These two volumes consisting of Foundations and Applications provide the current status of theoretical and empirical developments in "computing with words." In philosophy, the twentieth century is said to be the century of language. This is mainly due to Wittgenstein who said: "The meaning of a word is its use in the language game." "The concept game is a concept with blurred edges." In the first phrase, "the language game" implies the everyday human activity with language, and in the latter, "game" simply implies an ordinary word. Thus, Wittgenstein precisely stated that a word is fuzzy in real life. Unfortunately this idea about a word was not accepted in the conventional science. We had to wait for Zadeh's fuzzy sets theory. Remembering Wittgenstein's statement, we should consider, on the one hand, the concept of "computing with words" from a philosophical point of view. It deeply relates to the everyday use of a word in which the meaning of a word is fuzzy in its nature.

This book provides an overview of how comparable corpora can be used to overcome the lack of parallel resources when building machine translation systems for under-resourced languages and domains. It presents a wealth of methods and open tools for building comparable corpora from the Web, evaluating comparability and extracting parallel data that can be used for the machine translation task. It is divided into several sections, each covering a specific task such as building, processing, and using comparable corpora, focusing particularly on under-resourced language pairs and domains. The book is intended for anyone interested in data-driven machine translation for under-resourced languages and domains, especially for developers of machine translation systems, computational linguists and language workers. It offers a valuable resource for specialists and students in natural language processing, machine translation, corpus linguistics and computer-assisted translation, and promotes the broader use of comparable corpora in natural language processing and computational linguistics.

Parsing technology is concerned with finding syntactic structure in language. In parsing we have to deal with incomplete and not necessarily accurate formal descriptions of natural languages. Robustness and efficiency are among the main issuesin parsing. Corpora can be used to obtain frequency information about language use. This allows probabilistic parsing, an approach that aims at both robustness and efficiency increase. Approximation techniques, to be applied at the level of language description, parsing strategy, and syntactic representation, have the same objective. Approximation at the level of syntactic representation is also known as underspecification, a traditional technique to deal with syntactic ambiguity. In this book new parsing technologies are collected that aim at attacking the problems of robustness and efficiency by exactly these techniques: the design of probabilistic grammars and efficient probabilistic parsing algorithms, approximation techniques applied to grammars and parsers to increase parsing efficiency, and techniques for underspecification and the integration of semantic information in the syntactic analysis to deal with massive ambiguity. The book gives a state-of-the-art overview of current research and development in parsing technologies. In its chapters we see how probabilistic methods have entered the toolbox of computational linguistics in order to be applied in both parsing theory and parsing practice. The book is both a unique reference for researchers and an introduction to the field for interested graduate students.

These two volumes consIstmg of Foundations and Applications provide the current status of theoretical and empirical developments in "computing with words." In philosophy, the twentieth century is said to be the century of language. This is mainly due to Wittgenstein who said: "The meaning of a word is its use in the language game." "The concept game is a concept with blurred edges." In the first phrase, "the language game" implies the everyday human activity with language, and in the latter, "game" simply implies an ordinary word. Thus, Wittgenstein precisely stated that a word is fuzzy in real life. Unfortunately this idea about a word was not accepted in the conventional science. We had to wait for Zadeh's fuzzy sets theory. Remembering Wittgenstein's statement, we should consider, on the one hand, the concept of "computing with words" from a philosophical point of view. It deeply relates to the everyday use of a word in which the meaning of a word is fuzzy in its nature.

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 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 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.

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.

This book is an excellent introduction to multiword expressions. It provides a unique, comprehensive and up-to-date overview of this exciting topic in computational linguistics. The first part describes the diversity and richness of multiword expressions, including many examples in several languages. These constructions are not only complex and arbitrary, but also much more frequent than one would guess, making them a real nightmare for natural language processing applications. The second part introduces a new generic framework for automatic acquisition of multiword expressions from texts. Furthermore, it describes the accompanying free software tool, the mwetoolkit, which comes in handy when looking for expressions in texts (regardless of the language). Evaluation is greatly emphasized, underlining the fact that results depend on parameters like corpus size, language, MWE type, etc. The last part contains solid experimental results and evaluates the mwetoolkit, demonstrating its usefulness for computer-assisted lexicography and machine translation. This is the first book to cover the whole pipeline of multiword expression acquisition in a single volume. It is addresses the needs of students and researchers in computational and theoretical linguistics, cognitive sciences, artificial intelligence and computer science. Its good balance between computational and linguistic views make it the perfect starting point for anyone interested in multiword expressions, language and text processing in general.

This book is an account of the rise of definite and indefinite articles in Danish, Swedish and Icelandic, as documented in a choice of extant texts from 1200-1550. These three North Germanic languages show different development patterns in the rise of articles, despite the common origin, but each reveals interdependencies between the two processes. The matter is approached from both a quantitative and a qualitative perspective. The statistical analysis provides an improved overview on article grammaticalization, focusing on the factors at the basis of such process. The in-depth qualitative analysis of longer text passages places the crucial stage of the definite article grammaticalization with the so-called indirect anaphoric reference.

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.

A chatbot is expected to be capable of supporting a cohesive and coherent conversation and be knowledgeable, which makes it one of the most complex intelligent systems being designed nowadays. Designers have to learn to combine intuitive, explainable language understanding and reasoning approaches with high-performance statistical and deep learning technologies. Today, there are two popular paradigms for chatbot construction: 1. Build a bot platform with universal NLP and ML capabilities so that a bot developer for a particular enterprise, not being an expert, can populate it with training data; 2. Accumulate a huge set of training dialogue data, feed it to a deep learning network and expect the trained chatbot to automatically learn "how to chat". Although these two approaches are reported to imitate some intelligent dialogues, both of them are unsuitable for enterprise chatbots, being unreliable and too brittle. The latter approach is based on a belief that some learning miracle will happen and a chatbot will start functioning without a thorough feature and domain engineering by an expert and interpretable dialogue management algorithms. Enterprise high-performance chatbots with extensive domain knowledge require a mix of statistical, inductive, deep machine learning and learning from the web, syntactic, semantic and discourse NLP, ontology-based reasoning and a state machine to control a dialogue. This book will provide a comprehensive source of algorithms and architectures for building chatbots for various domains based on the recent trends in computational linguistics and machine learning. The foci of this book are applications of discourse analysis in text relevant assessment, dialogue management and content generation, which help to overcome the limitations of platform-based and data driven-based approaches. Supplementary material and code is available at https://github.com/bgalitsky/relevance-based-on-parse-trees

This book provides a timely and comprehensive overview of current theories and methods in fuzzy logic, as well as relevant applications in a variety of fields of science and technology. Dedicated to Lotfi A. Zadeh on his one year death anniversary, the book goes beyond a pure commemorative text. Yet, it offers a fresh perspective on a number of relevant topics, such as computing with words, theory of perceptions, possibility theory, and decision-making in a fuzzy environment. Written by Zadeh's closest colleagues and friends, the different chapters are intended both as a timely reference guide and a source of inspiration for scientists, developers and researchers who have been dealing with fuzzy sets or would like to learn more about their potential for their future research.

This book provides a refreshing perspective on the description, study and representation of consonant clusters in Polish. What are the sources of phonotactic complexity? What properties or principles motivate the phonological structure of initial and final consonant clusters? In answering these questions, a necessary turning point consists in investigating sequences of consonants at their most basic level, namely in terms of phonological features. The analysis is exploratory: it leads to discovering prevalent feature patterns in clusters from which new phonotactic generalizations are derived. A recurring theme in the book is that phonological features vary in weight depending on (1) their distribution in a cluster, (2) their position in a word, and (3) language domain. Positional feature weight reflects the relative importance of place, manner and voice features (e.g. coronal, dorsal, strident, continuant) in constructing cluster inventories, minimizing cognitive effort, facilitating production and triggering specific casual speech processes. Feature weights give rise to previously unidentified positional preferences. Rankings of features and preferences are a testing ground for principles of sonority, contrast, clarity of perception and ease of articulation. This volume addresses practitioners in the field seeking new methods of phonotactic modelling and approaches to complexity, as well as students interested in an overview of current research directions in the study of consonant clusters. Sequences of consonants in Polish are certainly among the most remarkable ones that readers will ever encounter in their linguistic explorations. In this volume, they will come to realise that hundreds of unusually long, odd-looking, sonority-violating, morphologically complex and infrequent clusters are in fact well-motivated and structured according to well-defined tactic patterns of features.

Parsing the Turing Test is a landmark exploration of both the philosophical and methodological issues surrounding the search for true artificial intelligence. Will computers and robots ever think and communicate the way humans do? When a computer crosses the threshold into self-consciousness, will it immediately jump into the Internet and create a World Mind? Will intelligent computers someday recognize the rather doubtful intelligence of human beings? Distinguished psychologists, computer scientists, philosophers, and programmers from around the world debate these weighty issues a " and, in effect, the future of the human race a " in this important volume.

The contributions to this volume are drawn from the interdisciplinary research c- ried out within the Sonderforschungsbereich (SFB 378), a special long-term funding scheme of the German National Science Foundation (DFG). Sonderforschungsbe- ich 378 was situated at Saarland University, with colleagues from arti?cial intel- gence, computational linguistics, computer science, philosophy, psychology - and in its ?nal phases - cognitive neuroscience and psycholinguistics. The funding covered a period of 12 years, which was split into four phases of 3 years each, ending in December of 2007. Every sub-period culminated in an intensive reviewing process, comprising written reports as well as on-site p- sentations and demonstrations to the external reviewers. We are most grateful to these reviewers for their extensive support and critical feedback; they contributed 1 their time and labor freely to the DFG, the independent and self-organized ins- tution of German scientists. The ?nal evaluation of the DFG reviewers judged the overall performance and the actual work with the highest possible mark, i.e. "excellent".

The book gives a comprehensive discussion of Database Semantics (DBS) as an agent-based data-driven theory of how natural language communication essentially works. In language communication, agents switch between speak mode, driven by cognition-internal content (input) resulting in cognition-external raw data (e.g. sound waves or pixels, which have no meaning or grammatical properties but can be measured by natural science), and hear mode, driven by the raw data produced by the speaker resulting in cognition-internal content. The motivation is to compare two approaches for an ontology of communication: agent-based data-driven vs. sign-based substitution-driven. Agent-based means: design of a cognitive agent with (i) an interface component for converting raw data into cognitive content (recognition) and converting cognitive content into raw data (action), (ii) an on-board, content-addressable memory (database) for the storage and content retrieval, (iii) separate treatments of the speak and the hear mode. Data-driven means: (a) mapping a cognitive content as input to the speak-mode into a language-dependent surface as output, (b) mapping a surface as input to the hear-mode into a cognitive content as output. Oppositely, sign-based means: no distinction between speak and hear mode, whereas substitution-driven means: using a single start symbol as input for generating infinitely many outputs, based on substitutions by rewrite rules. Collecting recent research of the author, this beautiful, novel and original exposition begins with an introduction to DBS, makes a linguistic detour on subject/predicate gapping and slot-filler repetition, and moves on to discuss computational pragmatics, inference and cognition, grammatical disambiguation and other related topics. The book is mostly addressed to experts working in the field of computational linguistics, as well as to enthusiasts interested in the history and early development of this subject, starting with the pre-computational foundations of theoretical computer science and symbolic logic in the 30s.

This is a book about semantic theories of modality. Its main goal is to explain and evaluate important contemporary theories within linguistics and to discuss a wide range of linguistic phenomena from the perspective of these theories. The introduction describes the variety of grammatical phenomena associated with modality, explaining why modal verbs, adjectives, and adverbs represent the core phenomena. Chapters are then devoted to the possible worlds semantics for modality developed in modal logic; current theories of modal semantics within linguistics; and the most important empirical areas of research. The author concludes by discussing the relation between modality and other topics, especially tense, aspect, mood, and discourse meaning.
Paul Portner's accessible guide to this key area of current research will be welcomed by students of linguistics at graduate level and above, as well as by researchers in philosophy, computational science, and related fields.

In Language and Chronology, Toner and Han apply innovative Machine Learning techniques to the problem of the dating of literary texts. Many ancient and medieval literatures lack reliable chronologies which could aid scholars in locating texts in their historical context. The new machine-learning method presented here uses chronological information gleaned from annalistic records to date a wide range of texts. The method is also applied to multi-layered texts to aid the identification of different chronological strata within single copies. While the algorithm is here applied to medieval Irish material of the period c.700-c.1700, it can be extended to written texts in any language or alphabet. The authors' approach presents a step change in Digital Humanities, moving us beyond simple querying of electronic texts towards the production of a sophisticated tool for literary and historical studies.

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 recent advances in NLP and speech technology, a topic attracting increasing interest in a variety of fields through its myriad applications, such as the demand for speech guided touchless technology during the Covid-19 pandemic. The authors present results of recent experimental research that provides contributions and solutions to different issues related to speech technology and speech in industry. Technologies include natural language processing, automatic speech recognition (for under-resourced dialects) and speech synthesis that are useful for applications such as intelligent virtual assistants, among others. Applications cover areas such as sentiment analysis and opinion mining, Arabic named entity recognition, and language modelling. This book is relevant for anyone interested in the latest in language and speech technology.

Novel Techniques for Dialectal Arabic Speech describes approaches to improve automatic speech recognition for dialectal Arabic. Since speech resources for dialectal Arabic speech recognition are very sparse, the authors describe how existing Modern Standard Arabic (MSA) speech data can be applied to dialectal Arabic speech recognition, while assuming that MSA is always a second language for all Arabic speakers. In this book, Egyptian Colloquial Arabic (ECA) has been chosen as a typical Arabic dialect. ECA is the first ranked Arabic dialect in terms of number of speakers, and a high quality ECA speech corpus with accurate phonetic transcription has been collected. MSA acoustic models were trained using news broadcast speech. In order to cross-lingually use MSA in dialectal Arabic speech recognition, the authors have normalized the phoneme sets for MSA and ECA. After this normalization, they have applied state-of-the-art acoustic model adaptation techniques like Maximum Likelihood Linear Regression (MLLR) and Maximum A-Posteriori (MAP) to adapt existing phonemic MSA acoustic models with a small amount of dialectal ECA speech data. Speech recognition results indicate a significant increase in recognition accuracy compared to a baseline model trained with only ECA data.

This handbook provides a comprehensive account of current research on the finite-state morphology of Georgian and enables the reader to enter quickly into Georgian morphosyntax and its computational processing. It combines linguistic analysis with application of finite-state technology to processing of the language. The book opens with the author's synoptic overview of the main lines of research, covers the properties of the word and its components, then moves up to the description of Georgian morphosyntax and the morphological analyzer and generator of Georgian.The book comprises three chapters and accompanying appendices. The aim of the first chapter is to describe the morphosyntactic structure of Georgian, focusing on differences between Old and Modern Georgian. The second chapter focuses on the application of finite-state technology to the processing of Georgian and on the compilation of a tokenizer, a morphological analyzer and a generator for Georgian. The third chapter discusses the testing and evaluation of the analyzer's output and the compilation of the Georgian Language Corpus (GLC), which is now accessible online and freely available to the research community.Since the development of the analyzer, the field of computational linguistics has advanced in several ways, but the majority of new approaches to language processing has not been tested on Georgian. So, the organization of the book makes it easier to handle new developments from both a theoretical and practical viewpoint.The book includes a detailed index and references as well as the full list of morphosyntactic tags. It will be of interest and practical use to a wide range of linguists and advanced students interested in Georgian morphosyntax generally as well as to researchers working in the field of computational linguistics and focusing on how languages with complicated morphosyntax can be handled through finite-state approaches.

This book presents a collection of original research articles that showcase the state of the art of research in corpus and computational linguistic approaches to Chinese language teaching, learning and assessment. It offers a comprehensive set of corpus resources and natural language processing tools that are useful for teaching, learning and assessing Chinese as a second or foreign language; methods for implementing such resources and techniques in Chinese pedagogy and assessment; as well as research findings on the effectiveness of using such resources and techniques in various aspects of Chinese pedagogy and assessment.

This book re-examines the notion of word associations, more precisely collocations. It attempts to come to a potentially more generally applicable definition of collocation and how to best extract, identify and measure collocations. The book highlights the role played by (i) automatic linguistic annotation (part-of-speech tagging, syntactic parsing, etc.), (ii) using semantic criteria to facilitate the identification of collocations, (iii) multi-word structured, instead of the widespread assumption of bipartite collocational structures, for capturing the intricacies of the phenomenon of syntagmatic attraction, (iv) considering collocation and valency as near neighbours in the lexis-grammar continuum and (v) the mathematical properties of statistical association measures in the automatic extraction of collocations from corpora. This book is an ideal guide to the use of statistics in collocation analysis and lexicography, as well as a practical text to the development of skills in the application of computational lexicography. Lexical Collocation Analysis: Advances and Applications begins with a proposal for integrating both collocational and valency phenomena within the overarching theoretical framework of construction grammar. Next the book makes the case for integrating advances in syntactic parsing and in collocational analysis. Chapter 3 offers an innovative look at complementing corpus data and dictionaries in the identification of specific types of collocations consisting of restricted predicate-argument combinations. This strategy complements corpus collocational data with network analysis techniques applied to dictionary entries. Chapter 4 explains the potential of collocational graphs and networks both as a visualization tool and as an analytical technique. Chapter 5 introduces MERGE (Multi-word Expressions from the Recursive Grouping of Elements), a data-driven approach to the identification and extraction of multi-word expressions from corpora. Finally the book concludes with an analysis and evaluation of factors influencing the performance of collocation extraction methods in parsed corpora.