The book explores new ways to reconstruct and enhance speech that is compromised by various neuro-motor disorders – collectively known as “dysarthria.” The authors address some of the extant lacunae in speech research of dysarthric conditions: they show how new methods can improve speaker recognition when speech is impaired due to developmental or acquired pathologies; they present a novel multi-dimensional approach to help the speech system both assess dysarthric speech and to perform intelligibility improvement of the impaired speech; they display well-performing software solutions for developmental and acquired speech impairments, and for vocal injuries; and they examine non-acoustic signals and muted nonverbal sounds in relation to audible speech conversion.
The book explores new ways to reconstruct and enhance speech that is compromised by various neuro-motor disorders – collectively known as “dysarthria.” The authors address some of the extant lacunae in speech research of dysarthric conditions: they show how new methods can improve speaker recognition when speech is impaired due to developmental or acquired pathologies; they present a novel multi-dimensional approach to help the speech system both assess dysarthric speech and to perform intelligibility improvement of the impaired speech; they display well-performing software solutions for developmental and acquired speech impairments, and for vocal injuries; and they examine non-acoustic signals and muted nonverbal sounds in relation to audible speech conversion.
Natural Language Processing (NLP) is a sub-field of Artificial Intelligence, linguistics, and computer science and is concerned with the generation, recognition, and understanding of human languages, both written and spoken. NLP systems examine the grammatical structure of sentences as well as the specific meanings of words, and then they utilize algorithms to extract meaning and produce results. Machine Learning and Deep Learning in Natural Language Processing aims at providing a review of current Neural Network techniques in the NLP field, in particular about Conversational Agents (chatbots), Text-to-Speech, management of non-literal content – like emotions, but also satirical expressions – and applications in the healthcare field. NLP has the potential to be a disruptive technology in various healthcare fields, but so far little attention has been devoted to that goal. This book aims at providing some examples of NLP techniques that can, for example, restore speech, detect Parkinson’s disease, or help psychotherapists. This book is intended for a wide audience. Beginners will find useful chapters providing a general introduction to NLP techniques, while experienced professionals will appreciate the chapters about advanced management of emotion, empathy, and non-literal content.
In recent years, scientific research and translation medicine have placed increased emphasis on computational methodology and data curation across many disciplines, both to advance underlying science and to instantiate precision-medicine protocols in the lab and in clinical practice. The nexus of concerns related to oncology, cardiology, and virology (SARS-CoV-2) presents a fortuitous context within which to examine the theory and practice of biomedical data curation. Innovative Data Integration and Conceptual Space Modeling for COVID, Cancer, and Cardiac Care argues that a well-rounded approach to data modeling should optimally embrace multiple perspectives inasmuch as data-modeling is neither a purely formal nor a purely conceptual discipline, but rather a hybrid of both. On the one hand, data models are designed for use by computer software components, and are, consequently, constrained by the mechanistic demands of software environments; data modeling strategies must accept the formal rigors imposed by unambiguous data-sharing and query-evaluation logic. In particular, data models are not well-suited for software-level deployment if such models do not translate seamlessly to clear strategies for querying data and ensuring data integrity as information is moved across multiple points. On the other hand, data modeling is, likewise, constrained by human conceptual tendencies, because the information which is managed by databases and data networks is ultimately intended to be visualized/utilized by humans as the end-user. Thus, at the intersection of both formal and humanistic methodology, data modeling takes on elements of both logico-mathematical frameworks (e.g., type systems and graph theory) and conceptual/philosophical paradigms (e.g., linguistics and cognitive science). The authors embrace this two-sided aspect of data models by seeking non-reductionistic points of convergence between formal and humanistic/conceptual viewpoints, and by leveraging biomedical contexts (viz., COVID, Cancer, and Cardiac Care) so as to provide motivating examples and case-studies in this volume. - Provides an analysis of how conceptual spaces and related cognitive linguistic approaches can inspire programming and query-processing models - Outlines the vital role that data modeling/curation has played in significant medical breakthroughs - Presents readers with an overview of how information-management approaches intersect with precision medicine, providing case studies of data-modeling in concrete scientific practice - Explores applications of image analysis and computer vision in the context of precision medicine - Examines the role of technology in scientific publishing, replication studies, and dataset curation
Advances in Ubiquitous Computing: Cyber-Physical Systems, Smart Cities and Ecological Monitoring debuts some of the newest methods and approaches to multimodal user-interface design, safety compliance, formal code verification and deployment requirements, as they pertain to cyber-physical systems, smart homes and smart cities, and biodiversity monitoring. In this anthology, the authors assiduously examine a panoply of topics related to wireless sensor networks. These topics include interacting with smart-home appliances and biomedical devices, designing multilingual speech recognition systems that are robust to vehicular, mechanical and other noises common to large metropolises, and an examination of new methods of speaker recognition to control for the emotion-state of the speaker, which can easily impede speaker verification over a wireless medium. This volume recognizes that any discussion of pervasive computing in smart cities must not end there, as the perilous effects of climate change proves that our lives are not circumscribed by the geographically sculpted boundaries of cities, counties, countries, or continents. Contributors address present and emerging technologies of scalable biodiversity monitoring: pest control, disease transmission, environmental monitoring, and habitat preservation. The need to collect, store, process, and interpret vast amounts of data originating from sources spread over large areas and for prolonged periods of time requires immediate data storage and processing, reliable networking, and solid communication infrastructure, along with intelligent data analysis and interpretation methods that can resolve contradictions and uncertainty in the data—all of which can be bolstered by modern advances in ubiquitous computing. - Examines the history, scope and advances in ubiquitous computing, including threats to wildlife, tracking of disease, smart cities and Wireless Sensor Networks - Discusses user interface design, implementation and deployment of cyber-physical systems, such as wireless sensor networks, Internet of Things devices, and other networks of physical devices that have computational capabilities and reporting devices - Covers the need for improved data sharing networks
This book provides the reader with empirical findings on innovative signal processing approaches to detecting pathologies in infant cries, by comparing new technological approaches to standard ones. The contributors examine novel approaches to machine adaptation to dysarthric speech.
"This book provides a comprehensive approach of signal processing tools regarding the enhancement, recognition, and protection of speech and audio signals. It offers researchers and practitioners the information they need to develop and implement efficient signal processing algorithms in the enhancement field"--Provided by publisher.
Computational Intelligence techniques have been widely explored in various domains including forensics. Analysis in forensic encompasses the study of pattern analysis that answer the question of interest in security, medical, legal, genetic studies and etc. However, forensic analysis is usually performed through experiments in lab which is expensive both in cost and time. Therefore, this book seeks to explore the progress and advancement of computational intelligence technique in different focus areas of forensic studies. This aims to build stronger connection between computer scientists and forensic field experts. This book, Computational Intelligence in Digital Forensics: Forensic Investigation and Applications, is the first volume in the Intelligent Systems Reference Library series. The book presents original research results and innovative applications of computational intelligence in digital forensics. This edited volume contains seventeen chapters and presents the latest state-of-the-art advancement of Computational Intelligence in Digital Forensics; in both theoretical and application papers related to novel discovery in intelligent forensics. The chapters are further organized into three sections: (1) Introduction, (2) Forensic Discovery and Investigation, which discusses the computational intelligence technologies employed in Digital Forensic, and (3) Intelligent Forensic Science Applications, which encompasses the applications of computational intelligence in Digital Forensic, such as human anthropology, human biometrics, human by products, drugs, and electronic devices.
With the proliferation of mobile devices and hearing devices, including hearing aids and cochlear implants, there is a growing and pressing need to design algorithms that can improve speech intelligibility without sacrificing quality. Responding to this need, Speech Enhancement: Theory and Practice, Second Edition introduces readers to the basic pr
This book aims to bring together Researchers, Scientists, Engineers, Scholars and Students in the areas of computer engineering and information technology, and provides a forum for the dissemination of original research results, new ideas, Research and development, practical experiments, which concentrate on both theory and practices, for the benefit of the society. The book also provides a premier interdisciplinary platform for researchers, practitioners and educators to present and discuss the most recent innovations, trends, and concerns as well as practical challenges encountered and solutions adopted in the fields of Computer Science and Information Technology in the context of Distributed computing, Big data, High performance computing, Internet-of-Things, and digital pedagogy. It is becoming increasingly important to develop adaptive, intelligent computing-centric, energy-aware, secure and privacy-aware mechanisms in high performance computing and IoT applications. This book aspires to convey researchers’ experiences, to present excellent result analysis, future scopes, and challenges facing the field of computer science, information technology, telecommunication, and digital pedagogy. This book aims to attract researchers and practitioners who are working in Information Technology and Computer Science. This book is about basics and high level concepts regarding intelligent computing paradigm, communications, and digital learning process. The book serves as a useful guide for Undergraduates, Postgraduates and Research Scholar in the field of Computer Science, Information Technology, and Electronics Engineering. We believe that this volume not only presents novel and interesting ideas but also will stimulate interesting discussions from the participants and inspire new ideas.
