Speech & Language Processing PDF Download

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

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Author: Masaru Tomita
Publisher: Springer Science & Business Media
ISBN: 1475718853
Category : Computers
Languages : en
Pages : 209

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Book Description
Parsing Efficiency is crucial when building practical natural language systems. 'Ibis is especially the case for interactive systems such as natural language database access, interfaces to expert systems and interactive machine translation. Despite its importance, parsing efficiency has received little attention in the area of natural language processing. In the areas of compiler design and theoretical computer science, on the other hand, parsing algorithms 3 have been evaluated primarily in terms of the theoretical worst case analysis (e.g. lXn», and very few practical comparisons have been made. This book introduces a context-free parsing algorithm that parses natural language more efficiently than any other existing parsing algorithms in practice. Its feasibility for use in practical systems is being proven in its application to Japanese language interface at Carnegie Group Inc., and to the continuous speech recognition project at Carnegie-Mellon University. This work was done while I was pursuing a Ph.D degree at Carnegie-Mellon University. My advisers, Herb Simon and Jaime Carbonell, deserve many thanks for their unfailing support, advice and encouragement during my graduate studies. I would like to thank Phil Hayes and Ralph Grishman for their helpful comments and criticism that in many ways improved the quality of this book. I wish also to thank Steven Brooks for insightful comments on theoretical aspects of the book (chapter 4, appendices A, B and C), and Rich Thomason for improving the linguistic part of tile book (the very beginning of section 1.1).

Author: Christopher Manning
Publisher: MIT Press
ISBN: 0262303795
Category : Language Arts & Disciplines
Languages : en
Pages : 719

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Book Description
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: Geert Adriaens
Publisher: Intellect Books
ISBN:
Category : Computers
Languages : en
Pages : 490

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Book Description
Parallel processing is not only a general topic of interest for computer scientists and researchers in artificial intelligence, but it is gaining more and more attention in the community of scientists studying natural language and its processing (computational linguists, AI researchers, psychologists). The growing need to integrate large divergent bodies of knowledge in natural language processing applications, or the belief that massively parallel systems are the only ones capable of handling the complexities and subtleties of natural language, are just two examples of the reasons for this increasing interest.

Author: Steven Bird
Publisher: "O'Reilly Media, Inc."
ISBN: 0596555717
Category : Computers
Languages : en
Pages : 506

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Book Description
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: Leonard Bolc
Publisher: Springer Science & Business Media
ISBN: 3642830307
Category : Computers
Languages : en
Pages : 381

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Book Description
Up to now there has been no scientific publication on natural lan guage research that presents a broad and complex description of the current problems of parsing in the context of Artificial Intelli gence. However, there are many interesting results from this domain appearing mainly in numerous articles published in pro fessional journals. In view of this situation, the objective of this book is to enable scientists from different countries to present the results of their research on natural language parsing in the form of more detailed papers than would be possible in professional jour nals. This book thus provides a collection of studies written by well known scientists whose earlier publications have greatly contributed to the development of research on natural language parsing. Jaime G. Carbonell and Philip J. Hayes present in their paper "Robust Parsing Using Multiple Construction-Specific Strategies" two small experimental parsers, implemented to illustrate the advantages of a multi-strategy approach to parsers, with strategies selected according to the type of construction being parsed at any given time. This presentation is followed by the description of a parsing algorithm, integrating some of the best features of the two smaller parsers, including case-frame instantiation and partial pat tern-matching strategies.

Author: Daniel Bikel
Publisher: IBM Press
ISBN: 0137047819
Category : Business & Economics
Languages : en
Pages : 829

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Book Description
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: David R. Dowty
Publisher: Cambridge University Press
ISBN: 9780521023108
Category : Language Arts & Disciplines
Languages : en
Pages : 428

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Book Description
This is a collection of new papers by leading researchers on natural language parsing. In the past, the problem of how people parse the sentences they hear - determine the identity of the words in these sentences and group these words into larger units - has been addressed in very different ways by experimental psychologists, by theoretical linguists, and by researchers in artificial intelligence, with little apparent relationship among the solutions proposed by each group. However, because of important advances in all these disciplines, research on parsing in each of these fields now seems to have something significant to contribute to the others, as this volume demonstrates. The volume includes some papers applying the results of experimental psychological studies of parsing to linguistic theory, others which present computational models of parsing, and a mathematical linguistics paper on tree-adjoining grammars and parsing.

Author: Li Deng
Publisher: Springer
ISBN: 9811052093
Category : Computers
Languages : en
Pages : 329

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Book Description
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.

Author: Yue Zhang
Publisher: Cambridge University Press
ISBN: 1108420214
Category : Computers
Languages : en
Pages : 487

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Book Description
This undergraduate textbook introduces essential machine learning concepts in NLP in a unified and gentle mathematical framework.