This book provides a clear and comprehensive description of the Ocotepec/Tapalapa variant of Chiapas Zoque. Zoque is one of the two major branches of the Mixe-Zoquean language family, spoken in the southern part of Mexico. Until the Spanish conquest in the sixteenth century the Mixe-Zoquean languages covered a large area from Veracruz on the Gulf coast to the border of Guatemala and the Pacific coast. Inscriptions in Zoque from the first half of the first millennium AD are the oldest known linguistic documents in Mesoamerica.The Zoquean area once included the entire heartland of the Olmecs, who almost certainly spoke a proto-Zoquean or proto-Mixe-Zoquean language. The Zoques are thus the most likely direct descendents of the oldest known civilization of Mexico. As a result of a long history of close contact, Zoque and Mayan share areal features, and there are lexical borrowings in both directions, but genetically and typologically they are clearly distinct. The Zoque-speaking area has shrunk considerably since pre-colonial times. In 1982 an eruption from the volcano Chichonal destroyed a central part of the Zoque core area and caused a mass migration of Zoque speakers to parts of Mexico where Spanish is the dominant language. This record of an unusual and critically endangered language will be a vital resource for linguists of all theoretical persuasions.

'Natural Language Processing in the Real World' is a practical guide for applying data science and machine learning to build Natural Language Processing (NLP) solutions. Where traditional, academic-taught NLP is often accompanied by a data source or dataset to aid solution building, this book is situated in the real-world where there may not be an existing rich dataset. This book covers the basic concepts behind NLP and text processing and discusses the applications across 15 industry verticals. From data sources and extraction to transformation and modelling, and classic Machine Learning to Deep Learning and Transformers, several popular applications of NLP are discussed and implemented. This book provides a hands-on and holistic guide for anyone looking to build NLP solutions, from students of Computer Science to those involved in large-scale industrial projects. .

The contributions to The Fruits of Empirical Linguistics. Volume 1: Process reveal why the data-driven approach makes for a research environment which is fast-moving and democratic: technological change has made the sources of linguistic data readily accessible. These contributions show the methods both professional and student linguists are using to gather more evidence more easily than before.

The practical task of building a talking robot requires a theory of how natural language communication works. Conversely, the best way to computationally verify a theory of natural language communication is to demonstrate its functioning concretely in the form of a talking robot, the epitome of human-machine communication. To build an actual robot requires hardware that provides appropriate recognition and action interfaces, and because such hardware is hard to develop the approach in this book is theoretical: the author presents an artificial cognitive agent with language as a software system called database semantics (DBS). Because a theoretical approach does not have to deal with the technical difficulties of hardware engineering there is no reason to simplify the system - instead the software components of DBS aim at completeness of function and of data coverage in word form recognition, syntactic-semantic interpretation and inferencing, leaving the procedural implementation of elementary concepts for later.

In this book the author first examines the universals of natural language and explains the Database Semantics approach. Then in Part I he examines the following natural language communication issues: using external surfaces; the cycle of natural language communication; memory structure; autonomous control; and learning. In Part II he analyzes the coding of content according to the aspects: semantic relations of structure; simultaneous amalgamation of content; graph-theoretical considerations; computing perspective in dialogue; and computing perspective in text. The book ends with a concluding chapter, a bibliography and an index.

The book will be of value to researchers, graduate students and engineers in the areas of artificial intelligence and robotics, in particular those who deal with natural language processing.

The book specifies a corpus architecture, including annotation and querying techniques, and its implementation. The corpus architecture is developed for empirical studies of translations, and beyond those for the study of texts which are inter-lingually comparable, particularly texts of similar registers. The compiled corpus, CroCo, is a resource for research and is, with some copyright restrictions, accessible to other research projects. Most of the research was undertaken as part of a DFG-Project into linguistic properties of translations. Fundamentally, this research project was a corpus-based investigation into the language pair English-German. The long-term goal is a contribution to the study of translation as a contact variety, and beyond this to language comparison and language contact more generally with the language pair English - German as our object languages. This goal implies a thorough interest in possible specific properties of translations, and beyond this in an empirical translation theory. The methodology developed is not restricted to the traditional exclusively system-based comparison of earlier days, where real-text excerpts or constructed examples are used as mere illustrations of assumptions and claims, but instead implements an empirical research strategy involving structured data (the sub-corpora and their relationships to each other, annotated and aligned on various theoretically motivated levels of representation), the formation of hypotheses and their operationalizations, statistics on the data, critical examinations of their significance, and interpretation against the background of system-based comparisons and other independent sources of explanation for the phenomena observed. Further applications of the resource developed in computational linguistics are outlined and evaluated.

This book shows ways of augmenting the capabilities of Natural Language Processing (NLP) systems by means of cognitive-mode language processing. The authors employ eye-tracking technology to record and analyze shallow cognitive information in the form of gaze patterns of readers/annotators who perform language processing tasks. The insights gained from such measures are subsequently translated into systems that help us (1) assess the actual cognitive load in text annotation, with resulting increase in human text-annotation efficiency, and (2) extract cognitive features that, when added to traditional features, can improve the accuracy of text classifiers. In sum, the authors' work successfully demonstrates that cognitive information gleaned from human eye-movement data can benefit modern NLP. Currently available Natural Language Processing (NLP) systems are weak AI systems: they seek to capture the functionality of human language processing, without worrying about how this processing is realized in human beings' hardware. In other words, these systems are oblivious to the actual cognitive processes involved in human language processing. This ignorance, however, is NOT bliss! The accuracy figures of all non-toy NLP systems saturate beyond a certain point, making it abundantly clear that "something different should be done."

Text classification is becoming a crucial task to analysts in different areas. In the last few decades, the production of textual documents in digital form has increased exponentially. Their applications range from web pages to scientific documents, including emails, news and books. Despite the widespread use of digital texts, handling them is inherently difficult - the large amount of data necessary to represent them and the subjectivity of classification complicate matters. This book gives a concise view on how to use kernel approaches for inductive inference in large scale text classification; it presents a series of new techniques to enhance, scale and distribute text classification tasks. It is not intended to be a comprehensive survey of the state-of-the-art of the whole field of text classification. Its purpose is less ambitious and more practical: to explain and illustrate some of the important methods used in this field, in particular kernel approaches and techniques.

Being presented with phrases of the kind, 'take the plunge' and 'write a letter', native speakers of English tend to agree that the former is more idiomatic that the latter. What exactly is it about these two phrases that guide speakers' judgements? Adopting a usage-based perspective, this study addresses the question 'which factors do speakers rely upon when assessing the idiomaticity of a construction?'.
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Rethinking Idiomaticity "is the first study to bring together a quantitative corpus-linguistic approach and quantitative judgement data to explore the nature of idiomaticity as a complex concept that comprises semantic and formal variation parameters. Wulff's fascinating book is suitable for researchers and postgraduates in the fields of lexicography, phraseology, corpus linguistics and those who are employing quantitative approaches.
Cognitive linguists interested in the empirical underpinnings of their theoretical assumptions will also find this required reading.

The general markup language XML has played an outstanding role in the mul- ple ways of processing electronic documents, XML being used either in the design of interface structures or as a formal framework for the representation of structure or content-related properties of documents. This book in its 13 chapters discusses aspects of XML-based linguistic information modeling combining: methodological issues, especially with respect to text-related information modeling, applicati- oriented research and issues of formal foundations. The contributions in this book are based on current research in Text Technology, Computational Linguistics and in the international domain of evolving standards for language resources. Rec- rent themes in this book are markup languages, explored from different points of view, and topics of text-related information modeling. These topics have been core areas of the research Unit "Text-technological Information Modeling" (www. te- technology. de) funded from 2002 to 2009 by the German Research Foundation (DFG). Positions developed in this book could also bene t from the presentations and discussion at the conference "Modelling Linguistic Information Resources" at the Center for Interdisciplinary Research (Zentrum fur .. interdisziplinare .. Forschung, ZiF) at Bielefeld, a center for advanced studies known for its international and interdisciplinary meetings and research. The editors would like to thank the DFG and ZiF for their nancial support, the publisher, the series editors, the reviewers and those people that helped to prepare the manuscript, especially Carolin Kram, Nils Diewald, Jens Stegmann and Peter M. Fischer and last but not least, all of the authors.

This book constitutes the thoroughly refereed proceedings of the Eleventh International Symposium on Natural Language Processing (SNLP-2016), held in Phranakhon Si Ayutthaya, Thailand on February 10-12, 2016. The SNLP promotes research in natural language processing and related fields, and provides a unique opportunity for researchers, professionals and practitioners to discuss various current and advanced issues of interest in NLP. The 2016 symposium was expanded to include the First Workshop in Intelligent Informatics and Smart Technology. Of the 66 high-quality papers accepted, this book presents twelve from the Symposium on Natural Language Processing track and ten from the Workshop in Intelligent Informatics and Smart Technology track (SSAI: Special Session on Artificial Intelligence).

Serious work using computers to support language teaching and learning began in the 1960s, but it was not until the beginning of the 1980s when microcomputers began to proliferate that groups of practitioners began forming professional groups and a formal identification of the field occurred. Although the early promise of computer-assisted language learning (or ?CALL?), to revolutionize second-language learning has not been met, the past quarter century has seen a fascinating range of growth. This is not only because of lessons learned from research and practice, but also due to the rapid and continuing shifts in the technology itself.

Nominally a branch of applied linguistics, 'CALL' is truly interdisciplinary, drawing its core concepts not only from linguistics, but also from computer science, speech engineering, psychology, sociology, second-language acquisition, and general education.

This new four-volume title from Routledge will allow 'CALL' practitioners, researchers, and students to easily access the best and most influential foundational and cutting-edge scholarship. The is also a comprehensive introduction to critical concepts in 'CALL' for applied linguists and language educators interested in the growing role of technology in second-language acquisition.

In this book, a novel approach that combines speech-based emotion recognition with adaptive human-computer dialogue modeling is described. With the robust recognition of emotions from speech signals as their goal, the authors analyze the effectiveness of using a plain emotion recognizer, a speech-emotion recognizer combining speech and emotion recognition, and multiple speech-emotion recognizers at the same time. The semi-stochastic dialogue model employed relates user emotion management to the corresponding dialogue interaction history and allows the device to adapt itself to the context, including altering the stylistic realization of its speech. This comprehensive volume begins by introducing spoken language dialogue systems and providing an overview of human emotions, theories, categorization and emotional speech. It moves on to cover the adaptive semi-stochastic dialogue model and the basic concepts of speech-emotion recognition. Finally, the authors show how speech-emotion recognizers can be optimized, and how an adaptive dialogue manager can be implemented. The book, with its novel methods to perform robust speech-based emotion recognition at low complexity, will be of interest to a variety of readers involved in human-computer interaction.

Yorick Wilks is a central figure in the fields of Natural Language Processing and Artificial Intelligence. His influence extends to many areas of these fields and includes contributions to machine translation, word sense disambiguation, dialogue modeling and information extraction.This book celebrates the work of Yorick Wilks from the perspective of his peers. It consists of original chapters each of which analyses an aspect of his work and links it to current thinking in that area. His work has spanned over four decades but is shown to be pertinent to recent developments in language processing such as the Semantic Web.This volume forms a two-part set together with 'Words and Intelligence I, Selected Works by Yorick Wilks', by the same editors.

The contributions in this volume provide a kaleidoscope of state-of-the-art research in corpus linguistics on lexis and lexicogrammar. Central issues are the presentation of major corpus resources (both corpora and software tools), the findings (especially about frequency) which are simply not accessible without such resources, their theoretical implications relating to both lexical units and word meanings, and the practical - especially pedagogical - applications of corpus findings. This is complemented by a lexicographer's view on the data structures implicit in the Oxford English Dictionary (OED). The volume, which has sprung from the 36th ICAME conference, held in at Trier University in May 2015, will be of relevance for theoretical and applied linguists interested in corpora, word usage, and the mental lexicon.

Qualitative reasoning about space and time - a reasoning at the human level - promises to become a fundamental aspect of future systems that will accompany us in daily activity. The aim of Spatial and Temporal Reasoning is to give a picture of current research in this area focusing on both representational and computational issues. The picture emphasizes some major lines of development in this multifaceted, constantly growing area. The material in the book also shows some common ground and a novel combination of spatial and temporal aspects of qualitative reasoning. Part I presents the overall scene. The chapter by Laure Vieu is on the state of the art in spatial representation and reasoning, and that by Alfonso Gerevini gives a similar survey on research in temporal reasoning. The specific contributions to these areas are then grouped in the two main parts. In Part II, Roberto Casati and Achille Varzi examine the ontological status of spatial entities; Anthony Cohn, Brandon Bennett, John Gooday, and Nicholas Gotts present a detailed theory of reasoning with qualitative relations about regions; Andrew Frank discusses the spatial needs of geographical information systems; and Annette Herskovits focuses on the linguistic expression of spatial relations. In Part III, James Allen and George Ferguson describe an interval temporal logic for the representation of actions and events; Drew McDermott presents an efficient way of predicting the outcome of plan execution; and Erik Sandewall introduces a semantics based on transitions for assessing theories of action and change. In Part IV, Antony Galton's chapter stands clearly between the two areas of space and time and outlines the main coordinates of an integrated approach.

Fuzzy modeling usually comes with two contradictory requirements: interpretability, which is the capability to express the real system behavior in a comprehensible way, and accuracy, which is the capability to faithfully represent the real system. In this framework, one of the most important areas is linguistic fuzzy modeling, where the legibility of the obtained model is the main objective. This task is usually developed by means of linguistic (Mamdani) fuzzy rule-based systems. An active research area is oriented towards the use of new techniques and structures to extend the classical, rigid linguistic fuzzy modeling with the main aim of increasing its precision degree. Traditionally, this accuracy improvement has been carried out without considering the corresponding interpretability loss. Currently, new trends have been proposed trying to preserve the linguistic fuzzy model description power during the optimization process. Written by leading experts in the field, this volume collects some representative researcher that pursue this approach.

This is the first book which brings together the fields of theoretical and empirical studies in syntax on the one hand and the methodology of quantitative linguistics on the other hand. The author provides the theoretical background for this enterprise on the basis of the philosophy of science and of linguistic considerations including a discussion of Chomsky's attitude against the application of statistical methods to syntactic phenomena. He gives a short introduction into the aims and methods of the quantitative approach to linguistics in general and to syntax in particular. The following chapters inform the reader about the measurement of syntactic properties, possibilities to acquire empirical data from syntactically annotated text corpora and the most common mathematical models and methods for the analysis of syntactic and syntagmatic material. Then, a number of prominent approaches and hypotheses about interrelations between properties of syntactic constructions are presented and evaluated on material from various languages and text kinds. Finally, the theory of synergetic linguistics and its application to syntax is introduced including the integration of such famous hypotheses as Yngve's depth hypothesis and Hawkins's "Early immediate constituent" principle. The book concludes with a number of perspectives with respect to follow-up studies and extensions to the presented models with interfaces to neighbouring disciplines.

"Mobile Speech and Advanced Natural Language Solutions" presents the discussion of the most recent advances in intelligent human-computer interaction, including fascinating new study findings on talk-in-interaction, which is the province of conversation analysis, a subfield in sociology/sociolinguistics, a new and emerging area in natural language understanding. Editors Amy Neustein and Judith A. Markowitz have recruited a talented group of contributors to introduce the next generation natural language technologies for practical speech processing applications that serve the consumer's need for well-functioning natural language-driven personal assistants and other mobile devices, while also addressing business' need for better functioning IVR-driven call centers that yield a more satisfying experience for the caller. This anthology is aimed at two distinct audiences: one consisting of speech engineers and system developers; the other comprised of linguists and cognitive scientists. The text builds on the experience and knowledge of each of these audiences by exposing them to the work of the other.

In this handbook, renowned scholars from a range of backgrounds provide a state of the art review of key developmental findings in language acquisition. The book places language acquisition phenomena in a richly linguistic and comparative context, highlighting the link between linguistic theory, language development, and theories of learning. The book is divided into six parts. Parts I and II examine the acquisition of phonology and morphology respectively, with chapters covering topics such as phonotactics and syllable structure, prosodic phenomena, compound word formation, and processing continuous speech. Part III moves on to the acquisition of syntax, including argument structure, questions, mood alternations, and possessives. In Part IV, chapters consider semantic aspects of language acquisition, including the expression of genericity, quantification, and scalar implicature. Finally, Parts V and VI look at theories of learning and aspects of atypical language development respectively.

This book assesses the place of logic, mathematics, and computer science in present day, interdisciplinary areas of computational linguistics. Computational linguistics studies natural language in its various manifestations from a computational point of view, both on the theoretical level (modeling grammar modules dealing with natural language form and meaning and the relation between these two) and on the practical level (developing applications for language and speech technology). It is a collection of chapters presenting new and future research. The book focuses mainly on logical approaches to computational processing of natural language and on the applicability of methods and techniques from the study of formal languages, programming, and other specification languages. It presents work from other approaches to linguistics, as well, especially because they inspire new work and approaches.

This volume provides an overview of the field of Hybrid Machine Translation (MT) and presents some of the latest research conducted by linguists and practitioners from different multidisciplinary areas. Nowadays, most important developments in MT are achieved by combining data-driven and rule-based techniques. These combinations typically involve hybridization of different traditional paradigms, such as the introduction of linguistic knowledge into statistical approaches to MT, the incorporation of data-driven components into rule-based approaches, or statistical and rule-based pre- and post-processing for both types of MT architectures. The book is of interest primarily to MT specialists, but also - in the wider fields of Computational Linguistics, Machine Learning and Data Mining - to translators and managers of translation companies and departments who are interested in recent developments concerning automated translation tools.

Automatic speech recognition suffers from a lack of robustness with respect to noise, reverberation and interfering speech. The growing field of speech recognition in the presence of missing or uncertain input data seeks to ameliorate those problems by using not only a preprocessed speech signal but also an estimate of its reliability to selectively focus on those segments and features that are most reliable for recognition. This book presents the state of the art in recognition in the presence of uncertainty, offering examples that utilize uncertainty information for noise robustness, reverberation robustness, simultaneous recognition of multiple speech signals, and audiovisual speech recognition. The book is appropriate for scientists and researchers in the field of speech recognition who will find an overview of the state of the art in robust speech recognition, professionals working in speech recognition who will find strategies for improving recognition results in various conditions of mismatch, and lecturers of advanced courses on speech processing or speech recognition who will find a reference and a comprehensive introduction to the field. The book assumes an understanding of the fundamentals of speech recognition using Hidden Markov Models.

This book is open access and available on www.bloomsburycollections.com. It is funded by Knowledge Unlatched. Corpus linguistics has much to offer history, being as both disciplines engage so heavily in analysis of large amounts of textual material. This book demonstrates the opportunities for exploring corpus linguistics as a method in historiography and the humanities and social sciences more generally. Focussing on the topic of prostitution in 17th-century England, it shows how corpus methods can assist in social research, and can be used to deepen our understanding and comprehension. McEnery and Baker draw principally on two sources - the newsbook Mercurius Fumigosis and the Early English Books Online Corpus. This scholarship on prostitution and the sex trade offers insight into the social position of women in history.

In Methods in Latin Computational Linguistics, Barbara McGillivray presents some of the most significant methodological foundations of the emerging field of Latin Computational Linguistics. The reader will find an overview of the computational resources and tools available for Latin and three corpus case studies covering morpho-syntactic and lexical-semantic aspects of Latin verb valency, as well as quantitative diachronic explorations of the argument realization of Latin prefixed verbs. The computational models and the multivariate data analysis techniques employed are explained with a detailed but accessible language. Barbara McGillivray convincingly shows the challenges and opportunities of combining computational methods and historical language data, and contributes to driving the technological change that is affecting Historical Linguistics and the Humanities.

This book lays out a path leading from the linguistic and cognitive basics, to classical rule-based and machine learning algorithms, to today's state-of-the-art approaches, which use advanced empirically grounded techniques, automatic knowledge acquisition, and refined linguistic modeling to make a real difference in real-world applications. Anaphora and coreference resolution both refer to the process of linking textual phrases (and, consequently, the information attached to them) within as well as across sentence boundaries, and to the same discourse referent. The book offers an overview of recent research advances, focusing on practical, operational approaches and their applications. In part I (Background), it provides a general introduction, which succinctly summarizes the linguistic, cognitive, and computational foundations of anaphora processing and the key classical rule- and machine-learning-based anaphora resolution algorithms. Acknowledging the central importance of shared resources, part II (Resources) covers annotated corpora, formal evaluation, preprocessing technology, and off-the-shelf anaphora resolution systems. Part III (Algorithms) provides a thorough description of state-of-the-art anaphora resolution algorithms, covering enhanced machine learning methods as well as techniques for accomplishing important subtasks such as mention detection and acquisition of relevant knowledge. Part IV (Applications) deals with a selection of important anaphora and coreference resolution applications, discussing particular scenarios in diverse domains and distilling a best-practice model for systematically approaching new application cases. In the concluding part V (Outlook), based on a survey conducted among the contributing authors, the prospects of the research field of anaphora processing are discussed, and promising new areas of interdisciplinary cooperation and emerging application scenarios are identified. Given the book's design, it can be used both as an accompanying text for advanced lectures in computational linguistics, natural language engineering, and computer science, and as a reference work for research and independent study. It addresses an audience that includes academic researchers, university lecturers, postgraduate students, advanced undergraduate students, industrial researchers, and software engineers.