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.

This book is about the nature of expression in speech. It is a comprehensive exploration of how such expression is produced and understood, and of how the emotional content of spoken words may be analysed, modelled, tested, and synthesized. Listeners can interpret tone-of-voice, assess emotional pitch, and effortlessly detect the finest modulations of speaker attitude; yet these processes present almost intractable difficulties to the researchers seeking to identify and understand them. In seeking to explain the production and perception of emotive content, Mark Tatham and Katherine Morton review the potential of biological and cognitive models. They examine how the features that make up the speech production and perception systems have been studied by biologists, psychologists, and linguists, and assess how far biological, behavioural, and linguistic models generate hypotheses that provide insights into the nature of expressive speech. The authors use recent techniques in speech synthesis and automatic speech recognition as a test bed for models of expression in speech.Acknowledging that such testing presupposes a comprehensive computational model of speech production, they put forward original proposals for its foundations and show how the relevant data structures may be modelled within its framework. This pioneering book will be of central interest to researchers in linguistics and in speech science, pathology, and technology. It will also be valuable for behavioural and cognitive scientists wanting to know more about this vital and elusive aspect of human behaviour.

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.

In this pioneering book Katarzyna Jaszczolt lays down the foundations of an original theory of meaning in discourse, reveals the cognitive foundations of discourse interpretation, and puts forward a new basis for the analysis of discourse processing. She provides a step-by-step introduction to the theory and its application, and explains new terms and formalisms as required. Dr. Jaszczolt unites the precision of truth-conditional, dynamic approaches with insights from neo-Gricean pragmatics into the role of speaker's intentions in communication. She shows that the compositionality of meaning may be understood as merger representations combining information from various sources including word meaning and sentence structure, various kinds of default interpretations, and conscious pragmatic inference.
Among the applications the author discusses are constructions that pose problems in semantic analysis such as referring expressions, propositional attitude constructions, presupposition, modality, numerals, and sentential connectives. She proposes solutions to cutting edge problems in the semantics/pragmatics interface - for example, how many levels of meaning should be distinguished; the status of underspecification; how much contextual information should be placed in the representation of the speaker's meaning; whether there are default interpretations; the stage of utterance interpretation at which pragmatic inference begins; and whether compositionality is a necessary feature of the theory of meaning and if so how it is to be defined.
The book is for students and researchers in semantics, pragmatics, computational linguistics, and philosophy of language at advanced undergraduatelevel and above.

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.

This text explores the consequences for language acquisition, language evolution and linguistic theory of taking the underlying architecture of the language faculty to be that of a dynamical system. The authors investigate whether it is possible for a complex adaptive system to identify the categories, structures and rules of a language given access only to instances of grammatical utterances of that language. The linguistic tradition says that this is impossible, but there is a growing body of literature in psychology and computer science arguing that grammar can be uncovered using purely statistical techniques applied to the distribution of forms in a string of words. The book goes on to discuss whether a learner requires information about structure that goes beyond the information that is contained in the meaning. Does the learner have to have knowledge of grammar per se prior to language acquisition, as has been traditionally assumed? The authors ask whether it is possible to adequately describe and explain linguistic phenomena if we restrict ourselves to the relatively impoverished apparatus that we require for language acquisition. They explore the consequences of adopting a radical form of minimalism to try to reconcile the linguistic facts with the book's perspective of language acquisition. Culicover and Nowak investigate to what extent it is possible to account for language variation in dynamical terms, as a consequence of the behaviour of the complex social network in which languages and the properties of languages are acquired by learners through interactions with other speakers over time.

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.

This work presents a discourse-aware Text Simplification approach that splits and rephrases complex English sentences within the semantic context in which they occur. Based on a linguistically grounded transformation stage, complex sentences are transformed into shorter utterances with a simple canonical structure that can be easily analyzed by downstream applications. To avoid breaking down the input into a disjointed sequence of statements that is difficult to interpret, the author incorporates the semantic context between the split propositions in the form of hierarchical structures and semantic relationships, thus generating a novel representation of complex assertions that puts a semantic layer on top of the simplified sentences. In a second step, she leverages the semantic hierarchy of minimal propositions to improve the performance of Open IE frameworks. She shows that such systems benefit in two dimensions. First, the canonical structure of the simplified sentences facilitates the extraction of relational tuples, leading to an improved precision and recall of the extracted relations. Second, the semantic hierarchy can be leveraged to enrich the output of existing Open IE approaches with additional meta-information, resulting in a novel lightweight semantic representation for complex text data in the form of normalized and context-preserving relational tuples.

This book brings together selected revised papers representing a multidisciplinary approach to language, music, and gesture, as well as their interaction. Among the number of multidisciplinary and comparative studies of the structure and organization of language and music, the presented book broadens the scope with the inclusion of gesture problems in the analyzed spectrum. A unique feature of the presented collection is that the papers, compiled in one volume, allow readers to see similarities and differences in gesture as an element of non-verbal communication and gesture as the main element of dance. In addition to enhancing the analysis, the data on the perception and comprehension of speech, music, and dance in regard to both their functioning in a natural situation and their reflection in various forms of performing arts makes this collection extremely useful for those who are interested in human cognitive abilities and performing skills. The book begins with a philosophical overview of recent neurophysiological studies reflecting the complexity of higher cognitive functions, which references the idea of the baroque style in art being neither linear nor stable. The following papers are allocated into 5 sections. The papers of the section "Language-Music-Gesture As Semiotic Systems" discuss the issues of symbolic and semiotic aspects of language, music, and gesture, including from the perspective of their notation. This is followed by the issues of "Language-Music-Gesture Onstage" and interaction within the idea of the "World as a Text." The papers of "Teaching Language and Music" present new teaching methods that take into account the interaction of all the cognitive systems examined. The papers of the last two sections focus on issues related primarily to language: The section "Verbalization Of Music And Gesture" considers the problem of describing musical text and non-verbal behavior with language, and papers in the final section "Emotions In Linguistics And Ai-Communication Systems" analyze the ways of expressing emotions in speech and the problems of organizing emotional communication with computer agents.

This 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.

This book explores some of the ethical, legal, and social implications of chatbots, or conversational artificial agents. It reviews the possibility of establishing meaningful social relationships with chatbots and investigates the consequences of those relationships for contemporary debates in the philosophy of Artificial Intelligence. The author introduces current technological challenges of AI and discusses how technological progress and social change influence our understanding of social relationships. He then argues that chatbots introduce epistemic uncertainty into human social discourse, but that this can be ameliorated by introducing a new ontological classification or 'status' for chatbots. This step forward would allow humans to reap the benefits of this technological development, without the attendant losses. Finally, the author considers the consequences of chatbots on human-human relationships, providing analysis on robot rights, human-centered design, and the social tension between robophobes and robophiles.

The goal of text ranking is to generate an ordered list of texts retrieved from a corpus in response to a query. Although the most common formulation of text ranking is search, instances of the task can also be found in many natural language processing (NLP) applications.This book provides an overview of text ranking with neural network architectures known as transformers, of which BERT (Bidirectional Encoder Representations from Transformers) is the best-known example. The combination of transformers and self-supervised pretraining has been responsible for a paradigm shift in NLP, information retrieval (IR), and beyond. This book provides a synthesis of existing work as a single point of entry for practitioners who wish to gain a better understanding of how to apply transformers to text ranking problems and researchers who wish to pursue work in this area. It covers a wide range of modern techniques, grouped into two high-level categories: transformer models that perform reranking in multi-stage architectures and dense retrieval techniques that perform ranking directly. Two themes pervade the book: techniques for handling long documents, beyond typical sentence-by-sentence processing in NLP, and techniques for addressing the tradeoff between effectiveness (i.e., result quality) and efficiency (e.g., query latency, model and index size). Although transformer architectures and pretraining techniques are recent innovations, many aspects of how they are applied to text ranking are relatively well understood and represent mature techniques. However, there remain many open research questions, and thus in addition to laying out the foundations of pretrained transformers for text ranking, this book also attempts to prognosticate where the field is heading.

Automating Linguistics offers an in-depth study of the history of the mathematisation and automation of the sciences of language. In the wake of the first mathematisation of the 1930s, two waves followed: machine translation in the 1950s and the development of computational linguistics and natural language processing in the 1960s. These waves were pivotal given the work of large computerised corpora in the 1990s and the unprecedented technological development of computers and software.Early machine translation was devised as a war technology originating in the sciences of war, amidst the amalgamate of mathematics, physics, logics, neurosciences, acoustics, and emerging sciences such as cybernetics and information theory. Machine translation was intended to provide mass translations for strategic purposes during the Cold War. Linguistics, in turn, did not belong to the sciences of war, and played a minor role in the pioneering projects of machine translation.Comparing the two trends, the present book reveals how the sciences of language gradually integrated the technologies of computing and software, resulting in the second-wave mathematisation of the study of language, which may be called mathematisation-automation. The integration took on various shapes contingent upon cultural and linguistic traditions (USA, ex-USSR, Great Britain and France). By contrast, working with large corpora in the 1990s, though enabled by unprecedented development of computing and software, was primarily a continuation of traditional approaches in the sciences of language sciences, such as the study of spoken and written texts, lexicography, and statistical studies of vocabulary.

This Element explores approaches to locating and examining social identity in corpora with and without the aid of demographic metadata. This is a key concern in corpus-aided studies of language and identity, and this Element sets out to explore the main challenges and affordances associated with either approach and to discern what either approach can (and cannot) show. It describes two case studies which each compare two approaches to social identity variables - sex and age - in a corpus of 14-million words of patient comments about NHS cancer services in England. The first approach utilises demographic tags to group comments according to patients' sex/age while the second involves categorising cases where patients disclose their sex/age in their comments. This Element compares the findings from either approach, with the approaches themselves being critically discussed in terms of their implications for corpus-aided studies of language and identity.

This book presents a taxonomy framework and survey of methods relevant to explaining the decisions and analyzing the inner workings of Natural Language Processing (NLP) models. The book is intended to provide a snapshot of Explainable NLP, though the field continues to rapidly grow. The book is intended to be both readable by first-year M.Sc. students and interesting to an expert audience. The book opens by motivating a focus on providing a consistent taxonomy, pointing out inconsistencies and redundancies in previous taxonomies. It goes on to present (i) a taxonomy or framework for thinking about how approaches to explainable NLP relate to one another; (ii) brief surveys of each of the classes in the taxonomy, with a focus on methods that are relevant for NLP; and (iii) a discussion of the inherent limitations of some classes of methods, as well as how to best evaluate them. Finally, the book closes by providing a list of resources for further research on explainability.

Corpus linguistics continues to be a vibrant methodology applied across highly diverse fields of research in the language sciences. With the current steep rise in corpus sizes, computational power, statistical literacy and multi-purpose software tools, and inspired by neighbouring disciplines, approaches have diversified to an extent that calls for an intensification of the accompanying critical debate. Bringing together a team of leading experts, this book follows a unique design, comparing advanced methods and approaches current in corpus linguistics, to stimulate reflective evaluation and discussion. Each chapter explores the strengths and weaknesses of different datasets and techniques, presenting a case study and allowing readers to gauge methodological options in practice. Contributions also provide suggestions for further reading, and data and analysis scripts are included in an online appendix. This is an important and timely volume, and will be essential reading for any linguist interested in corpus-linguistic approaches to variation and change.

The practices of visual artists can never be decontextualised from language. Firstly, artists are constantly in dialogue with their peers, dealers, critics, and audiences about their creative activities and these interactions impact on the work they produce. Secondly, artists' conceptualisations of what artistic practice encompasses are always shaped by wider social discourses. These discourses, however, and their manifestation in the language of everyday life are subject to continual change, and potentially reshape the way that artists conceptualise their practices. Using a 235,000-word diachronic corpus developed from artists' interviews and statements, this Element investigates shifts in artists' use of language to conceptualise their art practice from 1950 to 2019. It then compares these shifts to see if they align with changes in the wider English lexicon and whether there might be a relationship between everyday language change and the aesthetic and conceptual developments that take place in the art world.

Corpus Linguistics has revolutionised the world of language study and is an essential component of work in Applied Linguistics. This book, now in its second edition, provides a thorough introduction to all the key research issues in Corpus Linguistics, from the point of view of Applied Linguistics. The field has progressed a great deal since the first edition, so this edition has been completely rewritten to reflect these advances, whilst still maintaining the emphasis on hands-on corpus research of the first edition. It includes chapters on qualitative and quantitative research, applications in language teaching, discourse studies, and beyond. It also includes an extensive discussion of the place of Corpus Linguistics in linguistic theory, and provides numerous detailed examples of corpus studies throughout. Providing an accessible but thorough grounding to the fascinating, fast-moving field of Corpus Linguistics, this book is essential reading for the student and the researcher alike.

On social media, new forms of communication arise rapidly, many of which are intense, dispersed, and create new communities at a global scale. Such communities can act as distinct information bubbles with their own perspective on the world, and it is difficult for people to find and monitor all these perspectives and relate the different claims made. Within this digital jungle of perspectives on truth, it is difficult to make informed decisions on important things like vaccinations, democracy, and climate change. Understanding and modeling this phenomenon in its full complexity requires an interdisciplinary approach, utilizing the ample data provided by digital communication to offer new insights and opportunities. This interdisciplinary book gives a comprehensive view on social media communication, the different forms it takes, the impact and the technology used to mine it, and defines the roadmap to a more transparent Web.

Corpus Linguistics has revolutionised the world of language study and is an essential component of work in Applied Linguistics. This book, now in its second edition, provides a thorough introduction to all the key research issues in Corpus Linguistics, from the point of view of Applied Linguistics. The field has progressed a great deal since the first edition, so this edition has been completely rewritten to reflect these advances, whilst still maintaining the emphasis on hands-on corpus research of the first edition. It includes chapters on qualitative and quantitative research, applications in language teaching, discourse studies, and beyond. It also includes an extensive discussion of the place of Corpus Linguistics in linguistic theory, and provides numerous detailed examples of corpus studies throughout. Providing an accessible but thorough grounding to the fascinating, fast-moving field of Corpus Linguistics, this book is essential reading for the student and the researcher alike.

Corpora are ubiquitous in linguistic research, yet to date, there has been no consensus on how to conceptualize corpus representativeness and collect corpus samples. This pioneering book bridges this gap by introducing a conceptual and methodological framework for corpus design and representativeness. Written by experts in the field, it shows how corpora can be designed and built in a way that is both optimally suited to specific research agendas, and adequately representative of the types of language use in question. It considers questions such as 'what types of texts should be included in the corpus?', and 'how many texts are required?' - highlighting that the degree of representativeness rests on the dual pillars of domain considerations and distribution considerations. The authors introduce, explain, and illustrate all aspects of this corpus representativeness framework in a step-by-step fashion, using examples and activities to help readers develop practical skills in corpus design and evaluation.