Stress and accent are central, organizing features of grammar, but their precise nature continues to be a source of mystery and wonder. These issues come to the forefront in acquisition, where the tension between the abstract mental representations and the concrete physical manifestations of stress and accent is deeply reflected. Understanding the nature of the representations of stress and accent patterns, and understanding how stress and accent patterns are learned, informs all aspects of linguistic theory and language acquisition. These two themes - representation and acquisition - form the organizational backbone of this book. Each is addressed along different dimensions of stress and accent, including the position of an accent or stress within various prosodic domains and the acoustic dimensions along which the pronunciation of stress and accent may vary. The research presented in the book is multidisciplinary, encompassing theoretical linguistics, speech science, and computational and experimental research.

This book reviews ways to improve statistical machine speech translation between Polish and English. Research has been conducted mostly on dictionary-based, rule-based, and syntax-based, machine translation techniques. Most popular methodologies and tools are not well-suited for the Polish language and therefore require adaptation, and language resources are lacking in parallel and monolingual data. The main objective of this volume to develop an automatic and robust Polish-to-English translation system to meet specific translation requirements and to develop bilingual textual resources by mining comparable corpora.

Ruslan Mitkov's highly successful Oxford Handbook of Computational Linguistics has been substantially revised and expanded in this second edition. Alongside updated accounts of the topics covered in the first edition, it includes 17 new chapters on subjects such as semantic role-labelling, text-to-speech synthesis, translation technology, opinion mining and sentiment analysis, and the application of Natural Language Processing in educational and biomedical contexts, among many others. The volume is divided into four parts that examine, respectively: the linguistic fundamentals of computational linguistics; the methods and resources used, such as statistical modelling, machine learning, and corpus annotation; key language processing tasks including text segmentation, anaphora resolution, and speech recognition; and the major applications of Natural Language Processing, from machine translation to author profiling. The book will be an essential reference for researchers and students in computational linguistics and Natural Language Processing, as well as those working in related industries.

Aiming at exemplifying the methodology of learner corpus profiling, this book describes salient features of Romanian Learner English. As a starting point, the volume offers a comprehensive presentation of the Romanian-English contrastive studies. Another innovative aspect of the book refers to the use of the first Romanian Corpus of Learner English, whose compilation is the object of a methodological discussion. In one of the main chapters, the book introduces the methodology of learner corpus profiling and compares it with existing approaches. The profiling approach is emphasised by corpus-based quantitative and qualitative investigations of Romanian Learner English. Part of the investigation is dedicated to the lexico-grammatical profiles of articles, prepositions and genitives. The frequency-based collocation analyses are integrated with error analyses and extended into error pattern samples. Furthermore, contrasting typical Romanian Learner English constructions with examples from the German and the Italian learner corpora opens the path to new contrastive interlanguage analyses.

The content of this textbook is organized as a theory of language for the construction of talking robots. The main topic is the mechanism of natural language communication in both the speaker and the hearer. In the third edition the author has modernized the text, leaving the overview of traditional, theoretical, and computational linguistics, analytic philosophy of language, and mathematical complexity theory with their historical backgrounds intact. The format of the empirical analyses of English and German syntax and semantics has been adapted to current practice; and Chaps. 22-24 have been rewritten to focus more sharply on the construction of a talking robot.

This 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 provides a number of cross-linguistic case studies, exploring word classes in families including Afroasiatic, Sinitic, Mayan, Austronesian, and in sign languages. Chapters in the final part of the book discuss word classes from the perspective of various sub-disciplines of linguistics, ranging from first and second language acquisition to computational and corpus linguistics. Together, the contributions showcase the importance of word classes for the whole discipline of linguistics, while also highlighting the many ongoing debates in the areas and outlining fruitful avenues for future research.

This handbook presents an overview of the phenomenon of reference - the ability to refer to and pick out entities - which is an essential part of human language and cognition. In the volume's 21 chapters, international experts in the field offer a critical account of all aspects of reference from a range of theoretical perspectives. Chapters in the first part of the book are concerned with basic questions related to different types of referring expression and their interpretation. They address questions about the role of the speaker - including speaker intentions - and of the addressee, as well as the role played by the semantics of the linguistic forms themselves in establishing reference. This part also explores the nature of such concepts as definite and indefinite reference and specificity, and the conditions under which reference may fail. The second part of the volume looks at implications and applications, with chapters covering such topics as the acquisition of reference by children, the processing of reference both in the human brain and by machines. The volume will be of interest to linguists in a wide range of subfields, including semantics, pragmatics, computational linguistics, and psycho- and neurolinguistics, as well as scholars in related fields such as philosophy and computer science.

This book adopts a corpus-based critical discourse analysis approach and examines a corpus of newspaper articles from Pakistani and Indian publications to gain comparative insights into the ideological construction of China's Belt and Road Initiative (BRI) and the China-Pakistan Economic Corridor (CPEC) within news discourses. This book contributes to the works on perceptions of BRI in English newspapers of India and Pakistan. A multi-billion-dollar project of BRI or the "One Belt One Road" (OBOR), CPEC symbolizes a vision for regional revival under China's economic leadership and clout. Propelled by the Chinese Premier's dream to revive the Chinese economy as well as to restructure and catalyze infrastructural development in Asia, BRI is aimed at connecting Asia via land and sea routes with Europe, Africa, and the Middle Eastern states.

Sentiment analysis and opinion mining is the field of study that analyzes people's opinions, sentiments, evaluations, attitudes, and emotions from written language. It is one of the most active research areas in natural language processing and is also widely studied in data mining, Web mining, and text mining. In fact, this research has spread outside of computer science to the management sciences and social sciences due to its importance to business and society as a whole. The growing importance of sentiment analysis coincides with the growth of social media such as reviews, forum discussions, blogs, micro-blogs, Twitter, and social networks. For the first time in human history, we now have a huge volume of opinionated data recorded in digital form for analysis. Sentiment analysis systems are being applied in almost every business and social domain because opinions are central to almost all human activities and are key influencers of our behaviors. Our beliefs and perceptions of reality, and the choices we make, are largely conditioned on how others see and evaluate the world. For this reason, when we need to make a decision we often seek out the opinions of others. This is true not only for individuals but also for organizations. This book is a comprehensive introductory and survey text. It covers all important topics and the latest developments in the field with over 400 references. It is suitable for students, researchers and practitioners who are interested in social media analysis in general and sentiment analysis in particular. Lecturers can readily use it in class for courses on natural language processing, social media analysis, text mining, and data mining. Lecture slides are also available online. Table of Contents: Preface / Sentiment Analysis: A Fascinating Problem / The Problem of Sentiment Analysis / Document Sentiment Classification / Sentence Subjectivity and Sentiment Classification / Aspect-Based Sentiment Analysis / Sentiment Lexicon Generation / Opinion Summarization / Analysis of Comparative Opinions / Opinion Search and Retrieval / Opinion Spam Detection / Quality of Reviews / Concluding Remarks / Bibliography / Author Biography

The two-volume set LNCS 13396 and 13397 constitutes revised selected papers from the CICLing 2018 conference which took place in Hanoi, Vietnam, in March 2018.The total of 67 papers presented in the two volumes was carefully reviewed and selected from 181 submissions. The focus of the conference was on following topics such as computational linguistics and intelligent text and speech processing and others. The papers are organized in the following topical sections: General, Author profiling and authorship attribution, social network analysis, Information retrieval, information extraction, Lexical resources, Machine translation, Morphology, syntax, Semantics and text similarity, Sentiment analysis, Syntax and parsing, Text categorization and clustering, Text generation, and Text mining.

This is an essential guide to using digital resources in the study of English language and linguistics. Assuming no prior experience, it introduces the fundamentals of online corpora and equips readers with the skills needed to search and interpret corpus data. Later chapters focus on specific elements of linguistic analysis, namely vocabulary, grammar, discourse and pronunciation. Examples from five major online corpora illustrate key issues to consider in corpus analysis, while case studies and activities help students get to grips with the wide range of resources that are available and select those that best suit their needs. Perfect for students of corpus linguistics and applied linguistics, this engaging and accessible guide opens the door to an ever-expanding world of online resources. It is also ideal for anyone who is curious about how the English language works and has a desire to explore its many written and spoken forms. New to this Edition: - Fully revised and updated throughout, incorporating the latest developments in corpus linguistics - Expanded material on corpora in teaching, contextualising corpus texts and critical discourse analysis

The two-volume set LNCS 13396 and 13397 constitutes revised selected papers from the CICLing 2018 conference which took place in Hanoi, Vietnam, in March 2018.The total of 67 papers presented in the two volumes was carefully reviewed and selected from 181 submissions. The focus of the conference was on following topics such as computational linguistics and intelligent text and speech processing and others. The papers are organized in the following topical sections: General, Author profiling and authorship attribution, social network analysis, Information retrieval, information extraction, Lexical resources, Machine translation, Morphology, syntax, Semantics and text similarity, Sentiment analysis, Syntax and parsing, Text categorization and clustering, Text generation, and Text mining.

This open access book introduces Vector semantics, which links the formal theory of word vectors to the cognitive theory of linguistics. The computational linguists and deep learning researchers who developed word vectors have relied primarily on the ever-increasing availability of large corpora and of computers with highly parallel GPU and TPU compute engines, and their focus is with endowing computers with natural language capabilities for practical applications such as machine translation or question answering. Cognitive linguists investigate natural language from the perspective of human cognition, the relation between language and thought, and questions about conceptual universals, relying primarily on in-depth investigation of language in use. In spite of the fact that these two schools both have 'linguistics' in their name, so far there has been very limited communication between them, as their historical origins, data collection methods, and conceptual apparatuses are quite different. Vector semantics bridges the gap by presenting a formal theory, cast in terms of linear polytopes, that generalizes both word vectors and conceptual structures, by treating each dictionary definition as an equation, and the entire lexicon as a set of equations mutually constraining all meanings.

Specifically designed for linguists, this book provides an introduction to programming using Python for those with little to no experience of coding. Python is one of the most popular and widely-used programming languages as it's also available for free and runs on any operating system. All examples in the text involve language data and can be adapted or used directly for language research. The text focuses on key language-related issues: searching, text manipulation, text encoding and internet data, providing an excellent resource for language research. More experienced users of Python will also benefit from the advanced chapters on graphical user interfaces and functional programming.

The book covers theoretical work, approaches, applications, and techniques for computational models of information, language, and reasoning. Computational and technological developments that incorporate natural language are proliferating. Adequate coverage of natural language processing in artificial intelligence encounters problems on developments of specialized computational approaches and algorithms. Many difficulties are due to ambiguities in natural language and dependency of interpretations on contexts and agents. Classical approaches proceed with relevant updates, and new developments emerge in theories of formal and natural languages, computational models of information and reasoning, and related computerized applications. Its focus is on computational processing of human language and relevant medium languages, which can be theoretically formal, or for programming and specification of computational systems. The goal is to promote intelligent natural language processing, along with models of computation, language, reasoning, and other cognitive processes.

When viewed through a political lens, the act of defining terms in natural language arguably transforms knowledge into values. This unique volume explores how corporate, military, academic, and professional values shaped efforts to define computer terminology and establish an information engineering profession as a precursor to what would become computer science. As the Cold War heated up, U.S. federal agencies increasingly funded university researchers and labs to develop technologies, like the computer, that would ensure that the U.S. maintained economic prosperity and military dominance over the Soviet Union. At the same time, private corporations saw opportunities for partnering with university labs and military agencies to generate profits as they strengthened their business positions in civilian sectors. They needed a common vocabulary and principles of streamlined communication to underpin the technology development that would ensure national prosperity and military dominance. investigates how language standardization contributed to the professionalization of computer science as separate from mathematics, electrical engineering, and physics examines traditions of language standardization in earlier eras of rapid technology development around electricity and radio highlights the importance of the analogy of "the computer is like a human" to early explanations of computer design and logic traces design and development of electronic computers within political and economic contexts foregrounds the importance of human relationships in decisions about computer design This in-depth humanistic study argues for the importance of natural language in shaping what people come to think of as possible and impossible relationships between computers and humans. The work is a key reference in the history of technology and serves as a source textbook on the human-level history of computing. In addition, it addresses those with interests in sociolinguistic questions around technology studies, as well as technology development at the nexus of politics, business, and human relations.

The book features recent attempts to construct corpora for specific purposes - e.g. multifactorial Dutch (parallel), Geasy Easy Language Corpus (intralingual), HK LegCo interpreting corpus - and showcases sophisticated and innovative corpus analysis methods. It proposes new approaches to address classical themes - i.e. translation pedagogy, translation norms and equivalence, principles of translation - and brings interdisciplinary perspectives - e.g. contrastive linguistics, cognition and metaphor studies - to cast new light. It is a timely reference for the researchers as well as postgraduate students who are interested in the applications of corpus technology to solving translation and interpreting problems.

The breadth and spread of corpus-assisted discourse studies (CADS) indicate its usefulness for exploring language use within a social context. However, its theoretical foundations, limitations, and its epistemological implications must be considered so that we can adjust our research designs accordingly. This Element focuses on important meta-level questions around epistemology, while also offering a compact guide to which corpus linguistic tools are available and how they can contribute to finding out more about discourse. This Element will appeal to researchers both new and experienced, both within the CADS community and beyond.

Il volume presenta uno studio linguistico-testuale di un corpus di post di blog diaristici. L'analisi proposta si colloca all'intersezione di due indirizzi di riflessione, quello testuale e quello piu prettamente linguistico. Nell'ambito del primo il diario on-line viene studiato nelle sue peculiarita testuali e comunicative come genere di discorso all'interno di tre insiemi: generi autobiografici, generi della CMC e testi poco vincolanti. Nell'ambito del secondo viene esaminata la presenza nel corpus di una serie di tratti morfo-sintattici con l'obiettivo di poter qualificare i diari on-line in termini di distanza/vicinanza rispetto alla norma dell'italiano standard. Segue l'analisi di una serie di tratti sintattici tipici del parlato volta a scoprire in che misura i testi del corpus esaminato risultino orientati verso l'oralita.

The two-volume proceedings, LNCS 13249 and 13250, constitutes the thoroughly refereed post-workshop proceedings of the 22nd Chinese Lexical Semantics Workshop, CLSW 2021, held in Nanjing, China in May 2021. The 68 full papers and 4 short papers were carefully reviewed and selected from 261 submissions. They are organized in the following topical sections: Lexical Semantics and General Linguistics; Natural Language Processing and Language Computing; Cognitive Science and Experimental Studies; Lexical Resources and Corpus Linguistics.

One of the challenges brought on by the digital revolution of the recent decades is the mechanism by which information carried by texts can be extracted in order to access its contents. The processing of named entities remains a very active area of research, which plays a central role in natural language processing technologies and their applications. Named entity recognition, a tool used in information extraction tasks, focuses on recognizing small pieces of information in order to extract information on a larger scale. The authors use written text and examples in French and English to present the necessary elements for the readers to familiarize themselves with the main concepts related to named entities and to discover the problems associated with them, as well as the methods available in practice for solving these issues.

This SpringerBrief presents the data- information-and-time (DIT) model that precisely clarifies the semantics behind the terms data, information and their relations to the passage of real time. According to the DIT model a data item is a symbol that appears as a pattern (e.g., visual, sound, gesture, or any bit pattern) in physical space. It is generated by a human or a machine in the current contextual situation and is linked to a concept in the human mind or a set of operations of a machine. An information item delivers the sense or the idea that a human mind extracts out of a given natural language proposition that contains meaningful data items. Since the given tangible, intangible and temporal context are part of the explanation of a data item, a change of context can have an effect on the meaning of data and the sense of a proposition. The DIT model provides a framework to show how the flow of time can change the truth-value of a proposition. This book compares our notions of data, information, and time in differing contexts: in human communication, in the operation of a computer system and in a biological system. In the final Section a few simple examples demonstrate how the lessons learned from the DIT-model can help to improve the design of a computer system.

The relation between ontologies and language is currently at the forefront of natural language processing (NLP). Ontologies, as widely used models in semantic technologies, have much in common with the lexicon. A lexicon organizes words as a conventional inventory of concepts, while an ontology formalizes concepts and their logical relations. A shared lexicon is the prerequisite for knowledge-sharing through language, and a shared ontology is the prerequisite for knowledge-sharing through information technology. In building models of language, computational linguists must be able to accurately map the relations between words and the concepts that they can be linked to. This book focuses on the technology involved in enabling integration between lexical resources and semantic technologies. It will be of interest to researchers and graduate students in NLP, computational linguistics, and knowledge engineering, as well as in semantics, psycholinguistics, lexicology and morphology/syntax.

Labelling data is one of the most fundamental activities in science, and has underpinned practice, particularly in medicine, for decades, as well as research in corpus linguistics since at least the development of the Brown corpus. With the shift towards Machine Learning in Artificial Intelligence (AI), the creation of datasets to be used for training and evaluating AI systems, also known in AI as corpora, has become a central activity in the field as well. Early AI datasets were created on an ad-hoc basis to tackle specific problems. As larger and more reusable datasets were created, requiring greater investment, the need for a more systematic approach to dataset creation arose to ensure increased quality. A range of statistical methods were adopted, often but not exclusively from the medical sciences, to ensure that the labels used were not subjective, or to choose among different labels provided by the coders. A wide variety of such methods is now in regular use. This book is meant to provide a survey of the most widely used among these statistical methods supporting annotation practice. As far as the authors know, this is the first book attempting to cover the two families of methods in wider use. The first family of methods is concerned with the development of labelling schemes and, in particular, ensuring that such schemes are such that sufficient agreement can be observed among the coders. The second family includes methods developed to analyze the output of coders once the scheme has been agreed upon, particularly although not exclusively to identify the most likely label for an item among those provided by the coders. The focus of this book is primarily on Natural Language Processing, the area of AI devoted to the development of models of language interpretation and production, but many if not most of the methods discussed here are also applicable to other areas of AI, or indeed, to other areas of Data Science.

This open access book provides an in-depth description of the EU project European Language Grid (ELG). Its motivation lies in the fact that Europe is a multilingual society with 24 official European Union Member State languages and dozens of additional languages including regional and minority languages. The only meaningful way to enable multilingualism and to benefit from this rich linguistic heritage is through Language Technologies (LT) including Natural Language Processing (NLP), Natural Language Understanding (NLU), Speech Technologies and language-centric Artificial Intelligence (AI) applications. The European Language Grid provides a single umbrella platform for the European LT community, including research and industry, effectively functioning as a virtual home, marketplace, showroom, and deployment centre for all services, tools, resources, products and organisations active in the field. Today the ELG cloud platform already offers access to more than 13,000 language processing tools and language resources. It enables all stakeholders to deposit, upload and deploy their technologies and datasets. The platform also supports the long-term objective of establishing digital language equality in Europe by 2030 - to create a situation in which all European languages enjoy equal technological support. This is the very first book dedicated to Language Technology and NLP platforms. Cloud technology has only recently matured enough to make the development of a platform like ELG feasible on a larger scale. The book comprehensively describes the results of the ELG project. Following an introduction, the content is divided into four main parts: (I) ELG Cloud Platform; (II) ELG Inventory of Technologies and Resources; (III) ELG Community and Initiative; and (IV) ELG Open Calls and Pilot Projects.