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Author : Michael Hammond
Publisher : Cambridge University Press
Page : 313 pages
File Size : 54,8 Mb
Release : 2020-05-07
Category : Computers
ISBN : 9781108493444
An introduction to Python programming for linguists. Examples of code specifically designed for language analysis are featured throughout.
Author : Guido Van Rossum,Fred L. Drake Jr
Publisher : Network Theory.
Page : 164 pages
File Size : 53,6 Mb
Release : 2011-03
Category : Python (Computer program language)
ISBN : 1906966133
"This manual is part of the official reference documentation for Python, an object-oriented programming language created by Guido van Rossum. Python is free software. The term “free software” refers to your freedom to run, copy, distribute, study, change and improve the software. With Python you have all these freedoms. You can support free software by becoming an associate member of the Free Software Foundation. The Free Software Foundation is a tax-exempt charity dedicated to promoting the right to use, study, copy, modify, and redistribute computer programs. It also helps to spread awareness of the ethical and political issues of freedom in the use of software. For more information visit the website www.fsf.org. The development of Python itself is supported by the Python Software Foundation. Companies using Python can invest in the language by becoming sponsoring members of this group. Donations can also be made online through the Python website. Further information is available at http://www.python.org/psf/."--Page 1.
Author : Martin Weisser
Publisher : John Wiley & Sons
Page : 295 pages
File Size : 43,6 Mb
Release : 2024-01-31
Category : Computers
ISBN : 9781119907947
Learn how to use Python for linguistics and digital humanities research, perfect for students working with Python for the first time Python programming is no longer only for computer science students; it is now an essential skill in linguistics, the digital humanities (DH), and social science programs that involve text analytics. Python Programming for Linguistics and Digital Humanities provides a comprehensive introduction to this widely used programming language, offering guidance on using Python to perform various processing and analysis techniques on text. Assuming no prior knowledge of programming, this student-friendly guide covers essential topics and concepts such as installing Python, using the command line, working with strings, writing modular code, designing a simple graphical user interface (GUI), annotating language data in XML and TEI, creating basic visualizations, and more. This invaluable text explains the basic tools students will need to perform their own research projects and tackle various data analysis problems. Throughout the book, hands-on exercises provide students with the opportunity to apply concepts to particular questions or projects in processing textual data and solving language-related issues. Each chapter concludes with a detailed discussion of the code applied, possible alternatives, and potential pitfalls or error messages. Teaches students how to use Python to tackle the types of problems they will encounter in linguistics and the digital humanities Features numerous practical examples of language analysis, gradually moving from simple concepts and programs to more complex projects Describes how to build a variety of data visualizations, such as frequency plots and word clouds Focuses on the text processing applications of Python, including creating word and frequency lists, recognizing linguistic patterns, and processing words for morphological analysis Includes access to a companion website with all Python programs produced in the chapter exercises and additional Python programming resources Python Programming for Linguistics and Digital Humanities: Applications for Text-Focused Fields is a must-have resource for students pursuing text-based research in the humanities, the social sciences, and all subfields of linguistics, particularly computational linguistics and corpus linguistics.
Author : Steven Bird,Ewan Klein,Edward Loper
Publisher : "O'Reilly Media, Inc."
Page : 506 pages
File Size : 41,6 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 : Steven Moran,Michael Cysouw
Publisher : Language Science Press
Page : 145 pages
File Size : 45,6 Mb
Release : 2018-06-29
Category : Language Arts & Disciplines
ISBN : 9783961100903
This text is a practical guide for linguists, and programmers, who work with data in multilingual computational environments. We introduce the basic concepts needed to understand how writing systems and character encodings function, and how they work together at the intersection between the Unicode Standard and the International Phonetic Alphabet. Although these standards are often met with frustration by users, they nevertheless provide language researchers and programmers with a consistent computational architecture needed to process, publish and analyze lexical data from the world's languages. Thus we bring to light common, but not always transparent, pitfalls which researchers face when working with Unicode and IPA. Having identified and overcome these pitfalls involved in making writing systems and character encodings syntactically and semantically interoperable (to the extent that they can be), we created a suite of open-source Python and R tools to work with languages using orthography profiles that describe author- or document-specific orthographic conventions. In this cookbook we describe a formal specification of orthography profiles and provide recipes using open source tools to show how users can segment text, analyze it, identify errors, and to transform it into different written forms for comparative linguistics research. This book is a prime example of open publishing as envisioned by Language Science Press. It is open access, has accompanying open source software, has open peer review, versioning and so on. Read more in this blog post.
Author : Mark Johnson
Publisher : Wiley-Blackwell
Page : 208 pages
File Size : 53,7 Mb
Release : 2008
Category : Computers
ISBN : 1405145641
Linguistic research increasingly relies on large electronic corpora for its primary data. While off-the-shelf programs can perform a set of standard searches, specialized questions usually require a custom-written program to find their answers. Essential Python for Corpus Linguistics uses the programming language Python to explain how to write simple programs that extract linguistically useful information, such as the frequency of a given utterance in a particular context within a corpus, or instances of certain phrasal structures in a Treebank. Assuming no prior programming background, the book provides numerous example programs that search for phonological, morphological and syntactic constructions in corpora, and the associated web site provides sample data and programs, which make it easy to start working independently. This book is a valuable resource for linguists who use corpus methods but have no programming training.
Author : Michael Hammond
Publisher : John Wiley & Sons
Page : 232 pages
File Size : 48,9 Mb
Release : 2008-04-15
Category : Language Arts & Disciplines
ISBN : 9780470752227
This book is an introduction to the rudiments of Perl programming. It provides the general reader with an interest in language with the most usable and relevant aspects of Perl for writing programs that deal with language. Exposes the general reader with an interest in language to the most usable and relevant aspects of Perl for writing programs that deal with language. Contains simple examples and exercises that gradually introduce the reader to the essentials of good programming. Assumes no prior programming experience. Accompanied by exercises at the end of each chapter and offers all the code on the companion website: http://www.u.arizona.edu/~hammond
Author : Adrian Brasoveanu,Jakub Dotlačil
Publisher : Springer Nature
Page : 299 pages
File Size : 51,8 Mb
Release : 2020-01-01
Category : Language and languages
ISBN : 9783030318468
This open access book introduces a general framework that allows natural language researchers to enhance existing competence theories with fully specified performance and processing components. Gradually developing increasingly complex and cognitively realistic competence-performance models, it provides running code for these models and shows how to fit them to real-time experimental data. This computational cognitive modeling approach opens up exciting new directions for research in formal semantics, and linguistics more generally, and offers new ways of (re)connecting semantics and the broader field of cognitive science. The approach of this book is novel in more ways than one. Assuming the mental architecture and procedural modalities of Anderson's ACT-R framework, it presents fine-grained computational models of human language processing tasks which make detailed quantitative predictions that can be checked against the results of self-paced reading and other psycho-linguistic experiments. All models are presented as computer programs that readers can run on their own computer and on inputs of their choice, thereby learning to design, program and run their own models. But even for readers who won't do all that, the book will show how such detailed, quantitatively predicting modeling of linguistic processes is possible. A methodological breakthrough and a must for anyone concerned about the future of linguistics! (Hans Kamp) This book constitutes a major step forward in linguistics and psycholinguistics. It constitutes a unique synthesis of several different research traditions: computational models of psycholinguistic processes, and formal models of semantics and discourse processing. The work also introduces a sophisticated python-based software environment for modeling linguistic processes. This book has the potential to revolutionize not only formal models of linguistics, but also models of language processing more generally. (Shravan Vasishth) .
Author : Marjorie Mcshane,Sergei Nirenburg
Publisher : MIT Press
Page : 449 pages
File Size : 40,6 Mb
Release : 2021-03-02
Category : Computers
ISBN : 9780262362603
A human-inspired, linguistically sophisticated model of language understanding for intelligent agent systems. One of the original goals of artificial intelligence research was to endow intelligent agents with human-level natural language capabilities. Recent AI research, however, has focused on applying statistical and machine learning approaches to big data rather than attempting to model what people do and how they do it. In this book, Marjorie McShane and Sergei Nirenburg return to the original goal of recreating human-level intelligence in a machine. They present a human-inspired, linguistically sophisticated model of language understanding for intelligent agent systems that emphasizes meaning--the deep, context-sensitive meaning that a person derives from spoken or written language.
Author : Benjamin Bengfort,Rebecca Bilbro,Tony Ojeda
Publisher : "O'Reilly Media, Inc."
Page : 332 pages
File Size : 42,7 Mb
Release : 2018-06-11
Category : Computers
ISBN : 9781491962992
From news and speeches to informal chatter on social media, natural language is one of the richest and most underutilized sources of data. Not only does it come in a constant stream, always changing and adapting in context; it also contains information that is not conveyed by traditional data sources. The key to unlocking natural language is through the creative application of text analytics. This practical book presents a data scientist’s approach to building language-aware products with applied machine learning. You’ll learn robust, repeatable, and scalable techniques for text analysis with Python, including contextual and linguistic feature engineering, vectorization, classification, topic modeling, entity resolution, graph analysis, and visual steering. By the end of the book, you’ll be equipped with practical methods to solve any number of complex real-world problems. Preprocess and vectorize text into high-dimensional feature representations Perform document classification and topic modeling Steer the model selection process with visual diagnostics Extract key phrases, named entities, and graph structures to reason about data in text Build a dialog framework to enable chatbots and language-driven interaction Use Spark to scale processing power and neural networks to scale model complexity
Author : Cem Bozsahin
Publisher : Walter de Gruyter
Page : 304 pages
File Size : 49,7 Mb
Release : 2012-12-06
Category : Language Arts & Disciplines
ISBN : 9783110296877
The book examines to what extent the mediating relation between constituents and their semantics can arise from combinatory knowledge of words. It traces the roots of Combinatory Categorial Grammar, and uses the theory to promote a Humean question in linguistics and cognitive science: Why do we see limited constituency and dependency in natural languages, despite their diversity and potential infinity? A potential answer is that constituents and dependencies might have arisen from a single resource: adjacency. The combinatory formulation of adjacency constrains possible grammars.
Author : R. H. Baayen
Publisher : Cambridge University Press
Page : 40 pages
File Size : 47,9 Mb
Release : 2008-03-06
Category : Language Arts & Disciplines
ISBN : 9781139470735
Statistical analysis is a useful skill for linguists and psycholinguists, allowing them to understand the quantitative structure of their data. This textbook provides a straightforward introduction to the statistical analysis of language. Designed for linguists with a non-mathematical background, it clearly introduces the basic principles and methods of statistical analysis, using 'R', the leading computational statistics programme. The reader is guided step-by-step through a range of real data sets, allowing them to analyse acoustic data, construct grammatical trees for a variety of languages, quantify register variation in corpus linguistics, and measure experimental data using state-of-the-art models. The visualization of data plays a key role, both in the initial stages of data exploration and later on when the reader is encouraged to criticize various models. Containing over 40 exercises with model answers, this book will be welcomed by all linguists wishing to learn more about working with and presenting quantitative data.
Author : Rajesh Arumugam,Rajalingappaa Shanmugamani
Publisher : Packt Publishing Ltd
Page : 307 pages
File Size : 41,6 Mb
Release : 2018-07-18
Category : Computers
ISBN : 9781789135916
Foster your NLP applications with the help of deep learning, NLTK, and TensorFlow Key Features Weave neural networks into linguistic applications across various platforms Perform NLP tasks and train its models using NLTK and TensorFlow Boost your NLP models with strong deep learning architectures such as CNNs and RNNs Book Description Natural language processing (NLP) has found its application in various domains, such as web search, advertisements, and customer services, and with the help of deep learning, we can enhance its performances in these areas. Hands-On Natural Language Processing with Python teaches you how to leverage deep learning models for performing various NLP tasks, along with best practices in dealing with today’s NLP challenges. To begin with, you will understand the core concepts of NLP and deep learning, such as Convolutional Neural Networks (CNNs), recurrent neural networks (RNNs), semantic embedding, Word2vec, and more. You will learn how to perform each and every task of NLP using neural networks, in which you will train and deploy neural networks in your NLP applications. You will get accustomed to using RNNs and CNNs in various application areas, such as text classification and sequence labeling, which are essential in the application of sentiment analysis, customer service chatbots, and anomaly detection. You will be equipped with practical knowledge in order to implement deep learning in your linguistic applications using Python's popular deep learning library, TensorFlow. By the end of this book, you will be well versed in building deep learning-backed NLP applications, along with overcoming NLP challenges with best practices developed by domain experts. What you will learn Implement semantic embedding of words to classify and find entities Convert words to vectors by training in order to perform arithmetic operations Train a deep learning model to detect classification of tweets and news Implement a question-answer model with search and RNN models Train models for various text classification datasets using CNN Implement WaveNet a deep generative model for producing a natural-sounding voice Convert voice-to-text and text-to-voice Train a model to convert speech-to-text using DeepSpeech Who this book is for Hands-on Natural Language Processing with Python is for you if you are a developer, machine learning or an NLP engineer who wants to build a deep learning application that leverages NLP techniques. This comprehensive guide is also useful for deep learning users who want to extend their deep learning skills in building NLP applications. All you need is the basics of machine learning and Python to enjoy the book.
Author : Martin Weisser
Publisher : John Wiley & Sons
Page : 306 pages
File Size : 49,5 Mb
Release : 2016-02-16
Category : Language Arts & Disciplines
ISBN : 9781118831885
This is the first book of its kind to provide a practical and student-friendly guide to corpus linguistics that explains the nature of electronic data and how it can be collected and analyzed. Designed to equip readers with the technical skills necessary to analyze and interpret language data, both written and (orthographically) transcribed Introduces a number of easy-to-use, yet powerful, free analysis resources consisting of standalone programs and web interfaces for use with Windows, Mac OS X, and Linux Each section includes practical exercises, a list of sources and further reading, and illustrated step-by-step introductions to analysis tools Requires only a basic knowledge of computer concepts in order to develop the specific linguistic analysis skills required for understanding/analyzing corpus data
Author : Dragomir Radev
Publisher : Springer Science & Business Media
Page : 208 pages
File Size : 49,9 Mb
Release : 2013-02-11
Category : Language Arts & Disciplines
ISBN : 9783642343728
This is the second volume of a unique collection that brings together the best English-language problems created for students competing in the Computational Linguistics Olympiad. These problems are representative of the diverse areas presented in the competition and designed with three principles in mind: · To challenge the student analytically, without requiring any explicit knowledge or experience in linguistics or computer science; · To expose the student to the different kinds of reasoning required when encountering a new phenomenon in a language, both as a theoretical topic and as an applied problem; · To foster the natural curiosity students have about the workings of their own language, as well as to introduce them to the beauty and structure of other languages; · To learn about the models and techniques used by computers to understand human language. Aside from being a fun intellectual challenge, the Olympiad mimics the skills used by researchers and scholars in the field of computational linguistics. In an increasingly global economy where businesses operate across borders and languages, having a strong pool of computational linguists is a competitive advantage, and an important component to both security and growth in the 21st century. This collection of problems is a wonderful general introduction to the field of linguistics through the analytic problem solving technique. "A fantastic collection of problems for anyone who is curious about how human language works! These books take serious scientific questions and present them in a fun, accessible way. Readers exercise their logical thinking capabilities while learning about a wide range of human languages, linguistic phenomena, and computational models. " - Kevin Knight, USC Information Sciences Institute