Computational and corpus linguistics Books

Book SynopsisThis is the third, newly revised and extended edition of this successful book (that has already been translated into three languages). Like the previous editions, it is entirely based on the programming language and environment R and is still thoroughly hands-on (with thousands of lines of heavily annotated code for all computations and plots). However, this edition has been updated based on many workshops/bootcamps taught by the author all over the world for the past few years: This edition has been didactically streamlined with regard to its exposition, it adds two new chapters – one on mixed-effects modeling, one on classification and regression trees as well as random forests – plus it features new discussion of curvature, orthogonal and other contrasts, interactions, collinearity, the effects and emmeans packages, autocorrelation/runs, some more bits on programming, writing statistical functions, and simulations, and many practical tips based on 10 years of teaching with these materials.

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Book SynopsisThis handbook explores multiple facets of the study of word classes, also known as parts of speech or lexical categories. These categories are of fundamental importance to linguistic theory and description, both formal and functional, and for both language-internal analyses and cross-linguistic comparison. The volume consists of five parts that investigate word classes from different angles. Chapters in the first part address a range of fundamental issues including diversity and unity in word classes around the world, categorization at different levels of structure, the distinction between lexical and functional words, and hybrid categories. Part II examines the treatment of word classes across a wide range of contemporary linguistic theories, such as Cognitive Grammar, Minimalist Syntax, and Lexical Functional Grammar, while the focus of Part III is on individual word classes, from major categories such as verb and noun to minor ones such as adpositions and ideophones. Part IV provideTable of Contents1: Eva van Lier: Introduction Part I. Fundamental issues 2: Martin Haspelmath: Word class universals and language-particular analysis 3: Walter Bisang: Levels of analysis and word classes (root, stem, word) 4: Kasper Boye: Lexical versus functional words 5: Andrej L. Malchukov: Transcategorial operations 6: William A. Foley: Word class systems and other grammatical properties Part II. Theoretical approaches 7: Yoad Winter: Word classes in Formal Semantics 8: Cristiano Broccias: Word classes in Cognitive Grammar 9: Evelien Keizer: Word classes and gradience 10: J. Lachlan Mackenzie: Lexeme classes and word classes in Functional Discourse Grammar 11: William Croft: Word classes in Radical Construction Grammar 12: Hedde Zeijlstra: Word classes in Minimalist Syntax 13: Jan Don: Lexical categories in Distributed Morphology 14: Frank Van Eynde: Word classes in Head-driven Phrase Structure Grammar 15: Mary Dalrymple and Ida Toivonen: . Word classes in Lexical Functional Grammar Part III. Specific word classes 16: Alexander Letuchiy: Verbs 17: Jan Rijkhoff: Nouns 18: David Beck: Adjectives 19: Kees Hengeveld: Adverbs 20: Borja Herce: Adpositions 21: Holger Diessel: Demonstratives 22: Mark Dingemaanse: Ideophones 23: Mark Dingemaanse: Interjections Part IV. Word classes in genetic and areal language groups 24: Elsa Oréal and Martine Vanhove: Word classes in Egyptian, Semitic, and Cushitic (Afroasiatic) 25: Denis Creissels: Word classes in Mande languages 26: Dana Louagie: Word classes in Australian languages 27: Paolo Ramat: Word classes in Indo-European languages 28: Walter Bisang: Word classes in classical Chinese (Sinitic) 29: Donna B. Gerdts and Lauren Schneider: Word classes in Salish languages 30: Karen Michelson: Word classes in Iroquoian languages 31: Marianne Mithun: Word classes in Eskimo-Aleut languages 32: Valentina Vapnarsky: Word classes in Mayan languages 33: Françoise Rose: Word classes in Maweti-Guaraní languages 34: Pieter Muysken: Word classes in Quechuan languages 35: Ulrike Mosel: Word classes in Austronesian languages 36: Marian Klamer: Word classes in Timor-Alor-Pantar and the Papuan region 37: Vadim Kimmelman and Carl Börstell: Word classes in sign languages Part V. Word classes in linguistic sub-disciplines 38: Natalia Levshina: Word classes in corpus linguistics 39: Aaron K. Smith: Word classes and grammaticalization 40: Sabine Stoll: Word classes in first language acquisition 41: Seth Lindstromberg and Frank Boers: Word classes in second language acquisition 42: Yaron Matras and Evangelia Adamou: Word classes in language contact 43: Paul Ibbotson: Word classes in psycholinguistics 44: David Kemmerer: Word classes in neurolinguistics 46: Meladel Mistica, Ekaterina Vylomova, and Francis Bond: Word classes in computational linguistics and artificial intelligence

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Book SynopsisHow does human language work? How do we put ideas into words that others can understand? Can linguistics shed light on the way the brain operates? Foundations of Language puts linguistics back at the centre of the search to understand human consciousness. Ray Jackendoff begins by surveying the developments in linguistics over the years since Noam Chomsky''s Aspects of the Theory of Syntax. He goes on to propose a radical re-conception of how the brain processes language. This opens up vivid new perspectives on every major aspect of language and communication, including grammar, vocabulary, learning, the origins of human language, and how language relates to the real world. Foundations of Language makes important connections with other disciplines which have been isolated from linguistics for many years. It sets a new agenda for close cooperation between the study of language, mind, the brain, behaviour, and evolution.Trade ReviewThe book is ... a fascinating introduction to the world of linguistics. ... I found the book extremely interesting, captivating and important. If you are not sure about certain basic facts in the research of natural language, read this book. It will provide you with quite an objective view of the development of the research of language on all aspects. * Linguist List *A masterpiece * Nature *I believe this book has the potential to reorient linguistics more decisively than any book since Syntactic Structures shook the discipline almost half a century ago. * Robbins Burling, Language in Society *An excellent overview of the complexities of language * New Scientist *Table of ContentsPART I: PSYCHOLOGICAL AND BIOLOGICAL FOUNDATIONS ; 1. The Complexity of Linguistic Structure ; 2. Language as a Mental Phenomenon ; 3. Combinatoriality ; 4. Universal Grammar ; PART II: ARCHITECTURAL FOUNDATIONS ; 5. The Parallel Architecture ; 6. Lexical Storage Versus Online Construction ; 7. Implications for Processing ; 8. An Evolutionary Perspective on the Architecture ; PART III: SEMANTIC AND CONCEPTUAL FOUNDATIONS ; 9. Semantics as a Mentalistic Enterprise ; 10. Reference and Truth ; 11. Lexical Semantics ; 12. Phrasal Semantics ; 13. Concluding Remarks

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Book SynopsisThis book investigates the nature of generalization in language and examines how language is known by adults and acquired by children. It looks at how and why constructions are learned, the relation between their forms and functions, and how cross-linguistic and language-internal generalizations about them can be explained. Constructions at Work is divided into three parts: in the first Professor Goldberg provides an overview of constructionist approaches, including the constructionist approach to argument structure, and argues for a usage-based model of grammar. In Part II she addresses issues concerning how generalizations are constrained and constructional generalizations are learned. In Part III the author shows that a combination of function and processing accounts for a wide range of language-internal and cross-linguistic generalizations. She then considers the degree to which the function of constructions explains their distribution and examines cross-linguistic tendencies in arTrade ReviewI have found Ionstructions at WorkR^ a must-have book. The author's elegance and clarity of vision, her knowledge of research beyond linguistics proper, as well as her empathy with the reader and her honesty about the not-so-clear cases, are engaging. * J. Carlos Acuna-Farina, University of Santiago de Compostela *an important contribution to the study of how language operates in the mind and in the world and how these operations relate. * Folia Linguistica *Table of ContentsPart One: Constructions ; 1. Overview ; 2. Surface Generalizations ; 3. Item Specific Knowledge and Generalizations ; Part Two: Learning Generalizations ; 4. How Generalizations are Learned ; 5. How Generalizations are Constrained ; 6. Why Generalizations are Learned ; Part Three: Explaining Generalizations ; 7. Island Constraints and Scope ; 8. Grammatical Categorization: Subject Auxiliary Inversion ; 9. Cross-linguistic Generalizations in Argument Realization ; 10. Variations on a Constructionist Theme ; 11. Conclusion ; References ; Index

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Book SynopsisThis book provides a clear and comprehensive description of the Ocotepec/Tapalapa variant of Chiapas Zoque. Zoque is one of the two major branches of the Mixe-Zoquean language family, spoken in the southern part of Mexico. Until the Spanish conquest in the sixteenth century the Mixe-Zoquean languages covered a large area from Veracruz on the Gulf coast to the border of Guatemala and the Pacific coast. Inscriptions in Zoque from the first half of the first millennium AD are the oldest known linguistic documents in Mesoamerica.The Zoquean area once included the entire heartland of the Olmecs, who almost certainly spoke a proto-Zoquean or proto-Mixe-Zoquean language. The Zoques are thus the most likely direct descendents of the oldest known civilization of Mexico. As a result of a long history of close contact, Zoque and Mayan share areal features, and there are lexical borrowings in both directions, but genetically and typologically they are clearly distinct. The Zoque-speaking area has Table of Contents1. The Zoque Language ; 2. Phonology ; 3. Morphological Processes ; 4. The Noun ; 5. Determiners and Modifiers ; 6. Pronouns ; 7. The Verb ; 8. The Sentence ; 9. Subordination ; Bibliography

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Book SynopsisTable of Contents1. Linguistics: Core Concepts and Principles 2. Grammars 3. Open-Source Libraries, Application Frameworks, Workflow Systems, and Other Resources 4. Mathematical Essentials 5. Probability 6. Inference and Prediction Methods 7. Random Processes 8. Bayesian Methods 9. Machine Learning 10. Artificial Neural Networks for Natural Language Processing 11. Information Retrieval 12. Language Core Tasks 1 13. Language Core Tasks 2 14. Language Understanding Applications 1 15. Language Understanding Applications 2 16. Deep Learning for Natural Language Processing 17. Text Mining for Modeling Cyberattacks 18. World Languages and Crosslinguistics 19. Linguistic Elegance of the Languages of South India 20. Current Trends and Open Problems

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Book SynopsisPresents the motivations for, intuitions behind, and basic mathematical models of natural spoken language communication. This book offers an overview of various aspects of the problem from the physics of speech production through the hierarchy of linguistic structure and ending with some observations on language and mind.Trade Review"...a succinct presentation of the most important mathematical technology of speech technology and the author's ideas for overcoming the limitations of these techniques…" (Mathematical Reviews, 2005j)Table of ContentsAuthor's preface. 1 Introduction 2 Preliminaries 2.1 The physics of speech production 2.2 The source-filter model 2.3 Information-bearing features of the speech signal 2.4 Time-frequency representations 2.5 Classifications of acoustic patterns in speech 2.6 Temporal invariance and stationarity 2.7 Taxonomy of linguistic structure 3 Mathematical models of linguistic structure 3.1 Probabilistic functions of a discrete Markov process 3.2 Formal grammars and abstract automata 4 Syntactic analysis 4.1 Deterministic parsing algorithms 4.2 Probabilistic parsing algorithms 4.3 Parsing natural language 5 Grammatical inference 5.1 Exact inference and Gold's theorem 5.2 Baum's algorithm for regular grammars 5.3 Event counting in parse trees 5.4 Baker's algorithm for context-free grammars 6 Information-theoretic analysis of speech communication 6.1 The Miller et al. experiments 6.2 Entropy of an information source 6.3 Recognition error rates and entropy 7 Automatic speech recognition and constructive theories of language 7.1 Integrated architectures 7.2 Modular architectures 7.3 Parameter estimation from fluent speech 7.4 System performance 7.5 Other speech technologies 8 Automatic speech understanding and semantics 8.1 Transcription and comprehension 8.2 Limited domain semantics 8.3 The semantics of natural language 8.4 System architectures 8.5 Human and machine performance 9 Theories of mind and language 9.1 The challenge of automatic natural language understanding 9.2 Metaphors for mind 9.3 The artificial intelligence program 10 A speculation on the prospects for a science of the mind 10.1 The parable of the thermos bottle: measurements and symbols 10.2 The four questions of science 10.3 A constructive theory of the mind 10.4 The problem of consciousness 10.5 The role of sensorimotor function, associative memory and reinforcement learning in automatic acquisition of spoken language by an autonomous robot 10.6 Final thoughts: predicting the course of discovery

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Book SynopsisMakes the ideas of corpus linguistics accessible to teachers and, most important, provides ideas, instruction, and opportunities for teachers to use the applications of corpus linguistics in their classrooms. The book is intended for graduate students who are studying applied linguistics or TESOL, for teacher-trainers working with language instructors, and for practicing language teachers.

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Book SynopsisThis 1992 collection takes the exciting step of examining natural language phenomena from the perspective of both computational linguistics and formal semantics. Computational linguistics has until now been primarily concerned with the construction of computational models for handling the complexities of linguistic form, but has not tackled the questions of representing or computing meaning. Formal semantics, on the other hand, has attempted to account for the relations between forms and meanings, without necessarily attending to computational concerns. The book introduces the reader to the two disciplines and considers the prospects for the more unified and comprehensive computational theory of language which might obtain from their amalgamation. Of great interest to those working in the fields of computation, logic, semantics, artificial intelligence and linguistics generally.Trade Review"...makes important theoretical progress in the formalism of natural language processing. The accent is on the relations between the syntax and the semantics of natural language. Also, the commonalities of natural language and artificial intelligence are stressed....readers will find the state of the art in the theory of natural language processing and some important new contributions." Claudiu Popescu, Computing Reviews"This is a collection of excellent papers....The overall high quality of the contributions should make it valuable to all computational linguists interested in semantics." John Nerbonne, Computational LinguisticsTable of Contents1. Unification; 2. Representations and interpretations; 3. Syntactic categories and semantic type; 4. Fine-structure in categorical semantics; 5. Properties, propositions and semantic theory; 6. Algorithms for semantic interpretation; 7. Situation schemata and linguistic representation; 8. Application-oriented computational semantics; 9. Form and content in semantics; Epilogue: on the relation between computational linguistics and formal semantics; Bibliography.

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Book SynopsisThis book is an introduction to programming for linguists.Table of Contents1 Introduction; 1.1 Why Use Perl?; 1.2 The Command Prompt/Console; 1.3 How to Navigate a File System; 1.3.1 Understanding File System Hierarchies; 1.3.2 Navigating Through File Systems; 1.4 Plain Text Editors; 1.5 Installing Perl and Perl/Tk on Your Computer; 1.5.1 Installing Perl; 1.5.2 Installing the Perl/Tk Toolkit; 2 Basic Programming Concepts - 1; 2.1 How to Issue Instructions (Statements); 2.2 How to Store Data in Memory (Variables); 2.3 What to Store & How (Basic Data Types); 2.3.1 Scalars; 2.3.2 Arrays; 2.3.3 Hashes; 2.4 Understanding About Defaults (Special Variables); 2.5 Making Your Code More Intelligible (Comments); 3 Basic Programming Concepts - 2; 3.1 Making Decisions (Flow Control); 3.2 Doing Repetitive Tasks Automatically (Basic for Loops); 3.2.1 The for Loop; 3.2.2 Iterating over Array Elements; 3.2.3 The foreach Loop; 3.3 More Repetitiveness (Further Loops); 3.3.1 The while loop; 3.3.2 The until Loop; 3.3.3 Controlling Loops Further; 4 Working with Text (Basic String Handling); 4.1 Chomping & Chopping; 4.2 Extracting a Substring from a Longer String; 4.3 'Adding' Strings Together; 4.4 Establishing the Length of a String; 4.5 Handling Case; 5 Working with Stored Data (Basic File Handling); 5.1 Opening a Filehandle; 5.2 Tweaking Your Input and/or Output Options; 5.3 Reading from a Filehandle; 5.3.1 File Processing in List Context; 5.3.2 File Processing in Line Context; 5.3.3 Slurping in Scalar Context; 5.4 Default Filehandles; 5.5 Writing to a Filehandle; 5.6 Working with Directories; 6 Identifying Textual Patterns (Basic & Extended Regular Expressions); 6.1 Matching; 6.2 Character Classes; 6.3 Quantification; 6.4 Grouping, Alternation & Anchoring; 6.5 Memorising; 6.6 Modifiers; 6.7 Extended Regular Expressions;7 Modifying Textual Patterns (Substitution & Transliteration); 7.1 Substitution; 7.2 Greediness; 7.3 A Very Brief Introduction to Markup Languages (SGML, HTML & XML); 7.4 Transliteration; 8 Getting Things Into the Right Order (Basic Sorting); 8.1 Keys & Sort Order; 8.2 'Vocabulary Handling' (Creating Simple Word Lists); 9 Elementary Texts Stats (Creating Basic Frequency Lists); 9.1 Complex Sorting; 9.2 Word Frequency Lists; 9.3 Implementing a List; 9.4 Sorting & Printing the List; 10 More Repetitiveness or How to Tie Things Together (Introducing Modularity); 10.1 Functions & Subroutines; 10.1.1 Creating Your Own Subroutines; 10.1.2 Calling a Subroutine; 10.1.3 Localising Variables & Being Strict With Yourself; 10.2 References & Modules; 10.2.1 Basic Named References; 10.2.2 Anonymous References; 10.2.3 What Do Modules Look Like?; 10.2.4 Importing & Using Modules; 10.2.5 Writing a Simplistic HTML Page Downloader and Parser; 11 Objects; 11.1 OO Concepts; 11.2 Creating an Object in Perl; 11.3 Creating a Regular Verb Object; 11.4 Instantiating the Verb Object; 11.5 Creating Appropriate Accessor Methods; 12 Getting Graphical (Simple User Interfaces); 12.1 Elements of a GUI; 12.2 Basic Steps in Creating Tk Programs; 12.3 Adding Widgets; 12.4 The GUI Concordancer - An Advanced Example; 12.4.1 Adding a Menu Bar & the Remaining GUI Elements; 12.4.2 Programming the Functionality; 12.4.3 Handling the Text Widget; 13 Conclusion; Appendix A - Sample Solutions; Appendix B - How to Get Further Help on Perl; References

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Book SynopsisIntroduces the two most common numerical methods for heat transfer and fluid dynamics equations, using clear and accessible language. This unique approach covers all necessary mathematical preliminaries at the beginning of the book for the reader to sail smoothly through the chapters. Students will work step-by-step through the most common benchmark heat transfer and fluid dynamics problems, firmly grounding themselves in how the governing equations are discretized, how boundary conditions are imposed, and how the resulting algebraic equations are solved. Providing a detailed discussion of the discretization steps and time approximations, and clearly presenting concepts of explicit and implicit formulations, this graduate textbook has everything an instructor needs to prepare students for their exams and future careers. Each illustrative example shows students how to draw comparisons between the results obtained using the two numerical methods, and at the end of each chapter they can tTrade Review'I am delighted to recommend this textbook to beginners and early career researchers wanting to work in computational heat and fluid flow problems. This book is a useful tool for teaching postgraduate and senior undergraduate courses and will be an excellent addition to the bookshelves of senior researchers.' Perumal Nithiarasu, Swansea UniversityTable of ContentsPart I. Preliminaries: 1. Mathematical Preliminaries; 2. Equations of Heat Transfer and Fluid Mechanics; 3. Solution Methods for Algebraic Equations; Part II. The Finite Element Method: 4. The Finite Element Method: Steady-State Heat Transfer; 5. The Finite Element Method: Unsteady Heat Transfer; 6. Finite Element Analysis of Viscous Incompressible Flows; Part III. The Finite Volume Method: 7. The Finite Volume Method: Diffusion Problems; 8. The Finite Volume Method: Advection-Diffusion Problems; 9. Finite Volume Methods for Viscous Incompressible Flows; 10. Advanced Topics.

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Book SynopsisIn this Element, the authors introduce and apply a framework for the linguistic analysis of fake news. This title is also available as Open Access on Cambridge Core.Table of Contents1. Introduction; 2. Analysing the Language of Fake News; 3. Jayson Blair and the New York Times; 4. Corpus; 5. Analysis and Results; 6. Conclusion; References.

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Book SynopsisGenerative AI is a disruptive technology that has the potential to transform many aspects of how computer science is taught. Like previous innovations such as high-level programming languages and block-based programming languages, generative AI lowers the technical expertise necessary to create working programs, bringing the power of computation to more people. The programming process is already changing as a result of its presence, even for expert programmers. It also poses significant challenges to educators around re-thinking assessment as some well-established approaches may no longer be viable. Many traditional programming assignments can be completed using generative AI tools with minimal effort, thus potentially undermining learning. In this Element, the authors explore both the opportunities and the challenges for computer science education resulting from the widespread availability of generative AI.

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Book SynopsisGenerative AI is a disruptive technology that has the potential to transform many aspects of how computer science is taught. Like previous innovations such as high-level programming languages and block-based programming languages, generative AI lowers the technical expertise necessary to create working programs, bringing the power of computation to more people. The programming process is already changing as a result of its presence, even for expert programmers. It also poses significant challenges to educators around re-thinking assessment as some well-established approaches may no longer be viable. Many traditional programming assignments can be completed using generative AI tools with minimal effort, thus potentially undermining learning. In this Element, the authors explore both the opportunities and the challenges for computer science education resulting from the widespread availability of generative AI.

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Book SynopsisNatural Language Processing in the Real World is a practical guide for applying data science and machine learning to build Natural Language Processing (NLP) solutions. Where traditional, academic-taught NLP is often accompanied by a data source or dataset to aid solution building, this book is situated in the real world where there may not be an existing rich dataset. This book covers the basic concepts behind NLP and text processing and discusses the applications across 15 industry verticals. From data sources and extraction to transformation and modelling, and classic Machine Learning to Deep Learning and Transformers, several popular applications of NLP are discussed and implemented.This book provides a hands-on and holistic guide for anyone looking to build NLP solutions, from students of Computer Science to those involved in large-scale industrial projects.Trade Review"This book does a phenomenal job capturing the real-world techniques employed by industry experts to address complex problems with remarkable finesse and effectiveness. From foundational techniques to cutting-edge models, this book seamlessly blends practical code examples and insightful applications to provide a comprehensive understanding. Whether you're a novice or an experienced practitioner, this book will take you on a journey through the entire NLP landscape, providing the knowledge and skills needed to tackle any linguistic challenge and enhance your grasp of NLP. " - Sumanik Singh, Software Engineer at Amazon (Alexa Smart Home)"This book does an exceptional job of covering a wide range of NLP applications, making it a must-read for anyone interested in understanding the potential of this rapidly evolving field. It introduces the fundamental concepts of NLP in a clear and concise manner, ensuring that readers without a strong technical background can grasp the subject matter. It then delves deeper into advanced techniques and algorithms, providing readers with the necessary tools to implement NLP solutions effectively." - Neha Tiwari, Senior Data Scientist at Nielsen"This book does a phenomenal job capturing the real-world techniques employed by industry experts to address complex problems with remarkable finesse and effectiveness. From foundational techniques to cutting-edge models, this book seamlessly blends practical code examples and insightful applications to provide a comprehensive understanding. Whether you're a novice or an experienced practitioner, this book will take you on a journey through the entire NLP landscape, providing the knowledge and skills needed to tackle any linguistic challenge and enhance your grasp of NLP. " - Sumanik Singh, Software Engineer at Amazon (Alexa Smart Home)"This book does an exceptional job of covering a wide range of NLP applications, making it a must-read for anyone interested in understanding the potential of this rapidly evolving field. It introduces the fundamental concepts of NLP in a clear and concise manner, ensuring that readers without a strong technical background can grasp the subject matter. It then delves deeper into advanced techniques and algorithms, providing readers with the necessary tools to implement NLP solutions effectively." - Neha Tiwari, Senior Data Scientist at Nielsen"Often there is a gap between Education and Practice. This book is an essential resource to cover the gap and must-have for beginners as well as experienced professionals. As a researcher in academia and professor of machine learning, I find this book to be an eye opener for approaching NLP in a practical sense. Not only a great resource of people in academia, it is all you need to build NLP solutions in the real world regardless of the industry vertical you work in." - Dr. V. Kalaichelvi, Professor and Head, Department of EEE, Birla Institute of Technology & Science (BITS)"If you’re stuck before you even start your NLP project, this book is just what you need. From key data storage tools for text, to visualization techniques that make sense with language data, to practical use cases in many verticals, "Natural Language Processing in the Real World" will serve as your map, trailguide, and companion on your journey from fresh text dataset to prototype NLP app." - Rebecca Bilbro, Ph.D, Founder and CTO at Rotational Labs, Applied Text Analytics book author, Data Science faculty at Georgetown University"Natural Language Processing in the Real-World is a praiseworthy book that tackles a highly important subject. It provides an accurate representation of real-world applications and solutions, effectively bridging the gap between theory and practice. By exploring NLP across 15 different industry verticals, this book offers readers a comprehensive understanding of how NLP is implemented in practical scenarios. The inclusion of Python code for implementing NLP applications further enhances its worth, as it allows readers to apply their theoretical knowledge to real-world projects. As a researcher and academician, I consider this book to be an invaluable resource, and I believe it holds immense value for my students who are pursuing degrees in ML-related subjects and aspire to build careers in Data Science." - Vwani P. Roychowdhury, Professor, University of California, Los Angeles (UCLA)"The true value of natural language processing lies in its ability to quickly solve real-world business problems. While theory is important, it is the practical application of NLP and its connection to a company's mission that drives meaningful innovation and impact. This book provides a practical playbook, offering insights and techniques that bridge the gap between theory and practice. Data Science often carries the perception of being methodical and slow, but this book focuses on leveraging prototyping, stakeholder interaction, and iteration to integrate data science into the core of value delivery for companies. Whether you're an experienced practitioner or new to the field, this book empowers you to harness the power of NLP and transform the way we interact with language in the real world."- Joey McCord, Founder, CTO and Adjunct Professor"This exceptional guide offers profound insights into the various industries that leverage NLP, its alignment with business objectives, and practical guidance on developing Python-based applications. Whether you are a novice or an expert, this book is an invaluable resource. It comprehensively covers essential knowledge and has become an indispensable tool for enhancing my expertise and proficiency in NLP. I consider it an immensely valuable asset and a frequent reference in my work." - Dishant Banga, Sr. Data Analyst , BridgetreeTable of ContentsTable of Contents:List of FiguresList of TablesContributorsPrefaceAcknowledgements Chapter 1: NLP BasicsChapter 2: Data Sources and ExtractionChapter 3: Data Preprocessing and TransformationChapter 4: Data ModelingChapter 5: NLP Applications – Active UsageChapter 6: NLP Applications – Developing UsageChapter 7: Information Extraction and Text Transforming ModelsChapter 8: Text Categorisation and AffinitiesChapter 9: ChatbotsChapter 10: Customer Review AnalysisChapter 11: Recommendations and PredictionsChapter 12: More Real-World Scenarios and TipsBibliographyIndex

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Book SynopsisNatural Language Processing in the Real World is a practical guide for applying data science and machine learning to build Natural Language Processing (NLP) solutions. Where traditional, academic-taught NLP is often accompanied by a data source or dataset to aid solution building, this book is situated in the real world where there may not be an existing rich dataset.This book covers the basic concepts behind NLP and text processing and discusses the applications across 15 industry verticals. From data sources and extraction to transformation and modelling, and classic Machine Learning to Deep Learning and Transformers, several popular applications of NLP are discussed and implemented.This book provides a hands-on and holistic guide for anyone looking to build NLP solutions, from students of Computer Science to those involved in large-scale industrial projects.

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Book SynopsisThis book enables readers to interrogate the technical, rhetorical, theoretical, and socio-ethical challenges and opportunities involved in the development and adoption of augmentation technologies and artificial intelligence. The core of our human experience and identity is forever affected by the rise of augmentation technologies that enhance human capability or productivity. These technologies can add cognitive, physical, sensory, and emotional enhancements to the body or environment. This book demonstrates the benefits, risks, and relevance of emerging augmentation technologies such as braincomputer interaction devices for cognitive enhancement; robots marketed to improve human social interaction; wearables that extend human senses, augment creative abilities, or overcome physical limitations; implantables that amplify intelligence or memory; and devices, AI generators, or algorithms for emotional augmentation. It allows scholars and professionals to understand the impactTrade Review"Augmentation Technologies and Artificial Intelligence in Technical Communication: Designing Ethical Futures is a must-read for every technical communication professional who anticipates working alongside or communicating about augmentation technologies and artificial intelligence. Drawing on their extensive research and project experience with these technologies, co-authors Ann Hill Duin and Isabel Pedersen guide researchers, instructors and practicing professionals in the field through this emerging technology ecosystem, raise awareness of the affordances, benefits, and ethical dilemmas posed by these technologies, and explore specific applications of augmentation technologies and AI in the work of technical communicators, in teaching, and in influencing the future direction of the field. This is an ideal book for a textbook or for a study group on these technologies." — Saul Carliner, Concordia University, Canada."With this book, Duin and Pedersen provide an essential resource for those who work and study in the many areas of augmentation technology (AT) and artificial intelligence (AI). They bring technical & professional communication (TPC) firmly into this field. The authors have organized the rich landscape of resources in AT and AI to date—taxonomies, standards, policies, definitions, examples, and applications. They include ethical elements that are also critical to that landscape—human rights, accountability, security, safety, transparency, and explainability. In other words, this book is a repository of resources and a touchstone for future work in AT and AI . . . for TPC professionals as well as others working in the field." — Dr. Pam Estes Brewer, Mercer University, USA.Table of ContentsSection 1: Understand (rhetorics of) Augmentation Technologies 1. Augmentation Technologies and AI – An Ethical Design Futures Framework 2. Dimensions, Scope, and Classification for Augmentation Technologies 3. Agency, Affordances, and Enculturation of Augmentation Technologies Section 2: Build Literacies 4. Competencies, Design Considerations, and New Roles for Work with Augmentation Technologies and AI 5. Socio-ethical Consequences and Design Futures Section 3: Design Ethical Futures 6. Pedagogical Direction for Cultivating Augmentation Technology and AI Literacies 7. Professional Direction for Human-AI Interaction 8. Strategic and Tactical Approaches to Designing Ethical Futures for Augmentation Technologies and AI

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Book SynopsisNatural Language Processing (NLP) is a sub-field of Artificial Intelligence, linguistics, and computer science and is concerned with the generation, recognition, and understanding of human languages, both written and spoken. NLP systems examine the grammatical structure of sentences as well as the specific meanings of words, and then they utilize algorithms to extract meaning and produce results. Machine Learning and Deep Learning in Natural Language Processing aims at providing a review of current Neural Network techniques in the NLP field, in particular about Conversational Agents (chatbots), Text-to-Speech, management of non-literal content like emotions, but also satirical expressions and applications in the healthcare field.NLP has the potential to be a disruptive technology in various healthcare fields, but so far little attention has been devoted to that goal. This book aims at providing some examples of NLP techniques that can, for example, restTable of ContentsPreface. Editors. Contributors. Part I Introduction. Chapter 1 Introduction to Machine Learning, Deep Learning, and Natural Language Processing. Part II Overview of Conversational Agents. Chapter 2 Conversational Agents and Chatbots: Current Trends. Chapter 3 Unsupervised Hierarchical Model for Deep Empathetic Conversational Agents. Part III Sentiment and Emotions. Chapter 4 EMOTRON: An Expressive Text-to-Speech. Part IV Fake News and Satire. Chapter 5 Distinguishing Satirical and Fake News. Chapter 6 Automated Techniques for Identifying Claims and Assisting Fact Checkers. Part V Applications in Healthcare. Chapter 7 Whisper Restoration Combining Real- and Source-Model Filtered Speech for Clinical and Forensic Applications. Chapter 8 Analysis of Features for Machine Learning Approaches to Parkinson’s Disease Detection. Chapter 9 Conversational Agents, Natural Language Processing, and Machine Learning for Psychotherapy. INDEX.

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Book SynopsisApplying Natural Language Processing (NLP) concepts to help humans in their daily life, this book discusses an automatic translation of an unstructured Natural Language Question (NLQ) into a Structured Query Language (SQL) statement. Using SQL as a Relational DataBase (RDB) interaction language, database administrators or general users with little to no SQL querying abilities are provided with all the knowledge necessary to perform queries on RDBs in an interactive manner.Key Features: Includes extensive and illustrative examples to simplify the discussed concepts Discusses a novel, and yet simple, approach to NLP Introduces a lightweight NLQ into SQL translation approach through the use of RDB MetaTables as a Hash table Extensive literature review and thorough background information on every tool, concept and technique applied Providing a unique approach to NLQ into SQTable of ContentsPreface. 1 Introduction. 2 Background Study. 3 Literature Review. 4 Implementation Plan. 5 Implementation User Case Scenario. 6 Implementation Testing and Performance Measurements. 7 Implementation Results Discussion. 8 Conclusion and Future Work. Appendix 1. Appendix 2. Appendix 3. Appendix 4. Appendix 5. Appendix 6. Appendix 7. Appendix 8. Appendix 9. Glossary. References. Index.

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Book SynopsisAI for Communication offers an engaging exploration into the diverse applications of artificial intelligence (AI) within the realm of communication. By bridging the gap between the scientific and engineering realms of AI and communication, this book reveals how AI, since its inception during the Dartmouth Summer workshop of 1956, has inherently been a science of communication. Exploring key advancements such as machine translation, natural language processing, large language models, computational creativity, and social robotics, this book shows how these innovations not only disrupt but also actively transform human communication.The book is designed for students, teachers, and general readers who want to know how the field of communication impacts and influences the theory and practice of AI and how recent developments in AI will affect all aspects of human social interaction. 

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Book SynopsisMultilingual Artificial Intelligence is a guide for non-computer science specialists and learners looking to explore the implementation of AI technologies to solve real-life problems involving language data.Focusing on multilingual, multicultural, pre-trained large language models and their practical use through fine-tuning and prompt engineering, Wang and Smith demonstrate how to apply this new technology in areas such as information retrieval, semantic webs and retrieval augmented generation, to improve both human productivity and machine intelligence. Finally, it discusses the human impact of language technologies in the cultural context, and provides an AI competence framework for users to design their own learning journey.This innovative text is essential reading for all students, professionals and researchers in language, linguistics and related areas looking to understand how to integrate multilingual and multicultural artificial intelligence technology into the

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Book SynopsisHaving been catapulted into public discourse in the last few years, this book serves as an in-depth exploration of the ever-evolving domain of artificial intelligence (AI), large language models, and ChatGPT. It provides a meticulous and thorough analysis of AI, ChatGPT technology, and their prospective trajectories given the current trend, in addition to tracing the significant advancements that have materialized over time.Key Features: Discusses the fundamentals of AI for general readers Introduces readers to the ChatGPT chatbot and how it works Covers natural language processing (NLP), the foundational building block of ChatGPT Introduces readers to the deep learning transformer architecture Covers the fundamentals of ChatGPT training for practitioners Illustrated and organized in an accessible manner, this textbook contains particular appeal to st

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Book SynopsisHaving been catapulted into public discourse in the last few years, this book serves as an in-depth exploration of the ever-evolving domain of artificial intelligence (AI), large language models, and ChatGPT. It provides a meticulous and thorough analysis of AI, ChatGPT technology, and their prospective trajectories given the current trend, in addition to tracing the significant advancements that have materialized over time.Key Features: Discusses the fundamentals of AI for general readers Introduces readers to the ChatGPT chatbot and how it works Covers natural language processing (NLP), the foundational building block of ChatGPT Introduces readers to the deep learning transformer architecture Covers the fundamentals of ChatGPT training for practitioners Illustrated and organized in an accessible manner, this textbook contains particular appeal to students and course co

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Book SynopsisThis bookâs core argument is that an artificial intelligence that could equal or exceed human intelligence â sometimes called âartificial general intelligenceâ (AGI) â is for mathematical reasons impossible. It offers two specific reasons for this claim:1. Human intelligence is a capability of the human brain and central nervous system, which is a complex dynamic system2. Systems of this sort cannot be modelled mathematically in a way that allows them to operate inside a computer.In supporting their claim, the authors, Jobst Landgrebe and Barry Smith, marshal evidence from mathematics, physics, computer science, philosophy, linguistics, biology, and anthropology, setting up their book around three central questions: What are the essential marks of human intelligence? What is it that researchers try to do when they attempt to achieve âœArtificial Intelligenceâ (AI)? And why, after more than 50 years, are our interactions with AI, for example with our bankâs compu

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Book SynopsisLanguage, apart from its cultural and social dimension, has a scientific side that is connected not only to the study of ''grammar'' in a more or less traditional sense, but also to disciplines like mathematics, physics, chemistry and biology. This book explores developments in linguistic theory, looking in particular at the theory of generative grammar from the perspective of the natural sciences. It highlights the complex and dynamic nature of language, suggesting that a comprehensive and full understanding of such a species-specific property will only be achieved through interdisciplinary work.Table of ContentsIntroduction Ángel J. Gallego and Roger Martin; Part I. The Computational Component: 1. Deriving multiple 'object' constructions Tonia Bleam and Norbert Hornstein; 2. Verbal complex formation and overt subjects in infinitival complexes in Romance Francisco Ordóñez; 3. Two families of questions Howard Lasnik; 4. Context sensitive aspects of constituent negation Ricardo Etxepare and Myriam Uribe-Etxebarria; 5. Phasehood and Romance adverbial because-clauses Esther Torrego; 6. No-choice parameters, phi-features and the structure of DP Ian Roberts; Part II. Interfaces: 7. Linearizing chains at LF Jairo Nunes; 8. On the rationality of grammar Wolfram Hinzen; 9. The warped forge Pablo Bustos and Juan Romero; 10. Limiting semantic types Paul Pietroski; 11. Why is phonology different? No recursion William Idsardi; 12. Nothing in linguistics makes sense except in the light of change David Lightfoot; 13. Neurology and experience: the language organ and externalization Carlos P. Otero; Part III. Linguistics and Other Sciences: 14. My head's in knots: on Uriagereka's generalization and the knot-sentence connection Sergio Balari, Antonio Benítez-Burraco, Marta Camps, Víctor M. Longa and Guillermo Lorenzo; 15. (Neural) syntax Cedric Boeckx and Constantina Theofanopoulou; 16. Syntax and uncertainty Douglas Saddy; 17. The Golden phrase: steps to the physics of language Massimo Piattelli-Palmarini and David Medeiros; 18. Science, mind, and limits of understanding Noam Chomsky.

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Book SynopsisWith a machine learning approach and less focus on linguistic details, this gentle introduction to natural language processing develops fundamental mathematical and deep learning models for NLP under a unified framework. NLP problems are systematically organised by their machine learning nature, including classification, sequence labelling, and sequence-to-sequence problems. Topics covered include statistical machine learning and deep learning models, text classification and structured prediction models, generative and discriminative models, supervised and unsupervised learning with latent variables, neural networks, and transition-based methods. Rich connections are drawn between concepts throughout the book, equipping students with the tools needed to establish a deep understanding of NLP solutions, adapt existing models, and confidently develop innovative models of their own. Featuring a host of examples, intuition, and end of chapter exercises, plus sample code available as an onliTrade Review'An amazingly compact, and at the same time comprehensive, introduction and reference to natural language processing (NLP). It describes the NLP basics, then employs this knowledge to solve typical NLP problems. It achieves very high coverage of NLP through a clever abstraction to typical high-level tasks, such as sequence labelling. Finally, it explains the topics in deep learning. The book captivates through its simple elegance, depth, and accessibility to a wide range of readers from undergrads to experienced researchers.' Iryna Gurevych, Technical University of Darmstadt, Germany'An excellent introduction to the field of natural language processing including recent advances in deep learning. By organising the material in terms of machine learning techniques - instead of the more traditional division by linguistic levels or applications - the authors are able to discuss different topics within a single coherent framework, with a gradual progression from basic notions to more complex material.' Joakim Nivre, Uppsala University'The book is a valuable tool for both beginning and advanced researchers in the field.' Catalin Stoean, zbMATHTable of ContentsPart I. Basics: 1. Introduction; 2. Counting relative frequencies; 3. Feature vectors; 4. Discriminative linear classifiers; 5. A perspective from information theory; 6. Hidden variables; Part II. Structures: 7. Generative sequence labelling; 8. Discriminative sequence labelling; 9. Sequence segmentation; 10. Predicting tree structures; 11. Transition-based methods for structured prediction; 12. Bayesian models; Part III. Deep Learning: 13. Neural network; 14. Representation learning; 15. Neural structured prediction; 16. Working with two texts; 17. Pre-training and transfer learning; 18. Deep latent variable models; Index.

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Book SynopsisThe use of literature in second language teaching has been advocated for a number of years, yet despite this there have only been a limited number of studies which have sought to investigate its effects. Fewer still have focused on its potential effects as a model of spoken language or as a vehicle to develop speaking skills. Drawing upon multiple research studies, this volume fills that gap to explore how literature is used to develop speaking skills in second language learners. The volume is divided into two sections: literature and spoken language and literature and speaking skills. The first section focuses on studies exploring the use of literature to raise awareness of spoken language features, whilst the second investigates its potential as a vehicle to develop speaking skills. Each section contains studies with different designs and in various contexts including China, Japan and the UK. The research designs used mean that the chapters contain clear implications for classroom peTable of ContentsForeword; 1. Introduction; Part I. Literature and Spoken Language: 2. The realism of conversation in literature; 3. Using literature in text-driven materials to help develop spoken language awareness; 4. Literature, TV drama and spoken language awareness; 5. Haiku and spoken language: Corpus-Driven analyses of linguistic features in English-language haiku writing; 6. Screenplays as pedagogical medium for cultivating EFL learners' metapragmatic awareness of speech acts in spoken English; Part II. Literature and Speaking Skills: 7. EFL learners reading and discussing poems in English; 8. An analysis of collaborative dialogue in literature circles; 9. Exploring literary texts as a tool for developing L2 oral proficiency; 10. Conclusion: implications for pedagogy and research.

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Book SynopsisEvent structures are central in Linguistics and Artificial Intelligence research: people can easily refer to changes in the world, identify their participants, distinguish relevant information, and have expectations of what can happen next. Part of this process is based on mechanisms similar to narratives, which are at the heart of information sharing. But it remains difficult to automatically detect events or automatically construct stories from such event representations. This book explores how to handle today''s massive news streams and provides multidimensional, multimodal, and distributed approaches, like automated deep learning, to capture events and narrative structures involved in a ''story''. This overview of the current state-of-the-art on event extraction, temporal and casual relations, and storyline extraction aims to establish a new multidisciplinary research community with a common terminology and research agenda. Graduate students and researchers in natural language procTrade Review'Events are a key aspect of language meaning and the storylines underlying discourse. This book presents an accessible and comprehensive examination of events in language - from the philosophical and linguistic foundations to state of the art computational techniques for identifying, representing and reasoning about events and storylines.' James Allen, University of Rochester and Institute of Human and Machine Cognition'There is no technology with more potential to revolutionise digital media than the computational processing of stories. This comprehensive guide covers the field of event and storyline analysis from first principles to the state of the art. Anyone doing technical work in news innovation or future media should read this.' David Caswell, Executive Product Manager, BBC News Labs'Finally, a compendium of key, state-of-the-art ideas in narrative understanding, allowing researchers to see the big picture. Caselli, Hovy, Palmer, and Vossen have not only assembled key papers, but also created a beautiful conceptual overview of the field – a must-read for any researcher interested in narratives and storylines.' Peter Clark, Allen Institute for AITable of ContentsIntroduction and Overview Tommaso Caselli, Martha Palmer, Ed Hovy, and Piek Vossen; Part I. Foundational Components of Storylines: 1. The Role of Event-Based Representations and Reasoning in Language James Pustejovsky; 2. The Rich Event Ontology – Ontological Hub for Event Representations Claire Bonial, Susan W. Brown, Martha Palmer, and Ghazaleh Kazeminejad; 3. Decomposing Events and Storylines William Croft, Pavlìna Kalm and Michael Regan; 4. Extracting and Aligning Timelines Mark Finalyson, Andres Cremisini, and Mustafa Ocal; 5. Event Causality Paramita Mirza; 6. A Narratology-Based Framework for Storyline Extraction Piek Vossen, Tommaso Caselli, and Roxane Segers; Part II. Connecting the Dots: 7. The Richer Event Description Corpus for Event-Event Relations Tim O'Gorman, Kristin Wright-Bettner, and Martha Palmer; 8. Low-Resource Event Extraction via Share-and-Transfer and Remaining Challenges Heng Ji and Clare Voss; 9. Reading Certainty across Sources Ben Miller; 10. Narrative Homogeneity and Heterogeneity in Document Categories Dan Simonson and Tony Davis; 11. Exploring Machine-Learning Techniques for Linking Event Templates Jakub Piskorski, Fredi Šarić, Vanni Zavarella, and Martin Atkinson; 12. Semantic Storytelling – from Experiments and Prototypes to a Technical Solution Georg Rehm, Karolina Zaczynska, Peter Bourgonje, Malte Ostendorff, Julián Moreno-Schneider, Maria Berger, Jens Rauenbusch, André Schmidt, Mikka Wild, Joachim Böttger, Joachim Quantz, Jan Thomsen, and Rolf Fricke.

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Book SynopsisThis Element provides a basic introduction to sentiment analysis, aimed at helping students and professionals in corpus linguistics to understand what sentiment analysis is, how it is conducted, and where it can be applied. It begins with a definition of sentiment analysis and a discussion of the domains where sentiment analysis is conducted and used the most. Then, it introduces two main methods that are commonly used in sentiment analysis known as supervised machine-learning and unsupervised learning (or lexicon-based) methods, followed by a step-by-step explanation of how to perform sentiment analysis with R. The Element then provides two detailed examples or cases of sentiment and emotion analysis, with one using an unsupervised method and the other using a supervised learning method.Table of Contents1. Sentiment analysis: Background; 2. Methods for sentiment analysis; 3. How to do sentiment analysis with R; 4. Case study 1: A diachronic analysis of sentiments and emotions in the State of the Union Addresses; 5. Case study 2: A sentiment and emotion analysis of movie reviews; 6. Conclusion: Where we are and where we are heading; References.

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Book SynopsisThis book presents the methods, tools and techniques that are currently being used to recognise (automatically) the affect, emotion, personality and everything else beyond linguistics (paralinguistics') expressed by or embedded in human speech and language. It is the first book to provide such a systematic survey of paralinguistics in speech and language processing. The technology described has evolved mainly from automatic speech and speaker recognition and processing, but also takes into account recent developments within speech signal processing, machine intelligence and data mining. Moreover, the book offers a hands-on approach by integrating actual data sets, software, and open-source utilities which will make the book invaluable as a teaching tool and similarly useful for those professionals already in the field. Key features: Provides an integrated presentation of basic research (in phonetics/linguistics and humanities) with state-of-the-art Table of ContentsPreface xiii Acknowledgements xv List of Abbreviations xvii Part I Foundations 1 Introduction 3 1.1 What is Computational Paralinguistics? A First Approximation 3 1.2 History and Subject Area 7 1.3 Form versus Function 10 1.4 Further Aspects 12 1.4.1 The Synthesis of Emotion and Personality 12 1.4.2 Multimodality: Analysis and Generation 13 1.4.3 Applications, Usability and Ethics 15 1.5 Summary and Structure of the Book 17 References 18 2 Taxonomies 21 2.1 Traits versus States 21 2.2 Acted versus Spontaneous 25 2.3 Complex versus Simple 30 2.4 Measured versus Assessed 31 2.5 Categorical versus Continuous 33 2.6 Felt versus Perceived 35 2.7 Intentional versus Instinctual 37 2.8 Consistent versus Discrepant 38 2.9 Private versus Social 39 2.10 Prototypical versus Peripheral 40 2.11 Universal versus Culture-Specific 41 2.12 Unimodal versus Multimodal 43 2.13 All These Taxonomies – So What? 44 2.13.1 Emotion Data: The FAU AEC 45 2.13.2 Non-native Data: The C-AuDiT corpus 47 References 48 3 Aspects of Modelling 53 3.1 Theories and Models of Personality 53 3.2 Theories and Models of Emotion and Affect 55 3.3 Type and Segmentation of Units 58 3.4 Typical versus Atypical Speech 60 3.5 Context 61 3.6 Lab versus Life, or Through the Looking Glass 62 3.7 Sheep and Goats, or Single Instance Decision versus Cumulative Evidence and Overall Performance 64 3.8 The Few and the Many, or How to Analyse a Hamburger 65 3.9 Reifications, and What You are Looking for is What You Get 67 3.10 Magical Numbers versus Sound Reasoning 68 References 74 4 Formal Aspects 79 4.1 The Linguistic Code and Beyond 79 4.2 The Non-Distinctive Use of Phonetic Elements 81 4.2.1 Segmental Level: The Case of /r/ Variants 81 4.2.2 Supra-segmental Level: The Case of Pitch and Fundamental Frequency – and of Other Prosodic Parameters 82 4.2.3 In Between: The Case of Other Voice Qualities, Especially Laryngealisation 86 4.3 The Non-Distinctive Use of Linguistics Elements 91 4.3.1 Words and Word Classes 91 4.3.2 Phrase Level: The Case of Filler Phrases and Hedges 94 4.4 Disfluencies 96 4.5 Non-Verbal, Vocal Events 98 4.6 Common Traits of Formal Aspects 100 References 101 5 Functional Aspects 107 5.1 Biological Trait Primitives 109 5.1.1 Speaker Characteristics 111 5.2 Cultural Trait Primitives 112 5.2.1 Speech Characteristics 114 5.3 Personality 115 5.4 Emotion and Affect 119 5.5 Subjectivity and Sentiment Analysis 123 5.6 Deviant Speech 124 5.6.1 Pathological Speech 125 5.6.2 Temporarily Deviant Speech 129 5.6.3 Non-native Speech 130 5.7 Social Signals 131 5.8 Discrepant Communication 135 5.8.1 Indirect Speech, Irony, and Sarcasm 136 5.8.2 Deceptive Speech 138 5.8.3 Off-Talk 139 5.9 Common Traits of Functional Aspects 140 References 141 6 Corpus Engineering 159 6.1 Annotation 160 6.1.1 Assessment of Annotations 161 6.1.2 New Trends 164 6.2 Corpora and Benchmarks: Some Examples 164 6.2.1 FAU Aibo Emotion Corpus 165 6.2.2 aGender Corpus 165 6.2.3 TUM AVIC Corpus 166 6.2.4 Alcohol Language Corpus 168 6.2.5 Sleepy Language Corpus 168 6.2.6 Speaker Personality Corpus 169 6.2.7 Speaker Likability Database 170 6.2.8 NKI CCRT Speech Corpus 171 6.2.9 TIMIT Database 171 6.2.10 Final Remarks on Databases 172 References 173 Part II Modelling 7 Computational Modelling of Paralinguistics: Overview 179 References 183 8 Acoustic Features 185 8.1 Digital Signal Representation 185 8.2 Short Time Analysis 187 8.3 Acoustic Segmentation 190 8.4 Continuous Descriptors 190 8.4.1 Intensity 190 8.4.2 Zero Crossings 191 8.4.3 Autocorrelation 192 8.4.4 Spectrum and Cepstrum 194 8.4.5 Linear Prediction 198 8.4.6 Line Spectral Pairs 202 8.4.7 Perceptual Linear Prediction 203 8.4.8 Formants 205 8.4.9 Fundamental Frequency and Voicing Probability 207 8.4.10 Jitter and Shimmer 212 8.4.11 Derived Low-Level Descriptors 214 References 214 9 Linguistic Features 217 9.1 Textual Descriptors 217 9.2 Preprocessing 218 9.3 Reduction 218 9.3.1 Stopping 218 9.3.2 Stemming 219 9.3.3 Tagging 219 9.4 Modelling 220 9.4.1 Vector Space Modelling 220 9.4.2 On-line Knowledge 222 References 227 10 Supra-segmental Features 230 10.1 Functionals 231 10.2 Feature Brute-Forcing 232 10.3 Feature Stacking 233 References 234 11 Machine-Based Modelling 235 11.1 Feature Relevance Analysis 235 11.2 Machine Learning 238 11.2.1 Static Classification 238 11.2.2 Dynamic Classification: Hidden Markov Models 256 11.2.3 Regression 262 11.3 Testing Protocols 264 11.3.1 Partitioning 264 11.3.2 Balancing 266 11.3.3 Performance Measures 267 11.3.4 Result Interpretation 272 References 277 12 System Integration and Application 281 12.1 Distributed Processing 281 12.2 Autonomous and Collaborative Learning 284 12.3 Confidence Measures 286 References 287 13 ‘Hands-On’: Existing Toolkits and Practical Tutorial 289 13.1 Related Toolkits 289 13.2 openSMILE 290 13.2.1 Available Feature Extractors 293 13.3 Practical Computational Paralinguistics How-to 294 13.3.1 Obtaining and Installing openSMILE 295 13.3.2 Extracting Features 295 13.3.3 Classification and Regression 302 References 303 14 Epilogue 304 Appendix 307 A.1 openSMILE Feature Sets Used at Interspeech Challenges 307 A.2 Feature Encoding Scheme 310 References 314 Index 315

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Book SynopsisFrom tech giants to plucky startups, the world is full of companies boasting that they are on their way to replacing human interpreters, but are they right? Interpreters vs Machines offers a solid introduction to recent theory and research on human and machine interpreting, and then invites the reader to explore the future of interpreting. With a foreword by Dr Henry Liu, the 13th International Federation of Translators (FIT) President, and written by consultant interpreter and researcher Jonathan Downie, this book offers a unique combination of research and practical insight into the field of interpreting.Written in an innovative, accessible style with humorous touches and real-life case studies, this book is structured around the metaphor of playing and winning a computer game. It takes interpreters of all experience levels on a journey to better understand their own work, learn how computers attempt to interpret and explore possible futures for human interpreters. <Trade ReviewJonathan Downie continues his mission to bring interpreting research to the people. Outspokenly, he tackles fundamental questions for interpreters in the 21st Century. Firmly grounded in Interpreting Studies, Downie interlaces research with anecdotes well-founded in any interpreter’s daily life. It is an equally trailblazing and sulphurous book on the aspirations of machine interpreting, and the fatal mistake of not making a difference. The book is a welcome addition both to the debate on the future of interpreting and to my students’ literature list. Elisabet Tiselius, Stockholm University, SwedenA deep exploration of the limits of language, technology and the enabling power of human mediation in promoting understanding. This book puts interpreters back in the driver's seat, where they belong.Ewandro Magalhaes, Technology Advocate and Former Chief Interpreter in the UN System, USATable of ContentsIntroductionLevel One – The fundamentalsChapter 1: What is interpreting?Chapter 2: How humans interpretChapter 3: How computers "interpret"Level Two – How machines gained the upper handChapter 4: How we wrecked our own PRChapter 5: Speech translation's marvellous (but misleading) marketing Level Three – Choose your interpreting futureChapter 6: Human interpreting as a stopgapChapter 7: Hanging on with legal help Chapter 8: Mastering niches Chapter 9: Making interpreting matter againLevel Four – Interpreting that beats the botsChapter 10: Beating the bots Stage One: taking back interpreting PRChapter 11: Marketing interpreting that mattersChapter 12: Deliver more than wordsChapter 13: Coaching and supervisionLevel Five – One last thoughtChapter 14: It's time to call a truceBibliographyIndex

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Book SynopsisHow can you carry out discourse analysis using corpus linguistics? What research questions should I ask? Which methods should you use and when? What is a collocational network or a key cluster? Introducing the major techniques, methods and tools for corpus-assisted analysis of discourse, this book answers these questions and more, showing readers how to best use corpora in their analyses of discourse. Using carefully tailored case studies, each chapter is devoted to a central technique, including frequency, concordancing and keywords, going step by step through the process of applying different analytical procedures. Introducing a wide range of different corpora, from holiday brochures to political debates, the book considers the key debates and latest advances in the field. Fully revised and updated, this new edition includes:- A new chapter on how to conduct research projects in corpus-based discourse analysis- Completely rewritten chapters on collocation and advanced techniTrade ReviewBaker (Lancaster University, UK) looks at how corpora (computerized collections of naturally occurring language samples) can be used for discourse analysis. The book has four particular strengths. First, the author explains corpus methodologies thoroughly, including frequency and dispersion, concordances, collocates, and keyness. Second, the grounds his explanations in concrete analyses of discourse used in tourism brochures, fox-hunting debates, and news articles on refugees (among other texts), thereby offering exemplars of the methodology; included are several tabular examples of analysis. And fourth, he explores the strengths and limitations of corpus analysis, explaining the need for self-reflection with respect to methodological decision-making. An excellent guide to the scope and method of corpus linguistics as applied to discourse analysis, this book on research methods will be valuable to those in linguistics, rhetoric and communication, literary theory and other humanities fields. * Choice Reviews (of the first edition) *Is a necessity for any researcher, practitioner or student interested in the interplay of content, discourse and corpus linguistics. It is a practical, hands-on guide that articulately explores the complex workings of corpora building and analysis. It is a valuable contribution for both the novice exploring the field and the more experienced scholar aiming to refresh their understanding of this ever-growing, ever-evolving discipline. * Discourse Studies (of the first edition) *Corpus methodologies have a huge potential for use in discourse studies, and Paul Baker has written a superb introduction that combines common sense and academic expertise. As a practical 'how-to' advisor he provides an accessible explanation of the key technical and interpretative issues. As an advocate of innovation, he is sensitive to the priorities and the research paradigms of both the discourse analyst and the corpus linguist. This is a splendid book that will inspire a new generation of research. -- Professor Susan Hunston, Department of English, University of Birmingham (of the first edition)We are given examples of research which demonstrate the various techniques and these can be intriguing...Using Corpora in Discourse Analysis should indeed build bridges, for those who are not already using them, but it will also be useful to anyone interested in language as it is used in texts...the generative nature of the techniques should be stimulating for all those who monitor language use... -- Alison Duguid * Times Literary Supplement (of the first edition) *If you want to know what corpus linguistics can offer to sociolinguists interested in the relationship between language and gender, this book is the answer. I found it hard to put down. Written in a wonderfully accessible style, it provides detailed examples of the challenging questions, messy data, and satisfying, though often approximate, answers that corpus linguistics can provide. It confronts researchers with the real nitty-gritty of the challenges and rewards of each step of a corpus linguistics project. Researchers and students will both find it invaluable. -- Janet Holmes, Professor of Linguistics, Victoria University of Wellington, New Zealand (of the first edition)One of the best introductory texts on corpus assisted discourse analysis currently available. Baker expertly embeds concrete examples of critical data analysis within wider discussion of methodological choices, using a range of corpus tools. Readers will find the step by step guides particularly useful, along with Baker’s inimitable clear and engaging writing style. -- Valerie Hobbs, Senior Lecturer in Applied Linguistics, University of Sheffield, UKThis new edition combines clear explanations of key corpus concepts with significantly updated chapters. Highlighted throughout are the technological advancements in corpus tools as they are applied to contemporary research questions. Once again, Baker’s extensive expertise provides an invaluable resource for integrating discourse and corpus methodologies in linguistic research. -- Tammy Gales, Associate Professor of Linguistics, Hofstra University, USATable of Contents1. Introduction 2. The First Stages 3. Corpus Building and Annotation 4. Frequency and Dispersion 5. Concordances 6. Collocates 7. Keyness 8. Beyond Collocation 9. What Comes Next? Bibliography Index

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Book SynopsisHow can you carry out discourse analysis using corpus linguistics? What research questions should I ask? Which methods should you use and when? What is a collocational network or a key cluster? Introducing the major techniques, methods and tools for corpus-assisted analysis of discourse, this book answers these questions and more, showing readers how to best use corpora in their analyses of discourse. Using carefully tailored case studies, each chapter is devoted to a central technique, including frequency, concordancing and keywords, going step by step through the process of applying different analytical procedures. Introducing a wide range of different corpora, from holiday brochures to political debates, the book considers the key debates and latest advances in the field. Fully revised and updated, this new edition includes:- A new chapter on how to conduct research projects in corpus-based discourse analysis- Completely rewritten chapters on collocation and advanced techniTrade ReviewBaker (Lancaster University, UK) looks at how corpora (computerized collections of naturally occurring language samples) can be used for discourse analysis. The book has four particular strengths. First, the author explains corpus methodologies thoroughly, including frequency and dispersion, concordances, collocates, and keyness. Second, the grounds his explanations in concrete analyses of discourse used in tourism brochures, fox-hunting debates, and news articles on refugees (among other texts), thereby offering exemplars of the methodology; included are several tabular examples of analysis. And fourth, he explores the strengths and limitations of corpus analysis, explaining the need for self-reflection with respect to methodological decision-making. An excellent guide to the scope and method of corpus linguistics as applied to discourse analysis, this book on research methods will be valuable to those in linguistics, rhetoric and communication, literary theory and other humanities fields. * Choice Reviews (of the first edition) *Is a necessity for any researcher, practitioner or student interested in the interplay of content, discourse and corpus linguistics. It is a practical, hands-on guide that articulately explores the complex workings of corpora building and analysis. It is a valuable contribution for both the novice exploring the field and the more experienced scholar aiming to refresh their understanding of this ever-growing, ever-evolving discipline. * Discourse Studies (of the first edition) *Corpus methodologies have a huge potential for use in discourse studies, and Paul Baker has written a superb introduction that combines common sense and academic expertise. As a practical 'how-to' advisor he provides an accessible explanation of the key technical and interpretative issues. As an advocate of innovation, he is sensitive to the priorities and the research paradigms of both the discourse analyst and the corpus linguist. This is a splendid book that will inspire a new generation of research. -- Professor Susan Hunston, Department of English, University of Birmingham (of the first edition)We are given examples of research which demonstrate the various techniques and these can be intriguing...Using Corpora in Discourse Analysis should indeed build bridges, for those who are not already using them, but it will also be useful to anyone interested in language as it is used in texts...the generative nature of the techniques should be stimulating for all those who monitor language use... -- Alison Duguid * Times Literary Supplement (of the first edition) *If you want to know what corpus linguistics can offer to sociolinguists interested in the relationship between language and gender, this book is the answer. I found it hard to put down. Written in a wonderfully accessible style, it provides detailed examples of the challenging questions, messy data, and satisfying, though often approximate, answers that corpus linguistics can provide. It confronts researchers with the real nitty-gritty of the challenges and rewards of each step of a corpus linguistics project. Researchers and students will both find it invaluable. -- Janet Holmes, Professor of Linguistics, Victoria University of Wellington, New Zealand (of the first edition)One of the best introductory texts on corpus assisted discourse analysis currently available. Baker expertly embeds concrete examples of critical data analysis within wider discussion of methodological choices, using a range of corpus tools. Readers will find the step by step guides particularly useful, along with Baker’s inimitable clear and engaging writing style. -- Valerie Hobbs, Senior Lecturer in Applied Linguistics, University of Sheffield, UKThis new edition combines clear explanations of key corpus concepts with significantly updated chapters. Highlighted throughout are the technological advancements in corpus tools as they are applied to contemporary research questions. Once again, Baker’s extensive expertise provides an invaluable resource for integrating discourse and corpus methodologies in linguistic research. -- Tammy Gales, Associate Professor of Linguistics, Hofstra University, USATable of Contents1. Introduction 2. The First Stages 3. Corpus Building and Annotation 4. Frequency and Dispersion 5. Concordances 6. Collocates 7. Keyness 8. Beyond Collocation 9. What Comes Next? Bibliography Index

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Book SynopsisTrade ReviewA daring synthesis of queer theory, quantitative digital analysis and book history, this study showed me how little I knew about Shakespeare’s most enigmatic poem and its contexts. Genuinely original and potentially revolutionary. -- Jonathan Hope, Arizona State University, USAShakespeare’s Queer Analytics is an illuminating look at the perennially puzzling Love’s Martyr. Rodrigues skilfully brings computation, attribution studies, and queer theory together and makes important contributions to each of these fields. * Stephen Guy-Bray, University of British Columbia, Canada *Table of ContentsList of Plates, Figures, and Tables Series Editors' Preface Preface Acknowledgements Note on Text Introduction: Love’s Martyr and the Case for Queer Analytics Queering Computation 1. Queerness at Scale: The Radical Singularities of Love’s Martyr 2. Competitive Intimacies in the Poetical Essays Computing Queerness 3. “Neither two nor one were called”: Queer Logic and “The Phoenix and Turtle” Appendixes with Jonathan Hicks 1. Technical Appendix 2. Love’s Martyr’s Poetical Essays 3. Love’s Martyr’s Dialogues and Cantos Bibliography Notes Index

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Book SynopsisThe idea that the expression of radical beliefs is a predictor to future acts of political violence has been a central tenet of counter-extremism over the last two decades. Not only has this imposed a duty upon doctors, lecturers and teachers to inform on the radical beliefs of their patients and students but, as this book argues, it is also a fundamentally flawed concept. Informed by his own experience with the UK''s Prevent programme while teaching in a Muslim community, Rob Faure Walker explores the linguistic emergence of ''extremism'' in political discourse and the potentially damaging generative effect of this language. Taking a new approach which combines critical discourse analysis with critical realism, this book shows how the fear of being labelled as an ''extremist'' has resulted in counter-terrorism strategies which actually undermine moderating mechanisms in a democracy. Analysing the generative mechanisms by which the language of counter-extremism might actually prTrade ReviewSituating his own personal experiences in attempting to engage government, Faure Walker provides an important corrective to those who uncritically use words like ‘extremism’. This book will redefine an entire discourse on violence. * Asim Qureshi, Research Director, CAGE and Editor of ‘I Refuse to Condemn: Resisting Racism in Times of National Security’ *Faure Walker is one of the most important critical voices on the UK government’s Prevent strategy countering non-violent extremism. He offers a powerful exploration of the discourse of extremism and its negative effects. These are primarily experienced by British Muslims, but are beginning to enmesh wider populations in their damage to democracy and public life. It is necessary and salutary reading. * John Holmwood, Emeritus Professor of Sociology, University of Nottingham, UK *Table of ContentsPreface Acknowledgements Part I: Actual 1. Counter-Terrorism in the Classroom 2. Terrorism Studies Part II: Empirical 3. The Language of Counter-Extremism 4. The Emergence of ‘Extremism’ 5. The Emergence of ‘Radicalisation’ Part III: The Real 6. What Caused the emergence of ‘Extremism’ 7. Challenging the Violence of Counter-Extremism 8. The Crisis of ‘Extremism’ Notes Bibliography Index

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Book SynopsisThis handbook draws together international perspectives on technology and its application to language teaching and learning, written and edited by leading scholars in the field. It meets the increasing demand for pedagogically-informed online language instruction, which is particularly important in the context of the effects that the Covid-19 pandemic has had on the education sector on a global scale, as well as exploring language learning in informal and non-formal contexts. With contributions from5 continents and over 20 countries, including Australia, Canada, Cyprus, Denmark, Finland, France, Greece, Ireland, Japan, Spain, Sweden, the Netherlands, the UK and the USA, the book offers a thorough overview of the main influential theories and explores technology tools, approaches to research, and applications to practice. Carefully curated, this is an innovative and exciting volume for students, teachers, researchers and lecturers in language education.

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Book SynopsisJohn Regan is Lecturer in Literature and the Digital at Royal Holloway, University of London, UK.Trade ReviewExploring at scale ECCO and other corpora of 18-century texts with tools developed by researchers at the Concept Lab (Cambridge Centre for Digital Knowledge), this exciting new monograph blends expert knowledge of the period with the affordances of the digital to investigate collective meaning and knowledge formation in 18th-century Britain. For those interested in how words and their lexical associations reflect social, political, and ideological change, as well as in the revolutionary potential of distant reading large repositories of texts, this book is a rare treat. -- Ileana Baird, Zayed University, United Arab EmiratesTable of ContentsIntroduction Part I: New Digital Insights into Collective Meaning 1.‘Beauty’ and the ‘Beautiful’: Semantic Difference at Scale 2. The Cases of ‘Perception’ and ‘Knowledge’: Semantic Decay Amidst the British Print Explosion 3. ‘Attention’: A Useful, Salutary Failure 4. ‘More is Different’: How the Collective View Contributes to our Knowledge of the British Eighteenth Century Part II: Common Conceptions of ‘Slavery’ across Political and Religious Discourses 5.The Curious Case of the ‘System of Government’ 6. The Evolution of the Meaning of Liberty across the British Eighteenth Century 7.‘Protestant’ and the Antonymic Production of Collective Meaning Conclusion Appendix I: Straightening Out Uneven ECCO Appendix II: How mPMI Works and Why it is Better Than Other Methods for Discovering Collective Meaning Bibliography Index

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