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Author: Blade Kotelly
Publisher: Addison-Wesley Professional
ISBN: 9780321154927
Category : Computers
Languages : en
Pages : 208
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Book Description
Most people have experienced an automated speech-recognition system when calling a company. Instead of prompting callers to choose an option by entering numbers, the system asks questions and understands spoken responses. With a more advanced application, callers may feel as if they're having a conversation with another person. Not only will the system respond intelligently, its voice even has personality. The Art and Business of Speech Recognition examines both the rapid emergence and broad potential of speech-recognition applications. By explaining the nature, design, development, and use of such applications, this book addresses two particular needs: Business managers must understand the competitive advantage that speech-recognition applications provide: a more effective way to engage, serve, and retain customers over the phone. Application designers must know how to meet their most critical business goal: a satisfying customer experience. Author Blade Kotelly illuminates these needs from the perspective of an experienced, business-focused practitioner. Among the diverse applications he's worked on, perhaps his most influential design is the flight-information system developed for United Airlines, about which Julie Vallone wrote in Investor's Business Daily "By the end of the conversation, you might want to take the voice to dinner." If dinner is the analogy, this concise book is an ideal first course. Managers will learn the potential of speech-recognition applications to reduce costs, increase customer satisfaction, enhance the company brand, and even grow revenues. Designers, especially those just beginning to work in the voice domain, will learn user-interface design principles and techniques needed to develop and deploy successful applications. The examples in the book are real, the writing is accessible and lucid, and the solutions presented are attainable today. 0321154924B12242002
Author: Blade Kotelly
Publisher: Addison-Wesley Professional
ISBN: 9780321154927
Category : Computers
Languages : en
Pages : 208
Get Book Here
Book Description
Most people have experienced an automated speech-recognition system when calling a company. Instead of prompting callers to choose an option by entering numbers, the system asks questions and understands spoken responses. With a more advanced application, callers may feel as if they're having a conversation with another person. Not only will the system respond intelligently, its voice even has personality. The Art and Business of Speech Recognition examines both the rapid emergence and broad potential of speech-recognition applications. By explaining the nature, design, development, and use of such applications, this book addresses two particular needs: Business managers must understand the competitive advantage that speech-recognition applications provide: a more effective way to engage, serve, and retain customers over the phone. Application designers must know how to meet their most critical business goal: a satisfying customer experience. Author Blade Kotelly illuminates these needs from the perspective of an experienced, business-focused practitioner. Among the diverse applications he's worked on, perhaps his most influential design is the flight-information system developed for United Airlines, about which Julie Vallone wrote in Investor's Business Daily "By the end of the conversation, you might want to take the voice to dinner." If dinner is the analogy, this concise book is an ideal first course. Managers will learn the potential of speech-recognition applications to reduce costs, increase customer satisfaction, enhance the company brand, and even grow revenues. Designers, especially those just beginning to work in the voice domain, will learn user-interface design principles and techniques needed to develop and deploy successful applications. The examples in the book are real, the writing is accessible and lucid, and the solutions presented are attainable today. 0321154924B12242002
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: Hervé A. Bourlard
Publisher: Springer Science & Business Media
ISBN: 1461532108
Category : Technology & Engineering
Languages : en
Pages : 329
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Book Description
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: Jinyu Li
Publisher: Academic Press
ISBN: 0128026162
Category : Technology & Engineering
Languages : en
Pages : 308
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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: Shinji Watanabe
Publisher: Springer
ISBN: 331964680X
Category : Computers
Languages : en
Pages : 433
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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: 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: Lawrence R. Rabiner
Publisher:
ISBN: 9788129701381
Category : Automatic speech recognition
Languages : en
Pages : 507
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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: Neamat El Gayar
Publisher: World Scientific
ISBN: 9813229403
Category : Computers
Languages : en
Pages : 286
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Book Description
This book encompasses a collection of topics covering recent advances that are important to the Arabic language in areas of natural language processing, speech and image analysis. This book presents state-of-the-art reviews and fundamentals as well as applications and recent innovations.The book chapters by top researchers present basic concepts and challenges for the Arabic language in linguistic processing, handwritten recognition, document analysis, text classification and speech processing. In addition, it reports on selected applications in sentiment analysis, annotation, text summarization, speech and font analysis, word recognition and spotting and question answering.Moreover, it highlights and introduces some novel applications in vital areas for the Arabic language. The book is therefore a useful resource for young researchers who are interested in the Arabic language and are still developing their fundamentals and skills in this area. It is also interesting for scientists who wish to keep track of the most recent research directions and advances in this area.
Author: Dan Jurafsky
Publisher: Pearson Education India
ISBN: 9788131716724
Category :
Languages : en
Pages : 912
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Book Description
