Acoustical and Environmental Robustness in Automatic Speech Recognition PDF Download
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Author: A. Acero
Publisher: Springer Science & Business Media
ISBN: 1461531225
Category : Technology & Engineering
Languages : en
Pages : 197
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Book Description
The need for automatic speech recognition systems to be robust with respect to changes in their acoustical environment has become more widely appreciated in recent years, as more systems are finding their way into practical applications. Although the issue of environmental robustness has received only a small fraction of the attention devoted to speaker independence, even speech recognition systems that are designed to be speaker independent frequently perform very poorly when they are tested using a different type of microphone or acoustical environment from the one with which they were trained. The use of microphones other than a "close talking" headset also tends to severely degrade speech recognition -performance. Even in relatively quiet office environments, speech is degraded by additive noise from fans, slamming doors, and other conversations, as well as by the effects of unknown linear filtering arising reverberation from surface reflections in a room, or spectral shaping by microphones or the vocal tracts of individual speakers. Speech-recognition systems designed for long-distance telephone lines, or applications deployed in more adverse acoustical environments such as motor vehicles, factory floors, oroutdoors demand far greaterdegrees ofenvironmental robustness. There are several different ways of building acoustical robustness into speech recognition systems. Arrays of microphones can be used to develop a directionally-sensitive system that resists intelference from competing talkers and other noise sources that are spatially separated from the source of the desired speech signal.
Author: A. Acero
Publisher: Springer Science & Business Media
ISBN: 1461531225
Category : Technology & Engineering
Languages : en
Pages : 197
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Book Description
The need for automatic speech recognition systems to be robust with respect to changes in their acoustical environment has become more widely appreciated in recent years, as more systems are finding their way into practical applications. Although the issue of environmental robustness has received only a small fraction of the attention devoted to speaker independence, even speech recognition systems that are designed to be speaker independent frequently perform very poorly when they are tested using a different type of microphone or acoustical environment from the one with which they were trained. The use of microphones other than a "close talking" headset also tends to severely degrade speech recognition -performance. Even in relatively quiet office environments, speech is degraded by additive noise from fans, slamming doors, and other conversations, as well as by the effects of unknown linear filtering arising reverberation from surface reflections in a room, or spectral shaping by microphones or the vocal tracts of individual speakers. Speech-recognition systems designed for long-distance telephone lines, or applications deployed in more adverse acoustical environments such as motor vehicles, factory floors, oroutdoors demand far greaterdegrees ofenvironmental robustness. There are several different ways of building acoustical robustness into speech recognition systems. Arrays of microphones can be used to develop a directionally-sensitive system that resists intelference from competing talkers and other noise sources that are spatially separated from the source of the desired speech signal.
Author: Jinyu Li
Publisher: Academic Press
ISBN: 0128026162
Category : Technology & Engineering
Languages : en
Pages : 306
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Book Description
Robust Automatic Speech Recognition: A Bridge to Practical Applications establishes a solid foundation for automatic speech recognition that is robust against acoustic environmental distortion. It provides a thorough overview of classical and modern noise-and reverberation robust techniques that have been developed over the past thirty years, with an emphasis on practical methods that have been proven to be successful and which are likely to be further developed for future applications. The strengths and weaknesses of robustness-enhancing speech recognition techniques are carefully analyzed. The book covers noise-robust techniques designed for acoustic models which are based on both Gaussian mixture models and deep neural networks. In addition, a guide to selecting the best methods for practical applications is provided. The reader will: Gain a unified, deep and systematic understanding of the state-of-the-art technologies for robust speech recognition Learn the links and relationship between alternative technologies for robust speech recognition Be able to use the technology analysis and categorization detailed in the book to guide future technology development Be able to develop new noise-robust methods in the current era of deep learning for acoustic modeling in speech recognition The first book that provides a comprehensive review on noise and reverberation robust speech recognition methods in the era of deep neural networks Connects robust speech recognition techniques to machine learning paradigms with rigorous mathematical treatment Provides elegant and structural ways to categorize and analyze noise-robust speech recognition techniques Written by leading researchers who have been actively working on the subject matter in both industrial and academic organizations for many years
Author: Jean-Claude Junqua
Publisher: Springer Science & Business Media
ISBN: 1461312973
Category : Technology & Engineering
Languages : en
Pages : 457
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Book Description
Foreword Looking back the past 30 years. we have seen steady progress made in the area of speech science and technology. I still remember the excitement in the late seventies when Texas Instruments came up with a toy named "Speak-and-Spell" which was based on a VLSI chip containing the state-of-the-art linear prediction synthesizer. This caused a speech technology fever among the electronics industry. Particularly. applications of automatic speech recognition were rigorously attempt ed by many companies. some of which were start-ups founded just for this purpose. Unfortunately. it did not take long before they realized that automatic speech rec ognition technology was not mature enough to satisfy the need of customers. The fever gradually faded away. In the meantime. constant efforts have been made by many researchers and engi neers to improve the automatic speech recognition technology. Hardware capabilities have advanced impressively since that time. In the past few years. we have been witnessing and experiencing the advent of the "Information Revolution." What might be called the second surge of interest to com mercialize speech technology as a natural interface for man-machine communication began in much better shape than the first one. With computers much more powerful and faster. many applications look realistic this time. However. there are still tremendous practical issues to be overcome in order for speech to be truly the most natural interface between humans and machines.
Author: Tuomas Virtanen
Publisher: John Wiley & Sons
ISBN: 1119970881
Category : Technology & Engineering
Languages : en
Pages : 514
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Book Description
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
Author: Shinji Watanabe
Publisher: Springer
ISBN: 331964680X
Category : Computers
Languages : en
Pages : 436
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Book Description
This book covers the state-of-the-art in deep neural-network-based methods for noise robustness in distant speech recognition applications. It provides insights and detailed descriptions of some of the new concepts and key technologies in the field, including novel architectures for speech enhancement, microphone arrays, robust features, acoustic model adaptation, training data augmentation, and training criteria. The contributed chapters also include descriptions of real-world applications, benchmark tools and datasets widely used in the field. This book is intended for researchers and practitioners working in the field of speech processing and recognition who are interested in the latest deep learning techniques for noise robustness. It will also be of interest to graduate students in electrical engineering or computer science, who will find it a useful guide to this field of research.
Author: Antonio Peinado
Publisher: John Wiley & Sons
ISBN: 0470024011
Category : Technology & Engineering
Languages : en
Pages : 274
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Book Description
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.
Author: Jean-Claude Junqua
Publisher: Springer Science & Business Media
ISBN: 9401597197
Category : Language Arts & Disciplines
Languages : en
Pages : 277
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Book Description
In this book we address robustness issues at the speech recognition and natural language parsing levels, with a focus on feature extraction and noise robust recognition, adaptive systems, language modeling, parsing, and natural language understanding. This book attempts to give a clear overview of the main technologies used in language and speech processing, along with an extensive bibliography to enable topics of interest to be pursued further. It also brings together speech and language technologies often considered separately. Robustness in Language and Speech Technology serves as a valuable reference and although not intended as a formal university textbook, contains some material that can be used for a course at the graduate or undergraduate level.
Author: Michael Grimm
Publisher: BoD – Books on Demand
ISBN: 3902613084
Category : Computers
Languages : en
Pages : 471
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Book Description
This book on Robust Speech Recognition and Understanding brings together many different aspects of the current research on automatic speech recognition and language understanding. The first four chapters address the task of voice activity detection which is considered an important issue for all speech recognition systems. The next chapters give several extensions to state-of-the-art HMM methods. Furthermore, a number of chapters particularly address the task of robust ASR under noisy conditions. Two chapters on the automatic recognition of a speaker's emotional state highlight the importance of natural speech understanding and interpretation in voice-driven systems. The last chapters of the book address the application of conversational systems on robots, as well as the autonomous acquisition of vocalization skills.
Author: France Mihelič
Publisher: BoD – Books on Demand
ISBN: 953761929X
Category : Computers
Languages : en
Pages : 580
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Book Description
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.
Author: Jean-Claude Junqua
Publisher: Springer Science & Business Media
ISBN: 0306470276
Category : Technology & Engineering
Languages : en
Pages : 178
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Book Description
Robust Speech Recognition in Embedded Systems and PC Applications provides a link between the technology and the application worlds. As speech recognition technology is now good enough for a number of applications and the core technology is well established around hidden Markov models many of the differences between systems found in the field are related to implementation variants. We distinguish between embedded systems and PC-based applications. Embedded applications are usually cost sensitive and require very simple and optimized methods to be viable. Robust Speech Recognition in Embedded Systems and PC Applications reviews the problems of robust speech recognition, summarizes the current state of the art of robust speech recognition while providing some perspectives, and goes over the complementary technologies that are necessary to build an application, such as dialog and user interface technologies. Robust Speech Recognition in Embedded Systems and PC Applications is divided into five chapters. The first one reviews the main difficulties encountered in automatic speech recognition when the type of communication is unknown. The second chapter focuses on environment-independent/adaptive speech recognition approaches and on the mainstream methods applicable to noise robust speech recognition. The third chapter discusses several critical technologies that contribute to making an application usable. It also provides some design recommendations on how to design prompts, generate user feedback and develop speech user interfaces. The fourth chapter reviews several techniques that are particularly useful for embedded systems or to decrease computational complexity. It also presents some case studies for embedded applications and PC-based systems. Finally, the fifth chapter provides a future outlook for robust speech recognition, emphasizing the areas that the author sees as the most promising for the future. Robust Speech Recognition in Embedded Systems and PC Applications serves as a valuable reference and although not intended as a formal University textbook, contains some material that can be used for a course at the graduate or undergraduate level. It is a good complement for the book entitled Robustness in Automatic Speech Recognition: Fundamentals and Applications co-authored by the same author.
