Speech & Language Processing
Author | : Dan Jurafsky |
Publisher | : Pearson Education India |
Total Pages | : 912 |
Release | : 2000-09 |
Genre | : |
ISBN | : 9788131716724 |
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Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Language Processing In Discourse PDF full book. Access full book title Language Processing In Discourse.
Author | : Dan Jurafsky |
Publisher | : Pearson Education India |
Total Pages | : 912 |
Release | : 2000-09 |
Genre | : |
ISBN | : 9788131716724 |
Author | : Monika Doherty |
Publisher | : Routledge |
Total Pages | : 321 |
Release | : 2003-09-02 |
Genre | : Language Arts & Disciplines |
ISBN | : 1134460562 |
This book argues that language systems determine language use to a greater extent than is generally assumed. The author demonstrates how the typological characteristics of a language determine even the most general aspects of our stylistic preferences. Through extensive analysis of examples in German and English, the author demonstrates how analogous options of sentence structure must be surrendered in order to achieve felicitous translations. Two major aspects that determine the appropriateness of language use are examined: language processing and discourse-dependency. Essential reading for translation scholars and linguists involved in the comparative study of English and German, this book will also be of interest to scholars of psycholinguistics and cognitive science, as well as translators and linguists more generally.
Author | : Manfred Stede |
Publisher | : Morgan & Claypool Publishers |
Total Pages | : 168 |
Release | : 2012 |
Genre | : Computers |
ISBN | : 1608457346 |
Discourse Processing here is framed as marking up a text with structural descriptions on several levels, which can serve to support many language-processing or text-mining tasks. We first explore some ways of assigning structure on the document level: the logical document structure as determined by the layout of the text, its genre-specific content structure, and its breakdown into topical segments. Then the focus moves to phenomena of local coherence. We introduce the problem of coreference and look at methods for building chains of coreferring entities in the text. Next, the notion of coherence relation is introduced as the second important factor of local coherence. We study the role of connectives and other means of signaling such relations in text, and then return to the level of larger textual units, where tree or graph structures can be ascribed by recursively assigning coherence relations. Taken together, these descriptions can inform text summarization, information extraction, discourse-aware sentiment analysis, question answering, and the like. Table of Contents: Introduction / Large Discourse Units and Topics / Coreference Resolution / Small Discourse Units and Coherence Relations / Summary: Text Structure on Multiple Interacting Levels
Author | : Nitin Hardeniya |
Publisher | : Packt Publishing Ltd |
Total Pages | : 687 |
Release | : 2016-11-22 |
Genre | : Computers |
ISBN | : 178728784X |
Learn to build expert NLP and machine learning projects using NLTK and other Python libraries About This Book Break text down into its component parts for spelling correction, feature extraction, and phrase transformation Work through NLP concepts with simple and easy-to-follow programming recipes Gain insights into the current and budding research topics of NLP Who This Book Is For If you are an NLP or machine learning enthusiast and an intermediate Python programmer who wants to quickly master NLTK for natural language processing, then this Learning Path will do you a lot of good. Students of linguistics and semantic/sentiment analysis professionals will find it invaluable. What You Will Learn The scope of natural language complexity and how they are processed by machines Clean and wrangle text using tokenization and chunking to help you process data better Tokenize text into sentences and sentences into words Classify text and perform sentiment analysis Implement string matching algorithms and normalization techniques Understand and implement the concepts of information retrieval and text summarization Find out how to implement various NLP tasks in Python In Detail Natural Language Processing is a field of computational linguistics and artificial intelligence that deals with human-computer interaction. It provides a seamless interaction between computers and human beings and gives computers the ability to understand human speech with the help of machine learning. The number of human-computer interaction instances are increasing so it's becoming imperative that computers comprehend all major natural languages. The first NLTK Essentials module is an introduction on how to build systems around NLP, with a focus on how to create a customized tokenizer and parser from scratch. You will learn essential concepts of NLP, be given practical insight into open source tool and libraries available in Python, shown how to analyze social media sites, and be given tools to deal with large scale text. This module also provides a workaround using some of the amazing capabilities of Python libraries such as NLTK, scikit-learn, pandas, and NumPy. The second Python 3 Text Processing with NLTK 3 Cookbook module teaches you the essential techniques of text and language processing with simple, straightforward examples. This includes organizing text corpora, creating your own custom corpus, text classification with a focus on sentiment analysis, and distributed text processing methods. The third Mastering Natural Language Processing with Python module will help you become an expert and assist you in creating your own NLP projects using NLTK. You will be guided through model development with machine learning tools, shown how to create training data, and given insight into the best practices for designing and building NLP-based applications using Python. This Learning Path combines some of the best that Packt has to offer in one complete, curated package and is designed to help you quickly learn text processing with Python and NLTK. It includes content from the following Packt products: NTLK essentials by Nitin Hardeniya Python 3 Text Processing with NLTK 3 Cookbook by Jacob Perkins Mastering Natural Language Processing with Python by Deepti Chopra, Nisheeth Joshi, and Iti Mathur Style and approach This comprehensive course creates a smooth learning path that teaches you how to get started with Natural Language Processing using Python and NLTK. You'll learn to create effective NLP and machine learning projects using Python and NLTK.
Author | : Dafydd Gibbon |
Publisher | : Walter de Gruyter GmbH & Co KG |
Total Pages | : 416 |
Release | : 2016-09-26 |
Genre | : Language Arts & Disciplines |
ISBN | : 3110821893 |
Author | : Ela Kumar |
Publisher | : I. K. International Pvt Ltd |
Total Pages | : 220 |
Release | : 2013-12-30 |
Genre | : Computers |
ISBN | : 9380578776 |
Covers all aspects of the area of linguistic analysis and the computational systems that have been developed to perform the language analysis. The book is primarily meant for post graduate and undergraduate technical courses.
Author | : Mohamed Zakaria Kurdi |
Publisher | : John Wiley & Sons |
Total Pages | : 296 |
Release | : 2016-08-22 |
Genre | : Technology & Engineering |
ISBN | : 1848218486 |
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.
Author | : Dan Jurafsky |
Publisher | : Prentice Hall |
Total Pages | : 1027 |
Release | : 2009 |
Genre | : Automatic speech recognition |
ISBN | : 0131873210 |
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 | : Xuedong Huang |
Publisher | : Prentice Hall |
Total Pages | : 1018 |
Release | : 2001 |
Genre | : Computers |
ISBN | : |
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 | : A. Flammer |
Publisher | : Elsevier |
Total Pages | : 625 |
Release | : 2000-04-01 |
Genre | : Psychology |
ISBN | : 008086662X |
Research on discourse (or text) processing has only recently come into its own. It builds on the work of text analysis which has a long and distinguished history, but modern developments in psychology (e.g. memory research), artificial intelligence, linguistics and philosophy have contributed to this emergence in the last decade as a lively and promising research area. This book contains 46 selected and edited contributions from the International Symposium held in Fribourg in 1981, and represents a truly international overview of the developments in research on written and oral discourse. The contributions have been grouped according to problem area and not according to methodology, with the intention of focusing on the important issues in the field of discourse processing and of showing how diverse approaches contribute to a better understanding of the problems involved. The main themes are: text structure, coherence, inference, memory processes, attention and control, goal perspectives, and educational implications.