Multi-Modal Sentiment Analysis
Multi-Modal Sentiment Analysis

Author: Hua Xu

Publisher: Springer Nature

Published: 2023-11-26

Total Pages: 278

ISBN-13: 9819957761

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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.

Computational Paralinguistics
Computational Paralinguistics

Author: Björn Schuller

Publisher: John Wiley & Sons

Published: 2013-09-17

Total Pages: 330

ISBN-13: 1118706625

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This book presents the methods, tools and techniques that are currently being used to recognise (automatically) the affect, emotion, personality and everything else beyond linguistics (‘paralinguistics’) expressed by or embedded in human speech and language. It is the first book to provide such a systematic survey of paralinguistics in speech and language processing. The technology described has evolved mainly from automatic speech and speaker recognition and processing, but also takes into account recent developments within speech signal processing, machine intelligence and data mining. Moreover, the book offers a hands-on approach by integrating actual data sets, software, and open-source utilities which will make the book invaluable as a teaching tool and similarly useful for those professionals already in the field. Key features: Provides an integrated presentation of basic research (in phonetics/linguistics and humanities) with state-of-the-art engineering approaches for speech signal processing and machine intelligence. Explains the history and state of the art of all of the sub-fields which contribute to the topic of computational paralinguistics. C overs the signal processing and machine learning aspects of the actual computational modelling of emotion and personality and explains the detection process from corpus collection to feature extraction and from model testing to system integration. Details aspects of real-world system integration including distribution, weakly supervised learning and confidence measures. Outlines machine learning approaches including static, dynamic and context‐sensitive algorithms for classification and regression. Includes a tutorial on freely available toolkits, such as the open-source ‘openEAR’ toolkit for emotion and affect recognition co-developed by one of the authors, and a listing of standard databases and feature sets used in the field to allow for immediate experimentation enabling the reader to build an emotion detection model on an existing corpus.

Sentic Computing
Sentic Computing

Author: Erik Cambria

Publisher: Springer Science & Business Media

Published: 2012-07-28

Total Pages: 166

ISBN-13: 9400750706

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In this book common sense computing techniques are further developed and applied to bridge the semantic gap between word-level natural language data and the concept-level opinions conveyed by these. In particular, the ensemble application of graph mining and multi-dimensionality reduction techniques is exploited on two common sense knowledge bases to develop a novel intelligent engine for open-domain opinion mining and sentiment analysis. The proposed approach, termed sentic computing, performs a clause-level semantic analysis of text, which allows the inference of both the conceptual and emotional information associated with natural language opinions and, hence, a more efficient passage from (unstructured) textual information to (structured) machine-processable data.

Neural Information Processing
Neural Information Processing

Author: Mohammad Tanveer

Publisher: Springer Nature

Published: 2023-04-12

Total Pages: 660

ISBN-13: 3031301056

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The three-volume set LNCS 13623, 13624, and 13625 constitutes the refereed proceedings of the 29th International Conference on Neural Information Processing, ICONIP 2022, held as a virtual event, November 22–26, 2022. The 146 papers presented in the proceedings set were carefully reviewed and selected from 810 submissions. They were organized in topical sections as follows: Theory and Algorithms; Cognitive Neurosciences; Human Centered Computing; and Applications. The ICONIP conference aims to provide a leading international forum for researchers, scientists, and industry professionals who are working in neuroscience, neural networks, deep learning, and related fields to share their new ideas, progress, and achievements.

Multimodal Scene Understanding
Multimodal Scene Understanding

Author: Michael Ying Yang

Publisher: Academic Press

Published: 2019-07-16

Total Pages: 424

ISBN-13: 0128173599

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Multimodal Scene Understanding: Algorithms, Applications and Deep Learning presents recent advances in multi-modal computing, with a focus on computer vision and photogrammetry. It provides the latest algorithms and applications that involve combining multiple sources of information and describes the role and approaches of multi-sensory data and multi-modal deep learning. The book is ideal for researchers from the fields of computer vision, remote sensing, robotics, and photogrammetry, thus helping foster interdisciplinary interaction and collaboration between these realms. Researchers collecting and analyzing multi-sensory data collections – for example, KITTI benchmark (stereo+laser) - from different platforms, such as autonomous vehicles, surveillance cameras, UAVs, planes and satellites will find this book to be very useful. - Contains state-of-the-art developments on multi-modal computing - Shines a focus on algorithms and applications - Presents novel deep learning topics on multi-sensor fusion and multi-modal deep learning

Multimodality
Multimodality

Author: John Bateman

Publisher: Walter de Gruyter GmbH & Co KG

Published: 2017-04-10

Total Pages: 424

ISBN-13: 3110480042

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This textbook provides the first foundational introduction to the practice of analysing multimodality, covering the full breadth of media and situations in which multimodality needs to be a concern. Readers learn via use cases how to approach any multimodal situation and to derive their own specifically tailored sets of methods for conducting and evaluating analyses. Extensive references and critical discussion of existing approaches from many disciplines and in each of the multimodal domains addressed are provided. The authors adopt a problem-oriented perspective throughout, showing how an appropriate foundation for understanding multimodality as a phenomenon can be used to derive strong methodological guidance for analysis as well as supporting the adoption and combination of appropriate theoretical tools. Theoretical positions found in the literature are consequently always related back to the purposes of analysis rather than being promoted as valuable in their own right. By these means the book establishes the necessary theoretical foundations to engage productively with today’s increasingly complex combinations of multimodal artefacts and performances of all kinds.

Music Emotion Recognition
Music Emotion Recognition

Author: Yi-Hsuan Yang

Publisher: CRC Press

Published: 2011-02-22

Total Pages: 251

ISBN-13: 143985047X

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Providing a complete review of existing work in music emotion developed in psychology and engineering, Music Emotion Recognition explains how to account for the subjective nature of emotion perception in the development of automatic music emotion recognition (MER) systems. Among the first publications dedicated to automatic MER, it begins with

Opinion Mining and Sentiment Analysis
Opinion Mining and Sentiment Analysis

Author: Bo Pang

Publisher: Now Publishers Inc

Published: 2008

Total Pages: 149

ISBN-13: 1601981503

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This survey covers techniques and approaches that promise to directly enable opinion-oriented information-seeking systems.