Computational semantics is the art and science of computing meaning in natural language. The meaning of a sentence is derived from the meanings of the individual words in it, and this process can be made so precise that it can be implemented on a computer. Designed for students of linguistics, computer science, logic and philosophy, this comprehensive text shows how to compute meaning using the functional programming language Haskell. It deals with both denotational meaning (where meaning comes from knowing the conditions of truth in situations), and operational meaning (where meaning is an instruction for performing cognitive action). Including a discussion of recent developments in logic, it will be invaluable to linguistics students wanting to apply logic to their studies, logic students wishing to learn how their subject can be applied to linguistics, and functional programmers interested in natural language processing as a new application area.

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.

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.

With the first publication of this book in 1988, the centrality of the lexicon in language research was becoming increasingly apparent and the use of relational models of the lexicon had been the particular focus of research in a variety of disciplines since the early 1980s. This convergence of approach made the present collection especially welcome for bringing together reports of theoretical developments and applications in relational semantics in computer science, linguistics, cognitive science, anthropology and industrial research. It explains in detail some important applications of relational models to the construction of natural language interfaces, the building of thesauri for bibliographic information retrieval systems and the compilation of terminology banks for machine translation systems. Relational Models of the Lexicon not only provides an invaluable survey of research in relational semantics, but offers a stimulus for potential research advances in semantics, natural language processing and knowledge representation.

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.

This book addresses the research, analysis, and description of the methods and processes that are used in the annotation and processing of language corpora in advanced, semi-advanced, and non-advanced languages. It provides the background information and empirical data needed to understand the nature and depth of problems related to corpus annotation and text processing and shows readers how the linguistic elements found in texts are analyzed and applied to develop language technology systems and devices. As such, it offers valuable insights for researchers, educators, and students of linguistics and language technology.

This book presents a method of linking the ordered structure of the cosmos with human thoughts: the theory of language holography. In the view presented here, the cosmos is in harmony with the human body and language, and human thoughts are holographic with the cosmos at the level of language. In a word, the holographic relation is nothing more than the bridge by means of which Guanlian Qian connects the cosmos, human, and language. This is a vitally important contribution to linguistic and philosophical studies that cannot be ignored. The book has two main focus areas: outer language holography and inner language holography. These two areas constitute the core of the dynamic and holistic view put forward in the theory of language holography. The book's main properties can be summarized into the following points: First and foremost, it is a book created in toto by a Chinese scholar devoted to pragmatics, theoretical linguistics, and philosophy of language. Secondly, the book was accepted by a top Chinese publisher and was republished the second year, which reflected its value and appeal. Thirdly, in terms of writing style, the book is characterized by succinctness and logic. As a result, it reads fluidly and smoothly without redundancies, which is not that common in linguistic or even philosophical works. Lastly, as stated by the author in the introduction, "Creation is the development of previous capacities, but it is also the generation of new ones"; this book can be said to put this concept into practice. Overall, the book offers a unique resource to readers around the world who want to know more about the truly original and innovative studies of language in Chinese academia.

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 presents a theoretical study on aspect in Chinese, including both situation and viewpoint aspects. Unlike previous studies, which have largely classified linguistic units into different situation types, this study defines a set of ontological event types that are conceptually universal and on the basis of which different languages employ various linguistic devices to describe such events. To do so, it focuses on a particular component of events, namely the viewpoint aspect. It includes and discusses a wealth of examples to show how such ontological events are realized in Chinese. In addition, the study discusses how Chinese modal verbs and adverbs affect the distribution of viewpoint aspects associated with certain situation types. In turn, the book demonstrates how the proposed linguistic theory can be used in a computational context. Simply identifying events in terms of the verbs and their arguments is insufficient for real situations such as understanding the factivity and the logical/temporal relations between events. The proposed framework offers the possibility of analyzing events in Chinese text, yielding deep semantic information.

Recent decades have seen a fundamental change and transformation in the commercialisation and popularisation of sports and sporting events. Corpus Approaches to the Language of Sports uses corpus resources to offer new perspectives on the language and discourse of this increasingly popular and culturally significant area of research. Bringing together a range of empirical studies from leading scholars, this book bridges the gap between quantitative corpus approaches and more qualitative, multimodal discourse methods. Covering a wide range of sports, including football, cycling and basketball, the linguistic aspects of sports language are analysed across different genres and contexts. Highlighting the importance of studying the language of sports alongside its accompanying audio-visual modes of communication, chapters draw on new digitised collections of language to fully describe and understand the complexities of communication through various channels. In doing so, Corpus Approaches to the Language of Sports not only offers exciting new insights into the language of sports but also extends the scope of corpus linguistics beyond traditional monomodal approaches to put multimodality firmly on the agenda.

This book covers theoretical work, applications, approaches, and techniques for computational models of information and its presentation by language (artificial, human, or natural in other ways). Computational and technological developments that incorporate natural language are proliferating. Adequate coverage encounters difficult problems related to ambiguities and dependency on context and agents (humans or computational systems). The goal is to promote computational systems of intelligent natural language processing and related models of computation, language, thought, mental states, reasoning, and other cognitive processes.

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 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.

This handbook is a comprehensive practical resource on corpus linguistics. It features a range of basic and advanced approaches, methods and techniques in corpus linguistics, from corpus compilation principles to quantitative data analyses. The Handbook is organized in six Parts. Parts I to III feature chapters that discuss key issues and the know-how related to various topics around corpus design, methods and corpus types. Parts IV-V aim to offer a user-friendly introduction to the quantitative analysis of corpus data: for each statistical technique discussed, chapters provide a practical guide with R and come with supplementary online material. Part VI focuses on how to write a corpus linguistic paper and how to meta-analyze corpus linguistic research. The volume can serve as a course book as well as for individual study. It will be an essential reading for students of corpus linguistics as well as experienced researchers who want to expand their knowledge of the field.

Memory-based language processing - a machine learning and problem solving method for language technology - is based on the idea that the direct reuse of examples using analogical reasoning is more suited for solving language processing problems than the application of rules extracted from those examples. This book discusses the theory and practice of memory-based language processing, showing its comparative strengths over alternative methods of language modelling. Language is complex, with few generalizations, many sub-regularities and exceptions, and the advantage of memory-based language processing is that it does not abstract away from this valuable low-frequency information. By applying the model to a range of benchmark problems, the authors show that for linguistic areas ranging from phonology to semantics, it produces excellent results. They also describe TiMBL, a software package for memory-based language processing. The first comprehensive overview of the approach, this book will be invaluable for computational linguists, psycholinguists and language engineers.

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 book sheds new light on corpus-assisted translation pedagogy, an intersection of three distinct but cognate disciplines: corpus linguistics, translation and pedagogy. By taking an innovative and empirical approach to translation teaching, the study utilizes mixed methods, including translation experiments, surveys and in-depth focus groups. The results demonstrated the unique advantages and at the same time called attention to possible pitfalls of using corpora for translation teaching purposes. This book enriches our understanding of corpus application in the setting of translation between Chinese and English, two languages which are each distinctly different from one another. Readers will also discover new horizons in this burgeoning and interdisciplinary field of research. This book appeals to a broad readership, from scholars and researchers who are interested in translation technology to widen the scope of translation studies, translation trainers in search of effective teaching approaches to a growing number of cross-disciplinary postgraduate students longing to improve their translation skills and competence.

This book discusses the state of the art of automated essay scoring, its challenges and its potential. One of the earliest applications of artificial intelligence to language data (along with machine translation and speech recognition), automated essay scoring has evolved to become both a revenue-generating industry and a vast field of research, with many subfields and connections to other NLP tasks. In this book, we review the developments in this field against the backdrop of Elias Page's seminal 1966 paper titled "The Imminence of Grading Essays by Computer." Part 1 establishes what automated essay scoring is about, why it exists, where the technology stands, and what are some of the main issues. In Part 2, the book presents guided exercises to illustrate how one would go about building and evaluating a simple automated scoring system, while Part 3 offers readers a survey of the literature on different types of scoring models, the aspects of essay quality studied in prior research, and the implementation and evaluation of a scoring engine. Part 4 offers a broader view of the field inclusive of some neighboring areas, and Part \ref{part5} closes with summary and discussion. This book grew out of a week-long course on automated evaluation of language production at the North American Summer School for Logic, Language, and Information (NASSLLI), attended by advanced undergraduates and early-stage graduate students from a variety of disciplines. Teachers of natural language processing, in particular, will find that the book offers a useful foundation for a supplemental module on automated scoring. Professionals and students in linguistics, applied linguistics, educational technology, and other related disciplines will also find the material here useful.

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.

This book describes effective methods for automatically analyzing a sentence, based on the syntactic and semantic characteristics of the elements that form it. To tackle ambiguities, the authors use selectional preferences (SP), which measure how well two words fit together semantically in a sentence. Today, many disciplines require automatic text analysis based on the syntactic and semantic characteristics of language and as such several techniques for parsing sentences have been proposed. Which is better? In this book the authors begin with simple heuristics before moving on to more complex methods that identify nouns and verbs and then aggregate modifiers, and lastly discuss methods that can handle complex subordinate and relative clauses. During this process, several ambiguities arise. SP are commonly determined on the basis of the association between a pair of words. However, in many cases, SP depend on more words. For example, something (such as grass) may be edible, depending on who is eating it (a cow?). Moreover, things such as popcorn are usually eaten at the movies, and not in a restaurant. The authors deal with these phenomena from different points of view.

The book presents current research and developments in multilingual speech recognition. The author presents a Multilingual Phone Recognition System (Multi-PRS), developed using a common multilingual phone-set derived from the International Phonetic Alphabets (IPA) based transcription of six Indian languages - Kannada, Telugu, Bengali, Odia, Urdu, and Assamese. The author shows how the performance of Multi-PRS can be improved using tandem features. The book compares Monolingual Phone Recognition Systems (Mono-PRS) versus Multi-PRS and baseline versus tandem system. Methods are proposed to predict Articulatory Features (AFs) from spectral features using Deep Neural Networks (DNN). Multitask learning is explored to improve the prediction accuracy of AFs. Then, the AFs are explored to improve the performance of Multi-PRS using lattice rescoring method of combination and tandem method of combination. The author goes on to develop and evaluate the Language Identification followed by Monolingual phone recognition (LID-Mono) and common multilingual phone-set based multilingual phone recognition systems.

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.

This book deals with two fundamental issues in the semiotics of the image. The first is the relationship between image and observer: how does one look at an image? To answer this question, this book sets out to transpose the theory of enunciation formulated in linguistics over to the visual field. It also aims to clarify the gains made in contemporary visual semiotics relative to the semiology of Roland Barthes and Emile Benveniste. The second issue addressed is the relation between the forces, forms and materiality of the images. How do different physical mediums (pictorial, photographic and digital) influence visual forms? How does materiality affect the generativity of forms? On the forces within the images, the book addresses the philosophical thought of Gilles Deleuze and Rene Thom as well as the experiment of Aby Warburg's Atlas Mnemosyne. The theories discussed in the book are tested on a variety of corpora for analysis, including both paintings and photographs, taken from traditional as well as contemporary sources in a variety of social sectors (arts and sciences). Finally, semiotic methodology is contrasted with the computational analysis of large collections of images (Big Data), such as the "Media Visualization" analyses proposed by Lev Manovich and Cultural Analytics in the field of Computer Science to evaluate the impact of automatic analysis of visual forms on Digital Art History and more generally on the image sciences.