New Era for Robust Speech Recognition: Exploiting Deep Learning, Watanabe Shinji, Delcroix Marc, Metze Florian
Автор: Jinyu Li Название: Robust Automatic Speech Recognition ISBN: 0128023988 ISBN-13(EAN): 9780128023983 Издательство: Elsevier Science Рейтинг: Цена: 16842.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
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
Описание: This book covers all major aspects of cutting-edge research in the field of neuromorphic hardware engineering involving emerging nanoscale devices.
Автор: Pan Jeff Z., Vetere Guido, Gomez-Perez Jose Manuel Название: Exploiting Linked Data and Knowledge Graphs in Large Organisations ISBN: 3319833391 ISBN-13(EAN): 9783319833392 Издательство: Springer Рейтинг: Цена: 23757.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Part I Knowledge Graph Foundations & Architecture.- Part II Constructing, Understanding and Consuming Knowledge Graphs.- Part III Industrial Applications and Successful Stories.
Автор: Shinji Watanabe; Marc Delcroix; Florian Metze; Joh Название: New Era for Robust Speech Recognition ISBN: 3319646796 ISBN-13(EAN): 9783319646794 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 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.
Автор: Uday Kamath; John Liu; James Whitaker Название: Deep Learning for NLP and Speech Recognition ISBN: 3030145956 ISBN-13(EAN): 9783030145958 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 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 IntroductionThe 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 BasicsThe 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.
Описание: Social Media and the Internet of Things have resulted in an avalanche of data. Data is powerful but not in its raw form; it needs to be processed and modeled, and Python is one of the most robust tools out there to do so. It has an array of packages for predictive modeling and a suite of IDEs to choose from. This book is your guide to getting ...
Автор: Nikhil Jayakumar; Suganth Paul; Rajesh Garg Название: Minimizing and Exploiting Leakage in VLSI Design ISBN: 1489985298 ISBN-13(EAN): 9781489985293 Издательство: Springer Рейтинг: Цена: 18284.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents two techniques to reduce leakage power in digital VLSI ICs. The first reduces leakage through the selective use of high threshold voltage sleep transistors, while the second by applying the optimal Reverse Body Bias voltage.
Описание: This book covers all major aspects of cutting-edge research in the field of neuromorphic hardware engineering involving emerging nanoscale devices.
Автор: Dorothea Kolossa; Reinhold Haeb-Umbach Название: Robust Speech Recognition of Uncertain or Missing Data ISBN: 3642438687 ISBN-13(EAN): 9783642438684 Издательство: Springer Рейтинг: Цена: 16977.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 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.
Описание: Reviewing the problems of robust speech recognition, this book goes over the complementary technologies that are necessary to build an application, such as dialog and user interface technologies. This volume is suitable as a complement for the book entitled "Robustness in Automatic Speech Recognition: Fundamentals and Applications".
Автор: Kamath Uday, Liu John, Whitaker James Название: Deep Learning for Nlp and Speech Recognition ISBN: 3030145980 ISBN-13(EAN): 9783030145989 Издательство: Springer Рейтинг: Цена: 11179.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Notation xv.- Part 1: Machine Learning, NLP, and Speech Introduction.- Chapter 1 Introduction 1.- Chapter 2 Basics of Machine Learning 2.- Chapter 3 Text and Speech Basics 49.- Part 2: Deep Learning Basics.- Chapter 4 Basics of Deep Learning 105.- Chapter 5 Distributed Representations 213.- Chapter 6 Convolutional Neural Networks 275.- Chapter 7 Recurrent Neural Networks 329.- Chapter 8 Automatic Speech Recognition 387.- Part 3: Advance Deep Learning Techniques for Text and Speech.- Chapter 9 Attention and Memory Augmented Networks 429.- Chapter 10 Transfer learning: Scenarios, Self-Taught Learning, and Multitask Learning 485.- Chapter 11 Transfer Learning: Domain Adaptation 515.- Chapter 12 End-to-end Speech Recognition 559.- Chapter 13 Deep Reinforcement Learning for Text and Speech 601.- Future Outlook 647.
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