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Automatic speech recognition (ASR) is a very attractive means for human-machine interaction. The degree of maturity reached by speech recognition technologies during recent years allows the development of applications that use them. In particular, ASR shows an enormous potential in mobile environments, where devices such as mobile phones or PDAs are used, and for Internet Protocol (IP) applications. Speech Recognition Over Digital Channels is the first book of its kind to offer a complete system comprehension, addressing the topics of distributed and network-based speech recognition issues and standards, the concepts of speech processing and transmission, and system architectures and robustness. Describes the different client/server architectures for remote speech recognition systems, by means of which the client transmits speech parameters through a digital channel to a remote recognition server Focuses on robustness against both adverse acoustic environments (in the front-end) and bit errors/packet loss Discusses four ETSI standards for distributed speech recognition; the understanding of the standards and the technologies behind them Provides the necessary background for the comprehension of remote speech recognition technologies This book will appeal to a wide-ranging audience: engineers using speech recognition systems, researchers involved in ASR systems and those interested in processing and transmitting speech such as signal processing and communications communities. It will also be of interest to technical experts requiring an understanding of recognition over mobile and IP networks, and postgraduate students working on robust speech processing.
The advances in computing and networking have sparked an enormous interest in deploying automatic speech recognition on mobile devices and over communication networks. This book brings together academic researchers and industrial practitioners to address the issues in this emerging realm and presents the reader with a comprehensive introduction to the subject of speech recognition in devices and networks. It covers network, distributed and embedded speech recognition systems.
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
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.
This book focuses on speech processing in the presence of low-bit rate coding and varying background environments. The methods presented in the book exploit the speech events which are robust in noisy environments. Accurate estimation of these crucial events will be useful for carrying out various speech tasks such as speech recognition, speaker recognition and speech rate modification in mobile environments. The authors provide insights into designing and developing robust methods to process the speech in mobile environments. Covering temporal and spectral enhancement methods to minimize the effect of noise and examining methods and models on speech and speaker recognition applications in mobile environments.
Automatic speech recognition suffers from a lack of robustness with respect to noise, reverberation and interfering speech. The growing field of speech recognition in the presence of missing or uncertain input data seeks to ameliorate those problems by using not only a preprocessed speech signal but also an estimate of its reliability to selectively focus on those segments and features that are most reliable for recognition. This book presents the state of the art in recognition in the presence of uncertainty, offering examples that utilize uncertainty information for noise robustness, reverberation robustness, simultaneous recognition of multiple speech signals, and audiovisual speech recognition. The book is appropriate for scientists and researchers in the field of speech recognition who will find an overview of the state of the art in robust speech recognition, professionals working in speech recognition who will find strategies for improving recognition results in various conditions of mismatch, and lecturers of advanced courses on speech processing or speech recognition who will find a reference and a comprehensive introduction to the field. The book assumes an understanding of the fundamentals of speech recognition using Hidden Markov Models.
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.
This book addresses different aspects of the research field and a wide range of topics in speech signal processing, speech recognition and language processing. The chapters are divided in three different sections: Speech Signal Modeling, Speech Recognition and Applications. The chapters in the first section cover some essential topics in speech signal processing used for building speech recognition as well as for speech synthesis systems: speech feature enhancement, speech feature vector dimensionality reduction, segmentation of speech frames into phonetic segments. The chapters of the second part cover speech recognition methods and techniques used to read speech from various speech databases and broadcast news recognition for English and non-English languages. The third section of the book presents various speech technology applications used for body conducted speech recognition, hearing impairment, multimodal interfaces and facial expression recognition.
Speech processing and speech transmission technology are expanding fields of active research. New challenges arise from the 'anywhere, anytime' paradigm of mobile communications, the ubiquitous use of voice communication systems in noisy environments and the convergence of communication networks toward Internet based transmission protocols, such as Voice over IP. As a consequence, new speech coding, new enhancement and error concealment, and new quality assessment methods are emerging. Advances in Digital Speech Transmission provides an up-to-date overview of the field, including topics such as speech coding in heterogeneous communication networks, wideband coding, and the quality assessment of wideband speech. Provides an insight into the latest developments in speech processing and speech transmission, making it an essential reference to those working in these fields Offers a balanced overview of technology and applications Discusses topics such as speech coding in heterogeneous communications networks, wideband coding, and the quality assessment of the wideband speech Explains speech signal processing in hearing instruments and man-machine interfaces from applications point of view Covers speech coding for Voice over IP, blind source separation, digital hearing aids and speech processing for automatic speech recognition Advances in Digital Speech Transmission serves as an essential link between the basics and the type of technology and applications (prospective) engineers work on in industry labs and academia. The book will also be of interest to advanced students, researchers, and other professionals who need to brush up their knowledge in this field.
The portable device and mobile phone market has witnessed rapid growth in the last few years with the emergence of several revolutionary products such as mobile TV, converging iPhone and digital cameras that combine music, phone and video functionalities into one device. The proliferation of this market has further bene?ted from the competition in software and applications for smart phones such as Google’s Android operating system and Apple’s iPhone App- Store, stimulating tens of thousands of mobile applications that are made ava- able by individual and enterprise developers. Whereas the mobile device has become ubiquitous in people’s daily life not only as a cellular phone but also as a media player, a mobile computing device, and a personal assistant, it is p- ticularly important to address challenges timely in applying advanced pattern recognition, signal, information and multimedia processing techniques, and new emerging networking technologies to such mobile systems. The primary objective of this book is to foster interdisciplinary discussions and research in mobile multimedia processing techniques, applications and s- tems, as well as to provide stimulus to researchers on pushing the frontier of emerging new technologies and applications. One attempt on such discussions was the organization of the First Int- national Workshop of Mobile Multimedia Processing (WMMP 2008), held in Tampa, Florida, USA, on December 7, 2008. About 30 papers were submitted from10countriesacrosstheUSA,Asia andEurope.