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Author : Dan Jurafsky
Publisher : Pearson Education India
Page : 912 pages
File Size : 46,7 Mb
Release : 2000-09
Category : Electronic
ISBN : 8131716724
Author : Daniel Jurafsky,James H. Martin
Publisher : Unknown
Page : 934 pages
File Size : 49,6 Mb
Release : 2000-01
Category : Automatic speech recognition
ISBN : 013122798X
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.
Author : Dan Jurafsky,James H. Martin
Publisher : Unknown
Page : 934 pages
File Size : 54,8 Mb
Release : 2004
Category : Automatic speech recognition
ISBN : 8178085941
Author : Jacob Eisenstein
Publisher : MIT Press
Page : 535 pages
File Size : 47,9 Mb
Release : 2019-10-01
Category : Computers
ISBN : 9780262042840
A survey of computational methods for understanding, generating, and manipulating human language, which offers a synthesis of classical representations and algorithms with contemporary machine learning techniques. This textbook provides a technical perspective on natural language processing—methods for building computer software that understands, generates, and manipulates human language. It emphasizes contemporary data-driven approaches, focusing on techniques from supervised and unsupervised machine learning. The first section establishes a foundation in machine learning by building a set of tools that will be used throughout the book and applying them to word-based textual analysis. The second section introduces structured representations of language, including sequences, trees, and graphs. The third section explores different approaches to the representation and analysis of linguistic meaning, ranging from formal logic to neural word embeddings. The final section offers chapter-length treatments of three transformative applications of natural language processing: information extraction, machine translation, and text generation. End-of-chapter exercises include both paper-and-pencil analysis and software implementation. The text synthesizes and distills a broad and diverse research literature, linking contemporary machine learning techniques with the field's linguistic and computational foundations. It is suitable for use in advanced undergraduate and graduate-level courses and as a reference for software engineers and data scientists. Readers should have a background in computer programming and college-level mathematics. After mastering the material presented, students will have the technical skill to build and analyze novel natural language processing systems and to understand the latest research in the field.
Author : Christopher Manning,Hinrich Schutze
Publisher : MIT Press
Page : 719 pages
File Size : 50,6 Mb
Release : 1999-05-28
Category : Language Arts & Disciplines
ISBN : 9780262303798
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.
Author : Sowmya Vajjala,Bodhisattwa Majumder,Anuj Gupta,Harshit Surana
Publisher : O'Reilly Media
Page : 455 pages
File Size : 52,9 Mb
Release : 2020-06-17
Category : Computers
ISBN : 9781492054023
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
Author : Yue Zhang,Zhiyang Teng
Publisher : Cambridge University Press
Page : 487 pages
File Size : 50,6 Mb
Release : 2021-01-07
Category : Computers
ISBN : 9781108420211
This undergraduate textbook introduces essential machine learning concepts in NLP in a unified and gentle mathematical framework.
Author : Steven Bird,Ewan Klein,Edward Loper
Publisher : "O'Reilly Media, Inc."
Page : 506 pages
File Size : 42,5 Mb
Release : 2009-06-12
Category : Computers
ISBN : 9780596555719
This book offers a highly accessible introduction to natural language processing, the field that supports a variety of language technologies, from predictive text and email filtering to automatic summarization and translation. With it, you'll learn how to write Python programs that work with large collections of unstructured text. You'll access richly annotated datasets using a comprehensive range of linguistic data structures, and you'll understand the main algorithms for analyzing the content and structure of written communication. Packed with examples and exercises, Natural Language Processing with Python will help you: Extract information from unstructured text, either to guess the topic or identify "named entities" Analyze linguistic structure in text, including parsing and semantic analysis Access popular linguistic databases, including WordNet and treebanks Integrate techniques drawn from fields as diverse as linguistics and artificial intelligence This book will help you gain practical skills in natural language processing using the Python programming language and the Natural Language Toolkit (NLTK) open source library. If you're interested in developing web applications, analyzing multilingual news sources, or documenting endangered languages -- or if you're simply curious to have a programmer's perspective on how human language works -- you'll find Natural Language Processing with Python both fascinating and immensely useful.
Author : Xuedong Huang,Alejandro Acero,Hsiao-Wuen Hon
Publisher : Prentice Hall
Page : 1018 pages
File Size : 43,8 Mb
Release : 2001
Category : Computers
ISBN : UOM:39015051284142
Remarkable progress is being made in spoken language processing, but many powerful techniques have remained hidden in conference proceedings and academic papers, inaccessible to most practitioners. In this book, the leaders of the Speech Technology Group at Microsoft Research share these advances -- presenting not just the latest theory, but practical techniques for building commercially viable products.KEY TOPICS: Spoken Language Processing draws upon the latest advances and techniques from multiple fields: acoustics, phonology, phonetics, linguistics, semantics, pragmatics, computer science, electrical engineering, mathematics, syntax, psychology, and beyond. The book begins by presenting essential background on speech production and perception, probability and information theory, and pattern recognition. The authors demonstrate how to extract useful information from the speech signal; then present a variety of contemporary speech recognition techniques, including hidden Markov models, acoustic and language modeling, and techniques for improving resistance to environmental noise. Coverage includes decoders, search algorithms, large vocabulary speech recognition techniques, text-to-speech, spoken language dialog management, user interfaces, and interaction with non-speech interface modalities. The authors also present detailed case studies based on Microsoft's advanced prototypes, including the Whisper speech recognizer, Whistler text-to-speech system, and MiPad handheld computer.MARKET: For anyone involved with planning, designing, building, or purchasing spoken language technology.
Author : Daniel Bikel,Imed Zitouni
Publisher : IBM Press
Page : 829 pages
File Size : 44,8 Mb
Release : 2012-05-11
Category : Business & Economics
ISBN : 9780137047819
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.
Author : Peter Jackson,Isabelle Moulinier
Publisher : John Benjamins Publishing
Page : 243 pages
File Size : 44,5 Mb
Release : 2007-06-05
Category : Computers
ISBN : 9789027292445
This text covers the technologies of document retrieval, information extraction, and text categorization in a way which highlights commonalities in terms of both general principles and practical concerns. It assumes some mathematical background on the part of the reader, but the chapters typically begin with a non-mathematical account of the key issues. Current research topics are covered only to the extent that they are informing current applications; detailed coverage of longer term research and more theoretical treatments should be sought elsewhere. There are many pointers at the ends of the chapters that the reader can follow to explore the literature. However, the book does maintain a strong emphasis on evaluation in every chapter both in terms of methodology and the results of controlled experimentation.
Author : Robert Dale,Hermann Moisl,Harold Somers
Publisher : CRC Press
Page : 1015 pages
File Size : 46,7 Mb
Release : 2000-07-25
Category : Business & Economics
ISBN : 9780824746346
This study explores the design and application of natural language text-based processing systems, based on generative linguistics, empirical copus analysis, and artificial neural networks. It emphasizes the practical tools to accommodate the selected system.
Author : Delip Rao,Brian McMahan
Publisher : O'Reilly Media
Page : 256 pages
File Size : 47,8 Mb
Release : 2019-01-22
Category : Computers
ISBN : 9781491978207
Natural Language Processing (NLP) provides boundless opportunities for solving problems in artificial intelligence, making products such as Amazon Alexa and Google Translate possible. If you’re a developer or data scientist new to NLP and deep learning, this practical guide shows you how to apply these methods using PyTorch, a Python-based deep learning library. Authors Delip Rao and Brian McMahon provide you with a solid grounding in NLP and deep learning algorithms and demonstrate how to use PyTorch to build applications involving rich representations of text specific to the problems you face. Each chapter includes several code examples and illustrations. Explore computational graphs and the supervised learning paradigm Master the basics of the PyTorch optimized tensor manipulation library Get an overview of traditional NLP concepts and methods Learn the basic ideas involved in building neural networks Use embeddings to represent words, sentences, documents, and other features Explore sequence prediction and generate sequence-to-sequence models Learn design patterns for building production NLP systems
Author : Bronwen Patricia Dyson,Gisela Håkansson
Publisher : John Benjamins Publishing Company
Page : 211 pages
File Size : 46,7 Mb
Release : 2017-05-24
Category : Language Arts & Disciplines
ISBN : 9789027265876
This book aims to help researchers and teachers interested in language processing and Processability Theory (PT) to understand this theory and its applications. PT is an influential account of second language processing which hypothesizes that, due to the architecture of language processing, learners acquire second languages in developmental stages. This book lays out PT’s predictions and research on the development of diverse target languages – particularly English and Scandinavian languages – by learners of various categories. It discusses the typological issues facing PT and its contribution to an understanding of variation and cognitive constraints on pedagogy. However, the book also raises a critical eye to the literature which, after almost twenty years of evolution, requires explanation, clarification and, in some cases, extension. Why do some phenomena belong to different stages in different languages? Why are important types of variation under-represented? Is teaching as constrained as proposed in PT?
Author : Joseph Olive,Caitlin Christianson,John McCary
Publisher : Springer Science & Business Media
Page : 956 pages
File Size : 51,5 Mb
Release : 2011-03-02
Category : Computers
ISBN : 9781441977137
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.