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Author: Dan Jurafsky
Publisher: Pearson Education India
ISBN: 9788131716724
Category :
Languages : en
Pages : 912
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Book Description
Author: Dan Jurafsky
Publisher: Pearson Education India
ISBN: 9788131716724
Category :
Languages : en
Pages : 912
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Book Description
Author: Dong Yu
Publisher: Springer
ISBN: 1447157796
Category : Technology & Engineering
Languages : en
Pages : 329
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Book Description
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.
Author: Frederick Jelinek
Publisher: MIT Press
ISBN: 0262546604
Category : Language Arts & Disciplines
Languages : en
Pages : 307
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Book Description
This book reflects decades of important research on the mathematical foundations of speech recognition. It focuses on underlying statistical techniques such as hidden Markov models, decision trees, the expectation-maximization algorithm, information theoretic goodness criteria, maximum entropy probability estimation, parameter and data clustering, and smoothing of probability distributions. The author's goal is to present these principles clearly in the simplest setting, to show the advantages of self-organization from real data, and to enable the reader to apply the techniques. Bradford Books imprint
Author: Uday Kamath
Publisher: Springer
ISBN: 3030145964
Category : Computers
Languages : en
Pages : 640
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Book Description
This textbook explains Deep Learning Architecture, with applications to various NLP Tasks, including Document Classification, Machine Translation, Language Modeling, and Speech Recognition. With the widespread adoption of deep learning, natural language processing (NLP),and speech applications in many areas (including Finance, Healthcare, and Government) there is a growing need for one comprehensive resource that maps deep learning techniques to NLP and speech and provides insights into using the tools and libraries for real-world applications. Deep Learning for NLP and Speech Recognition explains recent deep learning methods applicable to NLP and speech, provides state-of-the-art approaches, and offers real-world case studies with code to provide hands-on experience. Many books focus on deep learning theory or deep learning for NLP-specific tasks while others are cookbooks for tools and libraries, but the constant flux of new algorithms, tools, frameworks, and libraries in a rapidly evolving landscape means that there are few available texts that offer the material in this book. The book is organized into three parts, aligning to different groups of readers and their expertise. The three parts are: Machine Learning, NLP, and Speech Introduction The first part has three chapters that introduce readers to the fields of NLP, speech recognition, deep learning and machine learning with basic theory and hands-on case studies using Python-based tools and libraries. Deep Learning Basics The five chapters in the second part introduce deep learning and various topics that are crucial for speech and text processing, including word embeddings, convolutional neural networks, recurrent neural networks and speech recognition basics. Theory, practical tips, state-of-the-art methods, experimentations and analysis in using the methods discussed in theory on real-world tasks. Advanced Deep Learning Techniques for Text and Speech The third part has five chapters that discuss the latest and cutting-edge research in the areas of deep learning that intersect with NLP and speech. Topics including attention mechanisms, memory augmented networks, transfer learning, multi-task learning, domain adaptation, reinforcement learning, and end-to-end deep learning for speech recognition are covered using case studies.
Author: Lawrence R. Rabiner
Publisher:
ISBN: 9788129701381
Category : Automatic speech recognition
Languages : en
Pages : 507
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Book Description
Author: Claudio Becchetti
Publisher: John Wiley & Sons
ISBN: 9788126517749
Category :
Languages : en
Pages : 432
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Book Description
Special Features: · Source codes for compiling and implementing ASR algorithms in C++ are included in electronic format on an accompanying CD-ROM· Contains a practical account of the functioning of ASR· Includes implementation-oriented mathematical and technical explanations of ASR· Features a stage-by-stage explanation of how to create an ASR interface· Can be used both for teaching speech recognition techniques and testing and development of new systems on digital signal processing hardware About The Book: Automatic Speech Recognition (ASR) is becoming increasingly prevalent in such applications as private telephone exchanges and real-time on-line telephone information services. This book introduces the principles of ASR systems, including the theory and the implementation issues behind multi-speaker continuous speech ASR. The book supplies the full C++ code to further clarify the implementation details of a typical commercial/laboratory ASR system and to allow the readers to reach practical solutions for ASR-related problems.About the topic/technology Automatic Speech Recognition (ASR) is the technology behind the voice-triggered computer menus. Uses of these systems are now proliferating rapidly and include private telephone exchanges and real-time on-line telephone information services.
Author: Alexander Waibel
Publisher: Elsevier
ISBN: 0080515843
Category : Computers
Languages : en
Pages : 640
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Book Description
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: Bruce Balentine
Publisher:
ISBN: 9780967127811
Category : Automatic speech recognition
Languages : en
Pages : 0
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Book Description
Author: Matthias Woelfel
Publisher: John Wiley & Sons
ISBN: 0470714077
Category : Technology & Engineering
Languages : en
Pages : 600
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Book Description
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: Zheng-Hua Tan
Publisher: Springer Science & Business Media
ISBN: 1848001436
Category : Technology & Engineering
Languages : en
Pages : 408
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Book Description
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.
