This book gives an overview of the research and application of speech technologies in different areas. One of the special characteristics of the book is that the authors take a broad view of the multiple research areas and take the multidisciplinary approach to the topics. One of the goals in this book is to emphasize the application. User experience, human factors and usability issues are the focus in this book.

Tanja Schultz and Katrin Kirchhoff have compiled a comprehensive overview of speech processing from a multilingual perspective. By taking this all-inclusive approach to speech processing, the editors have included theories, algorithms, and techniques that are required to support spoken input and output in a large variety of languages. Multilingual Speech Processing presents a comprehensive introduction to research problems and solutions, both from a theoretical as well as a practical perspective, and highlights technology that incorporates the increasing necessity for multilingual applications in our global community. Current challenges of speech processing and the feasibility of sharing data and system components across different languages guide contributors in their discussions of trends, prognoses and open research issues. This includes automatic speech recognition and speech synthesis, but also speech-to-speech translation, dialog systems, automatic language identification, and handling non-native speech. The book is complemented by an overview of multilingual resources, important research trends, and actual speech processing systems that are being deployed in multilingual human-human and human-machine interfaces. Researchers and developers in industry and academia with different backgrounds but a common interest in multilingual speech processing will find an excellent overview of research problems and solutions detailed from theoretical and practical perspectives. - State-of-the-art research with a global perspective by authors from the USA, Asia, Europe, and South Africa - The only comprehensive introduction to multilingual speech processing currently available - Detailed presentation of technological advances integral to security, financial, cellular and commercial applications

The 2nd International Conference on Artificial Intelligence and Speech Technology (AIST2020) was organized by Indira Gandhi Delhi Technical University for Women, Delhi, India on November 19–20, 2020. AIST2020 is dedicated to cutting-edge research that addresses the scientific needs of academic researchers and industrial professionals to explore new horizons of knowledge related to Artificial Intelligence and Speech Technologies. AIST2020 includes high-quality paper presentation sessions revealing the latest research findings, and engaging participant discussions. The main focus is on novel contributions which would open new opportunities for providing better and low-cost solutions for the betterment of society. These include the use of new AI-based approaches like Deep Learning, CNN, RNN, GAN, and others in various Speech related issues like speech synthesis, speech recognition, etc.

In this text, the editors aim to convert the mapping of speech patterns into mental representations. They cover theories of perception and cognition, issues in clinical speech pathology, and the practical concerns of speech technology.

This book deals with two important technologies in human-computer interaction: computer generation of synthetic speech and computer recognition of human speech. It addresses the problems in generating speech with varying precision of articulation and how to convey moods and attitudes.

This book provides a comprehensive overview of the recent advancement in the field of automatic speech recognition with a focus on deep learning models including deep neural networks and many of their variants. This is the first automatic speech recognition book dedicated to the deep learning approach. In addition to the rigorous mathematical treatment of the subject, the book also presents insights and theoretical foundation of a series of highly successful deep learning models.

Deals with the two important technologies in human-computer interaction, computer generation of synthetic speech and computer recognition of human speech. The book focuses on three main areas - recognition, production and dialogue.

Bridging the gap between the needs of the technical engineer and cognitive researchers related to speech technology applications. Systematic approach focusing on the utility of speech related product design Designed to respond to the growing need for specific theories, tools and methods for design, testing and evaluating speech related human-system interfaces. Targeted at designers, engineers, and decision makers working in the area of speech technology research

Mathematical Models of Spoken Language presents the motivations for, intuitions behind, and basic mathematical models of natural spoken language communication. A comprehensive overview is given of all aspects of the problem from the physics of speech production through the hierarchy of linguistic structure and ending with some observations on language and mind. The author comprehensively explores the argument that these modern technologies are actually the most extensive compilations of linguistic knowledge available.Throughout the book, the emphasis is on placing all the material in a mathematically coherent and computationally tractable framework that captures linguistic structure. It presents material that appears nowhere else and gives a unification of formalisms and perspectives used by linguists and engineers. Its unique features include a coherent nomenclature that emphasizes the deep connections amongst the diverse mathematical models and explores the methods by means of which they capture linguistic structure. This contrasts with some of the superficial similarities described in the existing literature; the historical background and origins of the theories and models; the connections to related disciplines, e.g. artificial intelligence, automata theory and information theory; an elucidation of the current debates and their intellectual origins; many important little-known results and some original proofs of fundamental results, e.g. a geometric interpretation of parameter estimation techniques for stochastic models and finally the author's own unique perspectives on the future of this discipline. There is a vast literature on Speech Recognition and Synthesis however, this book is unlike any other in the field. Although it appears to be a rapidly advancing field, the fundamentals have not changed in decades. Most of the results are presented in journals from which it is difficult to integrate and evaluate all of these recent ideas. Some of the fundamentals have been collected into textbooks, which give detailed descriptions of the techniques but no motivation or perspective. The linguistic texts are mostly descriptive and pictorial, lacking the mathematical and computational aspects. This book strikes a useful balance by covering a wide range of ideas in a common framework. It provides all the basic algorithms and computational techniques and an analysis and perspective, which allows one to intelligently read the latest literature and understand state-of-the-art techniques as they evolve.