{"title":"Computational and corpus linguistics Books","description":"","products":[{"product_id":"finite-element-and-finite-volume-methods-for-heat-transfer-and-fluid-dynamics-9781009275484","title":"Finite Element and Finite Volume Methods for Heat","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eIntroduces 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 t\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTrade Review\u003c\/b\u003e\u003cbr\u003e'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 University\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003ePart 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.","brand":"Cambridge University Press","offers":[{"title":"Default Title","offer_id":48738031075671,"sku":"9781009275484","price":71.24,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781009275484.jpg?v=1723811692"},{"product_id":"language-syntax-and-the-natural-sciences-9781107152946","title":"Language Syntax and the Natural Sciences","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eLanguage, 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.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003eIntroduction 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.","brand":"Cambridge University Press","offers":[{"title":"Default Title","offer_id":48738244198743,"sku":"9781107152946","price":72.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781107152946.jpg?v=1723811852"},{"product_id":"natural-language-processing-9781108420211","title":"Natural Language Processing","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eWith 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 onli\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTrade Review\u003c\/b\u003e\u003cbr\u003e'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\u003cbr\u003e'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\u003cbr\u003e'The book is a valuable tool for both beginning and advanced researchers in the field.' Catalin Stoean, zbMATH\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003ePart 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.","brand":"Cambridge University Press","offers":[{"title":"Default Title","offer_id":48738286666071,"sku":"9781108420211","price":55.09,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781108420211.jpg?v=1723811892"},{"product_id":"an-advanced-introduction-to-semantics-9781108723046","title":"An Advanced Introduction to Semantics","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eThis book is an advanced introduction to semantics that presents this crucial component of human language through the lens of the ''Meaning-Text'' theory - an approach that treats linguistic knowledge as a huge inventory of correspondences between thought and speech. Formally, semantics is viewed as an organized set of rules that connect a representation of meaning (Semantic Representation) to a representation of the sentence (Deep-Syntactic Representation). The approach is particularly interesting for computer assisted language learning, natural language processing and computational lexicography, as our linguistic rules easily lend themselves to formalization and computer applications. The model combines abstract theoretical constructions with numerous linguistic descriptions, as well as multiple practice exercises that provide a solid hands-on approach to learning how to describe natural language semantics.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTrade Review\u003c\/b\u003e\u003cbr\u003e'A practical and comprehensive approach to the description and analysis of linguistic meaning bridging the narrow interests of traditional formal theories and the looser approaches to semantic representation favoured by usage-based and typologically oriented researchers. The authors systematically introduce a rigorous and intuitively accessible approach to the representation of the meaning of words and sentences that is urgently needed by linguists interested in the description of language, cognitive scientists, lexicographers, and computational linguists in search of formalizable tools for the modelling of the semantics of natural language.' David Beck, University of Alberta\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003ePart I. Fundamentals: 1. Semantics in language and linguistics; 2. Some basic linguistic notions; Part II. Meaning in Language and Its Description: 3. Linguistic meaning; 4. Lexical meaning, lexical items and lexical units; 5. Lexicographic definition; 6. Lexical relations; 7. Lexical functions; 8. The lexical stock of a language and the dictionary; 9. Sentential meaning and meaning relations between sentences; Part III. Meaning-Text Model of Semantics: 10. Semantic representation; 11. Deep-syntactic representation; 12. Semantic rules; Concluding remarks; Appendix: some mathematical and logical notions useful to linguistics; Exercises; References; Notion and term index cum glossary; Definition index; Language index; Lexical unit and semanteme index.","brand":"Cambridge University Press","offers":[{"title":"Default Title","offer_id":48738319040855,"sku":"9781108723046","price":33.24,"currency_code":"GBP","in_stock":true}]},{"product_id":"using-corpora-in-discourse-analysis-9781350083752","title":"Using Corpora in Discourse Analysis","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cb\u003eHow 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?\u003c\/b\u003e  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 techni\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTrade Review\u003c\/b\u003e\u003cbr\u003eBaker (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) *\u003cbr\u003eIs 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) *\u003cbr\u003eCorpus 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)\u003cbr\u003eWe 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) *\u003cbr\u003eIf 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)\u003cbr\u003eOne 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, UK\u003cbr\u003eThis 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, USA\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e1. 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","brand":"Bloomsbury Publishing PLC","offers":[{"title":"Default Title","offer_id":48738586329431,"sku":"9781350083752","price":27.54,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781350083752.jpg?v=1720049562"},{"product_id":"the-emergence-of-extremism-9781350199507","title":"The Emergence of Extremism","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eThe 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 \u003ci\u003ePrevent\u003c\/i\u003e 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 pr\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTrade Review\u003c\/b\u003e\u003cbr\u003eSituating 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’ *\u003cbr\u003eFaure 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 *\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003ePreface               Acknowledgements       \u003cb\u003ePart I: Actual\u003c\/b\u003e   1.     Counter-Terrorism in the Classroom   2.     Terrorism Studies   \u003cb\u003ePart II: Empirical     \u003c\/b\u003e   3.     The Language of Counter-Extremism   4.     The Emergence of ‘Extremism’      5.     The Emergence of ‘Radicalisation’   \u003cb\u003ePart III: The Real     \u003c\/b\u003e   6.     What Caused the emergence of ‘Extremism’          7.     Challenging the Violence of Counter-Extremism               8.     The Crisis of ‘Extremism’               Notes   Bibliography Index","brand":"Bloomsbury Publishing PLC","offers":[{"title":"Default Title","offer_id":48738603827543,"sku":"9781350199507","price":24.69,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781350199507.jpg?v=1720049622"},{"product_id":"multivariate-humanities-9783030691493","title":"Multivariate Humanities","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eThis case study-based textbook in multivariate analysis for advanced students in the humanities emphasizes descriptive, exploratory analyses of various types of datasets from a wide range of sub-disciplines, promoting the use of multivariate analysis and illustrating its wide applicability. Fields featured include, but are not limited to, historical agriculture, arts (music and painting), theology, and stylometrics (authorship issues). Most analyses are based on existing data, earlier analysed in published peer-reviewed papers.\u003c\/p\u003e\u003cp\u003eFour preliminary methodological and statistical chapters provide general technical background to the case studies. The multivariate statistical methods presented and illustrated include data inspection, several varieties of principal component analysis, correspondence analysis, multidimensional scaling, cluster analysis, regression analysis, discriminant analysis, and three-mode analysis.\u003c\/p\u003e\u003cp\u003eThe bulk of the text is taken up by 14 case studies that lean heavily on graphical representations of statistical information such as biplots, using descriptive statistical techniques to support substantive conclusions. Each study features a description of the substantive background to the data, followed by discussion of appropriate multivariate techniques, and detailed results interpreted through graphical illustrations. Each study is concluded with a conceptual summary. Datasets in SPSS are included online.\u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e","brand":"Springer Nature Switzerland AG","offers":[{"title":"Default Title","offer_id":48743045529943,"sku":"9783030691493","price":82.49,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9783030691493.jpg?v=1720063870"},{"product_id":"mathematical-methods-in-linguistics-9789027722447","title":"Mathematical Methods in Linguistics","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eElementary set theory accustoms the students to mathematical  abstraction, includes the standard constructions of relations,  functions, and orderings, and leads to a discussion of the various  orders of infinity. The material on logic covers not only the standard  statement logic and first-order predicate logic but includes an  introduction to formal systems, axiomatization, and model theory. The  section on algebra is presented with an emphasis on lattices as well  as Boolean and Heyting algebras. Background for recent research in  natural language semantics includes sections on lambda-abstraction and  generalized quantifiers. Chapters on automata theory and formal  languages contain a discussion of languages between context-free and  context-sensitive and form the background for much current work in  syntactic theory and computational linguistics. The many exercises not  only reinforce basic skills but offer an entry to linguistic  applications of mathematical concepts. \u003cbr\u003e  For upper-level undergraduate students and graduate students in  theoretical linguistics, computer-science students with interests in  computational linguistics, logic programming and artificial  intelligence, mathematicians and logicians with interests in  linguistics and the semantics of natural language.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003ePreface. Part A. Set Theory. 1. Basic Concepts of Set  Theory. 2. Relations and Functions. 3. Properties of  Relations. 4. Infinities. Appendix A1. Part B. Logic and  Formal Systems. 5. Basic Concepts of Logic. 6.Statement  Logic. 7. Predicate Logic. 8. Formal Systems,  Axiomatization, and Model Theory. Appendix B1. Appendix BII.  Part C. Algebra. 9. Basic Concepts of Algebra. 10.  Operational Structures. 11. Lattices. 12. Boolean and  Heyting Algebras. Part D. English as a Formal Language.  13. Basic Concepts of Formal Languages. 14. Generalized  Quantifiers. 15. Intensionality. Part E. Languages,  Grammars, and Automata. 16. Basic Concepts of Languages,  Grammars, and Automata. 17. Finite Automata, Regular Languages  and Type 3 Grammars. 18. Pushdown Automata, Context-Free  Grammars and Languages. 19. Turing Machines, Recursively  Enumberable Languages, and Type 0 Grammars. 20. Linear Bounded  Automata, Context-Sensitive Languages and Type 1 Grammars. 21.  Languages Between Context-Free and Context-Sensitive. 22.  Transformational Grammars. Appendix EI. Appendix EII.  Review Problems. Index.","brand":"Springer","offers":[{"title":"Default Title","offer_id":48743234502999,"sku":"9789027722447","price":224.99,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9789027722447.jpg?v=1720064704"},{"product_id":"computational-linguistic-text-processing-logical-form-semantic-interpretation-discourse-relations-question-answering-9781600217005","title":"Computational Linguistic Text Processing: Logical","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e","brand":"Nova Science Publishers Inc","offers":[{"title":"Default Title","offer_id":48886604169559,"sku":"9781600217005","price":129.74,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781600217005.jpg?v=1722540825"},{"product_id":"vagueness-and-rationality-in-language-use-and-cognition-9783030159306","title":"Vagueness and Rationality in Language Use and","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eThis volume presents new conceptual and experimental studies which investigate the connection between vagueness and rationality from various systematic directions, such as philosophy, linguistics, cognitive psychology, computing science, and economics. Vagueness in language use and cognition has traditionally been interpreted in epistemic or semantic terms. The standard view of vagueness specifically suggests that considerations of agency or rationality, broadly conceived, can be left out of the equation. Most recently, new literature on vagueness has been released which suggests that the standard view is inadequate and that considerations of rationality should factor into more comprehensive models of vagueness. The methodological approaches presented here are diverse, ranging from philosophical interpretations of rational credence for vagueness to adaptations of choice theory (dynamic choice theory, revealed preference models, social choice theory), probabilistic models of pragmatic reasoning (Bayesian pragmatics), evolutionary game theory, and conceptual space models of categorisation.\u003cbr\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003ePart I: Vagueness in Rational Choice.- Vagueness and Imprecise Credence by Anna Mahtani.- Problems of Precision in Fuzzy Theories of Vagueness and Bayesian Epistemology by Nicholas J. J. Smith.- Regret, Sub-optimality, and Vagueness by Chrisoula Andreou.- Part II: Rationality in Vague Language Use and Cognition.- The Elusive Benefits of Vagueness: The Evidence so far by Matthew James Green and Kees van Deemter.- Towards an Ecology of Vagueness by José Pedro Correia and Michael Franke.- The Rationality of Vagueness by Igor Douven.- Semantic Indecision by Timoth W. Grinsell.- Grounding a Pragmatic Theory of Vagueness on Experimental Data: Semi-orders adn Weber's Law by Arnold Kochari and Robert van Rooij ","brand":"Springer Nature Switzerland AG","offers":[{"title":"Default Title","offer_id":48889011142999,"sku":"9783030159306","price":82.49,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9783030159306.jpg?v=1722552254"},{"product_id":"sprache-in-kulturellen-kontexten-language-in-cultural-contexts-9783847109679","title":"Sprache in kulturellen Kontexten \/ Language in","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e","brand":"V\u0026R unipress GmbH","offers":[{"title":"Default Title","offer_id":48889301926231,"sku":"9783847109679","price":54.19,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9783847109679.jpg?v=1722553711"},{"product_id":"the-oxford-handbook-of-word-classes-9780198852889","title":"The Oxford Handbook of Word Classes","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eThis 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 provide\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e1: 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","brand":"Oxford University Press","offers":[{"title":"Default Title","offer_id":49083401077079,"sku":"9780198852889","price":999.99,"currency_code":"GBP","in_stock":false}]},{"product_id":"shakespeares-queer-analytics-9781350178823","title":"Shakespeares Queer Analytics","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTrade Review\u003c\/b\u003e\u003cbr\u003eA 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, USA\u003cbr\u003e\u003ci\u003eShakespeare’s Queer Analytics \u003c\/i\u003eis an illuminating look at the perennially puzzling \u003ci\u003eLove’s Martyr. \u003c\/i\u003eRodrigues 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 *\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003eList of Plates, Figures, and Tables  Series Editors' Preface   Preface   Acknowledgements    Note on Text   Introduction: \u003ci\u003eLove’s Martyr\u003c\/i\u003e and the Case for Queer Analytics   \u003ci\u003eQueering Computation\u003c\/i\u003e 1. Queerness at Scale: The Radical Singularities of \u003ci\u003eLove’s Martyr\u003c\/i\u003e   2. Competitive Intimacies in the Poetical Essays    \u003ci\u003eComputing Queerness \u003c\/i\u003e 3. “Neither two nor one were called”: Queer Logic and “The Phoenix and Turtle”   \u003ci\u003eAppendixes\u003c\/i\u003e with Jonathan Hicks    1. Technical Appendix    2.\u003ci\u003e Love’s Martyr’s\u003c\/i\u003e Poetical Essays   3. \u003ci\u003eLove’s Martyr’s\u003c\/i\u003e Dialogues and Cantos   Bibliography    Notes    Index","brand":"Bloomsbury Publishing PLC","offers":[{"title":"Default Title","offer_id":49083873821015,"sku":"9781350178823","price":98.3,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781350178823.jpg?v=1725550287"},{"product_id":"essential-programming-for-linguistics-9780748638567","title":"Essential Programming for Linguistics","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eThis book is an introduction to programming for linguists.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e1 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 \u0026amp; 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 \u0026amp; 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 \u0026amp; Extended Regular Expressions); 6.1 Matching; 6.2 Character Classes; 6.3 Quantification; 6.4 Grouping, Alternation \u0026amp; Anchoring; 6.5 Memorising; 6.6 Modifiers; 6.7 Extended Regular Expressions;7 Modifying Textual Patterns (Substitution \u0026amp; Transliteration); 7.1 Substitution; 7.2 Greediness; 7.3 A Very Brief Introduction to Markup Languages (SGML, HTML \u0026amp; XML); 7.4 Transliteration; 8 Getting Things Into the Right Order (Basic Sorting); 8.1 Keys \u0026amp; 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 \u0026amp; Printing the List; 10 More Repetitiveness or How to Tie Things Together (Introducing Modularity); 10.1 Functions \u0026amp; Subroutines; 10.1.1 Creating Your Own Subroutines; 10.1.2 Calling a Subroutine; 10.1.3 Localising Variables \u0026amp; Being Strict With Yourself; 10.2 References \u0026amp; Modules; 10.2.1 Basic Named References; 10.2.2 Anonymous References; 10.2.3 What Do Modules Look Like?; 10.2.4 Importing \u0026amp; 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 \u0026amp; 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","brand":"Edinburgh University Press","offers":[{"title":"Default Title","offer_id":49404490187095,"sku":"9780748638567","price":24.99,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9780748638567.jpg?v=1730486624"},{"product_id":"the-bloomsbury-handbook-of-language-learning-and-technology-9781350340329","title":"The Bloomsbury Handbook of Language Learning and","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cb\u003eThis handbook draws together international perspectives on technology and its application to language teaching and learning\u003c\/b\u003e\u003cb\u003e, written and edited by leading scholars in the field. \u003c\/b\u003eIt 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.","brand":"Bloomsbury Publishing PLC","offers":[{"title":"Default Title","offer_id":49407538102615,"sku":"9781350340329","price":123.5,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781350340329.jpg?v=1730499709"},{"product_id":"the-corpus-phonology-of-english-9781474466998","title":"The Corpus Phonology of English","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003ePlacing contemporary spoken English at the centre of phonological research, this book tackles the issue of language variation and change through a range of methodological and theoretical approaches.","brand":"Edinburgh University Press","offers":[{"title":"Default Title","offer_id":49408883458391,"sku":"9781474466998","price":99.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781474466998.jpg?v=1730504555"},{"product_id":"linguistic-databases-9781575860923","title":"Linguistic Databases","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eLinguistic Databases explores the increasing use of databases in linguistics. The enormous potential in linguistic data - billions of utterances and messages daily - has been difficult to exploit. Many linguists have had to concentrate on introspective data with its inevitable blinders toward frequency, variation, and naturalness. Applications of linguistics have been handicapped. This volume explores the potential advantages of database applications to linguistics. Included in this volume are reports on database activities in phonetics, phonology, lexicography and syntax, comparative grammar, second-language acquisition, linguistic fieldwork, and language pathology. The book presents the specialized problems of multi-media (especially audio) and multi-lingual texts, including those in exotic writing systems. Implemented solutions are also discussed. The opportunities to use existing, minimally structured text repositories are presented.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e1. Introduction John Nerbonne; 2. Test suites for natural language processing Stephen Oepen, Klaus Netter and Judith Klein; 3. From annotated corpora to databases: the SgmlQL Jacques Le Maitre, Elisabeth Murisasco, and Monique Rolbert; 4. Markup of a test suite with SGML Martin Volk; 5. An open systems approach for an acoustic-phonetic continuous speech database: the S. tools database-management systems (STDBMS) Werner A. Deutsch, Ralf Vollman, Anton Noll, and Sylvia Moosmüller; 6. The reading database of syllable structure Erik Fudge and Linda Shockey; 7. A database application for the generation of phonetic atlas maps Edgar Haimerl; 8. Swiss-French polyphone and polyvar: telephone speech databases to model inter- and intra-speaker variability Gerard Chollet, Jean-Luc Cochard, Andrei Constantinescu, Cedric Jaboulet, and Philippe Langlais; 9. Investigating argument structure: the Russian nominalization database Andrew Bredenkamp, Louisa Sadler, and Andrew Spencer; 10. The use of a psycholinguistic database in the simplification of text for aphasic readers Siobhan Devlin and John Tait; 11. The computer learner Corpus: a testbed for electronic EFL Tools Sylviane Granger; 12. Linking wordnet to a Corpus query system Oliver Christ; 13. Multilingual data processing in the Cellar environment Gary F. Simons and John V. Thomson.","brand":"Centre for the Study of Language \u0026 Information","offers":[{"title":"Default Title","offer_id":49410307064151,"sku":"9781575860923","price":999.99,"currency_code":"GBP","in_stock":false}]},{"product_id":"the-structure-of-scientific-articles-applications-to-citation-indexing-and-summarization-9781575865560","title":"The Structure of Scientific Articles:","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eFinding a particular scientific document amid a sea of thousands of other documents can often seem like an insurmountable task. \"The Structure of Scientific Articles\" shows how linguistic theory can provide a solution by analyzing rhetorical structures to make information retrieval easier and faster. Through the use of an improved citation indexing system, this indispensable volume applies empirical discourse studies to pressing issues of document management, including attribution, the author's stance towards other work, and problem-solving processes.","brand":"Centre for the Study of Language \u0026 Information","offers":[{"title":"Default Title","offer_id":49410308276567,"sku":"9781575865560","price":26.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781575865560.jpg?v=1730509769"},{"product_id":"linguistic-issues-in-language-technology-vol-9-perspectives-on-semantic-representations-for-textual-inference-9781575868448","title":"Linguistic Issues in Language Technology Vol 9:","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eLinguistic Issues in Language Technology focuses on the relationships between linguistic insights and language technology. In conjunction with machine learning and statistical techniques, more sophisticated models of language and speech are needed to make significant progress in both existing and newly emerging areas of computational language analysis. The vast quantity of electronically accessible natural language data provides unprecedented opportunities for data-intensive analysis of linguistic phenomena, which can in turn enrich computational methods. Linguistic Issues in Language Technology provides a forum for this work. In this volume, contributors offer new perspectives on semantic representations for textual inference.","brand":"Centre for the Study of Language \u0026 Information","offers":[{"title":"Default Title","offer_id":49410308866391,"sku":"9781575868448","price":20.5,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781575868448.jpg?v=1730509772"},{"product_id":"lingvis-visual-analytics-for-linguistics-9781684000340","title":"Lingvis: Visual Analytics for Linguistics","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eThis volume collects landmark research in a burgeoning field of visual analytics for linguistics, called LingVis. Combining linguistic data and linguistically oriented research questions with techniques and methodologies developed in the computer science fields of visual analytics and information visualization, LingVis is motivated by the growing need within linguistic research for dealing with large amounts of complex, multidimensional data sets. An innovative exploration into the future of LingVis in the digital age, this foundational book both provides a representation of the current state of the field and communicates its new possibilities for addressing complex linguistic questions across the larger linguistic community.","brand":"Centre for the Study of Language \u0026 Information","offers":[{"title":"Default Title","offer_id":49411368583511,"sku":"9781684000340","price":57.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781684000340.jpg?v=1730513362"},{"product_id":"argument-mining-linguistic-foundations-9781786303035","title":"Argument Mining: Linguistic Foundations","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eThis book is an introduction to the linguistic concepts of argumentation relevant for argument mining, an important research and development activity which can be viewed as a highly complex form of information retrieval, requiring high-level natural language processing technology.  While the first four chapters develop the linguistic and conceptual aspects of argument expression, the last four are devoted to their application to argument mining. These chapters investigate the facets of argument annotation, as well as argument mining system architectures and evaluation. How annotations may be used to develop linguistic data and how to train learning algorithms is outlined. A simple implementation is then proposed. The book ends with an analysis of non-verbal argumentative discourse.  Argument Mining is an introductory book for engineers or students of linguistics, artificial intelligence and natural language processing. Most, if not all, the concepts of argumentation crucial for argument mining are carefully introduced and illustrated in a simple manner.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cp\u003ePreface xi\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 1. Introduction and Challenges \u003c\/b\u003e\u003cb\u003e1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1.1. What is argumentation? 1\u003c\/p\u003e \u003cp\u003e1.2. Argumentation and argument mining 4\u003c\/p\u003e \u003cp\u003e1.3. The origins of argumentation 7\u003c\/p\u003e \u003cp\u003e1.4. The argumentative discourse 8\u003c\/p\u003e \u003cp\u003e1.5. Contemporary trends 10\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 2. The Structure of Argumentation \u003c\/b\u003e\u003cb\u003e13\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2.1. The argument–conclusion pair 13\u003c\/p\u003e \u003cp\u003e2.2. The elementary argumentative schema 14\u003c\/p\u003e \u003cp\u003e2.2.1. Toulmin’s argumentative model 14\u003c\/p\u003e \u003cp\u003e2.2.2. Some elaborations and refinements of Toulmin’s model 17\u003c\/p\u003e \u003cp\u003e2.2.3. The geometry of arguments 18\u003c\/p\u003e \u003cp\u003e2.3. Modeling agreement and disagreement 20\u003c\/p\u003e \u003cp\u003e2.3.1. Agreeing versus disagreeing 20\u003c\/p\u003e \u003cp\u003e2.3.2. The art of resolving divergences 23\u003c\/p\u003e \u003cp\u003e2.4. The structure of an argumentation: argumentation graphs 25\u003c\/p\u003e \u003cp\u003e2.5. The role of argument schemes in argumentation 27\u003c\/p\u003e \u003cp\u003e2.5.1. Argument schemes: main concepts 27\u003c\/p\u003e \u003cp\u003e2.5.2. A few simple illustrations 28\u003c\/p\u003e \u003cp\u003e2.5.3. Argument schemes based on analogy 29\u003c\/p\u003e \u003cp\u003e2.5.4. Argument schemes based on causality 30\u003c\/p\u003e \u003cp\u003e2.6. Relations between Toulmin’s model and argumentation schemes 31\u003c\/p\u003e \u003cp\u003e2.6.1. Warrants as a popular opinion 32\u003c\/p\u003e \u003cp\u003e2.6.2. Argument schemes based on rules, explanations or hypothesis 34\u003c\/p\u003e \u003cp\u003e2.6.3. Argument schemes based on multiple supports or attacks 35\u003c\/p\u003e \u003cp\u003e2.6.4. Causality and warrants 37\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 3. The Linguistics of Argumentation \u003c\/b\u003e\u003cb\u003e39\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3.1. The structure of claims 40\u003c\/p\u003e \u003cp\u003e3.2. The linguistics of justifications 45\u003c\/p\u003e \u003cp\u003e3.3. Evaluating the strength of claims, justifications and arguments 47\u003c\/p\u003e \u003cp\u003e3.3.1. Strength factors within a proposition 49\u003c\/p\u003e \u003cp\u003e3.3.2. Structuring expressions of strength by semantic category 51\u003c\/p\u003e \u003cp\u003e3.3.3. A simple representation of strength when combining several factors 52\u003c\/p\u003e \u003cp\u003e3.3.4. Pragmatic factors of strength expression 53\u003c\/p\u003e \u003cp\u003e3.4. Rhetoric and argumentation 59\u003c\/p\u003e \u003cp\u003e3.4.1. Rhetoric and communication 60\u003c\/p\u003e \u003cp\u003e3.4.2. Logos: the art of reasoning and of constructing demonstrations 61\u003c\/p\u003e \u003cp\u003e3.4.3. Ethos: the orator profile 62\u003c\/p\u003e \u003cp\u003e3.4.4. Pathos: how to persuade an audience 63\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 4. Advanced Features of Argumentation for Argument Mining \u003c\/b\u003e\u003cb\u003e65\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4.1. Managing incoherent claims and justifications 65\u003c\/p\u003e \u003cp\u003e4.1.1. The case of justifications supporting opposite claims 66\u003c\/p\u003e \u003cp\u003e4.1.2. The case of opposite justifications justifying the same claim 67\u003c\/p\u003e \u003cp\u003e4.2. Relating claims and justifications: the need for knowledge and reasoning 67\u003c\/p\u003e \u003cp\u003e4.2.1. Investigating relatedness via corpus analysis 68\u003c\/p\u003e \u003cp\u003e4.2.2. A corpus analysis of the knowledge involved 69\u003c\/p\u003e \u003cp\u003e4.2.3. Observation synthesis 72\u003c\/p\u003e \u003cp\u003e4.3. Argument synthesis in natural language 74\u003c\/p\u003e \u003cp\u003e4.3.1. Features of a synthesis 75\u003c\/p\u003e \u003cp\u003e4.3.2. Structure of an argumentation synthesis 76\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 5. From Argumentation to Argument Mining \u003c\/b\u003e\u003cb\u003e79\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e5.1. Some facets of argument mining 79\u003c\/p\u003e \u003cp\u003e5.2. Designing annotation guidelines: some methodological elements 81\u003c\/p\u003e \u003cp\u003e5.3. What results can be expected from an argument mining system? 82\u003c\/p\u003e \u003cp\u003e5.4. Architecture of an argument mining system 83\u003c\/p\u003e \u003cp\u003e5.5. The next chapters 84\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 6. Annotation Frameworks and Principles of Argument Analysis \u003c\/b\u003e\u003cb\u003e85\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e6.1. Principles of argument analysis 86\u003c\/p\u003e \u003cp\u003e6.1.1. Argumentative discourse units 86\u003c\/p\u003e \u003cp\u003e6.1.2. Conclusions and premises 88\u003c\/p\u003e \u003cp\u003e6.1.3. Warrants and backings 89\u003c\/p\u003e \u003cp\u003e6.1.4. Qualifiers 89\u003c\/p\u003e \u003cp\u003e6.1.5. Argument schemes 90\u003c\/p\u003e \u003cp\u003e6.1.6. Attack relations: rebuttals, refutations, undercutters 90\u003c\/p\u003e \u003cp\u003e6.1.7. Illocutionary forces, speech acts 92\u003c\/p\u003e \u003cp\u003e6.1.8. Argument relations 93\u003c\/p\u003e \u003cp\u003e6.1.9. Implicit argument components and tailored annotation frameworks 95\u003c\/p\u003e \u003cp\u003e6.2. Examples of argument analysis frameworks 97\u003c\/p\u003e \u003cp\u003e6.2.1. Rhetorical Structure Theory 97\u003c\/p\u003e \u003cp\u003e6.2.2. Toulmin’s model 98\u003c\/p\u003e \u003cp\u003e6.2.3. Inference Anchoring Theory 99\u003c\/p\u003e \u003cp\u003e6.2.4. Summary 102\u003c\/p\u003e \u003cp\u003e6.3. Guidelines for argument analysis 103\u003c\/p\u003e \u003cp\u003e6.3.1. Principles of annotation guidelines 103\u003c\/p\u003e \u003cp\u003e6.3.2. Inter-annotator agreements 104\u003c\/p\u003e \u003cp\u003e6.3.3. Interpretation of IAA measures 105\u003c\/p\u003e \u003cp\u003e6.3.4. Some examples of IAAs 106\u003c\/p\u003e \u003cp\u003e6.3.5. Summary 107\u003c\/p\u003e \u003cp\u003e6.4. Annotation tools 108\u003c\/p\u003e \u003cp\u003e6.4.1. Brat 108\u003c\/p\u003e \u003cp\u003e6.4.2. RST tool 109\u003c\/p\u003e \u003cp\u003e6.4.3. AGORA-net 110\u003c\/p\u003e \u003cp\u003e6.4.4. Araucaria 110\u003c\/p\u003e \u003cp\u003e6.4.5. Rationale 111\u003c\/p\u003e \u003cp\u003e6.4.6. OVA+ 112\u003c\/p\u003e \u003cp\u003e6.4.7. Summary 113\u003c\/p\u003e \u003cp\u003e6.5. Argument corpora 114\u003c\/p\u003e \u003cp\u003e6.5.1. COMARG 115\u003c\/p\u003e \u003cp\u003e6.5.2. A news editorial corpus 115\u003c\/p\u003e \u003cp\u003e6.5.3. THF Airport ArgMining corpus 115\u003c\/p\u003e \u003cp\u003e6.5.4. A Wikipedia articles corpus 115\u003c\/p\u003e \u003cp\u003e6.5.5. AraucariaDB 115\u003c\/p\u003e \u003cp\u003e6.5.6. An annotated essays corpus 116\u003c\/p\u003e \u003cp\u003e6.5.7. A written dialogs corpus 116\u003c\/p\u003e \u003cp\u003e6.5.8. A web discourse corpus 116\u003c\/p\u003e \u003cp\u003e6.5.9. Argument Interchange Format Database 116\u003c\/p\u003e \u003cp\u003e6.5.10. Summary 117\u003c\/p\u003e \u003cp\u003e6.6. Conclusion 118\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 7. Argument Mining Applications and Systems \u003c\/b\u003e\u003cb\u003e119\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e7.1. Application domains for argument mining 119\u003c\/p\u003e \u003cp\u003e7.1.1. Opinion analysis augmented by argument mining 120\u003c\/p\u003e \u003cp\u003e7.1.2. Summarization 120\u003c\/p\u003e \u003cp\u003e7.1.3. Essays 120\u003c\/p\u003e \u003cp\u003e7.1.4. Dialogues 120\u003c\/p\u003e \u003cp\u003e7.1.5. Scientific and news articles 120\u003c\/p\u003e \u003cp\u003e7.1.6. The web 121\u003c\/p\u003e \u003cp\u003e7.1.7. Legal field 121\u003c\/p\u003e \u003cp\u003e7.1.8. Medical field 121\u003c\/p\u003e \u003cp\u003e7.1.9. Education 121\u003c\/p\u003e \u003cp\u003e7.2. Principles of argument mining systems 122\u003c\/p\u003e \u003cp\u003e7.2.1. Argumentative discourse units detection 123\u003c\/p\u003e \u003cp\u003e7.2.2. Units labeling 123\u003c\/p\u003e \u003cp\u003e7.2.3. Argument structure detection 124\u003c\/p\u003e \u003cp\u003e7.2.4. Argument completion 125\u003c\/p\u003e \u003cp\u003e7.2.5. Argument structure representation 125\u003c\/p\u003e \u003cp\u003e7.3. Some existing systems for argument mining 126\u003c\/p\u003e \u003cp\u003e7.3.1. Automatic detection of rhetorical relations 126\u003c\/p\u003e \u003cp\u003e7.3.2. Argument zoning 126\u003c\/p\u003e \u003cp\u003e7.3.3. Stance detection 127\u003c\/p\u003e \u003cp\u003e7.3.4. Argument mining for persuasive essays 127\u003c\/p\u003e \u003cp\u003e7.3.5. Argument mining for web discourse 127\u003c\/p\u003e \u003cp\u003e7.3.6. Argument mining for social media 128\u003c\/p\u003e \u003cp\u003e7.3.7. Argument scheme classification and enthymemes reconstruction 128\u003c\/p\u003e \u003cp\u003e7.3.8. Argument classes and argument strength classification 128\u003c\/p\u003e \u003cp\u003e7.3.9. Textcoop 129\u003c\/p\u003e \u003cp\u003e7.3.10. IBM debating technologies 129\u003c\/p\u003e \u003cp\u003e7.3.11. Argument mining for legal texts 129\u003c\/p\u003e \u003cp\u003e7.4. Efficiency and limitations of existing argument mining systems 130\u003c\/p\u003e \u003cp\u003e7.5. Conclusion 131\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 8. A Computational Model and a Simple Grammar-Based Implementation \u003c\/b\u003e\u003cb\u003e133\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e8.1. Identification of argumentative units 134\u003c\/p\u003e \u003cp\u003e8.1.1. Challenges raised by the identification of argumentative units 134\u003c\/p\u003e \u003cp\u003e8.1.2. Some linguistic techniques to identify ADUs 135\u003c\/p\u003e \u003cp\u003e8.2. Mining for claims 139\u003c\/p\u003e \u003cp\u003e8.2.1. The grammar formalisms 140\u003c\/p\u003e \u003cp\u003e8.2.2. Lexical issues 142\u003c\/p\u003e \u003cp\u003e8.2.3. Grammatical issues 145\u003c\/p\u003e \u003cp\u003e8.2.4. Templates for claim analysis 148\u003c\/p\u003e \u003cp\u003e8.3. Mining for supports and attacks 150\u003c\/p\u003e \u003cp\u003e8.3.1. Structures introduced by connectors 150\u003c\/p\u003e \u003cp\u003e8.3.2. Structures introduced by propositional attitudes 151\u003c\/p\u003e \u003cp\u003e8.3.3. Other linguistic forms to express supports or attacks 152\u003c\/p\u003e \u003cp\u003e8.4. Evaluating strength 153\u003c\/p\u003e \u003cp\u003e8.5. Epilogue 154\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 9. Non-Verbal Dimensions of Argumentation: a Challenge for Argument Mining \u003c\/b\u003e\u003cb\u003e155\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e9.1. The text and its additions 156\u003c\/p\u003e \u003cp\u003e9.1.1. Text, pictures and icons 156\u003c\/p\u003e \u003cp\u003e9.1.2. Transcriptions of oral debates 156\u003c\/p\u003e \u003cp\u003e9.2. Argumentation and visual aspects 157\u003c\/p\u003e \u003cp\u003e9.3. Argumentation and sound aspects 158\u003c\/p\u003e \u003cp\u003e9.3.1. Music and rationality 159\u003c\/p\u003e \u003cp\u003e9.3.2. Main features of musical structure: musical knowledge representation 160\u003c\/p\u003e \u003cp\u003e9.4. Impact of non-verbal aspects on argument strength and on argument schemes 161\u003c\/p\u003e \u003cp\u003e9.5. Ethical aspects 162\u003c\/p\u003e \u003cp\u003eBibliography 163\u003c\/p\u003e \u003cp\u003eIndex 175\u003c\/p\u003e","brand":"ISTE Ltd and John Wiley \u0026 Sons Inc","offers":[{"title":"Default Title","offer_id":49412277764439,"sku":"9781786303035","price":125.06,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781786303035.jpg?v=1730516238"},{"product_id":"formalizing-natural-languages-the-nooj-approach-9781848219021","title":"Formalizing Natural Languages: The NooJ Approach","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eThis book is at the very heart of linguistics. It provides the theoretical and methodological framework needed to create a successful linguistic project.\u003c\/p\u003e \u003cp\u003ePotential applications of descriptive linguistics include spell-checkers, intelligent search engines, information extractors and annotators, automatic summary producers, automatic translators, and more. These applications have considerable economic potential, and it is therefore important for linguists to make use of these technologies and to be able to contribute to them.\u003c\/p\u003e \u003cp\u003eThe author provides linguists with tools to help them formalize natural languages and aid in the building of software able to automatically process texts written in natural language (Natural Language Processing, or NLP).\u003c\/p\u003e \u003cp\u003eComputers are a vital tool for this, as characterizing a phenomenon using mathematical rules leads to its formalization. NooJ – a linguistic development environment software developed by the author – is described and practically applied to examples of NLP.\u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTrade Review\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eThis book lays ground for better understanding of both computational linguistics (CL) and natural language processing (NLP) perspectives, i.e. it shows how to describe language (CL) in order to build the best NLP applications (NLP). The book bridges the gap between theoretical linguistic phenomena and practical language models. It shows how computational linguists and language engineers working together can bring us closer to better language understanding by both humans and computers.\u003c\/p\u003e \u003cp\u003eThe author takes us on a stroll through the layers of language processing, explaining very soundly and giving examples and counterexamples that bring additional clarification for each step we make on that path. Starting with the tiny bits of written language, the alphabet, via dictionary and atomic linguistic units that occupy it, he clarifies the importance of each step, giving us solid ground to build upon any language project we might venture to undertake.\u003c\/p\u003e \u003cp\u003eSilberztein knows how to invite an audience into his Project, as he calls it, and introduces the topic in such a manner that makes you want to read the book until the last page (and solve all the CL and NLP problems on the way). He smoothly transitions through Parts one, two and three, building one topic upon the previous one, as if playing with lego blocks.\u003c\/p\u003e \u003cp\u003eHe begins by demonstrating the importance of defining basic (atomic) linguistic units starting with the alphabet and vocabulary that prepare us for the construction of electronic dictionaries. It is the design of the e-dictionary that will allow us and support us in formalizing the language of our interest. Thus, it is not a surprise that a thorough classification and understanding of our basic resources is needed to prepare (and prepare well) and specify affixes [\u003ci\u003ere-, de-, un-, -ation], simple words [home, love, sky], multiword units [sweet potatoes, more and more, round table] and expressions [to give up, to turn off, to take off] that we will play around with to construct and annotate new words, phrases and sentences.\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eHe then takes regular grammars, context-free grammars, context-sensitive grammars and unrestricted grammars and he makes them all work via NooJ’s multifaceted approach. The (beautiful) simplicity of this application is aligned with the way we, as humans, process vocabulary, grammar, orthography, syntax, semantics…thus making the NooJ as a tool easy to use by beginners and more advanced users alike.\u003c\/p\u003e \u003cp\u003eIt is only expected that the journey will end with applications both in parsing and generating written text. We are presented with the lexical analysis, syntactic analysis (local and structural) and transformational analysis that open up the door for more sophisticated NLP applications (Question Answering, Machine Translation, Semantic Analyzer, etc.)\u003c\/p\u003e \u003cp\u003eThe most expected audience of ‘\"Formalizing Natural Languages: The NooJ Approach’ are linguists i.e. computational linguists and NLP people (or as the author likes to call them language engieers). But, since the book holds the key that can open a whole sea of possible applications in the domains of other subfields, I would recommend it to etymologists, sociolinguists, psycholinguists, forensic linguists, internet linguists, corpus linguists or to any data scientist today. Having each chapter end with exercises and additional internet links, the book is also suitable as a class reading in NLP and CL classes, machine translation and similar. The book is presented in a way as to improve the understanding of the ways the natural language can be formalized and has the power to reveal some new applications to almost any type of written text. Since the book and NooJ as a tool came into existence in the era dominated by unstructured data, the potential of presented tool is limited only by the imagination of its user. \u003cbr\u003e—Kristina Kocijan, Department of Information and Communication Sciences Faculty of Humanities and Social Sciences University of Zagreb, Croatia\u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eAcknowledgments xi\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 1. Introduction: the Project 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1.1. Characterizing a set of infinite size 4\u003c\/p\u003e \u003cp\u003e1.2. Computers and linguistics 5\u003c\/p\u003e \u003cp\u003e1.3. Levels of formalization 6\u003c\/p\u003e \u003cp\u003e1.4. Not applicable 7\u003c\/p\u003e \u003cp\u003e1.4.1. Poetry and plays on words 7\u003c\/p\u003e \u003cp\u003e1.4.2. Stylistics and rhetoric 9\u003c\/p\u003e \u003cp\u003e1.4.3. Anaphora, coreference resolution, and semantic disambiguation 10\u003c\/p\u003e \u003cp\u003e1.4.4. Extralinguistic calculations 12\u003c\/p\u003e \u003cp\u003e1.5. NLP applications 12\u003c\/p\u003e \u003cp\u003e1.5.1. Automatic translation 14\u003c\/p\u003e \u003cp\u003e1.5.2. Part-of-speech (POS) tagging 18\u003c\/p\u003e \u003cp\u003e1.5.3. Linguistic rather than stochastic analysis 27\u003c\/p\u003e \u003cp\u003e1.6. Linguistic formalisms: NooJ 27\u003c\/p\u003e \u003cp\u003e1.7. Conclusion and structure of this book 30\u003c\/p\u003e \u003cp\u003e1.8. Exercises 31\u003c\/p\u003e \u003cp\u003e1.9. Internet links 32\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart 1. Linguistic Units 35\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 2. Formalizing the Alphabet 37\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2.1. Bits and bytes 37\u003c\/p\u003e \u003cp\u003e2.2. Digitizing information 39\u003c\/p\u003e \u003cp\u003e2.3. Representing natural numbers 39\u003c\/p\u003e \u003cp\u003e2.3.1. Decimal notation 39\u003c\/p\u003e \u003cp\u003e2.3.2. Binary notation 40\u003c\/p\u003e \u003cp\u003e2.3.3. Hexadecimal notation 41\u003c\/p\u003e \u003cp\u003e2.4. Encoding characters 41\u003c\/p\u003e \u003cp\u003e2.4.1. Standardization of encodings 43\u003c\/p\u003e \u003cp\u003e2.4.2. Accented Latin letters, diacritical marks, and ligatures 45\u003c\/p\u003e \u003cp\u003e2.4.3. Extended ASCII encodings 46\u003c\/p\u003e \u003cp\u003e2.4.4. Unicode 47\u003c\/p\u003e \u003cp\u003e2.5. Alphabetical order 53\u003c\/p\u003e \u003cp\u003e2.6. Classification of characters 56\u003c\/p\u003e \u003cp\u003e2.7. Conclusion 56\u003c\/p\u003e \u003cp\u003e2.8. Exercises 57\u003c\/p\u003e \u003cp\u003e2.9. Internet links 57\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 3. Defining Vocabulary 59\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3.1. Multiple vocabularies and the evolution of vocabulary 59\u003c\/p\u003e \u003cp\u003e3.2. Derivation 63\u003c\/p\u003e \u003cp\u003e3.2.1. Derivation applies to vocabulary elements 63\u003c\/p\u003e \u003cp\u003e3.2.2. Derivations are unpredictable 64\u003c\/p\u003e \u003cp\u003e3.2.3. Atomicity of derived words 65\u003c\/p\u003e \u003cp\u003e3.3. Atomic linguistic units (ALUs) 67\u003c\/p\u003e \u003cp\u003e3.3.1. Classification of ALUs 67\u003c\/p\u003e \u003cp\u003e3.4. Multiword units versus analyzable sequences of simple words 70\u003c\/p\u003e \u003cp\u003e3.4.1. Semantics 72\u003c\/p\u003e \u003cp\u003e3.4.2. Usage 76\u003c\/p\u003e \u003cp\u003e3.4.3. Transformational analysis 77\u003c\/p\u003e \u003cp\u003e3.5. Conclusion 80\u003c\/p\u003e \u003cp\u003e3.6. Exercises 81\u003c\/p\u003e \u003cp\u003e3.7. Internet links 81\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 4. Electronic Dictionaries 83\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4.1. Could editorial dictionaries be reused? 83\u003c\/p\u003e \u003cp\u003e4.2. LADL electronic dictionaries 90\u003c\/p\u003e \u003cp\u003e4.2.1. Lexicon-grammar 90\u003c\/p\u003e \u003cp\u003e4.2.2. DELA 93\u003c\/p\u003e \u003cp\u003e4.3. Dubois and Dubois-Charlier electronic dictionaries 94\u003c\/p\u003e \u003cp\u003e4.3.1. The Dictionnaire électronique des mots 95\u003c\/p\u003e \u003cp\u003e4.3.2. Les Verbes Français (LVF) 97\u003c\/p\u003e \u003cp\u003e4.4. Specifications for the construction of an electronic dictionary 99\u003c\/p\u003e \u003cp\u003e4.4.1. One ALU = one lexical entry 99\u003c\/p\u003e \u003cp\u003e4.4.2. Importance of derivation 100\u003c\/p\u003e \u003cp\u003e4.4.3. Orthographic variation 101\u003c\/p\u003e \u003cp\u003e4.4.4. Inflection of simple words, compound words, and expressions 103\u003c\/p\u003e \u003cp\u003e4.4.5. Expressions 104\u003c\/p\u003e \u003cp\u003e4.4.6. Integration of syntax and semantics 104\u003c\/p\u003e \u003cp\u003e4.5. Conclusion 107\u003c\/p\u003e \u003cp\u003e4.6. Exercises  108\u003c\/p\u003e \u003cp\u003e4.7. Internet links 108\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart 2. Languages, Grammars and Machines 111\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 5. Languages, Grammars, and Machines  113\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e5.1. Definitions 113\u003c\/p\u003e \u003cp\u003e5.1.1. Letters and alphabets 113\u003c\/p\u003e \u003cp\u003e5.1.2. Words and languages 114\u003c\/p\u003e \u003cp\u003e5.1.3. ALU, vocabularies, phrases, and languages 114\u003c\/p\u003e \u003cp\u003e5.1.4. Empty string 115\u003c\/p\u003e \u003cp\u003e5.1.5. Free language 116\u003c\/p\u003e \u003cp\u003e5.1.6. Grammars 116\u003c\/p\u003e \u003cp\u003e5.1.7. Machines 117\u003c\/p\u003e \u003cp\u003e5.2. Generative grammars 118\u003c\/p\u003e \u003cp\u003e5.3. Chomsky-Schützenberger hierarchy 119\u003c\/p\u003e \u003cp\u003e5.3.1. Linguistic formalisms 122\u003c\/p\u003e \u003cp\u003e5.4. The NooJ approach  124\u003c\/p\u003e \u003cp\u003e5.4.1. A multifaceted approach 124\u003c\/p\u003e \u003cp\u003e5.4.2. Unified notation 125\u003c\/p\u003e \u003cp\u003e5.4.3. Cascading architecture 127\u003c\/p\u003e \u003cp\u003e5.5. Conclusion 127\u003c\/p\u003e \u003cp\u003e5.6. Exercises  128\u003c\/p\u003e \u003cp\u003e5.7. Internet links 129\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 6. Regular Grammars 131\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e6.1. Regular expressions 131\u003c\/p\u003e \u003cp\u003e6.1.1. Some examples of regular expressions 135\u003c\/p\u003e \u003cp\u003e6.2. Finite-state graphs 137\u003c\/p\u003e \u003cp\u003e6.3. Non-deterministic and deterministic graphs 139\u003c\/p\u003e \u003cp\u003e6.4. Minimal deterministic graphs 141\u003c\/p\u003e \u003cp\u003e6.5. Kleene’s theorem 142\u003c\/p\u003e \u003cp\u003e6.6. Regular expressions with outputs and finite-state transducers 146\u003c\/p\u003e \u003cp\u003e6.7. Extensions of regular grammars 151\u003c\/p\u003e \u003cp\u003e6.7.1. Lexical symbols 151\u003c\/p\u003e \u003cp\u003e6.7.2. Syntactic symbols 153\u003c\/p\u003e \u003cp\u003e6.7.3. Symbols defined by grammars 154\u003c\/p\u003e \u003cp\u003e6.7.4. Special operators 155\u003c\/p\u003e \u003cp\u003e6.8. Conclusion 159\u003c\/p\u003e \u003cp\u003e6.9. Exercises 159\u003c\/p\u003e \u003cp\u003e6.10. Internet links 159\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 7. Context-Free Grammars 161\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e7.1. Recursion 164\u003c\/p\u003e \u003cp\u003e7.1.1. Right recursion 166\u003c\/p\u003e \u003cp\u003e7.1.2. Left recursion 167\u003c\/p\u003e \u003cp\u003e7.1.3. Middle recursion 168\u003c\/p\u003e \u003cp\u003e7.2. Parse trees  170\u003c\/p\u003e \u003cp\u003e7.3. Conclusion 173\u003c\/p\u003e \u003cp\u003e7.4. Exercises 173\u003c\/p\u003e \u003cp\u003e7.5. Internet links 174\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 8. Context-Sensitive Grammars 175\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e8.1. The NooJ approach  176\u003c\/p\u003e \u003cp\u003e8.1.1. The anbncn language 177\u003c\/p\u003e \u003cp\u003e8.1.2. The language a2n 180\u003c\/p\u003e \u003cp\u003e8.1.3. Handling reduplications 181\u003c\/p\u003e \u003cp\u003e8.1.4. Grammatical agreements 182\u003c\/p\u003e \u003cp\u003e8.1.5. Lexical constraints in morphological grammars 185\u003c\/p\u003e \u003cp\u003e8.2. NooJ contextual constraints 186\u003c\/p\u003e \u003cp\u003e8.3. NooJ variables 188\u003c\/p\u003e \u003cp\u003e8.3.1. Variables’ scope 188\u003c\/p\u003e \u003cp\u003e8.3.2. Computing a variable’s value 189\u003c\/p\u003e \u003cp\u003e8.3.3. Inheriting a variable’s value 191\u003c\/p\u003e \u003cp\u003e8.4. Conclusion 191\u003c\/p\u003e \u003cp\u003e8.5. Exercises  192\u003c\/p\u003e \u003cp\u003e8.6. Internet links 192\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 9. Unrestricted Grammars 195\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e9.1. Linguistic adequacy 197\u003c\/p\u003e \u003cp\u003e9.2. Conclusion 199\u003c\/p\u003e \u003cp\u003e9.3. Exercise 199\u003c\/p\u003e \u003cp\u003e9.4. Internet links 199\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart 3. Automatic Linguistic Parsing 201\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 10. Text Annotation Structure 205\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e10.1. Parsing a text 205\u003c\/p\u003e \u003cp\u003e10.2. Annotations 206\u003c\/p\u003e \u003cp\u003e10.2.1. Limits of XML\/TEI representation 207\u003c\/p\u003e \u003cp\u003e10.3. Text annotation structure (TAS) 208\u003c\/p\u003e \u003cp\u003e10.4. Exercise 211\u003c\/p\u003e \u003cp\u003e10.5. Internet links 212\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 11. Lexical Analysis 213\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e11.1. Tokenization 213\u003c\/p\u003e \u003cp\u003e11.1.1. Letter recognition 214\u003c\/p\u003e \u003cp\u003e11.1.2. Apostrophe\/quote 217\u003c\/p\u003e \u003cp\u003e11.1.3. Dash\/hyphen 219\u003c\/p\u003e \u003cp\u003e11.1.4. Dot\/period\/point ambiguity 222\u003c\/p\u003e \u003cp\u003e11.2. Word forms  224\u003c\/p\u003e \u003cp\u003e11.2.1. Space and punctuation 224\u003c\/p\u003e \u003cp\u003e11.2.2. Numbers 226\u003c\/p\u003e \u003cp\u003e11.2.3. Words in upper case 228\u003c\/p\u003e \u003cp\u003e11.3. Morphological analyses 229\u003c\/p\u003e \u003cp\u003e11.3.1. Inflectional morphology  230\u003c\/p\u003e \u003cp\u003e11.3.2. Derivational morphology 234\u003c\/p\u003e \u003cp\u003e11.3.3. Lexical morphology  236\u003c\/p\u003e \u003cp\u003e11.3.4. Agglutinations  239\u003c\/p\u003e \u003cp\u003e11.4. Multiword unit recognition 241\u003c\/p\u003e \u003cp\u003e11.5. Recognizing expressions 243\u003c\/p\u003e \u003cp\u003e11.5.1. Characteristic constituent 244\u003c\/p\u003e \u003cp\u003e11.5.2. Varying the characteristic constituent 245\u003c\/p\u003e \u003cp\u003e11.5.3. Varying the light verb 246\u003c\/p\u003e \u003cp\u003e11.5.4. Resolving ambiguity 247\u003c\/p\u003e \u003cp\u003e11.5.5. Annotating expressions 251\u003c\/p\u003e \u003cp\u003e11.6. Conclusion  254\u003c\/p\u003e \u003cp\u003e11.7. Exercise  255\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 12. Syntactic Analysis 257\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e12.1. Local grammars 257\u003c\/p\u003e \u003cp\u003e12.1.1. Named entities 257\u003c\/p\u003e \u003cp\u003e12.1.2. Grammatical word sequences 262\u003c\/p\u003e \u003cp\u003e12.1.3. Automatically identifying ambiguity 263\u003c\/p\u003e \u003cp\u003e12.2. Structural grammars 265\u003c\/p\u003e \u003cp\u003e12.2.1. Complex atomic linguistic units 266\u003c\/p\u003e \u003cp\u003e12.2.2. Structured annotations 268\u003c\/p\u003e \u003cp\u003e12.2.3. Ambiguities 270\u003c\/p\u003e \u003cp\u003e12.2.4. Syntax trees vs parse trees 273\u003c\/p\u003e \u003cp\u003e12.2.5. Dependency grammar and tree 276\u003c\/p\u003e \u003cp\u003e12.2.6. Resolving ambiguity transparently 279\u003c\/p\u003e \u003cp\u003e12.3. Conclusion 280\u003c\/p\u003e \u003cp\u003e12.4. Exercises 281\u003c\/p\u003e \u003cp\u003e12.5. Internet links 281\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 13. Transformational Analysis 283\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e13.1. Implementing transformations 286\u003c\/p\u003e \u003cp\u003e13.2. Theoretical problems 292\u003c\/p\u003e \u003cp\u003e13.2.1. Equivalence of transformation sequences 292\u003c\/p\u003e \u003cp\u003e13.2.2. Ambiguities in transformed sentences 293\u003c\/p\u003e \u003cp\u003e13.2.3. Theoretical sentences 294\u003c\/p\u003e \u003cp\u003e13.2.4. The number of transformations to be implemented 295\u003c\/p\u003e \u003cp\u003e13.3. Transformational analysis with NooJ 297\u003c\/p\u003e \u003cp\u003e13.3.1. Applying a grammar in “generation” mode 298\u003c\/p\u003e \u003cp\u003e13.3.2. The transformation’s arguments 299\u003c\/p\u003e \u003cp\u003e13.4. Question answering 303\u003c\/p\u003e \u003cp\u003e13.5. Semantic analysis 304\u003c\/p\u003e \u003cp\u003e13.6. Machine translation 305\u003c\/p\u003e \u003cp\u003e13.7. Conclusion 309\u003c\/p\u003e \u003cp\u003e13.8. Exercises 309\u003c\/p\u003e \u003cp\u003e13.9. Internet links 310\u003c\/p\u003e \u003cp\u003eConclusion 311\u003c\/p\u003e \u003cp\u003eBibliography 315\u003c\/p\u003e \u003cp\u003eIndex 327\u003c\/p\u003e","brand":"ISTE Ltd and John Wiley \u0026 Sons Inc","offers":[{"title":"Default Title","offer_id":49413722308951,"sku":"9781848219021","price":125.06,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781848219021.jpg?v=1730521170"},{"product_id":"multivariate-humanities-9783030691523","title":"Multivariate Humanities","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eThis case study-based textbook in multivariate analysis for advanced students in the humanities emphasizes descriptive, exploratory analyses of various types of datasets from a wide range of sub-disciplines, promoting the use of multivariate analysis and illustrating its wide applicability. Fields featured include, but are not limited to, historical agriculture, arts (music and painting), theology, and stylometrics (authorship issues). Most analyses are based on existing data, earlier analysed in published peer-reviewed papers.\u003c\/p\u003e\u003cp\u003eFour preliminary methodological and statistical chapters provide general technical background to the case studies. The multivariate statistical methods presented and illustrated include data inspection, several varieties of principal component analysis, correspondence analysis, multidimensional scaling, cluster analysis, regression analysis, discriminant analysis, and three-mode analysis.\u003c\/p\u003e\u003cp\u003eThe bulk of the text is taken up by 14 case studies that lean heavily on graphical representations of statistical information such as biplots, using descriptive statistical techniques to support substantive conclusions. Each study features a description of the substantive background to the data, followed by discussion of appropriate multivariate techniques, and detailed results interpreted through graphical illustrations. Each study is concluded with a conceptual summary. Datasets in SPSS are included online.\u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e","brand":"Springer Nature Switzerland AG","offers":[{"title":"Default Title","offer_id":49415630127447,"sku":"9783030691523","price":59.99,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9783030691523.jpg?v=1730527578"},{"product_id":"natural-scientific-language-processing-and-research-knowledge-graphs-9783031657931","title":"Natural Scientific Language Processing and","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e","brand":"Springer Nature Switzerland","offers":[{"title":"Default Title","offer_id":49415752745303,"sku":"9783031657931","price":98.99,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9783031657931.jpg?v=1730527988"},{"product_id":"mathematical-models-for-speech-technology-9780470844076","title":"Mathematical Models for Speech Technology","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003ePresents 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.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTrade Review\u003c\/b\u003e\u003cbr\u003e\"...a succinct presentation of the most important mathematical technology of speech technology and the author's ideas for overcoming the limitations of these techniques…\" (\u003ci\u003eMathematical Reviews\u003c\/i\u003e, 2005j)\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003eAuthor's preface.\u003cbr\u003e \u003cbr\u003e 1 Introduction\u003cbr\u003e \u003cbr\u003e 2 Preliminaries\u003cbr\u003e \u003cbr\u003e 2.1 The physics of speech production\u003cbr\u003e \u003cbr\u003e 2.2 The source-filter model\u003cbr\u003e \u003cbr\u003e 2.3 Information-bearing features of the speech signal\u003cbr\u003e \u003cbr\u003e 2.4 Time-frequency representations\u003cbr\u003e \u003cbr\u003e 2.5 Classifications of acoustic patterns in speech\u003cbr\u003e \u003cbr\u003e 2.6 Temporal invariance and stationarity\u003cbr\u003e \u003cbr\u003e 2.7 Taxonomy of linguistic structure\u003cbr\u003e \u003cbr\u003e 3 Mathematical models of linguistic structure\u003cbr\u003e \u003cbr\u003e 3.1 Probabilistic functions of a discrete Markov process\u003cbr\u003e \u003cbr\u003e 3.2 Formal grammars and abstract automata\u003cbr\u003e \u003cbr\u003e 4 Syntactic analysis\u003cbr\u003e \u003cbr\u003e 4.1 Deterministic parsing algorithms\u003cbr\u003e \u003cbr\u003e 4.2 Probabilistic parsing algorithms\u003cbr\u003e \u003cbr\u003e 4.3 Parsing natural language\u003cbr\u003e \u003cbr\u003e 5 Grammatical inference\u003cbr\u003e \u003cbr\u003e 5.1 Exact inference and Gold's theorem\u003cbr\u003e \u003cbr\u003e 5.2 Baum's algorithm for regular grammars\u003cbr\u003e \u003cbr\u003e 5.3 Event counting in parse trees\u003cbr\u003e \u003cbr\u003e 5.4 Baker's algorithm for context-free grammars\u003cbr\u003e \u003cbr\u003e 6 Information-theoretic analysis of speech communication\u003cbr\u003e \u003cbr\u003e 6.1 The Miller et al. experiments\u003cbr\u003e \u003cbr\u003e 6.2 Entropy of an information source\u003cbr\u003e \u003cbr\u003e 6.3 Recognition error rates and entropy\u003cbr\u003e \u003cbr\u003e 7 Automatic speech recognition and constructive theories of language\u003cbr\u003e \u003cbr\u003e 7.1 Integrated architectures\u003cbr\u003e \u003cbr\u003e 7.2 Modular architectures\u003cbr\u003e \u003cbr\u003e 7.3 Parameter estimation from fluent speech\u003cbr\u003e \u003cbr\u003e 7.4 System performance\u003cbr\u003e \u003cbr\u003e 7.5 Other speech technologies\u003cbr\u003e \u003cbr\u003e 8 Automatic speech understanding and semantics\u003cbr\u003e \u003cbr\u003e 8.1 Transcription and comprehension\u003cbr\u003e \u003cbr\u003e 8.2 Limited domain semantics\u003cbr\u003e \u003cbr\u003e 8.3 The semantics of natural language\u003cbr\u003e \u003cbr\u003e 8.4 System architectures\u003cbr\u003e \u003cbr\u003e 8.5 Human and machine performance\u003cbr\u003e \u003cbr\u003e 9 Theories of mind and language\u003cbr\u003e \u003cbr\u003e 9.1 The challenge of automatic natural language understanding\u003cbr\u003e \u003cbr\u003e 9.2 Metaphors for mind\u003cbr\u003e \u003cbr\u003e 9.3 The artificial intelligence program\u003cbr\u003e \u003cbr\u003e 10 A speculation on the prospects for a science of the mind\u003cbr\u003e \u003cbr\u003e 10.1 The parable of the thermos bottle: measurements and symbols\u003cbr\u003e \u003cbr\u003e 10.2 The four questions of science\u003cbr\u003e \u003cbr\u003e 10.3 A constructive theory of the mind\u003cbr\u003e \u003cbr\u003e 10.4 The problem of consciousness\u003cbr\u003e \u003cbr\u003e 10.5 The role of sensorimotor function, associative memory and reinforcement learning in automatic acquisition of spoken language by an autonomous robot\u003cbr\u003e \u003cbr\u003e 10.6 Final thoughts: predicting the course of discovery","brand":"John Wiley \u0026 Sons Inc","offers":[{"title":"Default Title","offer_id":49525393129815,"sku":"9780470844076","price":110.25,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9780470844076.jpg?v=1731860344"},{"product_id":"computational-paralinguistics-9781119971368","title":"Computational Paralinguistics","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eThis 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.\u003c\/p\u003e \u003cp\u003eIt 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.\u003c\/p\u003e \u003cp\u003eMoreover, 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.\u003c\/p\u003e \u003cp\u003eKey features:\u003c\/p\u003e \u003cul\u003e \u003cli\u003eProvides an integrated presentation of basic research (in phonetics\/linguistics and humanities) with state-of-the-art \u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003ePreface xiii  \u003cp\u003eAcknowledgements xv\u003c\/p\u003e \u003cp\u003eList of Abbreviations xvii\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart I Foundations\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 Introduction 3\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1.1 What is Computational Paralinguistics? A First Approximation 3\u003c\/p\u003e \u003cp\u003e1.2 History and Subject Area 7\u003c\/p\u003e \u003cp\u003e1.3 Form versus Function 10\u003c\/p\u003e \u003cp\u003e1.4 Further Aspects 12\u003c\/p\u003e \u003cp\u003e1.4.1 The Synthesis of Emotion and Personality 12\u003c\/p\u003e \u003cp\u003e1.4.2 Multimodality: Analysis and Generation 13\u003c\/p\u003e \u003cp\u003e1.4.3 Applications, Usability and Ethics 15\u003c\/p\u003e \u003cp\u003e1.5 Summary and Structure of the Book 17\u003c\/p\u003e \u003cp\u003eReferences 18\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Taxonomies 21\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2.1 Traits versus States 21\u003c\/p\u003e \u003cp\u003e2.2 Acted versus Spontaneous 25\u003c\/p\u003e \u003cp\u003e2.3 Complex versus Simple 30\u003c\/p\u003e \u003cp\u003e2.4 Measured versus Assessed 31\u003c\/p\u003e \u003cp\u003e2.5 Categorical versus Continuous 33\u003c\/p\u003e \u003cp\u003e2.6 Felt versus Perceived 35\u003c\/p\u003e \u003cp\u003e2.7 Intentional versus Instinctual 37\u003c\/p\u003e \u003cp\u003e2.8 Consistent versus Discrepant 38\u003c\/p\u003e \u003cp\u003e2.9 Private versus Social 39\u003c\/p\u003e \u003cp\u003e2.10 Prototypical versus Peripheral 40\u003c\/p\u003e \u003cp\u003e2.11 Universal versus Culture-Specific 41\u003c\/p\u003e \u003cp\u003e2.12 Unimodal versus Multimodal 43\u003c\/p\u003e \u003cp\u003e2.13 All These Taxonomies – So What? 44\u003c\/p\u003e \u003cp\u003e2.13.1 Emotion Data: The FAU AEC 45\u003c\/p\u003e \u003cp\u003e2.13.2 Non-native Data: The C-AuDiT corpus 47\u003c\/p\u003e \u003cp\u003eReferences 48\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Aspects of Modelling 53\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3.1 Theories and Models of Personality 53\u003c\/p\u003e \u003cp\u003e3.2 Theories and Models of Emotion and Affect 55\u003c\/p\u003e \u003cp\u003e3.3 Type and Segmentation of Units 58\u003c\/p\u003e \u003cp\u003e3.4 Typical versus Atypical Speech 60\u003c\/p\u003e \u003cp\u003e3.5 Context 61\u003c\/p\u003e \u003cp\u003e3.6 Lab versus Life, or Through the Looking Glass 62\u003c\/p\u003e \u003cp\u003e3.7 Sheep and Goats, or Single Instance Decision versus Cumulative Evidence and Overall Performance 64\u003c\/p\u003e \u003cp\u003e3.8 The Few and the Many, or How to Analyse a Hamburger 65\u003c\/p\u003e \u003cp\u003e3.9 Reifications, and What You are Looking for is What You Get 67\u003c\/p\u003e \u003cp\u003e3.10 Magical Numbers versus Sound Reasoning 68\u003c\/p\u003e \u003cp\u003eReferences 74\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Formal Aspects 79\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4.1 The Linguistic Code and Beyond 79\u003c\/p\u003e \u003cp\u003e4.2 The Non-Distinctive Use of Phonetic Elements 81\u003c\/p\u003e \u003cp\u003e4.2.1 Segmental Level: The Case of \/r\/ Variants 81\u003c\/p\u003e \u003cp\u003e4.2.2 Supra-segmental Level: The Case of Pitch and Fundamental Frequency – and of Other Prosodic Parameters 82\u003c\/p\u003e \u003cp\u003e4.2.3 In Between: The Case of Other Voice Qualities, Especially Laryngealisation 86\u003c\/p\u003e \u003cp\u003e4.3 The Non-Distinctive Use of Linguistics Elements 91\u003c\/p\u003e \u003cp\u003e4.3.1 Words and Word Classes 91\u003c\/p\u003e \u003cp\u003e4.3.2 Phrase Level: The Case of Filler Phrases and Hedges 94\u003c\/p\u003e \u003cp\u003e4.4 Disfluencies 96\u003c\/p\u003e \u003cp\u003e4.5 Non-Verbal, Vocal Events 98\u003c\/p\u003e \u003cp\u003e4.6 Common Traits of Formal Aspects 100\u003c\/p\u003e \u003cp\u003eReferences 101\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Functional Aspects 107\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e5.1 Biological Trait Primitives 109\u003c\/p\u003e \u003cp\u003e5.1.1 Speaker Characteristics 111\u003c\/p\u003e \u003cp\u003e5.2 Cultural Trait Primitives 112\u003c\/p\u003e \u003cp\u003e5.2.1 Speech Characteristics 114\u003c\/p\u003e \u003cp\u003e5.3 Personality 115\u003c\/p\u003e \u003cp\u003e5.4 Emotion and Affect 119\u003c\/p\u003e \u003cp\u003e5.5 Subjectivity and Sentiment Analysis 123\u003c\/p\u003e \u003cp\u003e5.6 Deviant Speech 124\u003c\/p\u003e \u003cp\u003e5.6.1 Pathological Speech 125\u003c\/p\u003e \u003cp\u003e5.6.2 Temporarily Deviant Speech 129\u003c\/p\u003e \u003cp\u003e5.6.3 Non-native Speech 130\u003c\/p\u003e \u003cp\u003e5.7 Social Signals 131\u003c\/p\u003e \u003cp\u003e5.8 Discrepant Communication 135\u003c\/p\u003e \u003cp\u003e5.8.1 Indirect Speech, Irony, and Sarcasm 136\u003c\/p\u003e \u003cp\u003e5.8.2 Deceptive Speech 138\u003c\/p\u003e \u003cp\u003e5.8.3 Off-Talk 139\u003c\/p\u003e \u003cp\u003e5.9 Common Traits of Functional Aspects 140\u003c\/p\u003e \u003cp\u003eReferences 141\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Corpus Engineering 159\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e6.1 Annotation 160\u003c\/p\u003e \u003cp\u003e6.1.1 Assessment of Annotations 161\u003c\/p\u003e \u003cp\u003e6.1.2 New Trends 164\u003c\/p\u003e \u003cp\u003e6.2 Corpora and Benchmarks: Some Examples 164\u003c\/p\u003e \u003cp\u003e6.2.1 FAU Aibo Emotion Corpus 165\u003c\/p\u003e \u003cp\u003e6.2.2 aGender Corpus 165\u003c\/p\u003e \u003cp\u003e6.2.3 TUM AVIC Corpus 166\u003c\/p\u003e \u003cp\u003e6.2.4 Alcohol Language Corpus 168\u003c\/p\u003e \u003cp\u003e6.2.5 Sleepy Language Corpus 168\u003c\/p\u003e \u003cp\u003e6.2.6 Speaker Personality Corpus 169\u003c\/p\u003e \u003cp\u003e6.2.7 Speaker Likability Database 170\u003c\/p\u003e \u003cp\u003e6.2.8 NKI CCRT Speech Corpus 171\u003c\/p\u003e \u003cp\u003e6.2.9 TIMIT Database 171\u003c\/p\u003e \u003cp\u003e6.2.10 Final Remarks on Databases 172\u003c\/p\u003e \u003cp\u003eReferences 173\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart II Modelling\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Computational Modelling of Paralinguistics: Overview 179\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eReferences 183\u003c\/p\u003e \u003cp\u003e8 Acoustic Features 185\u003c\/p\u003e \u003cp\u003e8.1 Digital Signal Representation 185\u003c\/p\u003e \u003cp\u003e8.2 Short Time Analysis 187\u003c\/p\u003e \u003cp\u003e8.3 Acoustic Segmentation 190\u003c\/p\u003e \u003cp\u003e8.4 Continuous Descriptors 190\u003c\/p\u003e \u003cp\u003e8.4.1 Intensity 190\u003c\/p\u003e \u003cp\u003e8.4.2 Zero Crossings 191\u003c\/p\u003e \u003cp\u003e8.4.3 Autocorrelation 192\u003c\/p\u003e \u003cp\u003e8.4.4 Spectrum and Cepstrum 194\u003c\/p\u003e \u003cp\u003e8.4.5 Linear Prediction 198\u003c\/p\u003e \u003cp\u003e8.4.6 Line Spectral Pairs 202\u003c\/p\u003e \u003cp\u003e8.4.7 Perceptual Linear Prediction 203\u003c\/p\u003e \u003cp\u003e8.4.8 Formants 205\u003c\/p\u003e \u003cp\u003e8.4.9 Fundamental Frequency and Voicing Probability 207\u003c\/p\u003e \u003cp\u003e8.4.10 Jitter and Shimmer 212\u003c\/p\u003e \u003cp\u003e8.4.11 Derived Low-Level Descriptors 214\u003c\/p\u003e \u003cp\u003eReferences 214\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Linguistic Features 217\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e9.1 Textual Descriptors 217\u003c\/p\u003e \u003cp\u003e9.2 Preprocessing 218\u003c\/p\u003e \u003cp\u003e9.3 Reduction 218\u003c\/p\u003e \u003cp\u003e9.3.1 Stopping 218\u003c\/p\u003e \u003cp\u003e9.3.2 Stemming 219\u003c\/p\u003e \u003cp\u003e9.3.3 Tagging 219\u003c\/p\u003e \u003cp\u003e9.4 Modelling 220\u003c\/p\u003e \u003cp\u003e9.4.1 Vector Space Modelling 220\u003c\/p\u003e \u003cp\u003e9.4.2 On-line Knowledge 222\u003c\/p\u003e \u003cp\u003eReferences 227\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 Supra-segmental Features 230\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e10.1 Functionals 231\u003c\/p\u003e \u003cp\u003e10.2 Feature Brute-Forcing 232\u003c\/p\u003e \u003cp\u003e10.3 Feature Stacking 233\u003c\/p\u003e \u003cp\u003eReferences 234\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 Machine-Based Modelling 235\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e11.1 Feature Relevance Analysis 235\u003c\/p\u003e \u003cp\u003e11.2 Machine Learning 238\u003c\/p\u003e \u003cp\u003e11.2.1 Static Classification 238\u003c\/p\u003e \u003cp\u003e11.2.2 Dynamic Classification: Hidden Markov Models 256\u003c\/p\u003e \u003cp\u003e11.2.3 Regression 262\u003c\/p\u003e \u003cp\u003e11.3 Testing Protocols 264\u003c\/p\u003e \u003cp\u003e11.3.1 Partitioning 264\u003c\/p\u003e \u003cp\u003e11.3.2 Balancing 266\u003c\/p\u003e \u003cp\u003e11.3.3 Performance Measures 267\u003c\/p\u003e \u003cp\u003e11.3.4 Result Interpretation 272\u003c\/p\u003e \u003cp\u003eReferences 277\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12 System Integration and Application 281\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e12.1 Distributed Processing 281\u003c\/p\u003e \u003cp\u003e12.2 Autonomous and Collaborative Learning 284\u003c\/p\u003e \u003cp\u003e12.3 Confidence Measures 286\u003c\/p\u003e \u003cp\u003eReferences 287\u003c\/p\u003e \u003cp\u003e\u003cb\u003e13 ‘Hands-On’: Existing Toolkits and Practical Tutorial 289\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e13.1 Related Toolkits 289\u003c\/p\u003e \u003cp\u003e13.2 openSMILE 290\u003c\/p\u003e \u003cp\u003e13.2.1 Available Feature Extractors 293\u003c\/p\u003e \u003cp\u003e13.3 Practical Computational Paralinguistics How-to 294\u003c\/p\u003e \u003cp\u003e13.3.1 Obtaining and Installing openSMILE 295\u003c\/p\u003e \u003cp\u003e13.3.2 Extracting Features 295\u003c\/p\u003e \u003cp\u003e13.3.3 Classification and Regression 302\u003c\/p\u003e \u003cp\u003eReferences 303\u003c\/p\u003e \u003cp\u003e14 Epilogue 304\u003c\/p\u003e \u003cp\u003e\u003cb\u003eAppendix 307\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eA.1 openSMILE Feature Sets Used at Interspeech Challenges 307\u003c\/p\u003e \u003cp\u003eA.2 Feature Encoding Scheme 310\u003c\/p\u003e \u003cp\u003eReferences 314\u003c\/p\u003e \u003cp\u003eIndex 315\u003c\/p\u003e\n\u003c\/li\u003e\n\u003c\/ul\u003e","brand":"John Wiley \u0026 Sons Inc","offers":[{"title":"Default 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Volume 1","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eThis volume provides an up-to-date survey of the field of corpus linguistics, a field whose methodology has revolutionized much of the empirical work done in most fields of linguistic study over the past decade.\u003c\/p\u003e \u003cp\u003eCorpus linguistics investigates human language by starting out from large collections of texts - spoken, written, or recorded. These language corpora, which are now regularly available in electronic form, are the basis for quantitative and qualitative research on almost any question of linguistic interest. Many techniques that are in use in corpus linguistics today are rooted in the tradition of the late 18th and 19th century, when linguistics began to make use of mathematical and empirical methods. Modern corpus linguistics has used and developed these methods in close connection with computer science and computational linguistics.\u003c\/p\u003e \u003cp\u003eThe handbook sketches the history of corpus linguistics, shows its potential, discusses its problems, and describes various methods of collecting, annotating, and searching corpora as well as processing corpus data. It also reports case studies that illustrate the wide range of linguistic research questions addressed in corpus linguistics. The over 60 articles included in the handbook are divided into five sections:\u003cbr\u003e(1) the origins and history of corpus linguistics and surveys of its relationship to central fields of linguistics \u003cbr\u003e(2) corpus compilation \u003cbr\u003e(3) corpus types \u003cbr\u003e(4) preprocessing of corpora \u003cbr\u003e(5) the use and exploitation of corpora. \u003c\/p\u003e \u003cp\u003eThe final section gives an overview of the results of corpus studies obtained in phonetics, phonology, morphology, syntax, semantics, sociolinguistics, historical linguistics, stylometry, dialectology, and discourse analysis. It also reports on recent advances made in human and machine translation, contrastive studies, computer-assisted language learning, and automatic summarization.\u003c\/p\u003e \u003cp\u003eThe contributors to the volume are internationally known experts in their respective fields. The handbook is intended for a wide audience ranging from teachers, university students, and scholars to anyone interested in the use of computers in linguistic analyses and applications.\u003cbr\u003e\u003c\/p\u003e","brand":"De Gruyter","offers":[{"title":"Default Title","offer_id":50470533235031,"sku":"9783110180435","price":267.32,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9783110180435.jpg?v=1744898616"},{"product_id":"computational-analysis-and-understanding-of-natural-languages-principles-methods-and-applications-9780444640420","title":"Computational Analysis and Understanding of","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e1. 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","brand":"Elsevier Science","offers":[{"title":"Default Title","offer_id":51018240819543,"sku":"9780444640420","price":180.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9780444640420.jpg?v=1750776134"},{"product_id":"shakespeare-and-scale-9781009306713","title":"Shakespeare and Scale","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e","brand":"Cambridge University Press","offers":[{"title":"Default Title","offer_id":51018614145367,"sku":"9781009306713","price":17.0,"currency_code":"GBP","in_stock":true}]},{"product_id":"the-language-of-fake-news-9781009349130","title":"The Language of Fake News","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eIn 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.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e1. 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.","brand":"Cambridge University Press","offers":[{"title":"Default Title","offer_id":51018622304599,"sku":"9781009349130","price":17.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781009349130.jpg?v=1750777555"},{"product_id":"generative-ai-in-computer-science-education-9781009581707","title":"Generative AI in Computer Science Education","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eGenerative 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.","brand":"Cambridge University Press","offers":[{"title":"Default Title","offer_id":51018658414935,"sku":"9781009581707","price":17.0,"currency_code":"GBP","in_stock":true}]},{"product_id":"natural-language-processing-in-the-real-world-9781032195339","title":"Natural Language Processing in the Real World","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cem\u003eNatural Language Processing in the Real World\u003c\/em\u003e 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. \u003cp\u003eThis 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.\u003c\/p\u003e\u003cp\u003eThis 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.\u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTrade Review\u003c\/b\u003e\u003cbr\u003e\u003cp\u003e\"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)\u003c\/p\u003e\u003cp\u003e\"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\u003c\/p\u003e\u003cp\u003e\"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)\u003c\/p\u003e\u003cp\u003e\"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\u003c\/p\u003e\u003cp\u003e\"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 \u0026amp; Science (BITS)\u003c\/p\u003e\u003cp\u003e\"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\u003c\/p\u003e\u003cp\u003e\"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)\u003c\/p\u003e\u003cp\u003e\"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.\"\u003c\/p\u003e\u003cp\u003e- Joey McCord, Founder, CTO and Adjunct Professor\u003c\/p\u003e\u003cp\u003e\"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 , Bridgetree\u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eTable of Contents:\u003c\/p\u003e\u003cp\u003eList of Figures\u003c\/p\u003e\u003cp\u003eList of Tables\u003c\/p\u003e\u003cp\u003eContributors\u003c\/p\u003e\u003cp\u003ePreface\u003c\/p\u003e\u003cp\u003eAcknowledgements \u003c\/p\u003e\u003cp\u003eChapter 1: NLP Basics\u003c\/p\u003e\u003cp\u003eChapter 2: Data Sources and Extraction\u003c\/p\u003e\u003cp\u003eChapter 3: Data Preprocessing and Transformation\u003c\/p\u003e\u003cp\u003eChapter 4: Data Modeling\u003c\/p\u003e\u003cp\u003eChapter 5: NLP Applications – Active Usage\u003c\/p\u003e\u003cp\u003eChapter 6: NLP Applications – Developing Usage\u003c\/p\u003e\u003cp\u003eChapter 7: Information Extraction and Text Transforming Models\u003c\/p\u003e\u003cp\u003eChapter 8: Text Categorisation and Affinities\u003c\/p\u003e\u003cp\u003eChapter 9: Chatbots\u003c\/p\u003e\u003cp\u003eChapter 10: Customer Review Analysis\u003c\/p\u003e\u003cp\u003eChapter 11: Recommendations and Predictions\u003c\/p\u003e\u003cp\u003eChapter 12: More Real-World Scenarios and Tips\u003c\/p\u003e\u003cp\u003eBibliography\u003cbr\u003eIndex\u003c\/p\u003e","brand":"Taylor \u0026 Francis Ltd","offers":[{"title":"Default Title","offer_id":51018892083543,"sku":"9781032195339","price":59.99,"currency_code":"GBP","in_stock":true}]},{"product_id":"natural-language-processing-in-the-real-world-9781032207032","title":"Natural Language Processing in the Real World","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003e\u003cem\u003eNatural Language Processing in the Real World\u003c\/em\u003e 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.\u003c\/p\u003e\u003cp\u003eThis 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.\u003c\/p\u003e\u003cp\u003eThis 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.\u003c\/p\u003e","brand":"CRC Press","offers":[{"title":"Default Title","offer_id":51018899849559,"sku":"9781032207032","price":999.99,"currency_code":"GBP","in_stock":false}]},{"product_id":"augmentation-technologies-and-artificial-intelligence-in-technical-communication-9781032263755","title":"Augmentation Technologies and Artificial","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eThis 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. \u003c\/p\u003e\u003cp\u003eThe 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 impact\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTrade Review\u003c\/b\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003e\"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.\" — \u003cb\u003eSaul Carliner\u003c\/b\u003e, \u003ci\u003eConcordia University, Canada\u003c\/i\u003e.\u003c\/p\u003e\u003cp\u003e\"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 \u0026amp; 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.\" — \u003cb\u003eDr. Pam Estes Brewer\u003c\/b\u003e, \u003ci\u003eMercer University, USA\u003c\/i\u003e.\u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cp\u003e\u003cstrong\u003eSection 1: Understand (rhetorics of) Augmentation Technologies \u003c\/strong\u003e1. 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 \u003cstrong\u003eSection 2: Build Literacies \u003c\/strong\u003e4. Competencies, Design Considerations, and New Roles for Work with Augmentation Technologies and AI 5. Socio-ethical Consequences and Design Futures \u003cstrong\u003eSection 3: Design Ethical Futures \u003c\/strong\u003e6. 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 \u003c\/p\u003e","brand":"Taylor \u0026 Francis Ltd","offers":[{"title":"Default Title","offer_id":51018933371223,"sku":"9781032263755","price":36.99,"currency_code":"GBP","in_stock":true}]},{"product_id":"machine-learning-and-deep-learning-in-natural-language-processing-9781032264639","title":"Machine Learning and Deep Learning in Natural","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eNatural 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. \u003cb\u003e\u003ci\u003eMachine Learning and Deep Learning in Natural Language Processing \u003c\/i\u003e\u003c\/b\u003eaims 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.\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eNLP 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, rest\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003ePreface. Editors. Contributors. \u003cb\u003ePart I Introduction. \u003c\/b\u003eChapter 1 Introduction to Machine Learning, Deep Learning, and Natural Language Processing. \u003cb\u003ePart II Overview of Conversational Agents. \u003c\/b\u003eChapter 2 Conversational Agents and Chatbots: Current Trends. Chapter 3 Unsupervised Hierarchical Model for Deep Empathetic Conversational Agents. \u003cb\u003ePart III Sentiment and Emotions. \u003c\/b\u003eChapter 4 EMOTRON: An Expressive Text-to-Speech. \u003cb\u003ePart IV Fake News and Satire. \u003c\/b\u003eChapter 5 Distinguishing Satirical and Fake News. Chapter 6 Automated Techniques for Identifying Claims and Assisting Fact Checkers. \u003cb\u003ePart V Applications in Healthcare. \u003c\/b\u003eChapter 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.\u003c\/p\u003e","brand":"Taylor \u0026 Francis Ltd","offers":[{"title":"Default Title","offer_id":51018933993815,"sku":"9781032264639","price":80.99,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781032264639.jpg?v=1750778725"},{"product_id":"nlp-application-9781032538358","title":"NLP Application","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eApplying 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.\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cb\u003e\u003c\/b\u003e\u003cp\u003eKey Features:\u003c\/p\u003e\u003cul\u003e\n\u003cp\u003e\u003c\/p\u003e\n\u003cli\u003eIncludes extensive and illustrative examples to simplify the discussed concepts\u003c\/li\u003e\n\u003cp\u003e\u003c\/p\u003e\n\u003cp\u003e\u003c\/p\u003e\n\u003cli\u003eDiscusses a novel, and yet simple, approach to NLP\u003c\/li\u003e\n\u003cp\u003e\u003c\/p\u003e\n\u003cp\u003e\u003c\/p\u003e\n\u003cli\u003eIntroduces a lightweight NLQ into SQL translation approach through the use of RDB MetaTables as a Hash table\u003c\/li\u003e\n\u003cp\u003e\u003c\/p\u003e\n\u003cp\u003e\u003c\/p\u003e\n\u003cli\u003eExtensive literature review and thorough background information on every tool, concept and technique applied\u003c\/li\u003e\n\u003cp\u003e\u003c\/p\u003e\n\u003c\/ul\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eProviding a unique approach to NLQ into SQ\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003ePreface. 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. \u003ci\u003eAppendix 1. Appendix 2. Appendix 3. Appendix 4. Appendix 5. Appendix 6. Appendix 7. Appendix 8. Appendix 9. Glossary. References. Index.\u003c\/i\u003e\u003c\/p\u003e","brand":"Taylor \u0026 Francis Ltd","offers":[{"title":"Default Title","offer_id":51019108352343,"sku":"9781032538358","price":48.99,"currency_code":"GBP","in_stock":true}]},{"product_id":"ai-for-communication-9781032571706","title":"AI for Communication","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003e\u003ci\u003eAI for Communication\u003c\/i\u003e 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.\u003c\/p\u003e\u003cp\u003eThe 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.\u003c\/p\u003e\u003cp\u003e \u003c\/p\u003e","brand":"Taylor \u0026 Francis Ltd","offers":[{"title":"Default Title","offer_id":51019122803031,"sku":"9781032571706","price":22.99,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781032571706.jpg?v=1750779377"},{"product_id":"multilingual-artificial-intelligence-9781032747224","title":"Multilingual Artificial Intelligence","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eMultilingual 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.\u003c\/p\u003e\u003cp\u003eFocusing 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.\u003c\/p\u003e\u003cp\u003eThis 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\u003c\/p\u003e","brand":"Taylor \u0026 Francis","offers":[{"title":"Default Title","offer_id":51019188273495,"sku":"9781032747224","price":37.99,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781032747224.jpg?v=1750779567"},{"product_id":"artificial-intelligence-and-large-language-models-9781032754819","title":"Artificial Intelligence and Large Language Models","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eHaving 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.\u003c\/p\u003e\u003cp\u003eKey Features:\u003c\/p\u003e\u003cul\u003e \u003cp\u003e \u003c\/p\u003e \u003cli\u003eDiscusses the fundamentals of AI for general readers\u003c\/li\u003e \u003cp\u003e \u003c\/p\u003e \u003cli\u003eIntroduces readers to the ChatGPT chatbot and how it works \u003c\/li\u003e \u003cp\u003e \u003c\/p\u003e \u003cli\u003eCovers natural language processing (NLP), the foundational building block of ChatGPT\u003c\/li\u003e \u003cp\u003e \u003c\/p\u003e \u003cli\u003eIntroduces readers to the deep learning transformer architecture\u003c\/li\u003e \u003cp\u003e \u003c\/p\u003e \u003cli\u003eCovers the fundamentals of ChatGPT training for practitioners\u003c\/li\u003e \u003c\/ul\u003e\u003cp\u003eIllustrated and organized in an accessible manner, this textbook contains particular appeal to students and course co\u003c\/p\u003e","brand":"CRC Press","offers":[{"title":"Default Title","offer_id":51019193188695,"sku":"9781032754819","price":120.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781032754819.jpg?v=1750779574"},{"product_id":"artificial-intelligence-and-large-language-models-9781032754802","title":"Artificial Intelligence and Large Language Models","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eHaving 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.\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cb\u003e\u003c\/b\u003e\u003cp\u003eKey Features:\u003c\/p\u003e\u003cul\u003e\n\u003cp\u003e\u003c\/p\u003e\n\u003cli\u003eDiscusses the fundamentals of AI for general readers\u003c\/li\u003e\n\u003cp\u003e\u003c\/p\u003e\n\u003cp\u003e\u003c\/p\u003e\n\u003cli\u003eIntroduces readers to the ChatGPT chatbot and how it works \u003c\/li\u003e\n\u003cp\u003e\u003c\/p\u003e\n\u003cp\u003e\u003c\/p\u003e\n\u003cli\u003eCovers natural language processing (NLP), the foundational building block of ChatGPT\u003c\/li\u003e\n\u003cp\u003e\u003c\/p\u003e\n\u003cp\u003e\u003c\/p\u003e\n\u003cli\u003eIntroduces readers to the deep learning transformer architecture\u003c\/li\u003e\n\u003cp\u003e\u003c\/p\u003e\n\u003cp\u003e\u003c\/p\u003e\n\u003cli\u003eCovers the fundamentals of ChatGPT training for practitioners\u003c\/li\u003e\n\u003cp\u003e\u003c\/p\u003e\n\u003c\/ul\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eIllustrated and organized in an accessible manner, this textbook contains particular appeal to st\u003c\/p\u003e","brand":"Taylor \u0026 Francis Ltd","offers":[{"title":"Default Title","offer_id":51019193286999,"sku":"9781032754802","price":48.99,"currency_code":"GBP","in_stock":true}]},{"product_id":"why-machines-will-never-rule-the-world-9781032941400","title":"Why Machines Will Never Rule the World","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eThis 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:\u003c\/p\u003e\u003cp\u003e1. Human intelligence is a capability of the human brain and central nervous system, which is a complex dynamic system\u003c\/p\u003e\u003cp\u003e2. Systems of this sort cannot be modelled mathematically in a way that allows them to operate inside a computer.\u003c\/p\u003e\u003cp\u003eIn 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\u003c\/p\u003e","brand":"Taylor \u0026 Francis","offers":[{"title":"Default Title","offer_id":51019277762903,"sku":"9781032941400","price":36.99,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781032941400.jpg?v=1750779733"},{"product_id":"english-corpus-linguistics-9781107681835","title":"English Corpus Linguistics","description":"\u003cp\u003eNow in its second edition, this is a step-by-step guide to creating and analyzing linguistic corpora. It has been extensively updated to reflect the new developments in this rapidly evolving field, and is illustrated with a wide range of examples, making it essential reading for students in all areas of linguistics.\u003c\/p\u003e","brand":"Cambridge University Press","offers":[{"title":"Default Title","offer_id":51019396448599,"sku":"9781107681835","price":21.84,"currency_code":"GBP","in_stock":true}]},{"product_id":"literature-spoken-language-and-speaking-skills-in-second-language-learning-9781108460798","title":"Literature Spoken Language and Speaking Skills in","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eThe 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 pe\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003eForeword; 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.","brand":"Cambridge University Press","offers":[{"title":"Default Title","offer_id":51019405394263,"sku":"9781108460798","price":22.99,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781108460798.jpg?v=1750780171"},{"product_id":"data-and-methods-in-corpus-linguistics-9781108731034","title":"Data and Methods in Corpus Linguistics","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e","brand":"Cambridge University Press","offers":[{"title":"Default Title","offer_id":51019415519575,"sku":"9781108731034","price":24.69,"currency_code":"GBP","in_stock":true}]},{"product_id":"interpreters-vs-machines-9781138586437","title":"Interpreters vs Machines","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eFrom 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? \u003ci\u003eInterpreters vs Machines\u003c\/i\u003e 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.\u003c\/p\u003e\u003cp\u003eWritten 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. \u0026lt;\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTrade Review\u003c\/b\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003eJonathan 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. \u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eElisabet Tiselius\u003c\/strong\u003e, Stockholm University, Sweden\u003c\/p\u003e\u003cp\u003eA 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.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eEwandro Magalhaes\u003c\/strong\u003e, Technology Advocate and Former Chief Interpreter in the UN System, USA\u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eIntroduction\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eLevel One\u003c\/strong\u003e – \u003cstrong\u003eThe fundamentals\u003c\/strong\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eChapter 1\u003c\/strong\u003e: What is interpreting?\u003c\/p\u003e\u003cp\u003e\u003cb\u003eChapter 2: \u003c\/b\u003eHow humans interpret\u003c\/p\u003e\u003cp\u003e\u003cb\u003eChapter 3: \u003c\/b\u003eHow computers \"interpret\"\u003c\/p\u003e\u003cp\u003eLevel Two – How machines gained the upper hand\u003c\/p\u003e\u003cp\u003eChapter 4: How we wrecked our own PR\u003c\/p\u003e\u003cp\u003e\u003cb\u003eChapter 5: \u003c\/b\u003eSpeech translation's marvellous (but misleading) marketing\u003cb\u003e \u003c\/b\u003e\u003c\/p\u003e\u003cp\u003eLevel Three – Choose your interpreting future\u003c\/p\u003e\u003cp\u003eChapter 6: Human interpreting as a stopgap\u003c\/p\u003e\u003cp\u003e\u003cb\u003eChapter 7: \u003c\/b\u003eHanging on with legal help \u003c\/p\u003e\u003cp\u003e\u003cb\u003eChapter 8: \u003c\/b\u003eMastering niches\u003cb\u003e \u003c\/b\u003e\u003c\/p\u003e\u003cp\u003eChapter 9: Making interpreting matter again\u003c\/p\u003e\u003cp\u003eLevel Four – Interpreting that beats the bots\u003c\/p\u003e\u003cp\u003eChapter 10: Beating the bots Stage One: taking back interpreting PR\u003c\/p\u003e\u003cp\u003e\u003cb\u003eChapter 11: \u003c\/b\u003eMarketing interpreting that matters\u003c\/p\u003e\u003cp\u003e\u003cb\u003eChapter 12: \u003c\/b\u003eDeliver more than words\u003c\/p\u003e\u003cp\u003e\u003cb\u003eChapter 13: \u003c\/b\u003eCoaching and supervision\u003c\/p\u003e\u003cp\u003eLevel Five – One last thought\u003c\/p\u003e\u003cp\u003eChapter 14: It's time to call a truce\u003c\/p\u003e\u003cp\u003e\u003cem\u003eBibliography\u003c\/em\u003e\u003c\/p\u003e\u003cp\u003eIndex\u003c\/p\u003e","brand":"Taylor \u0026 Francis Ltd","offers":[{"title":"Default Title","offer_id":51019503534423,"sku":"9781138586437","price":32.99,"currency_code":"GBP","in_stock":true}]},{"product_id":"using-corpora-in-discourse-analysis-9781350083745","title":"Using Corpora in Discourse Analysis","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cb\u003eHow 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?\u003c\/b\u003e  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 techni\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTrade Review\u003c\/b\u003e\u003cbr\u003eBaker (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) *\u003cbr\u003eIs 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) *\u003cbr\u003eCorpus 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)\u003cbr\u003eWe 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) *\u003cbr\u003eIf 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)\u003cbr\u003eOne 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, UK\u003cbr\u003eThis 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, USA\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e1. 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","brand":"Bloomsbury Publishing PLC","offers":[{"title":"Default Title","offer_id":51019626217815,"sku":"9781350083745","price":85.5,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781350083745.jpg?v=1750780824"},{"product_id":"semantic-change-and-collective-knowledge-in-18th-century-britain-9781350360495","title":"Semantic Change and Collective Knowledge in 18th","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cb\u003eJohn Regan\u003c\/b\u003e is Lecturer in Literature and the Digital at Royal Holloway, University of London, UK.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTrade Review\u003c\/b\u003e\u003cbr\u003eExploring 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 Emirates\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003eIntroduction \u003cb\u003ePart I: New Digital Insights into Collective Meaning\u003c\/b\u003e 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 \u003cb\u003ePart II: Common Conceptions of ‘Slavery’ across Political and Religious Discourses\u003c\/b\u003e 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","brand":"Bloomsbury Publishing (UK)","offers":[{"title":"Default Title","offer_id":51019653087575,"sku":"9781350360495","price":999.99,"currency_code":"GBP","in_stock":false}]},{"product_id":"functional-grammar-in-prolog-an-integrated-implementation-for-english-french-and-dutch-9783110129793","title":"Functional Grammar in Prolog: An Integrated","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e","brand":"De Gruyter","offers":[{"title":"Default Title","offer_id":51021145440599,"sku":"9783110129793","price":90.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9783110129793.jpg?v=1750785289"},{"product_id":"a-grammar-of-stories-an-introduction-9789027925350","title":"A Grammar of Stories: An Introduction","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e","brand":"De Gruyter","offers":[{"title":"Default Title","offer_id":51021335298391,"sku":"9789027925350","price":90.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9789027925350.jpg?v=1750785752"}],"url":"https:\/\/bookcurl.com\/collections\/computational-and-corpus-linguistics.oembed?page=4","provider":"Book Curl","version":"1.0","type":"link"}