Speech technology - the use of speech as a means of sending information to, and receiving information from computer systems has been in use as a research tool for many years. Only recently has it begun to move out of the laboratory and into commercially worthwhile applications, first with compressed and synthesised spoken messages, then with computer recognition of spoken messages, and today with diverse applications involving both recognition and reproduction of human speech. We have written this book because we believe the technology has now advanced to the point where many more applications of voice recognition and response are both feasible and economically attractive. Computers that can understand everyday speech are still a distant prospect, but provided the limitations of present day equipment are clearly understood there is much that can be achieved with it. Our aim is to show, in non-technical language, what is now possible with the help of speech technology. The text includes many examples of current applications in industry, commerce and other fields, and we have selected five current industrial applications combining speech recognition and response for more detailed attention. Industrial cases have been chosen both because we see industry as an important growth area for speech applications in the next few years, and because it presents some of the greatest difficulties in speech recognition - if you can make it work in industry, then you can make it work almost anywhere.

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.

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.

Automatic speech recognition (ASR) systems are finding increasing use in everyday life. Many of the commonplace environments where the systems are used are noisy, for example users calling up a voice search system from a busy cafeteria or a street. This can result in degraded speech recordings and adversely affect the performance of speech recognition systems. As the use of ASR systems increases, knowledge of the state-of-the-art in techniques to deal with such problems becomes critical to system and application engineers and researchers who work with or on ASR technologies. This book presents a comprehensive survey of the state-of-the-art in techniques used to improve the robustness of speech recognition systems to these degrading external influences. Key features: Reviews all the main noise robust ASR approaches, including signal separation, voice activity detection, robust feature extraction, model compensation and adaptation, missing data techniques and recognition of reverberant speech. Acts as a timely exposition of the topic in light of more widespread use in the future of ASR technology in challenging environments. Addresses robustness issues and signal degradation which are both key requirements for practitioners of ASR. Includes contributions from top ASR researchers from leading research units in the field

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.

Explains how voice recognition technology works, how it has evolved over time, and what the technology is used for today.