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.
Download or read book Multimodal Affective Computing written by Ramón Zatarain Cabada and published by Springer. This book was released on 2023-07-05 with total page 0 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.
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.
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.
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.
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.
Download or read book Applied Affective Computing written by Leimin Tian and published by Morgan & Claypool. This book was released on 2022-02-04 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: Affective computing is a nascent field situated at the intersection of artificial intelligence with social and behavioral science. It studies how human emotions are perceived and expressed, which then informs the design of intelligent agents and systems that can either mimic this behavior to improve their intelligence or incorporate such knowledge to effectively understand and communicate with their human collaborators. Affective computing research has recently seen significant advances and is making a critical transformation from exploratory studies to real-world applications in the emerging research area known as applied affective computing. This book offers readers an overview of the state-of-the-art and emerging themes in affective computing, including a comprehensive review of the existing approaches to affective computing systems and social signal processing. It provides in-depth case studies of applied affective computing in various domains, such as social robotics and mental well-being. It also addresses ethical concerns related to affective computing and how to prevent misuse of the technology in research and applications. Further, this book identifies future directions for the field and summarizes a set of guidelines for developing next-generation affective computing systems that are effective, safe, and human-centered. For researchers and practitioners new to affective computing, this book will serve as an introduction to the field to help them in identifying new research topics or developing novel applications. For more experienced researchers and practitioners, the discussions in this book provide guidance for adopting a human-centered design and development approach to advance affective computing.
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.
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."--
Download or read book Affective Computing and Sentiment Analysis written by Khurshid Ahmad and published by Springer Science & Business Media. This book was released on 2011-08-24 with total page 158 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume maps the watershed areas between two 'holy grails' of computer science: the identification and interpretation of affect – including sentiment and mood. The expression of sentiment and mood involves the use of metaphors, especially in emotive situations. Affect computing is rooted in hermeneutics, philosophy, political science and sociology, and is now a key area of research in computer science. The 24/7 news sites and blogs facilitate the expression and shaping of opinion locally and globally. Sentiment analysis, based on text and data mining, is being used in the looking at news and blogs for purposes as diverse as: brand management, film reviews, financial market analysis and prediction, homeland security. There are systems that learn how sentiments are articulated. This work draws on, and informs, research in fields as varied as artificial intelligence, especially reasoning and machine learning, corpus-based information extraction, linguistics, and psychology.
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.
Download or read book Machine Learning Systems for Multimodal Affect Recognition written by Markus Kächele and published by Springer Nature. This book was released on 2019-11-19 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: Markus Kächele offers a detailed view on the different steps in the affective computing pipeline, ranging from corpus design and recording over annotation and feature extraction to post-processing, classification of individual modalities and fusion in the context of ensemble classifiers. He focuses on multimodal recognition of discrete and continuous emotional and medical states. As such, specifically the peculiarities that arise during annotation and processing of continuous signals are highlighted. Furthermore, methods are presented that allow personalization of datasets and adaptation of classifiers to new situations and persons.
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.
Download or read book The Handbook of Multimodal Multisensor Interfaces Volume 2 written by Sharon Oviatt and published by Morgan & Claypool. This book was released on 2018-10-08 with total page 555 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Affective Computing written by Jimmy Or and published by BoD – Books on Demand. This book was released on 2008-05-01 with total page 454 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an overview of state of the art research in Affective Computing. It presents new ideas, original results and practical experiences in this increasingly important research field. The book consists of 23 chapters categorized into four sections. Since one of the most important means of human communication is facial expression, the first section of this book (Chapters 1 to 7) presents a research on synthesis and recognition of facial expressions. Given that we not only use the face but also body movements to express ourselves, in the second section (Chapters 8 to 11) we present a research on perception and generation of emotional expressions by using full-body motions. The third section of the book (Chapters 12 to 16) presents computational models on emotion, as well as findings from neuroscience research. In the last section of the book (Chapters 17 to 22) we present applications related to affective computing.
Download or read book Affective Computing and Interaction Psychological Cognitive and Neuroscientific Perspectives written by Gkay, Didem and published by IGI Global. This book was released on 2010-10-31 with total page 458 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since interactions may occur between animals, humans, or computational agents, an interdisciplinary approach which investigates foundations of affective communication in a variety of platforms is indispensable. In the field of affective computing, a collection of research, merging decades of research on emotions in psychology, cognition and neuroscience will inspire creative future research projects and contribute to the prosperity of this emerging field. Affective Computing and Interaction: Psychological, Cognitive and Neuroscientific Perspectives examines the current state and the future prospects of affect in computing within the context of interactions. Uniting several aspects of affective interactions and topics in affective computing, this reference reviews basic foundations of emotions, furthers an understanding of the contribution of affect to our lives and concludes by revealing current trends and promising technologies for reducing the emotional gap between humans and machines, all within the context of interactions.
Download or read book Principles and Applications of Socio Cognitive and Affective Computing written by Geetha, S. and published by IGI Global. This book was released on 2022-09-30 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent advances in socio-cognitive and affective computing require further study as countless benefits and opportunities have emerged from these innovative technologies that may be useful in a number of contexts throughout daily life. In order to ensure these technologies are appropriately utilized across sectors, the challenges and strategies for adoption as well as potential uses must be thoroughly considered. Principles and Applications of Socio-Cognitive and Affective Computing discusses several aspects of affective interactions and concepts in affective computing, the fundamentals of emotions, and emerging research and exciting techniques for bridging the emotional disparity between humans and machines, all within the context of interactions. The book also considers problem and solution guidelines emerging in cognitive computing, thus summarizing the roadmap of current machine computational intelligence techniques for affective computing. Covering a range of topics such as social interaction, robotics, and virtual reality, this reference work is crucial for scientists, engineers, industry professionals, academicians, researchers, scholars, practitioners, instructors, and students.
