Download or read book Acoustic Modeling for Emotion Recognition written by Koteswara Rao Anne and published by Springer. This book was released on 2015-03-14 with total page 72 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents state of art research in speech emotion recognition. Readers are first presented with basic research and applications – gradually more advance information is provided, giving readers comprehensive guidance for classify emotions through speech. Simulated databases are used and results extensively compared, with the features and the algorithms implemented using MATLAB. Various emotion recognition models like Linear Discriminant Analysis (LDA), Regularized Discriminant Analysis (RDA), Support Vector Machines (SVM) and K-Nearest neighbor (KNN) and are explored in detail using prosody and spectral features, and feature fusion techniques.
Download or read book Cognitive Analytics Concepts Methodologies Tools and Applications written by Management Association, Information Resources and published by IGI Global. This book was released on 2020-03-06 with total page 1961 pages. Available in PDF, EPUB and Kindle. Book excerpt: Due to the growing use of web applications and communication devices, the use of data has increased throughout various industries, including business and healthcare. It is necessary to develop specific software programs that can analyze and interpret large amounts of data quickly in order to ensure adequate usage and predictive results. Cognitive Analytics: Concepts, Methodologies, Tools, and Applications provides emerging perspectives on the theoretical and practical aspects of data analysis tools and techniques. It also examines the incorporation of pattern management as well as decision-making and prediction processes through the use of data management and analysis. Highlighting a range of topics such as natural language processing, big data, and pattern recognition, this multi-volume book is ideally designed for information technology professionals, software developers, data analysts, graduate-level students, researchers, computer engineers, software engineers, IT specialists, and academicians.
Download or read book Robust Feature Learning for Acoustic Emotion Recognition written by Rui Xia and published by . This book was released on 2015 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt: With increasing needs and developments of human-computer interaction systems, building robust systems to let computers understand humans' mood has become one of the essential components. Automatic emotion recognition/detection is necessary for machines to explore humans' emotional expressions. This dissertation focuses on learning robust features for building acoustic emotion recognition systems.We first investigate extracting features from frame-level based features. We adopt the ivector space modeling method to extract high-level features. Furthermore, based on i-vector space modeling, we develop the novel framework to generate multiple i-vector feature sets associated with emotion classes. The i-vector feature sets yield competitive performance with supra-segmental level based features, and the performance improves using a decision combination of the frame level based system and supra-segmental level based system. Second, based on supra-segmental level features, we apply deep learning techniques to extract high-level emotional feature representations. We propose a framework based on the neural network structure to project the original feature space into two different feature representations, and extract the one with more emotional cues as new features. In addition, we propose to model genders individually in the neural network structure in order to alleviate the gender variability to improve emotion recognition performance. Furthermore, we utilize multi-task learning by considering continuous dimensional information to improve categorical emotion recognition. Finally, we develop a novel framework using Deep Belief Network (DBN) in the paradigm of i-vector space modeling approach. This framework can combine the advantages of the two approaches. The DBN is discriminatively trained using reference labels automatically generated by the universal background model (UBM) and Gaussian Mixture Models (GMMs). The i-vector feature set obtained from this proposed method outperforms the traditional i-vector extracting framework. We believe a robust feature set is very important in emotion recognition systems. This dissertation will contribute to a general approach to learn a high-level rich emotional feature representation, which can advance the performance of current emotion recognition systems.
Download or read book Signal and Acoustic Modeling for Speech and Communication Disorders written by Hemant A. Patil and published by Walter de Gruyter GmbH & Co KG. This book was released on 2018-12-17 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: Signal and Acoustic Modeling for Speech and Communication Disorders demonstrates how speech signal processing and acoustic modeling can be instrumental in early detection and successful intervention with speech deficits resulting from Parkinson’s disease, Autism Spectrum disorder, cleft palate, intellectual disabilities, and neuro-motor impairments. Utilizing some of the most advanced methods in signal and acoustic modeling, this eminent group of contributors show how such technologies can inure to the benefit of healthcare and to society writ large. Paradoxically, what most of us take for granted still remains a Sisyphean battle for those with speech and language disorders, who struggle every day to make themselves heard and understood. The purpose of this book is to stimulate a vibrant discussion among speech scientists, system designers, and practitioners on how to best marshal the latest advances in signal and acoustic modeling to address some of the most challenging speech and communication disorders affecting a wide variety of patient populations across the world.
Download or read book Music Emotion Recognition written by Yi-Hsuan Yang and published by CRC Press. This book was released on 2011-02-22 with total page 251 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book Investigation of Acoustic Models for Emotion Recognition Using a Spontaneous Speech Corpus written by Tetsuo Kosaka and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Speech and Computer written by Alexey Karpov and published by Springer. This book was released on 2018-09-10 with total page 791 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 20th International Conference on Speech and Computer, SPECOM 2018, held in Leipzig, Germany, in September 2018. The 79 papers presented in this volume were carefully reviewed and selected from 132 submissions. The papers present current research in the area of computer speech processing, including recognition, synthesis, understanding and related domains like signal processing, language and text processing, computational paralinguistics, multi-modal speech processing or human-computer interaction.
Download or read book Springer Handbook of Speech Processing written by Jacob Benesty and published by Springer Science & Business Media. This book was released on 2007-11-28 with total page 1170 pages. Available in PDF, EPUB and Kindle. Book excerpt: This handbook plays a fundamental role in sustainable progress in speech research and development. With an accessible format and with accompanying DVD-Rom, it targets three categories of readers: graduate students, professors and active researchers in academia, and engineers in industry who need to understand or implement some specific algorithms for their speech-related products. It is a superb source of application-oriented, authoritative and comprehensive information about these technologies, this work combines the established knowledge derived from research in such fast evolving disciplines as Signal Processing and Communications, Acoustics, Computer Science and Linguistics.
Download or read book Towards Adaptive Spoken Dialog Systems written by Alexander Schmitt and published by Springer Science & Business Media. This book was released on 2012-09-19 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: In Monitoring Adaptive Spoken Dialog Systems, authors Alexander Schmitt and Wolfgang Minker investigate statistical approaches that allow for recognition of negative dialog patterns in Spoken Dialog Systems (SDS). The presented stochastic methods allow a flexible, portable and accurate use. Beginning with the foundations of machine learning and pattern recognition, this monograph examines how frequently users show negative emotions in spoken dialog systems and develop novel approaches to speech-based emotion recognition using hybrid approach to model emotions. The authors make use of statistical methods based on acoustic, linguistic and contextual features to examine the relationship between the interaction flow and the occurrence of emotions using non-acted recordings several thousand real users from commercial and non-commercial SDS. Additionally, the authors present novel statistical methods that spot problems within a dialog based on interaction patterns. The approaches enable future SDS to offer more natural and robust interactions. This work provides insights, lessons and inspiration for future research and development, not only for spoken dialog systems, but for data-driven approaches to human-machine interaction in general.
Download or read book Modeling and Predicting Affect in Audio Signals written by Pauline Mouawad and published by . This book was released on 2017 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The present thesis describes a multidisciplinary research project on emotion recognition in sounds, covering psychological theories, acoustic-based signal analysis, machine learning and chaotic dynamics.In our social interactions and relationships, we rely greatly on the communication of information and on our perception of the messages transmitted. In fact communication happens when signals transmit information between a source and a destination. The signal can be verbal,and the information is then carried by sound patterns, such as words. In non verbal vocal communication however, information can be perceptual patterns that convey affective cues,that we sense and appraise in the form of intentions, attitudes, moods and emotions.The prevalence of the affective component can be seen in human computer interactions(HCI) where the development of automated applications that understand and express emotions has become crucial. Such systems need to be meaningful and friendly to the end user, so thatour interaction with them becomes a positive experience. Although the automatic recognition of emotions in sounds has received increased attention in recent years, it is still a young fieldof research. Not only does it contribute to Affective Computing in general, but it also provides insight into the significance of sounds in our daily life.In this thesis the problem of affect recognition is addressed from a dual perspective: we start by taking a standard approach of acoustic-based signal analysis, where we survey and experiment with existing features to determine their role in emotion communication. Then,we turn to chaotic dynamics and time series symbolization, to understand the role of the inherent dynamics of sounds in affective expressiveness. We conduct our studies in the context of nonverbal sounds, namely voice, music and environmental sounds.From a human listening point of view, an annotation task is conducted to build a ground truth of nonverbal singing voices, labelled with categorical descriptions of the two-dimensional model of affect. Two types of sounds are included in the study: vocal and glottal.From a psychological perspective, the present research addresses a debate that is of long standing among scientists and psychologists, concerning the common origins of music and voice.The question is addressed from an acoustic-based analysis as well as a nonlinear dynamics approach.From a modeling viewpoint, this work proposes a novel nonlinear dynamics approach for the recognition of affect in sound, based on chaotic dynamics and adaptive time series symbolization.Throughout this thesis, key contrasts in the expressiveness of affect are illustrated among the different types of sounds, through the analysis of acoustic properties, nonlinear dynamics metrics and predictions performances. Finally from a progressive perspective, we suggest that future works investigate features that are motivated by cognitive studies. We also suggest to examine to what extent our features reflect cognitive processes. Additionally we recommend that our dynamic features be tested inlarge scale ER studies through the participation in ER challenges, with an aim to verify if they gain consensus.
Download or read book Affective Computing and Intelligent Interaction written by Ana Paiva and published by Springer. This book was released on 2007-09-04 with total page 796 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Second International Conference on Affective Computing and Intelligent Interaction, ACII 2007. It covers affective facial expression and recognition, affective body expression and recognition, affective speech processing, affective text and dialogue processing, recognizing affect using physiological measures, computational models of emotion and theoretical foundations, and affective sound and music processing.
Download or read book Computational Paralinguistics written by Björn Schuller and published by John Wiley & Sons. This book was released on 2013-09-17 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Toward Robotic Socially Believable Behaving Systems Volume I written by Anna Esposito and published by Springer. This book was released on 2016-03-21 with total page 251 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume is a collection of research studies on the modeling of emotions in complex autonomous systems. Several experts in the field are reporting their efforts and reviewing the literature in order to shed lights on how the processes of coding and decoding emotional states took place in humans, which are the physiological, physical, and psychological variables involved, invent new mathematical models and algorithms to describe them, and motivate these investigations in the light of observable societal changes and needs, such as the aging population and the cost of health care services. The consequences are the implementation of emotionally and socially believable machines, acting as helpers into domestic spheres, where emotions drive behaviors and actions. The contents of the book are highly multidisciplinary since the modeling of emotions in robotic socially believable systems requires a holistic perspective on topics coming from different research domains such as computer science, engineering, sociology, psychology, linguistic, and information communication. The book is of interest both to experts and students since last research works on a so complex multidisciplinary topic are described in a neat and didactical scientific language.
Download or read book Emotion Recognition written by Amit Konar and published by John Wiley & Sons. This book was released on 2015-01-27 with total page 580 pages. Available in PDF, EPUB and Kindle. Book excerpt: A timely book containing foundations and current research directions on emotion recognition by facial expression, voice, gesture and biopotential signals This book provides a comprehensive examination of the research methodology of different modalities of emotion recognition. Key topics of discussion include facial expression, voice and biopotential signal-based emotion recognition. Special emphasis is given to feature selection, feature reduction, classifier design and multi-modal fusion to improve performance of emotion-classifiers. Written by several experts, the book includes several tools and techniques, including dynamic Bayesian networks, neural nets, hidden Markov model, rough sets, type-2 fuzzy sets, support vector machines and their applications in emotion recognition by different modalities. The book ends with a discussion on emotion recognition in automotive fields to determine stress and anger of the drivers, responsible for degradation of their performance and driving-ability. There is an increasing demand of emotion recognition in diverse fields, including psycho-therapy, bio-medicine and security in government, public and private agencies. The importance of emotion recognition has been given priority by industries including Hewlett Packard in the design and development of the next generation human-computer interface (HCI) systems. Emotion Recognition: A Pattern Analysis Approach would be of great interest to researchers, graduate students and practitioners, as the book Offers both foundations and advances on emotion recognition in a single volume Provides a thorough and insightful introduction to the subject by utilizing computational tools of diverse domains Inspires young researchers to prepare themselves for their own research Demonstrates direction of future research through new technologies, such as Microsoft Kinect, EEG systems etc.
Download or read book Speech Recognition written by France Mihelič and published by BoD – Books on Demand. This book was released on 2008-11-01 with total page 580 pages. Available in PDF, EPUB and Kindle. Book excerpt: Chapters in the first part of the book cover all the essential speech processing techniques for building robust, automatic speech recognition systems: the representation for speech signals and the methods for speech-features extraction, acoustic and language modeling, efficient algorithms for searching the hypothesis space, and multimodal approaches to speech recognition. The last part of the book is devoted to other speech processing applications that can use the information from automatic speech recognition for speaker identification and tracking, for prosody modeling in emotion-detection systems and in other speech processing applications that are able to operate in real-world environments, like mobile communication services and smart homes.
Download or read book Exploring the Benefits of Discretization of Acoustic Features for Speech Emotion Recognition written by Thurid Vogt and published by . This book was released on 2009 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Handbook of Pattern Recognition and Computer Vision written by C. H. Chen and published by World Scientific. This book was released on 1999 with total page 1045 pages. Available in PDF, EPUB and Kindle. Book excerpt: The very significant advances in computer vision and pattern recognition and their applications in the last few years reflect the strong and growing interest in the field as well as the many opportunities and challenges it offers. The second edition of this handbook represents both the latest progress and updated knowledge in this dynamic field. The applications and technological issues are particularly emphasized in this edition to reflect the wide applicability of the field in many practical problems. To keep the book in a single volume, it is not possible to retain all chapters of the first edition. However, the chapters of both editions are well written for permanent reference.
