This volume presents articles that focus on the application of formal models in the study of language in a variety of innovative ways, and is dedicated to Jacques Moeschler, professor at University of Geneva, to mark the occasion of his 60th birthday. The contributions, by seasoned and budding linguists of all different linguistic backgrounds, reflect Jacques Moeschler's diverse and visionary research over the years. The book contains three parts. The first part shows how different formal models can be applied to the analysis of such diverse problems as the syntax, semantics and pragmatics of tense, aspect and deictic expressions, syntax and pragmatics of quantifiers and semantics and pragmatics of connectives and negation. The second part presents the application of formal models to the treatment of cognitive issues related to the use of language, and in particular, demonstrating cognitive accounts of different types of human interactions, the context in utterance interpretation (salience, inferential comprehension processes), figurative uses of language (irony pretence), the role of syntax in Theory of Mind in autism and the analysis of the aesthetics of nature. Finally, the third part addresses computational and corpus-based approaches to natural language for investigating language variation, language universals and discourse related issues. This volume will be of great interest to syntacticians, pragmaticians, computer scientists, semanticians and psycholinguists.

This book explores novel aspects of social robotics, spoken dialogue systems, human-robot interaction, spoken language understanding, multimodal communication, and system evaluation. It offers a variety of perspectives on and solutions to the most important questions about advanced techniques for social robots and chat systems. Chapters by leading researchers address key research and development topics in the field of spoken dialogue systems, focusing in particular on three special themes: dialogue state tracking, evaluation of human-robot dialogue in social robotics, and socio-cognitive language processing. The book offers a valuable resource for researchers and practitioners in both academia and industry whose work involves advanced interaction technology and who are seeking an up-to-date overview of the key topics. It also provides supplementary educational material for courses on state-of-the-art dialogue system technologies, social robotics, and related research fields.

The emergence of intelligent technologies, sophisticated natural language processing methodologies and huge textual repositories, invites a new approach for the challenge of automatically identifying personality dimensions through the analysis of textual data. This short book aims to (1) introduce the challenge of computational personality analysis, (2) present a unique approach to personality analysis and (3) illustrate this approach through case studies and worked-out examples. This book is of special relevance to psychologists, especially those interested in the new insights offered by new computational and data-intensive tools, and to computational social scientists interested in human personality and language processing.

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.

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.

The book offers a detailed guide to temporal ordering, exploring open problems in the field and providing solutions and extensive analysis. It addresses the challenge of automatically ordering events and times in text. Aided by TimeML, it also describes and presents concepts relating to time in easy-to-compute terms. Working out the order that events and times happen has proven difficult for computers, since the language used to discuss time can be vague and complex. Mapping out these concepts for a computational system, which does not have its own inherent idea of time, is, unsurprisingly, tough. Solving this problem enables powerful systems that can plan, reason about events, and construct stories of their own accord, as well as understand the complex narratives that humans express and comprehend so naturally. This book presents a theory and data-driven analysis of temporal ordering, leading to the identification of exactly what is difficult about the task. It then proposes and evaluates machine-learning solutions for the major difficulties. It is a valuable resource for those working in machine learning for natural language processing as well as anyone studying time in language, or involved in annotating the structure of time in documents.

The two-volume set LNCS 9623 + 9624 constitutes revised selected papers from the CICLing 2016 conference which took place in Konya, Turkey, in April 2016. The total of 89 papers presented in the two volumes was carefully reviewed and selected from 298 submissions. The book also contains 4 invited papers and a memorial paper on Adam Kilgarriff's Legacy to Computational Linguistics. The papers are organized in the following topical sections: Part I: In memoriam of Adam Kilgarriff; general formalisms; embeddings, language modeling, and sequence labeling; lexical resources and terminology extraction; morphology and part-of-speech tagging; syntax and chunking; named entity recognition; word sense disambiguation and anaphora resolution; semantics, discourse, and dialog. Part II: machine translation and multilingualism; sentiment analysis, opinion mining, subjectivity, and social media; text classification and categorization; information extraction; and applications.

The two-volume set LNCS 9623 + 9624 constitutes revised selected papers from the CICLing 2016 conference which took place in Konya, Turkey, in April 2016. The total of 89 papers presented in the two volumes was carefully reviewed and selected from 298 submissions. The book also contains 4 invited papers and a memorial paper on Adam Kilgarriff's Legacy to Computational Linguistics. The papers are organized in the following topical sections: Part I: In memoriam of Adam Kilgarriff; general formalisms; embeddings, language modeling, and sequence labeling; lexical resources and terminology extraction; morphology and part-of-speech tagging; syntax and chunking; named entity recognition; word sense disambiguation and anaphora resolution; semantics, discourse, and dialog. Part II: machine translation and multilingualism; sentiment analysis, opinion mining, subjectivity, and social media; text classification and categorization; information extraction; and applications.

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 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).

Event structures are central in Linguistics and Artificial Intelligence research: people can easily refer to changes in the world, identify their participants, distinguish relevant information, and have expectations of what can happen next. Part of this process is based on mechanisms similar to narratives, which are at the heart of information sharing. But it remains difficult to automatically detect events or automatically construct stories from such event representations. This book explores how to handle today's massive news streams and provides multidimensional, multimodal, and distributed approaches, like automated deep learning, to capture events and narrative structures involved in a 'story'. This overview of the current state-of-the-art on event extraction, temporal and casual relations, and storyline extraction aims to establish a new multidisciplinary research community with a common terminology and research agenda. Graduate students and researchers in natural language processing, computational linguistics, and media studies will benefit from this book.

This is the latest addition to a group of handbooks covering the field of morphology, alongside The Oxford Handbook of Case (2008), The Oxford Handbook of Compounding (2009), and The Oxford Handbook of Derivational Morphology (2014). It provides a comprehensive state-of-the-art overview of work on inflection - the expression of grammatical information through changes in word forms. The volume's 24 chapters are written by experts in the field from a variety of theoretical backgrounds, with examples drawn from a wide range of languages. The first part of the handbook covers the fundamental building blocks of inflectional form and content: morphemes, features, and means of exponence. Part 2 focuses on what is arguably the most characteristic property of inflectional systems, paradigmatic structure, and the non-trivial nature of the mapping between function and form. The third part deals with change and variation over time, and the fourth part covers computational issues from a theoretical and practical standpoint. Part 5 addresses psycholinguistic questions relating to language acquisition and neurocognitive disorders. The final part is devoted to sketches of individual inflectional systems, illustrating a range of typological possibilities across a genetically diverse set of languages from Africa, Asia and the Pacific, Australia, Europe, and South America.

This book constitutes the proceedings of the 21st International Conference on Developments in Language Theory, DLT 2017, held in Liege, Belgium, in August 2017.The 24 full papers and 6 (abstract of) invited papers were carefully reviewed and selected from 47 submissions. The papers cover the following topics and areas: combinatorial and algebraic properties of words and languages; grammars acceptors and transducers for strings, trees, graphics, arrays; algebraic theories for automata and languages; codes; efficient text algorithms; symbolic dynamics; decision problems; relationships to complexity theory and logic; picture description and analysis, polyominoes and bidimensional patterns; cryptography; concurrency; celluar automata; bio-inspiredcomputing; quantum computing.

This book presents an overview of speaker recognition technologies with an emphasis on dealing with robustness issues. Firstly, the book gives an overview of speaker recognition, such as the basic system framework, categories under different criteria, performance evaluation and its development history. Secondly, with regard to robustness issues, the book presents three categories, including environment-related issues, speaker-related issues and application-oriented issues. For each category, the book describes the current hot topics, existing technologies, and potential research focuses in the future. The book is a useful reference book and self-learning guide for early researchers working in the field of robust speech recognition.

Thanks to the availability of texts on the Web in recent years, increased knowledge and information have been made available to broader audiences. However, the way in which a text is written-its vocabulary, its syntax-can be difficult to read and understand for many people, especially those with poor literacy, cognitive or linguistic impairment, or those with limited knowledge of the language of the text. Texts containing uncommon words or long and complicated sentences can be difficult to read and understand by people as well as difficult to analyze by machines. Automatic text simplification is the process of transforming a text into another text which, ideally conveying the same message, will be easier to read and understand by a broader audience. The process usually involves the replacement of difficult or unknown phrases with simpler equivalents and the transformation of long and syntactically complex sentences into shorter and less complex ones. Automatic text simplification, a research topic which started 20 years ago, now has taken on a central role in natural language processing research not only because of the interesting challenges it posesses but also because of its social implications. This book presents past and current research in text simplification, exploring key issues including automatic readability assessment, lexical simplification, and syntactic simplification. It also provides a detailed account of machine learning techniques currently used in simplification, describes full systems designed for specific languages and target audiences, and offers available resources for research and development together with text simplification evaluation techniques.

Neural networks are a family of powerful machine learning models. This book focuses on the application of neural network models to natural language data. The first half of the book (Parts I and II) covers the basics of supervised machine learning and feed-forward neural networks, the basics of working with machine learning over language data, and the use of vector-based rather than symbolic representations for words. It also covers the computation-graph abstraction, which allows to easily define and train arbitrary neural networks, and is the basis behind the design of contemporary neural network software libraries. The second part of the book (Parts III and IV) introduces more specialized neural network architectures, including 1D convolutional neural networks, recurrent neural networks, conditioned-generation models, and attention-based models. These architectures and techniques are the driving force behind state-of-the-art algorithms for machine translation, syntactic parsing, and many other applications. Finally, we also discuss tree-shaped networks, structured prediction, and the prospects of multi-task learning.

The two-volume set LNCS 13451 and 13452 constitutes revised selected papers from the CICLing 2019 conference which took place in La Rochelle, France, April 2019.The total of 95 papers presented in the two volumes was carefully reviewed and selected from 335 submissions. The book also contains 3 invited papers. The papers are organized in the following topical sections: General, Information extraction, Information retrieval, Language modeling, Lexical resources, Machine translation, Morphology, sintax, parsing, Name entity recognition, Semantics and text similarity, Sentiment analysis, Speech processing, Text categorization, Text generation, and Text mining.

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 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.

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

This book 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.

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.

This book applies linguistic analysis to the poetry of Emeritus Professor Edwin Thumboo, a Singaporean poet and leading figure in Commonwealth literature. The work explores how the poet combines grammar and metaphor to create meaning, making the reader aware of the linguistic resources developed by Thumboo as the basis for his unique technique. The author approaches the poems from a functional linguistic perspective, investigating the multiple layers of meaning and metaphor that go into producing these highly textured, grammatically intricate verbal works of art. The approach is based on the Systemic Functional Theory, which aids the study of how the poet uses language (grammar) to craft his text in a playful way that reflects a love of the language. The multilingual and multicultural experiences of the poet are considered to have contributed to his uniquely creative use of language. This work demonstrates how the Systemic Functional Theory, with its emphasis on exploring the semogenic (meaning-making) power of language, provides the perspective we need to better understand poets' works as intentional acts of meaning. Readers will discover how the works of Edwin Thumboo illustrate well a point made by Barthes, who noted that "Bits of code, formulae, rhythmic models, fragments of social languages, etc. pass into the text and are redistributed within it, for there is always language before and around the text." With a focus on meaning, this functional analysis of poetry offers an insightful look at the linguistic basis of Edwin Thumboo's poetic technique. The work will appeal to scholars with an interest in linguistic analysis and poetry from the Commonwealth and new literature, and it can also be used to support courses on literary stylistics or text linguistics.

This book constitutes the refereed proceedings of the 6th International Conference of the CLEF Initiative, CLEF 2015, held in Toulouse, France, in September 2015. The 31 full papers and 20 short papers presented were carefully reviewed and selected from 68 submissions. They cover a broad range of issues in the fields of multilingual and multimodal information access evaluation, also included are a set of labs and workshops designed to test different aspects of mono and cross-language information retrieval systems.

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.