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Framing Sustainability in Language and Communication
This collection brings together established and emerging scholars for a critical framing of sustainability through the lens of language and communication, social semiotics, and media studies.The volume underscores the importance of re-envisioning sustainability around not only climate change and biodiversity loss but in broader systems of ecological, social, and economic imbalances on a global scale.The book begins with a visual essay which provides a semiotic foundation for understandings of sustainability across disciplinary approaches in the chapters that follow.Subsequent chapters are organized around four thematic parts: reframing sustainability in a colonial world; the semiotics of sustainability; communicating sustainability in everyday life; and sustainability communication in the arts.A closing commentary by Crispin Thurlow offers critical reflections on sustainability within language and communication research and beyond.This book will be of interest to scholars addressing sustainability across diverse disciplines, including language and communication, social semiotics, linguistic anthropology, environmental communication, media studies, and development studies.
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Natural Language Generation
In late 2022, the prominence of Natural Language Generation (NLG) surged with the advent of advanced language models like ChatGPT.While these developments have captivated both academic and commercial sectors, the focus has predominantly been on the latest innovations, often overlooking the rich history and foundational work in NLG.This book aims to provide a comprehensive overview of NLG, encompassing not only language models but also alternative approaches, user requirements, evaluation methods, safety and testing protocols, and practical applications.Drawing on decades of NLG research, the book is designed to be a valuable resource for both researchers and developers, offering insights that remain relevant far beyond the current technological landscape. Natural Language Generation focuses on data-to-text but also looks at other types of NLG including text summarization. The book takes a holistic approach to NLG, looking at requirements (what users are looking for), design, data issues, testing, evaluation, safety and ethical issues as well as technology. The holistic approach is unique to this book and is very valuable for people building real-world NLG systems, and for academics and researchers who are interested in applied NLG. The author, who previously co-authored a seminal NLG book in 2000, emphasizes high-level concepts and methodologies, ensuring the material's longevity and utility.The book is structured to balance technical depth with practical relevance, including chapters on rule-based and neural NLG approaches, user requirements, rigorous evaluation techniques, and safety considerations.Real-world applications, particularly in journalism, business intelligence, summarization, and medicine, are explored to illustrate NLG's potential and scalability.With personal anecdotes and examples from the author's experiences, this book provides a unique and engaging perspective on the evolving field of NLG, making it an indispensable guide for those looking to harness the power of language generation technologies.
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Getting Started with Natural Language Processing : A friendly introduction using Python
Getting Started with Natural Language Processing is a hands-on guide filled with everything you need to get started with NLP in a friendly, understandable tutorial.Full of Python code and hands-on projects, each chapter provides a concrete example with practical techniques that you can put into practice right away. By following the numerous Python-based examples and real-world case studies, you'll apply NLP to search applications, extracting meaning from text, sentiment analysis, user profiling, and more.When you're done, you'll have a solid grounding in NLP that will serve as a foundation for further learning. Key Features * Extracting information from raw text * Named entity recognition * Automating summarization of key facts * Topic labeling For beginners to NLP with basic Python skills. About the technology Natural Language Processing is a set of data science techniques that enable machines to make sense of human text and speech.Advances in machine learning and deep learning have made NLP more efficient and reliable than ever, leading to a huge number of new tools and resources.From improving search applications to sentiment analysis, the possible applications of NLP are vast and growing. Ekaterina Kochmar is an Affiliated Lecturer and a Senior Research Associate at the Natural Language and Information Processing group of the Department of Computer Science and Technology, University of Cambridge.She holds an MA degree in Computational Linguistics, an MPhil in Advanced Computer Science, and a PhD in Natural Language Processing.
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Neurolanguage Coaching : Brain Friendly Language Learning
Discover: - why the brain blocks when learning a language- which coaching and teaching methods are brain-friendly – and which are brain-zappers- how to harness principles of coaching and neuroscience to give your learner fantastic results, every time. It seems every day an exciting new discovery is made about the human brain.Neurolanguage Coaching is a model that brings together crucial findings in the fields of neuroscience and integrates these into a coaching process to revolutionise language learning as we know it. As well as highlighting evidence of interest to all practising and aspiring language coaches, this book offers invaluable insight distilled from years of coaching, and from teaching other coaches, giving practical advice to fit any coaching situation, and every highly unique brain. Within is also a toolkit full of new, tried-and-tested, brain-friendly Neurolanguage coaching models, as well as how and why applying these Neurolanguage Coaching techniques can lead to more happy, fluent and confident learners. This is a book for language teachers, educators, language learners, polyglots, coaches interested in languages and anyone who is interested to discover more about their own brain!
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Natural Language Processing with Python : Analyzing Text with the Natural Language Tool Kit
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.
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Real-World Natural Language Processing
Voice assistants, automated customer service agents, and other cutting-edge human-to-computer interactions rely on accurately interpreting language as it is written and spoken. Real-world Natural Language Processing teaches you how to create practical NLP applications without getting bogged down in complex language theory and the mathematics of deep learning.In this engaging book, you’ll explore the core tools and techniques required to build a huge range of powerful NLP apps. about the technologyNatural language processing is the part of AI dedicated to understanding and generating human text and speech.NLP covers a wide range of algorithms and tasks, from classic functions such as spell checkers, machine translation, and search engines to emerging innovations like chatbots, voice assistants, and automatic text summarization.Wherever there is text, NLP can be useful for extracting meaning and bridging the gap between humans and machines. about the book Real-world Natural Language Processing teaches you how to create practical NLP applications using Python and open source NLP libraries such as AllenNLP and Fairseq.In this practical guide, you’ll begin by creating a complete sentiment analyzer, then dive deep into each component to unlock the building blocks you’ll use in all different kinds of NLP programs.By the time you’re done, you’ll have the skills to create named entity taggers, machine translation systems, spelling correctors, and language generation systems. what's inside Design, develop, and deploy basic NLP applicationsNLP libraries such as AllenNLP and FairseqAdvanced NLP concepts such as attention and transfer learning about the readerAimed at intermediate Python programmers.No mathematical or machine learning knowledge required. about the author Masato Hagiwara received his computer science PhD from Nagoya University in 2009, focusing on Natural Language Processing and machine learning.He has interned at Google and Microsoft Research, and worked at Baidu Japan, Duolingo, and Rakuten Institute of Technology.He now runs his own consultancy business advising clients, including startups and research institutions.
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