human-computer interaction. This book focuses on the research and practical applications of multi-modal sentiment analysis for human-computer natural interaction, particularly in the areas of multi-modal information feature representation, feature fusion, and sentiment classification. Multi-modal sentiment analysis for natural interaction is a comprehensive research field that involves the integration of natural language processing, computer vision, machine learning, pattern recognition, algorithm, robot intelligent system, human-computer interaction, etc. Currently, research on multi-modal sentiment analysis in natural interaction is developing rapidly. This book can be used as a professional textbook in the fields of natural interaction, intelligent question answering (customer service), natural language processing, human-computer interaction, etc. It can also serve as an important reference book for the development of systems and products in intelligent robots, natural language processing, human-computer interaction, and related fields.

Author : Erik Cambria
Publisher : Springer
ISBN 13 : 3319236547
Total Pages : 176 pages
Book Rating : 4.44/5 ( download)

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Download or read book Sentic Computing written by Erik Cambria and published by Springer. This book was released on 2015-12-11 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume presents a knowledge-based approach to concept-level sentiment analysis at the crossroads between affective computing, information extraction, and common-sense computing, which exploits both computer and social sciences to better interpret and process information on the Web. Concept-level sentiment analysis goes beyond a mere word-level analysis of text in order to enable a more efficient passage from (unstructured) textual information to (structured) machine-processable data, in potentially any domain. Readers will discover the following key novelties, that make this approach so unique and avant-garde, being reviewed and discussed: • Sentic Computing's multi-disciplinary approach to sentiment analysis-evidenced by the concomitant use of AI, linguistics and psychology for knowledge representation and inference • Sentic Computing’s shift from syntax to semantics-enabled by the adoption of the bag-of-concepts model instead of simply counting word co-occurrence frequencies in text • Sentic Computing's shift from statistics to linguistics-implemented by allowing sentiments to flow from concept to concept based on the dependency relation between clauses This volume is the first in the Series Socio-Affective Computing edited by Dr Amir Hussain and Dr Erik Cambria and will be of interest to researchers in the fields of socially intelligent, affective and multimodal human-machine interaction and systems.

Author : Soujanya Poria
Publisher : Springer
ISBN 13 : 3319950207
Total Pages : 214 pages
Book Rating : 4.04/5 ( download)

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Download or read book Multimodal Sentiment Analysis written by Soujanya Poria and published by Springer. This book was released on 2018-10-24 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Author : Klaus R. Scherer
Publisher : Oxford University Press
ISBN 13 : 0199566704
Total Pages : 408 pages
Book Rating : 4.09/5 ( download)

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Download or read book A Blueprint for Affective Computing written by Klaus R. Scherer and published by Oxford University Press. This book was released on 2010-09-23 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: 'Affective computing' is a branch of computing concerned with the theory and construction of machines which can detect, respond to, and simulate human emotional states. This book presents an interdisciplinary exploration of this rapidly expanding field, aimed at those in psychology, computational neuroscience, computer science, and AI.

Author : Rafael A. Calvo
Publisher : Oxford Library of Psychology
ISBN 13 : 0199942234
Total Pages : 625 pages
Book Rating : 4.37/5 ( download)

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Download or read book The Oxford Handbook of Affective Computing written by Rafael A. Calvo and published by Oxford Library of Psychology. This book was released on 2015 with total page 625 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The Oxford Handbook of Affective Computing is a definitive reference in the burgeoning field of affective computing (AC), a multidisciplinary field encompassing computer science, engineering, psychology, education, neuroscience, and other disciplines. AC research explores how affective factors influence interactions between humans and technology, how affect sensing and affect generation techniques can inform our understanding of human affect, and on the design, implementation, and evaluation of systems involving affect at their core. The volume features 41 chapters and is divided into five sections: history and theory, detection, generation, methodologies, and applications. Section 1 begins with the making of AC and a historical review of the science of emotion. The following chapters discuss the theoretical underpinnings of AC from an interdisciplinary viewpoint. Section 2 examines affect detection or recognition, a commonly investigated area. Section 3 focuses on aspects of affect generation, including the synthesis of emotion and its expression via facial features, speech, postures, and gestures. Cultural issues are also discussed. Section 4 focuses on methodological issues in AC research, including data collection techniques, multimodal affect databases, formats for the representation of emotion, crowdsourcing techniques, machine learning approaches, affect elicitation techniques, useful AC tools, and ethical issues. Finally, Section 5 highlights applications of AC in such domains as formal and informal learning, games, robotics, virtual reality, autism research, health care, cyberpsychology, music, deception, reflective writing, and cyberpsychology. This compendium will prove suitable for use as a textbook and serve as a valuable resource for everyone with an interest in AC."--

Author : Antonio Fernández-Caballero
Publisher : MDPI
ISBN 13 : 3038971987
Total Pages : 255 pages
Book Rating : 4.86/5 ( download)

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Download or read book Socio-Cognitive and Affective Computing written by Antonio Fernández-Caballero and published by MDPI. This book was released on 2018-09-21 with total page 255 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a printed edition of the Special Issue "Socio-Cognitive and Affective Computing" that was published in Applied Sciences

Author : Zhen Cui
Publisher : Frontiers Media SA
ISBN 13 : 2832526365
Total Pages : 151 pages
Book Rating : 4.61/5 ( download)

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Download or read book Deep Learning Techniques Applied to Affective Computing written by Zhen Cui and published by Frontiers Media SA. This book was released on 2023-06-14 with total page 151 pages. Available in PDF, EPUB and Kindle. Book excerpt: Affective computing refers to computing that relates to, arises from, or influences emotions. The goal of affective computing is to bridge the gap between humans and machines and ultimately endow machines with emotional intelligence for improving natural human-machine interaction. In the context of human-robot interaction (HRI), it is hoped that robots can be endowed with human-like capabilities of observation, interpretation, and emotional expression. The research on affective computing has recently achieved extensive progress with many fields contributing including neuroscience, psychology, education, medicine, behavior, sociology, and computer science. Current research in affective computing concentrates on estimating human emotions through different forms of signals such as speech, face, text, EEG, fMRI, and many others. In neuroscience, the neural mechanisms of emotion are explored by combining neuroscience with the psychological study of personality, emotion, and mood. In psychology and philosophy, emotion typically includes a subjective, conscious experience characterized primarily by psychophysiological expressions, biological reactions, and mental states. The multi-disciplinary features of understanding “emotion” result in the fact that inferring the emotion of humans is definitely difficult. As a result, a multi-disciplinary approach is required to facilitate the development of affective computing. One of the challenging problems in affective computing is the affective gap, i.e., the inconsistency between the extracted feature representations and subjective emotions. To bridge the affective gap, various hand-crafted features have been widely employed to characterize subjective emotions. However, these hand-crafted features are usually low-level, and they may hence not be discriminative enough to depict subjective emotions. To address this issue, the recently-emerged deep learning (also called deep neural networks) techniques provide a possible solution. Due to the used multi-layer network structure, deep learning techniques are capable of learning high-level contributing features from a large dataset and have exhibited excellent performance in multiple application domains such as computer vision, signal processing, natural language processing, human-computer interaction, and so on. The goal of this Research Topic is to gather novel contributions on deep learning techniques applied to affective computing across the diverse fields of psychology, machine learning, neuroscience, education, behavior, sociology, and computer science to converge with those active in other research areas, such as speech emotion recognition, facial expression recognition, Electroencephalogram (EEG) based emotion estimation, human physiological signal (heart rate) estimation, affective human-robot interaction, multimodal affective computing, etc. We welcome researchers to contribute their original papers as well as review articles to provide works regarding the neural approach from computation to affective computing systems. This Research Topic aims to bring together research including, but not limited to: • Deep learning architectures and algorithms for affective computing tasks such as emotion recognition from speech, face, text, EEG, fMRI, and many others. • Explainability of deep Learning algorithms for affective computing. • Multi-task learning techniques for emotion, personality and depression detection, etc. • Novel datasets for affective computing • Applications of affective computing in robots, such as emotion-aware human-robot interaction and social robots, etc.