Download or read book Speech Language Processing written by Dan Jurafsky and published by Pearson Education India. This book was released on 2000-09 with total page 912 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Natural Language Acquisition on the Autism Spectrum written by Marge Blanc and published by . This book was released on 2012 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Natural Language Processing and Computational Linguistics written by Mohamed Zakaria Kurdi and published by John Wiley & Sons. This book was released on 2016-08-17 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: Natural language processing (NLP) is a scientific discipline which is found at the interface of computer science, artificial intelligence and cognitive psychology. Providing an overview of international work in this interdisciplinary field, this book gives the reader a panoramic view of both early and current research in NLP. Carefully chosen multilingual examples present the state of the art of a mature field which is in a constant state of evolution. In four chapters, this book presents the fundamental concepts of phonetics and phonology and the two most important applications in the field of speech processing: recognition and synthesis. Also presented are the fundamental concepts of corpus linguistics and the basic concepts of morphology and its NLP applications such as stemming and part of speech tagging. The fundamental notions and the most important syntactic theories are presented, as well as the different approaches to syntactic parsing with reference to cognitive models, algorithms and computer applications.
Download or read book Deep Learning for NLP and Speech Recognition written by Uday Kamath and published by Springer. This book was released on 2019-06-10 with total page 621 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Mathematical Foundations of Speech and Language Processing written by Mark Johnson and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: Speech and language technologies continue to grow in importance as they are used to create natural and efficient interfaces between people and machines, and to automatically transcribe, extract, analyze, and route information from high-volume streams of spoken and written information. The workshops on Mathematical Foundations of Speech Processing and Natural Language Modeling were held in the Fall of 2000 at the University of Minnesota's NSF-sponsored Institute for Mathematics and Its Applications, as part of a "Mathematics in Multimedia" year-long program. Each workshop brought together researchers in the respective technologies on the one hand, and mathematicians and statisticians on the other hand, for an intensive week of cross-fertilization. There is a long history of benefit from introducing mathematical techniques and ideas to speech and language technologies. Examples include the source-channel paradigm, hidden Markov models, decision trees, exponential models and formal languages theory. It is likely that new mathematical techniques, or novel applications of existing techniques, will once again prove pivotal for moving the field forward. This volume consists of original contributions presented by participants during the two workshops. Topics include language modeling, prosody, acoustic-phonetic modeling, and statistical methodology.
Download or read book Applied Natural Language Processing in the Enterprise written by Ankur A. Patel and published by "O'Reilly Media, Inc.". This book was released on 2021-05-12 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: NLP has exploded in popularity over the last few years. But while Google, Facebook, OpenAI, and others continue to release larger language models, many teams still struggle with building NLP applications that live up to the hype. This hands-on guide helps you get up to speed on the latest and most promising trends in NLP. With a basic understanding of machine learning and some Python experience, you'll learn how to build, train, and deploy models for real-world applications in your organization. Authors Ankur Patel and Ajay Uppili Arasanipalai guide you through the process using code and examples that highlight the best practices in modern NLP. Use state-of-the-art NLP models such as BERT and GPT-3 to solve NLP tasks such as named entity recognition, text classification, semantic search, and reading comprehension Train NLP models with performance comparable or superior to that of out-of-the-box systems Learn about Transformer architecture and modern tricks like transfer learning that have taken the NLP world by storm Become familiar with the tools of the trade, including spaCy, Hugging Face, and fast.ai Build core parts of the NLP pipeline--including tokenizers, embeddings, and language models--from scratch using Python and PyTorch Take your models out of Jupyter notebooks and learn how to deploy, monitor, and maintain them in production
Download or read book Handbook of Natural Language Processing and Machine Translation written by Joseph Olive and published by Springer Science & Business Media. This book was released on 2011-03-02 with total page 956 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive handbook, written by leading experts in the field, details the groundbreaking research conducted under the breakthrough GALE program--The Global Autonomous Language Exploitation within the Defense Advanced Research Projects Agency (DARPA), while placing it in the context of previous research in the fields of natural language and signal processing, artificial intelligence and machine translation. The most fundamental contrast between GALE and its predecessor programs was its holistic integration of previously separate or sequential processes. In earlier language research programs, each of the individual processes was performed separately and sequentially: speech recognition, language recognition, transcription, translation, and content summarization. The GALE program employed a distinctly new approach by executing these processes simultaneously. Speech and language recognition algorithms now aid translation and transcription processes and vice versa. This combination of previously distinct processes has produced significant research and performance breakthroughs and has fundamentally changed the natural language processing and machine translation fields. This comprehensive handbook provides an exhaustive exploration into these latest technologies in natural language, speech and signal processing, and machine translation, providing researchers, practitioners and students with an authoritative reference on the topic.
Download or read book Deep Learning in Natural Language Processing written by Li Deng and published by Springer. This book was released on 2018-05-23 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, deep learning has fundamentally changed the landscapes of a number of areas in artificial intelligence, including speech, vision, natural language, robotics, and game playing. In particular, the striking success of deep learning in a wide variety of natural language processing (NLP) applications has served as a benchmark for the advances in one of the most important tasks in artificial intelligence. This book reviews the state of the art of deep learning research and its successful applications to major NLP tasks, including speech recognition and understanding, dialogue systems, lexical analysis, parsing, knowledge graphs, machine translation, question answering, sentiment analysis, social computing, and natural language generation from images. Outlining and analyzing various research frontiers of NLP in the deep learning era, it features self-contained, comprehensive chapters written by leading researchers in the field. A glossary of technical terms and commonly used acronyms in the intersection of deep learning and NLP is also provided. The book appeals to advanced undergraduate and graduate students, post-doctoral researchers, lecturers and industrial researchers, as well as anyone interested in deep learning and natural language processing.
Download or read book Natural Language Processing and Speech Technology written by Dafydd Gibbon and published by Walter de Gruyter GmbH & Co KG. This book was released on 2016-09-26 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Speaking written by Willem J. M. Levelt and published by MIT Press. This book was released on 1993-08-26 with total page 588 pages. Available in PDF, EPUB and Kindle. Book excerpt: In Speaking, Willem "Pim" Levelt, Director of the Max-Planck-Institut für Psycholinguistik, accomplishes the formidable task of covering the entire process of speech production, from constraints on conversational appropriateness to articulation and self-monitoring of speech. Speaking is unique in its balanced coverage of all major aspects of the production of speech, in the completeness of its treatment of the entire speech process, and in its strategy of exemplifying rather than formalizing theoretical issues.
Download or read book Natural Language Processing and Computational Linguistics written by Mohamed Zakaria Kurdi and published by John Wiley & Sons. This book was released on 2016-08-22 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: Natural language processing (NLP) is a scientific discipline which is found at the interface of computer science, artificial intelligence and cognitive psychology. Providing an overview of international work in this interdisciplinary field, this book gives the reader a panoramic view of both early and current research in NLP. Carefully chosen multilingual examples present the state of the art of a mature field which is in a constant state of evolution. In four chapters, this book presents the fundamental concepts of phonetics and phonology and the two most important applications in the field of speech processing: recognition and synthesis. Also presented are the fundamental concepts of corpus linguistics and the basic concepts of morphology and its NLP applications such as stemming and part of speech tagging. The fundamental notions and the most important syntactic theories are presented, as well as the different approaches to syntactic parsing with reference to cognitive models, algorithms and computer applications.
Download or read book Foundations of Statistical Natural Language Processing written by Christopher Manning and published by MIT Press. This book was released on 1999-05-28 with total page 719 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical approaches to processing natural language text have become dominant in recent years. This foundational text is the first comprehensive introduction to statistical natural language processing (NLP) to appear. The book contains all the theory and algorithms needed for building NLP tools. It provides broad but rigorous coverage of mathematical and linguistic foundations, as well as detailed discussion of statistical methods, allowing students and researchers to construct their own implementations. The book covers collocation finding, word sense disambiguation, probabilistic parsing, information retrieval, and other applications.
Download or read book Speech and Language Processing written by Dan Jurafsky and published by Prentice Hall. This book was released on 2009 with total page 1027 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book takes an empirical approach to language processing, based on applying statistical and other machine-learning algorithms to large corpora. Methodology boxes are included in each chapter. Each chapter is built around one or more worked examples to demonstrate the main idea of the chapter. Covers the fundamental algorithms of various fields, whether originally proposed for spoken or written language to demonstrate how the same algorithm can be used for speech recognition and word-sense disambiguation. Emphasis on web and other practical applications. Emphasis on scientific evaluation. Useful as a reference for professionals in any of the areas of speech and language processing.
Download or read book Practical Natural Language Processing written by Sowmya Vajjala and published by O'Reilly Media. This book was released on 2020-06-17 with total page 455 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many books and courses tackle natural language processing (NLP) problems with toy use cases and well-defined datasets. But if you want to build, iterate, and scale NLP systems in a business setting and tailor them for particular industry verticals, this is your guide. Software engineers and data scientists will learn how to navigate the maze of options available at each step of the journey. Through the course of the book, authors Sowmya Vajjala, Bodhisattwa Majumder, Anuj Gupta, and Harshit Surana will guide you through the process of building real-world NLP solutions embedded in larger product setups. You’ll learn how to adapt your solutions for different industry verticals such as healthcare, social media, and retail. With this book, you’ll: Understand the wide spectrum of problem statements, tasks, and solution approaches within NLP Implement and evaluate different NLP applications using machine learning and deep learning methods Fine-tune your NLP solution based on your business problem and industry vertical Evaluate various algorithms and approaches for NLP product tasks, datasets, and stages Produce software solutions following best practices around release, deployment, and DevOps for NLP systems Understand best practices, opportunities, and the roadmap for NLP from a business and product leader’s perspective
Download or read book Multilingual Natural Language Processing Applications written by Daniel Bikel and published by IBM Press. This book was released on 2012-05-11 with total page 829 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multilingual Natural Language Processing Applications is the first comprehensive single-source guide to building robust and accurate multilingual NLP systems. Edited by two leading experts, it integrates cutting-edge advances with practical solutions drawn from extensive field experience. Part I introduces the core concepts and theoretical foundations of modern multilingual natural language processing, presenting today’s best practices for understanding word and document structure, analyzing syntax, modeling language, recognizing entailment, and detecting redundancy. Part II thoroughly addresses the practical considerations associated with building real-world applications, including information extraction, machine translation, information retrieval/search, summarization, question answering, distillation, processing pipelines, and more. This book contains important new contributions from leading researchers at IBM, Google, Microsoft, Thomson Reuters, BBN, CMU, University of Edinburgh, University of Washington, University of North Texas, and others. Coverage includes Core NLP problems, and today’s best algorithms for attacking them Processing the diverse morphologies present in the world’s languages Uncovering syntactical structure, parsing semantics, using semantic role labeling, and scoring grammaticality Recognizing inferences, subjectivity, and opinion polarity Managing key algorithmic and design tradeoffs in real-world applications Extracting information via mention detection, coreference resolution, and events Building large-scale systems for machine translation, information retrieval, and summarization Answering complex questions through distillation and other advanced techniques Creating dialog systems that leverage advances in speech recognition, synthesis, and dialog management Constructing common infrastructure for multiple multilingual text processing applications This book will be invaluable for all engineers, software developers, researchers, and graduate students who want to process large quantities of text in multiple languages, in any environment: government, corporate, or academic.
Download or read book Essential Speech and Language Technology for Dutch written by Peter Spyns and published by Springer Science & Business Media. This book was released on 2013-02-26 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book provides an overview of more than a decade of joint R&D efforts in the Low Countries on HLT for Dutch. It not only presents the state of the art of HLT for Dutch in the areas covered, but, even more importantly, a description of the resources (data and tools) for Dutch that have been created are now available for both academia and industry worldwide. The contributions cover many areas of human language technology (for Dutch): corpus collection (including IPR issues) and building (in particular one corpus aiming at a collection of 500M word tokens), lexicology, anaphora resolution, a semantic network, parsing technology, speech recognition, machine translation, text (summaries) generation, web mining, information extraction, and text to speech to name the most important ones. The book also shows how a medium-sized language community (spanning two territories) can create a digital language infrastructure (resources, tools, etc.) as a basis for subsequent R&D. At the same time, it bundles contributions of almost all the HLT research groups in Flanders and the Netherlands, hence offers a view of their recent research activities. Targeted readers are mainly researchers in human language technology, in particular those focusing on Dutch. It concerns researchers active in larger networks such as the CLARIN, META-NET, FLaReNet and participating in conferences such as ACL, EACL, NAACL, COLING, RANLP, CICling, LREC, CLIN and DIR ( both in the Low Countries), InterSpeech, ASRU, ICASSP, ISCA, EUSIPCO, CLEF, TREC, etc. In addition, some chapters are interesting for human language technology policy makers and even for science policy makers in general.
Download or read book Finite state Language Processing written by Emmanuel Roche and published by MIT Press. This book was released on 1997 with total page 494 pages. Available in PDF, EPUB and Kindle. Book excerpt: Finite-state devices, such as finite-state automata, graphs, and finite-state transducers, have been present since the emergence of computer science and are extensively used in areas as various as program compilation, hardware modeling, and database management. Although finite-state devices have been known for some time in computational linguistics, more powerful formalisms such as context-free grammars or unification grammars have typically been preferred. Recent mathematical and algorithmic results in the field of finite-state technology have had a great impact on the representation of electronic dictionaries and on natural language processing, resulting in a new technology for language emerging out of both industrial and academic research. This book presents a discussion of fundamental finite-state algorithms, and constitutes an approach from the perspective of natural language processing.
