Distant Speech Recognition

Author : Matthias Woelfel,John McDonough
Publisher : John Wiley & Sons
Page : 600 pages
File Size : 47,9 Mb
Release : 2009-04-20
Category : Technology & Engineering
ISBN : 9780470714072

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Distant Speech Recognition by Matthias Woelfel,John McDonough Pdf

A complete overview of distant automatic speech recognition The performance of conventional Automatic Speech Recognition (ASR) systems degrades dramatically as soon as the microphone is moved away from the mouth of the speaker. This is due to a broad variety of effects such as background noise, overlapping speech from other speakers, and reverberation. While traditional ASR systems underperform for speech captured with far-field sensors, there are a number of novel techniques within the recognition system as well as techniques developed in other areas of signal processing that can mitigate the deleterious effects of noise and reverberation, as well as separating speech from overlapping speakers. Distant Speech Recognitionpresents a contemporary and comprehensive description of both theoretic abstraction and practical issues inherent in the distant ASR problem. Key Features: Covers the entire topic of distant ASR and offers practical solutions to overcome the problems related to it Provides documentation and sample scripts to enable readers to construct state-of-the-art distant speech recognition systems Gives relevant background information in acoustics and filter techniques, Explains the extraction and enhancement of classification relevant speech features Describes maximum likelihood as well as discriminative parameter estimation, and maximum likelihood normalization techniques Discusses the use of multi-microphone configurations for speaker tracking and channel combination Presents several applications of the methods and technologies described in this book Accompanying website with open source software and tools to construct state-of-the-art distant speech recognition systems This reference will be an invaluable resource for researchers, developers, engineers and other professionals, as well as advanced students in speech technology, signal processing, acoustics, statistics and artificial intelligence fields.

Author : Shinji Watanabe,Marc Delcroix,Florian Metze,John R. Hershey
Publisher : Springer
Page : 436 pages
File Size : 55,7 Mb
Release : 2017-10-30
Category : Computers
ISBN : 9783319646800

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New Era for Robust Speech Recognition by Shinji Watanabe,Marc Delcroix,Florian Metze,John R. Hershey Pdf

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,Jose Segura
Publisher : John Wiley & Sons
Page : 274 pages
File Size : 47,9 Mb
Release : 2006-08-04
Category : Technology & Engineering
ISBN : 9780470024010

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Speech Recognition Over Digital Channels by Antonio Peinado,Jose Segura Pdf

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 : Joseph Keshet,Samy Bengio
Publisher : John Wiley & Sons
Page : 268 pages
File Size : 44,7 Mb
Release : 2009-04-27
Category : Technology & Engineering
ISBN : 0470742038

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Automatic Speech and Speaker Recognition by Joseph Keshet,Samy Bengio Pdf

This book discusses large margin and kernel methods for speech and speaker recognition Speech and Speaker Recognition: Large Margin and Kernel Methods is a collation of research in the recent advances in large margin and kernel methods, as applied to the field of speech and speaker recognition. It presents theoretical and practical foundations of these methods, from support vector machines to large margin methods for structured learning. It also provides examples of large margin based acoustic modelling for continuous speech recognizers, where the grounds for practical large margin sequence learning are set. Large margin methods for discriminative language modelling and text independent speaker verification are also addressed in this book. Key Features: Provides an up-to-date snapshot of the current state of research in this field Covers important aspects of extending the binary support vector machine to speech and speaker recognition applications Discusses large margin and kernel method algorithms for sequence prediction required for acoustic modeling Reviews past and present work on discriminative training of language models, and describes different large margin algorithms for the application of part-of-speech tagging Surveys recent work on the use of kernel approaches to text-independent speaker verification, and introduces the main concepts and algorithms Surveys recent work on kernel approaches to learning a similarity matrix from data This book will be of interest to researchers, practitioners, engineers, and scientists in speech processing and machine learning fields.

Author : Armin Martin Sehr
Publisher : Unknown
Page : 226 pages
File Size : 43,5 Mb
Release : 2010
Category : Electronic
ISBN : 3868535764

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Reverberation Modeling for Robust Distant-talking Speech Recognition by Armin Martin Sehr Pdf

Author : Jinyu Li,Li Deng,Reinhold Haeb-Umbach,Yifan Gong
Publisher : Academic Press
Page : 306 pages
File Size : 50,7 Mb
Release : 2015-10-30
Category : Technology & Engineering
ISBN : 9780128026168

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Robust Automatic Speech Recognition by Jinyu Li,Li Deng,Reinhold Haeb-Umbach,Yifan Gong Pdf

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 : Tuomas Virtanen,Rita Singh,Bhiksha Raj
Publisher : John Wiley & Sons
Page : 514 pages
File Size : 54,8 Mb
Release : 2012-11-28
Category : Technology & Engineering
ISBN : 9781119970880

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Techniques for Noise Robustness in Automatic Speech Recognition by Tuomas Virtanen,Rita Singh,Bhiksha Raj Pdf

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 : Homayoon Beigi
Publisher : Springer Science & Business Media
Page : 942 pages
File Size : 48,8 Mb
Release : 2011-12-09
Category : Technology & Engineering
ISBN : 9780387775920

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Fundamentals of Speaker Recognition by Homayoon Beigi Pdf

An emerging technology, Speaker Recognition is becoming well-known for providing voice authentication over the telephone for helpdesks, call centres and other enterprise businesses for business process automation. "Fundamentals of Speaker Recognition" introduces Speaker Identification, Speaker Verification, Speaker (Audio Event) Classification, Speaker Detection, Speaker Tracking and more. The technical problems are rigorously defined, and a complete picture is made of the relevance of the discussed algorithms and their usage in building a comprehensive Speaker Recognition System. Designed as a textbook with examples and exercises at the end of each chapter, "Fundamentals of Speaker Recognition" is suitable for advanced-level students in computer science and engineering, concentrating on biometrics, speech recognition, pattern recognition, signal processing and, specifically, speaker recognition. It is also a valuable reference for developers of commercial technology and for speech scientists. Please click on the link under "Additional Information" to view supplemental information including the Table of Contents and Index.

Author : Dan Jurafsky
Publisher : Pearson Education India
Page : 912 pages
File Size : 47,6 Mb
Release : 2000-09
Category : Electronic
ISBN : 8131716724

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Speech & Language Processing by Dan Jurafsky Pdf

Author : A. Acero
Publisher : Springer Science & Business Media
Page : 197 pages
File Size : 48,5 Mb
Release : 2012-12-06
Category : Technology & Engineering
ISBN : 9781461531227

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Acoustical and Environmental Robustness in Automatic Speech Recognition by A. Acero Pdf

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 : Jean-Claude Junqua,Jean-Paul Haton
Publisher : Springer Science & Business Media
Page : 457 pages
File Size : 51,9 Mb
Release : 2012-12-06
Category : Technology & Engineering
ISBN : 9781461312970

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Robustness in Automatic Speech Recognition by Jean-Claude Junqua,Jean-Paul Haton Pdf

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 : Alexander Waibel,Kai-Fu Lee
Publisher : Elsevier
Page : 640 pages
File Size : 51,6 Mb
Release : 1990-12-25
Category : Computers
ISBN : 9780080515847

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Readings in Speech Recognition by Alexander Waibel,Kai-Fu Lee Pdf

After more than two decades of research activity, speech recognition has begun to live up to its promise as a practical technology and interest in the field is growing dramatically. Readings in Speech Recognition provides a collection of seminal papers that have influenced or redirected the field and that illustrate the central insights that have emerged over the years. The editors provide an introduction to the field, its concerns and research problems. Subsequent chapters are devoted to the main schools of thought and design philosophies that have motivated different approaches to speech recognition system design. Each chapter includes an introduction to the papers that highlights the major insights or needs that have motivated an approach to a problem and describes the commonalities and differences of that approach to others in the book.

Author : Ami Moyal,Vered Aharonson,Ella Tetariy,Michal Gishri
Publisher : Springer Science & Business Media
Page : 53 pages
File Size : 43,7 Mb
Release : 2013-02-28
Category : Technology & Engineering
ISBN : 9781461464891

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Phonetic Search Methods for Large Speech Databases by Ami Moyal,Vered Aharonson,Ella Tetariy,Michal Gishri Pdf

“Phonetic Search Methods for Large Databases” focuses on Keyword Spotting (KWS) within large speech databases. The brief will begin by outlining the challenges associated with Keyword Spotting within large speech databases using dynamic keyword vocabularies. It will then continue by highlighting the various market segments in need of KWS solutions, as well as, the specific requirements of each market segment. The work also includes a detailed description of the complexity of the task and the different methods that are used, including the advantages and disadvantages of each method and an in-depth comparison. The main focus will be on the Phonetic Search method and its efficient implementation. This will include a literature review of the various methods used for the efficient implementation of Phonetic Search Keyword Spotting, with an emphasis on the authors’ own research which entails a comparative analysis of the Phonetic Search method which includes algorithmic details. This brief is useful for researchers and developers in academia and industry from the fields of speech processing and speech recognition, specifically Keyword Spotting.

Author : Hervé A. Bourlard,Nelson Morgan
Publisher : Springer Science & Business Media
Page : 329 pages
File Size : 55,9 Mb
Release : 2012-12-06
Category : Technology & Engineering
ISBN : 9781461532101

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Connectionist Speech Recognition by Hervé A. Bourlard,Nelson Morgan Pdf

Connectionist Speech Recognition: A Hybrid Approach describes the theory and implementation of a method to incorporate neural network approaches into state of the art continuous speech recognition systems based on hidden Markov models (HMMs) to improve their performance. In this framework, neural networks (and in particular, multilayer perceptrons or MLPs) have been restricted to well-defined subtasks of the whole system, i.e. HMM emission probability estimation and feature extraction. The book describes a successful five-year international collaboration between the authors. The lessons learned form a case study that demonstrates how hybrid systems can be developed to combine neural networks with more traditional statistical approaches. The book illustrates both the advantages and limitations of neural networks in the framework of a statistical systems. Using standard databases and comparison with some conventional approaches, it is shown that MLP probability estimation can improve recognition performance. Other approaches are discussed, though there is no such unequivocal experimental result for these methods. Connectionist Speech Recognition is of use to anyone intending to use neural networks for speech recognition or within the framework provided by an existing successful statistical approach. This includes research and development groups working in the field of speech recognition, both with standard and neural network approaches, as well as other pattern recognition and/or neural network researchers. The book is also suitable as a text for advanced courses on neural networks or speech processing.

Author : Dong Yu,Li Deng
Publisher : Springer
Page : 321 pages
File Size : 53,9 Mb
Release : 2014-11-11
Category : Technology & Engineering
ISBN : 9781447157793

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Automatic Speech Recognition by Dong Yu,Li Deng Pdf

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.