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Markov Models and Linguistic Theory
No detailed description available for "Markov Models and Linguistic Theory".
Competing Models of Linguistic Change
The articles of this volume are centered around two competing views on language change originally presented at the 2003 International Conference on Historical Linguistics in the two important plenary papers by Henning Andersen and William Croft. The latter proposes an evolutionary model of language change within a domain-neutral model of a 'generalized analysis of selection', whereas Henning Andersen takes it that cultural phenomena could not possibly be handled, i.e. observed, described, understood, in the same way as natural phenomena. These papers are models of succinct presentation of important theoretical framework. The other papers present and discuss additional models of change, e.g. ...
Computational Cognitive Modeling and Linguistic Theory
This open access book introduces a general framework that allows natural language researchers to enhance existing competence theories with fully specified performance and processing components. Gradually developing increasingly complex and cognitively realistic competence-performance models, it provides running code for these models and shows how to fit them to real-time experimental data. This computational cognitive modeling approach opens up exciting new directions for research in formal semantics, and linguistics more generally, and offers new ways of (re)connecting semantics and the broader field of cognitive science. The approach of this book is novel in more ways than one. Assuming th...
Usage-based Models of Language
How do humans learn how to speak and understand language? For years, linguists have developed numerous models in attempts to explain humans' ability to communicate through language. Historically, these approaches were rooted and restricted in rule-based linguistic representations. Only recently has the field of linguistics been willing to forego formal representations and models to accommodate the usage-based perspective of studying language. Deviating from traditional methods, the contributions presented in this volume are among the first works to approach linguistic theory by developing and utilizing usage-based models. The contributing authors were among the principal leaders in their fie...
Linguistic Variation
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Data and Evidence in Linguistics
The question of what types of data and evidence can be used is one of the most important topics in linguistics. This book is the first to comprehensively present the methodological problems associated with linguistic data and evidence. Its originality is twofold. First, the authors' approach accounts for a series of unexplained characteristics of linguistic theorising: the uncertainty and diversity of data, the role of evidence in the evaluation of hypotheses, the problem solving strategies as well as the emergence and resolution of inconsistencies. Second, the findings are obtained by the application of a new model of plausible argumentation which is also of relevance from a general argumentation theoretical point of view. All concepts and theses are systematically introduced and illustrated by a number of examples from different linguistic theories, and a detailed case-study section shows how the proposed model can be applied to specific linguistic problems.
Computational Modeling of Human Language Acquisition
Human language acquisition has been studied for centuries, but using computational modeling for such studies is a relatively recent trend. However, computational approaches to language learning have become increasingly popular, mainly due to advances in developing machine learning techniques, and the availability of vast collections of experimental data on child language learning and child-adult interaction. Many of the existing computational models attempt to study the complex task of learning a language under cognitive plausibility criteria (such as memory and processing limitations that humans face), and to explain the developmental stages observed in children. By simulating the process o...
Language and Text
Specialists in quantitative linguistics the world over have recourse to a solid and universal methodology. These days, their methods and mathematical models must also respond to new communication phenomena and the flood of data produced daily. While various disciplines (computer science, media science) have different ways of processing this onslaught of information, the linguistic approach is arguably the most relevant and effective. This book includes recent results from many renowned contemporary practitioners in the field. Our target audiences are academics, researchers, graduate students, and others involved in linguistics, digital humanities, and applied mathematics.
Natural Language in Business Process Models
Natural language is one of the most important means of human communication. It enables us to express our will, to exchange thoughts and to document our knowledge in written sources. Owing to its substantial role in many facets of human life, technology for automatically analyzing and processing natural language has recently become increasingly important. In fact, natural language processing tools have paved the way for entirely new business opportunities. The goal of this book is to facilitate the automatic analysis of natural language in process models and to employ this analysis for assisting process model stakeholders. Therefore, a technique is defined that automatically recognizes and an...
