The volume brings together papers emerging from the GlobE conference (University of Warsaw). The authors explore major topics in Discourse Studies, offering insights into the field's theoretical foundations and discussing the results of its empirical applications. The book integrates different lines of research in Discourse Studies as undertaken at academic centres Europe-wide and beyond. In this diversity, the editors identify certain dominant lines of study, including (new) media discourse, political discourse in the age of social/digital media, or professional discourse in globalized workplace contexts. At the same time, the volume shows that Discourse Studies not only investigate emerging language phenomena, but also critically reassess research issues formerly addressed.

This open access volume constitutes the refereed proceedings of the 27th biennial conference of the German Society for Computational Linguistics and Language Technology, GSCL 2017, held in Berlin, Germany, in September 2017, which focused on language technologies for the digital age. The 16 full papers and 10 short papers included in the proceedings were carefully selected from 36 submissions. Topics covered include text processing of the German language, online media and online content, semantics and reasoning, sentiment analysis, and semantic web description languages.

This book provides an overview of a recent and flexible approach to speech synthesis design to develop the first statistical parametric speech synthesizer for Ibibio, a West African tonal language. The design precludes the inflexibility encountered when modeling tonal features of the language and can be used for other tonal African languages. Mobile use and technological innovations in developing African nations have exploded. With mobile technology, many of the barriers caused by infrastructure issues have vanished. In order to address issues that are unique to African tonal languages, the book uses Ibibio as a model. The text reviews the language's speech characteristics, required for building the front end components of the design and propose a finite state transducer (FST), useful for modelling the language's tonetactics. The statistical parametric approach discussed in the text, implements the Hidden Markov Model (HMM) technique, with the goal of creating a generic structure that learns the model from the text itself, and uses the data-driven approach to input specification.

This book constitutes the refereed proceedings of the 11th International Conference, NooJ 2017, held in Kenitra and Rabat, Morocco, in May 2017. The 20 revised full papers presented in this volume were carefully reviewed and selected from 56 submissions. NooJ is a linguistic development environment that provides tools for linguists to construct linguistic resources that formalize a large gamut of linguistic phenomena: typography, orthography, lexicons for simple words, multiword units and discontinuous expressions, inflectional and derivational morphology, local, structural and transformational syntax, and semantics. The papers in this volume are organized in topical sections on vocabulary and morphology; syntactic analysis; natural language processing applications; NooJ's future.

This book serves as a starting point for Semantic Web (SW) students and researchers interested in discovering what Natural Language Processing (NLP) has to offer. NLP can effectively help uncover the large portions of data held as unstructured text in natural language, thus augmenting the real content of the Semantic Web in a significant and lasting way. The book covers the basics of NLP, with a focus on Natural Language Understanding (NLU), referring to semantic processing, information extraction and knowledge acquisition, which are seen as the key links between the SW and NLP communities. Major emphasis is placed on mining sentences in search of entities and relations. In the course of this "quest", challenges will be encountered for various text analysis tasks, including part-of-speech tagging, parsing, semantic disambiguation, named entity recognition and relation extraction. Standard algorithms associated with these tasks are presented to provide an understanding of the fundamental concepts. Furthermore, the importance of experimental design and result analysis is emphasized, and accordingly, most chapters include small experiments on corpus data with quantitative and qualitative analysis of the results. This book is divided into four parts. Part I "Searching for Entities in Text" is dedicated to the search for entities in textual data. Next, Part II "Working with Corpora" investigates corpora as valuable resources for NLP work. In turn, Part III "Semantic Grounding and Relatedness" focuses on the process of linking surface forms found in text to entities in resources. Finally, Part IV "Knowledge Acquisition" delves into the world of relations and relation extraction. The book also includes three appendices: "A Look into the Semantic Web" gives a brief overview of the Semantic Web and is intended to bring readers less familiar with the Semantic Web up to speed, so that they too can fully benefit from the material of this book. "NLP Tools and Platforms" provides information about NLP platforms and tools, while "Relation Lists" gathers lists of relations under different categories, showing how relations can be varied and serve different purposes. And finally, the book includes a glossary of over 200 terms commonly used in NLP. The book offers a valuable resource for graduate students specializing in SW technologies and professionals looking for new tools to improve the applicability of SW techniques in everyday life - or, in short, everyone looking to learn about NLP in order to expand his or her horizons. It provides a wealth of information for readers new to both fields, helping them understand the underlying principles and the challenges they may encounter.

This book features contributions to the XVIIth International Conference "Linguistic and Cultural Studies: Traditions and Innovations" (LKTI 2017), providing insights into theory, research, scientific achievements, and best practices in the fields of pedagogics, linguistics, and language teaching and learning with a particular focus on Siberian perspectives and collaborations between academics from other Russian regions. Covering topics including curriculum development, designing and delivering courses and vocational training, the book is intended for academics working at all levels of education striving to improve educational environments in their context - school, tertiary education and continuous professional development.

The present volume of the Yearbook of Corpus Linguistics and Pragmatics series, presents cutting-edge corpus pragmatics research on language use in new social and educational environments. The Yearbook of Corpus Linguistics and Pragmatics offers a platform to scholars who carry out rigorous and interdisciplinary research on language in real use. Corpus Linguistics and Pragmatics have traditionally represented two paths of scientific research, parallel but often mutually exclusive and excluding. Corpus Linguistics can offer a precise methodology based on mathematics and statistics while Pragmatics strives to interpret intended meaning in real language. This series will give readers insight into how pragmatics can be used to explain real corpus data, and how corpora can illustrate pragmatic intuitions.

This book is a collection of papers using samples of real language data (corpora) to explore variation in the use of English. This collection celebrates the achievements of Toshio Saito, a pioneer in corpus linguistics within Japan and founder of the Japan Association for English Corpus Studies (JAECS). The main aims throughout the collection are to present practical solutions for methodological and interpretational problems common in such research, and to make the research methods and issues as accessible as possible, to educate and inspire future researchers. Together, the papers represent many different dimensions of variation, including: differences in (frequency of) use under different linguistic conditions; differences between styles or registers of use; change over time; differences between regional varieties; differences between social groups; and differences in use by one individual on different occasions. The papers are grouped into four sections: studies considering methodological problems in the use of real language samples; studies describing features of language usage in different linguistic environments in modern English; studies following change over time; and case studies illustrating variation in usage for different purposes, or by different groups or individuals, in society.

This book constitutes the thoroughly refereed post-workshop proceedings of the 18th Chinese Lexical Semantics Workshop, CLSW 2017, held in Leshan, China, in May 2017. The 48 full papers and 5 short papers included in this volume were carefully reviewed and selected from 176 submissions. They are organized in the following topical sections: lexical semantics; applications of natural language processing; lexical resources; and corpus linguistics.

This book introduces methods for copyright protection and compression for speech signals. The first method introduces copyright protection of speech signal using watermarking; the second introduces compression of the speech signal using Compressive Sensing (CS). Both methods are tested and analyzed. The speech watermarking method uses technology such as Finite Ridgelet Transform (FRT), Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD). The performance of the method is evaluated and compared with existing watermarking methods. In the speech compression method, the standard Compressive Sensing (CS) process is used for compression of the speech signal. The performance of the proposed method is evaluated using various transform bases like Discrete Fourier Transform (DFT), Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT), Singular Value Decomposition (SVD), and Fast Discrete Curvelet Transform (FDCuT).

This book discusses the contribution of articulatory and excitation source information in discriminating sound units. The authors focus on excitation source component of speech -- and the dynamics of various articulators during speech production -- for enhancement of speech recognition (SR) performance. Speech recognition is analyzed for read, extempore, and conversation modes of speech. Five groups of articulatory features (AFs) are explored for speech recognition, in addition to conventional spectral features. Each chapter provides the motivation for exploring the specific feature for SR task, discusses the methods to extract those features, and finally suggests appropriate models to capture the sound unit specific knowledge from the proposed features. The authors close by discussing various combinations of spectral, articulatory and source features, and the desired models to enhance the performance of SR systems.

This book constitutes the refereed proceedings of the 12th China Workshop on Machine Translation, CWMT 2016, held in Urumqi, China, in August 2016. The 10 English papers presented in this volume were carefully reviewed and selected from 76 submissions. They deal with statistical machine translation, hybrid machine translation, machine translation evaluation, post editing, alignment, and inducing bilingual knowledge from corpora.

This book presents a comprehensive overview of semi-supervised approaches to dependency parsing. Having become increasingly popular in recent years, one of the main reasons for their success is that they can make use of large unlabeled data together with relatively small labeled data and have shown their advantages in the context of dependency parsing for many languages. Various semi-supervised dependency parsing approaches have been proposed in recent works which utilize different types of information gleaned from unlabeled data. The book offers readers a comprehensive introduction to these approaches, making it ideally suited as a textbook for advanced undergraduate and graduate students and researchers in the fields of syntactic parsing and natural language processing.

This book introduces formal semantics techniques for a natural language processing audience. Methods discussed involve: (i) the denotational techniques used in model-theoretic semantics, which make it possible to determine whether a linguistic expression is true or false with respect to some model of the way things happen to be; and (ii) stages of interpretation, i.e., ways to arrive at meanings by evaluating and converting source linguistic expressions, possibly with respect to contexts, into output (logical) forms that could be used with (i). The book demonstrates that the methods allow wide coverage without compromising the quality of semantic analysis. Access to unrestricted, robust and accurate semantic analysis is widely regarded as an essential component for improving natural language processing tasks, such as: recognizing textual entailment, information extraction, summarization, automatic reply, and machine translation.

This book covers key issues related to Geospatial Semantic Web, including geospatial web services for spatial data interoperability; geospatial ontology for semantic interoperability; ontology creation, sharing, and integration; querying knowledge and information from heterogeneous data source; interfaces for Geospatial Semantic Web, VGI (Volunteered Geographic Information) and Geospatial Semantic Web; challenges of Geospatial Semantic Web; and development of Geospatial Semantic Web applications. This book also describes state-of-the-art technologies that attempt to solve these problems such as WFS, WMS, RDF, OWL and GeoSPARQL and demonstrates how to use the Geospatial Semantic Web technologies to solve practical real-world problems such as spatial data interoperability.

The aim of this book is to advocate and promote network models of linguistic systems that are both based on thorough mathematical models and substantiated in terms of linguistics. In this way, the book contributes first steps towards establishing a statistical network theory as a theoretical basis of linguistic network analysis the boarder of the natural sciences and the humanities. This book addresses researchers who want to get familiar with theoretical developments, computational models and their empirical evaluation in the field of complex linguistic networks. It is intended to all those who are interested in statistical models of linguistic systems from the point of view of network research. This includes all relevant areas of linguistics ranging from phonological, morphological and lexical networks on the one hand and syntactic, semantic and pragmatic networks on the other. In this sense, the volume concerns readers from many disciplines such as physics, linguistics, computer science and information science. It may also be of interest for the upcoming area of systems biology with which the chapters collected here share the view on systems from the point of view of network analysis.

This book provides a wide variety of algorithms and models to integrate linguistic knowledge into Statistical Machine Translation (SMT). It helps advance conventional SMT to linguistically motivated SMT by enhancing the following three essential components: translation, reordering and bracketing models. It also serves the purpose of promoting the in-depth study of the impacts of linguistic knowledge on machine translation. Finally it provides a systematic introduction of Bracketing Transduction Grammar (BTG) based SMT, one of the state-of-the-art SMT formalisms, as well as a case study of linguistically motivated SMT on a BTG-based platform.

Edited under the auspices of the Association of Logic, Language andInformation (FoLLI), this book constitutes the refereed proceedings ofthe 20th anniversary of the International Conference on LogicalAspects of Computational Linguistics, LACL 2016, held in LORIA Nancy,France, in December 2016. The 19 contributed papers, presentedtogether with 4 invited papers and 6 abstracts, were carefullyreviewed and selected from 38 submissions. The focus of the conferenceis the use of type theoretic, proof theoretic, and model theoreticmethods for describing and formalising natural language syntax,semantics, and pragmatics as well as the implementation of thecorresponding tools.

The Yearbook of Corpus Linguistics and Pragmatics addresses the interface between the two disciplines and offers a platform to scholars who combine both methodologies to present rigorous and interdisciplinary findings about language in real use. Corpus linguistics and Pragmatics have traditionally represented two paths of scientific thought, parallel but often mutually exclusive and excluding. Corpus Linguistics can offer a meticulous methodology based on mathematics and statistics, while Pragmatics is characterized by its effort in the interpretation of intended meaning in real language. This series will give readers insight into how pragmatics can be used to explain real corpus data and also, how corpora can illustrate pragmatic intuitions. The present volume, Yearbook of Corpus Linguistics and Pragmatics 2014: New Empirical and Theoretical Paradigms in Corpus Pragmatics, proposes innovative research models in the liaison between pragmatics and corpus linguistics to explain language in current cultural and social contexts.

In the past few decades the use of increasingly large text corpora has grown rapidly in language and linguistics research. This was enabled by remarkable strides in natural language processing (NLP) technology, technology that enables computers to automatically and efficiently process, annotate and analyze large amounts of spoken and written text in linguistically and/or pragmatically meaningful ways. It has become more desirable than ever before for language and linguistics researchers who use corpora in their research to gain an adequate understanding of the relevant NLP technology to take full advantage of its capabilities. This volume provides language and linguistics researchers with an accessible introduction to the state-of-the-art NLP technology that facilitates automatic annotation and analysis of large text corpora at both shallow and deep linguistic levels. The book covers a wide range of computational tools for lexical, syntactic, semantic, pragmatic and discourse analysis, together with detailed instructions on how to obtain, install and use each tool in different operating systems and platforms. The book illustrates how NLP technology has been applied in recent corpus-based language studies and suggests effective ways to better integrate such technology in future corpus linguistics research. This book provides language and linguistics researchers with a valuable reference for corpus annotation and analysis.

The contributions in this volume focus on the Bayesian interpretation of natural languages, which is widely used in areas of artificial intelligence, cognitive science, and computational linguistics. This is the first volume to take up topics in Bayesian Natural Language Interpretation and make proposals based on information theory, probability theory, and related fields. The methodologies offered here extend to the target semantic and pragmatic analyses of computational natural language interpretation. Bayesian approaches to natural language semantics and pragmatics are based on methods from signal processing and the causal Bayesian models pioneered by especially Pearl. In signal processing, the Bayesian method finds the most probable interpretation by finding the one that maximizes the product of the prior probability and the likelihood of the interpretation. It thus stresses the importance of a production model for interpretation as in Grice’s contributions to pragmatics or in interpretation by abduction.

This book covers state-of-the-art topics on the practical implementation of Spoken Dialog Systems and intelligent assistants in everyday applications. It presents scientific achievements in language processing that result in the development of successful applications and addresses general issues regarding the advances in Spoken Dialog Systems with applications in robotics, knowledge access and communication. Emphasis is placed on the following topics: speaker/language recognition, user modeling / simulation, evaluation of dialog system, multi-modality / emotion recognition from speech, speech data mining, language resource and databases, machine learning for spoken dialog systems and educational and healthcare applications.

This pioneering book teaches readers to use R within four core analytical areas applicable to the Humanities: networks, text, geospatial data, and images. This book is also designed to be a bridge: between quantitative and qualitative methods, individual and collaborative work, and the humanities and social sciences. Humanities Data with R does not presuppose background programming experience. Early chapters take readers from R set-up to exploratory data analysis (continuous and categorical data, multivariate analysis, and advanced graphics with emphasis on aesthetics and facility). Following this, networks, geospatial data, image data, natural language processing and text analysis each have a dedicated chapter. Each chapter is grounded in examples to move readers beyond the intimidation of adding new tools to their research. Everything is hands-on: networks are explained using U.S. Supreme Court opinions, and low-level NLP methods are applied to short stories by Sir Arthur Conan Doyle. After working through these examples with the provided data, code and book website, readers are prepared to apply new methods to their own work. The open source R programming language, with its myriad packages and popularity within the sciences and social sciences, is particularly well-suited to working with humanities data. R packages are also highlighted in an appendix. This book uses an expanded conception of the forms data may take and the information it represents. The methodology will have wide application in classrooms and self-study for the humanities, but also for use in linguistics, anthropology, and political science. Outside the classroom, this intersection of humanities and computing is particularly relevant for research and new modes of dissemination across archives, museums and libraries.

The 1990s saw a paradigm change in the use of corpus-driven methods in NLP. In the field of multilingual NLP (such as machine translation and terminology mining) this implied the use of parallel corpora. However, parallel resources are relatively scarce: many more texts are produced daily by native speakers of any given language than translated. This situation resulted in a natural drive towards the use of comparable corpora, i.e. non-parallel texts in the same domain or genre. Nevertheless, this research direction has not produced a single authoritative source suitable for researchers and students coming to the field. The proposed volume provides a reference source, identifying the state of the art in the field as well as future trends. The book is intended for specialists and students in natural language processing, machine translation and computer-assisted translation.