Speech & Language Processing PDF Download

Author: Dan Jurafsky
Publisher: Pearson Education India
ISBN: 9788131716724
Category :
Languages : en
Pages : 912

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Author: Scott Baker
Publisher: Ashe Publishing
ISBN:
Category : Language Arts & Disciplines
Languages : en
Pages : 83

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Book Description
Want to dictate up to 5000 WORDS an hour? Want to do it with 99% ACCURACY from the day you start? NEW EDITION: UPDATED to cover the latest Dragon Professional Individual v15 for PC & v6 for Mac FREE video training included! As writers, we all know what an incredible tool dictation software can be. It enables us to write faster and avoid the dangers of RSI and a sedentary lifestyle. But many of us give up on dictating when we find we can't get the accuracy we need to be truly productive. This book changes all of that. With almost two decades of using Dragon software under his belt and a wealth of insider knowledge from within the dictation industry, Scott Baker will reveal how to supercharge your writing and achieve sky-high recognition accuracy from the moment you start using the software. You will learn: - Hidden tricks to use when installing Dragon NaturallySpeaking on a Windows PC or Dragon Dictate for Mac; - How to choose the right microphone and set it up perfectly for speech recognition; - The little-known techniques that will ensure around 99% accuracy from your first install – and how to make this even better over time; - Setting up fail-safe dictation profiles with multiple microphones and voice recorders, without impacting your accuracy; - How to train the software to adapt to both your voice AND writing style and avoid your accuracy declining; - Strategies for achieving your entire daily word count in just one or two hours; - Many more tips and tricks you won't find anywhere else. At the end of the book, you'll also find an exclusive list of resources and links to FREE video training to take your knowledge even further. It's time to write at the speed of speech – and transform your writing workflow forever! Subject keywords: Dragon Dictate Naturally Speaking for PC Mac, dictating your book or novel, dictation for writers authors beginners advanced, creative writing guides, self publishing

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: Michael Harris Cohen
Publisher: Addison-Wesley Professional
ISBN: 9780321185761
Category : Computers
Languages : en
Pages : 366

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Book Description
This book is a comprehensive and authoritative guide to voice user interface (VUI) design. The VUI is perhaps the most critical factor in the success of any automated speech recognition (ASR) system, determining whether the user experience will be satisfying or frustrating, or even whether the customer will remain one. This book describes a practical methodology for creating an effective VUI design. The methodology is scientifically based on principles in linguistics, psychology, and language technology, and is illustrated here by examples drawn from the authors' work at Nuance Communications, the market leader in ASR development and deployment. The book begins with an overview of VUI design issues and a description of the technology. The authors then introduce the major phases of their methodology. They first show how to specify requirements and make high-level design decisions during the definition phase. They next cover, in great detail, the design phase, with clear explanations and demonstrations of each design principle and its real-world applications. Finally, they examine problems unique to VUI design in system development, testing, and tuning. Key principles are illustrated with a running sample application. A companion Web site provides audio clips for each example: www.VUIDesign.org The cover photograph depicts the first ASR system, Radio Rex: a toy dog who sits in his house until the sound of his name calls him out. Produced in 1911, Rex was among the few commercial successes in earlier days of speech recognition. Voice User Interface Design reveals the design principles and practices that produce commercial success in an era when effective ASRs are not toys but competitive necessities.

Author: A Purushotham Reddy
Publisher: A Purushotham Reddy
ISBN:
Category : Antiques & Collectibles
Languages : en
Pages : 2066

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Book Description
Database Management Using AI: A Comprehensive Guide is a professional yet accessible exploration of how artificial intelligence (AI) is reshaping the world of database management. Designed for database administrators, data scientists, and tech enthusiasts, this book walks readers through the transformative impact of AI on modern data systems. The guide begins with the fundamentals of database management, covering key concepts such as data models, SQL, and the principles of database design. From there, it delves into the powerful role AI plays in optimizing database performance, enhancing security, and automating complex tasks like data retrieval, query optimization, and schema design. The book doesn't stop at theory. It brings AI to life with practical case studies showing how AI-driven database systems are being used in industries such as e-commerce, healthcare, finance, and logistics. These real-world examples demonstrate AI's role in improving efficiency, reducing errors, and driving intelligent decision-making. Key topics covered include: Introduction to Database Systems: Fundamentals of database management, from relational databases to modern NoSQL systems. AI Integration: How AI enhances database performance, automates routine tasks, and strengthens security. Real-World Applications: Case studies from diverse sectors like healthcare, finance, and retail, showcasing the practical impact of AI in database management. Predictive Analytics and Data Mining: How AI tools leverage data to make accurate predictions and uncover trends. Future Trends: Explore cutting-edge innovations like autonomous databases and cloud-based AI solutions that are shaping the future of data management. With its clear explanations and actionable insights, Database Management Using AI equips readers with the knowledge to navigate the fast-evolving landscape of AI-powered databases, making it a must-have resource for those looking to stay ahead in the digital age.

Author: Alberto Artasanchez
Publisher: Packt Publishing Ltd
ISBN: 1839216077
Category : Computers
Languages : en
Pages : 619

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Book Description
New edition of the bestselling guide to artificial intelligence with Python, updated to Python 3.x, with seven new chapters that cover RNNs, AI and Big Data, fundamental use cases, chatbots, and more. Key FeaturesCompletely updated and revised to Python 3.xNew chapters for AI on the cloud, recurrent neural networks, deep learning models, and feature selection and engineeringLearn more about deep learning algorithms, machine learning data pipelines, and chatbotsBook Description Artificial Intelligence with Python, Second Edition is an updated and expanded version of the bestselling guide to artificial intelligence using the latest version of Python 3.x. Not only does it provide you an introduction to artificial intelligence, this new edition goes further by giving you the tools you need to explore the amazing world of intelligent apps and create your own applications. This edition also includes seven new chapters on more advanced concepts of Artificial Intelligence, including fundamental use cases of AI; machine learning data pipelines; feature selection and feature engineering; AI on the cloud; the basics of chatbots; RNNs and DL models; and AI and Big Data. Finally, this new edition explores various real-world scenarios and teaches you how to apply relevant AI algorithms to a wide swath of problems, starting with the most basic AI concepts and progressively building from there to solve more difficult challenges so that by the end, you will have gained a solid understanding of, and when best to use, these many artificial intelligence techniques. What you will learnUnderstand what artificial intelligence, machine learning, and data science areExplore the most common artificial intelligence use casesLearn how to build a machine learning pipelineAssimilate the basics of feature selection and feature engineeringIdentify the differences between supervised and unsupervised learningDiscover the most recent advances and tools offered for AI development in the cloudDevelop automatic speech recognition systems and chatbotsApply AI algorithms to time series dataWho this book is for The intended audience for this book is Python developers who want to build real-world Artificial Intelligence applications. Basic Python programming experience and awareness of machine learning concepts and techniques is mandatory.

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: 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: Ian Goodfellow
Publisher: MIT Press
ISBN: 0262337371
Category : Computers
Languages : en
Pages : 801

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Book Description
An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. “Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.” —Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.

Author: M. Afshar Alam
Publisher: European Alliance for Innovation
ISBN: 1631903969
Category : Business & Economics
Languages : en
Pages : 413

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Book Description
The International Conference on ICT for Digital, Smart, and Sustainable Development provides an annual platform for researchers, academicians, and professionals from across the world. ICIDSSD 22, held at Jamia Hamdard, New Delhi, India, is the second international conference of this series of conferences to be held annually. The conference majorly focuses on the recent developments in the areas relating to Information and Communication Technologies and contributing to Sustainable Development. ICIDSSD ’22 has attracted research papers pertaining to an array of exciting research areas. The selected papers cover a wide range of topics including but not limited to Sustainable Development, Green Computing, Smart City, Artificial Intelligence, Big Data, Machine Learning, Cloud Computing LT, ANN, Security, and Data Science. Papers have primarily been judged on originality, presentation, relevance, and quality of work. Papers that clearly demonstrate results have been preferred. After the formal process of peer review, the editorial board has finally selected the most relevant papers to be included in this volume. We are sure that these research works will enrich our knowledge and motivate us towards exploring the latest avenues in research. We would like to thank our Hon'ble Vice Chancellor, Prof. (Dr) M.Afshar Alarn, for his constant and commendable support extended to us toward the path of excellence. Alongside him, we would like to thank the Registrar, Mr. Syed Saud Akhtar, and other officials of the University for supporting this conference. We thank our esteemed authors for having shown confidence in us and entrusting us with the publication of their research papers. The success of the conference would not have been possible without the submission of their quality research works. We thank the members of the International Scientific Advisory Committee, Technical Program Committee and members of all the other committees for their advice, guidance, and efforts. Also, we are grateful to our technical partners and sponsors, viz. HNF, EAI, ISTE, AICTE, TIC, CSI, JETE, and DST for sponsorship and assistance. We also thank the Department of Higher Education, MHRD for the timely issuance of ISBN for the proceedings of the conference. Finally, we are thankful to all who have contributed to the success of this conference.