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The Role Of Markov Models In Linguistic Theory
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Book Synopsis Markov Models and Linguistic Theory by : Friederick J. Damerau
Download or read book Markov Models and Linguistic Theory written by Friederick J. Damerau and published by Walter de Gruyter GmbH & Co KG. This book was released on 2018-12-03 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt: No detailed description available for "Markov Models and Linguistic Theory".
Book Synopsis The Application of Hidden Markov Models in Speech Recognition by : Mark Gales
Download or read book The Application of Hidden Markov Models in Speech Recognition written by Mark Gales and published by Now Publishers Inc. This book was released on 2008 with total page 125 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Application of Hidden Markov Models in Speech Recognition presents the core architecture of a HMM-based LVCSR system and proceeds to describe the various refinements which are needed to achieve state-of-the-art performance.
Book Synopsis Markov Models for Pattern Recognition by : Gernot A. Fink
Download or read book Markov Models for Pattern Recognition written by Gernot A. Fink and published by Springer Science & Business Media. This book was released on 2014-01-14 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thoroughly revised and expanded new edition now includes a more detailed treatment of the EM algorithm, a description of an efficient approximate Viterbi-training procedure, a theoretical derivation of the perplexity measure and coverage of multi-pass decoding based on n-best search. Supporting the discussion of the theoretical foundations of Markov modeling, special emphasis is also placed on practical algorithmic solutions. Features: introduces the formal framework for Markov models; covers the robust handling of probability quantities; presents methods for the configuration of hidden Markov models for specific application areas; describes important methods for efficient processing of Markov models, and the adaptation of the models to different tasks; examines algorithms for searching within the complex solution spaces that result from the joint application of Markov chain and hidden Markov models; reviews key applications of Markov models.
Book Synopsis Markov Models and Linguistic Theory by : Frederick J. Damerau
Download or read book Markov Models and Linguistic Theory written by Frederick J. Damerau and published by . This book was released on 1971 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Linguistic Structure Prediction by : Noah A. Smith
Download or read book Linguistic Structure Prediction written by Noah A. Smith and published by Morgan & Claypool Publishers. This book was released on 2011 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: A major part of natural language processing now depends on the use of text data to build linguistic analyzers. We consider statistical, computational approaches to modeling linguistic structure. We seek to unify across many approaches and many kinds of linguistic structures. Assuming a basic understanding of natural language processing and/or machine learning, we seek to bridge the gap between the two fields. Approaches to decoding (i.e., carrying out linguistic structure prediction) and supervised and unsupervised learning of models that predict discrete structures as outputs are the focus. We also survey natural language processing problems to which these methods are being applied, and we address related topics in probabilistic inference, optimization, and experimental methodology. Table of Contents: Representations and Linguistic Data / Decoding: Making Predictions / Learning Structure from Annotated Data / Learning Structure from Incomplete Data / Beyond Decoding: Inference
Book Synopsis Markov Models & Optimization by : M.H.A. Davis
Download or read book Markov Models & Optimization written by M.H.A. Davis and published by CRC Press. This book was released on 1993-08-01 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a radically new approach to problems of evaluating and optimizing the performance of continuous-time stochastic systems. This approach is based on the use of a family of Markov processes called Piecewise-Deterministic Processes (PDPs) as a general class of stochastic system models. A PDP is a Markov process that follows deterministic trajectories between random jumps, the latter occurring either spontaneously, in a Poisson-like fashion, or when the process hits the boundary of its state space. This formulation includes an enormous variety of applied problems in engineering, operations research, management science and economics as special cases; examples include queueing systems, stochastic scheduling, inventory control, resource allocation problems, optimal planning of production or exploitation of renewable or non-renewable resources, insurance analysis, fault detection in process systems, and tracking of maneuvering targets, among many others. The first part of the book shows how these applications lead to the PDP as a system model, and the main properties of PDPs are derived. There is particular emphasis on the so-called extended generator of the process, which gives a general method for calculating expectations and distributions of system performance functions. The second half of the book is devoted to control theory for PDPs, with a view to controlling PDP models for optimal performance: characterizations are obtained of optimal strategies both for continuously-acting controllers and for control by intervention (impulse control). Throughout the book, modern methods of stochastic analysis are used, but all the necessary theory is developed from scratch and presented in a self-contained way. The book will be useful to engineers and scientists in the application areas as well as to mathematicians interested in applications of stochastic analysis.
Book Synopsis Syntactic Structures by : Noam Chomsky
Download or read book Syntactic Structures written by Noam Chomsky and published by Walter de Gruyter GmbH & Co KG. This book was released on 2020-05-18 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt: No detailed description available for "Syntactic Structures".
Download or read book Markov Chains written by Paul A. Gagniuc and published by John Wiley & Sons. This book was released on 2017-07-31 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: A fascinating and instructive guide to Markov chains for experienced users and newcomers alike This unique guide to Markov chains approaches the subject along the four convergent lines of mathematics, implementation, simulation, and experimentation. It introduces readers to the art of stochastic modeling, shows how to design computer implementations, and provides extensive worked examples with case studies. Markov Chains: From Theory to Implementation and Experimentation begins with a general introduction to the history of probability theory in which the author uses quantifiable examples to illustrate how probability theory arrived at the concept of discrete-time and the Markov model from experiments involving independent variables. An introduction to simple stochastic matrices and transition probabilities is followed by a simulation of a two-state Markov chain. The notion of steady state is explored in connection with the long-run distribution behavior of the Markov chain. Predictions based on Markov chains with more than two states are examined, followed by a discussion of the notion of absorbing Markov chains. Also covered in detail are topics relating to the average time spent in a state, various chain configurations, and n-state Markov chain simulations used for verifying experiments involving various diagram configurations. • Fascinating historical notes shed light on the key ideas that led to the development of the Markov model and its variants • Various configurations of Markov Chains and their limitations are explored at length • Numerous examples—from basic to complex—are presented in a comparative manner using a variety of color graphics • All algorithms presented can be analyzed in either Visual Basic, Java Script, or PHP • Designed to be useful to professional statisticians as well as readers without extensive knowledge of probability theory Covering both the theory underlying the Markov model and an array of Markov chain implementations, within a common conceptual framework, Markov Chains: From Theory to Implementation and Experimentation is a stimulating introduction to and a valuable reference for those wishing to deepen their understanding of this extremely valuable statistical tool. Paul A. Gagniuc, PhD, is Associate Professor at Polytechnic University of Bucharest, Romania. He obtained his MS and his PhD in genetics at the University of Bucharest. Dr. Gagniuc’s work has been published in numerous high profile scientific journals, ranging from the Public Library of Science to BioMed Central and Nature journals. He is the recipient of several awards for exceptional scientific results and a highly active figure in the review process for different scientific areas.
Book Synopsis Hidden Markov Models by : Robert J Elliott
Download or read book Hidden Markov Models written by Robert J Elliott and published by Springer Science & Business Media. This book was released on 2008-09-27 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: As more applications are found, interest in Hidden Markov Models continues to grow. Following comments and feedback from colleagues, students and other working with Hidden Markov Models the corrected 3rd printing of this volume contains clarifications, improvements and some new material, including results on smoothing for linear Gaussian dynamics. In Chapter 2 the derivation of the basic filters related to the Markov chain are each presented explicitly, rather than as special cases of one general filter. Furthermore, equations for smoothed estimates are given. The dynamics for the Kalman filter are derived as special cases of the authors’ general results and new expressions for a Kalman smoother are given. The Chapters on the control of Hidden Markov Chains are expanded and clarified. The revised Chapter 4 includes state estimation for discrete time Markov processes and Chapter 12 has a new section on robust control.
Book Synopsis Probabilistic Linguistics by : Rens Bod
Download or read book Probabilistic Linguistics written by Rens Bod and published by A Bradford Book. This book was released on 2003-04-08 with total page 465 pages. Available in PDF, EPUB and Kindle. Book excerpt: For the past forty years, linguistics has been dominated by the idea that language is categorical and linguistic competence discrete. It has become increasingly clear, however, that many levels of representation, from phonemes to sentence structure, show probabilistic properties, as does the language faculty. Probabilistic linguistics conceptualizes categories as distributions and views knowledge of language not as a minimal set of categorical constraints but as a set of gradient rules that may be characterized by a statistical distribution. Whereas categorical approaches focus on the endpoints of distributions of linguistic phenomena, probabilistic approaches focus on the gradient middle ground. Probabilistic linguistics integrates all the progress made by linguistics thus far with a probabilistic perspective. This book presents a comprehensive introduction to probabilistic approaches to linguistic inquiry. It covers the application of probabilistic techniques to phonology, morphology, semantics, syntax, language acquisition, psycholinguistics, historical linguistics, and sociolinguistics. It also includes a tutorial on elementary probability theory and probabilistic grammars.
Book Synopsis Markov Processes for Stochastic Modeling by : Oliver Ibe
Download or read book Markov Processes for Stochastic Modeling written by Oliver Ibe and published by Newnes. This book was released on 2013-05-22 with total page 515 pages. Available in PDF, EPUB and Kindle. Book excerpt: Markov processes are processes that have limited memory. In particular, their dependence on the past is only through the previous state. They are used to model the behavior of many systems including communications systems, transportation networks, image segmentation and analysis, biological systems and DNA sequence analysis, random atomic motion and diffusion in physics, social mobility, population studies, epidemiology, animal and insect migration, queueing systems, resource management, dams, financial engineering, actuarial science, and decision systems. Covering a wide range of areas of application of Markov processes, this second edition is revised to highlight the most important aspects as well as the most recent trends and applications of Markov processes. The author spent over 16 years in the industry before returning to academia, and he has applied many of the principles covered in this book in multiple research projects. Therefore, this is an applications-oriented book that also includes enough theory to provide a solid ground in the subject for the reader. - Presents both the theory and applications of the different aspects of Markov processes - Includes numerous solved examples as well as detailed diagrams that make it easier to understand the principle being presented - Discusses different applications of hidden Markov models, such as DNA sequence analysis and speech analysis.
Download or read book Management of Data written by and published by Allied Publishers. This book was released on 2010 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis The Handbook of Brain Theory and Neural Networks by : Michael A. Arbib
Download or read book The Handbook of Brain Theory and Neural Networks written by Michael A. Arbib and published by MIT Press. This book was released on 2003 with total page 1328 pages. Available in PDF, EPUB and Kindle. Book excerpt: This second edition presents the enormous progress made in recent years in the many subfields related to the two great questions : how does the brain work? and, How can we build intelligent machines? This second edition greatly increases the coverage of models of fundamental neurobiology, cognitive neuroscience, and neural network approaches to language. (Midwest).
Book Synopsis Inference in Hidden Markov Models by : Olivier Cappé
Download or read book Inference in Hidden Markov Models written by Olivier Cappé and published by Springer Science & Business Media. This book was released on 2006-04-12 with total page 656 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a comprehensive treatment of inference for hidden Markov models, including both algorithms and statistical theory. Topics range from filtering and smoothing of the hidden Markov chain to parameter estimation, Bayesian methods and estimation of the number of states. In a unified way the book covers both models with finite state spaces and models with continuous state spaces (also called state-space models) requiring approximate simulation-based algorithms that are also described in detail. Many examples illustrate the algorithms and theory. This book builds on recent developments to present a self-contained view.
Book Synopsis Directions in Corpus Linguistics by : Jan Svartvik
Download or read book Directions in Corpus Linguistics written by Jan Svartvik and published by Walter de Gruyter. This book was released on 2011-06-01 with total page 501 pages. Available in PDF, EPUB and Kindle. Book excerpt: TRENDS IN LINGUISTICS is a series of books that open new perspectives in our understanding of language. The series publishes state-of-the-art work on core areas of linguistics across theoretical frameworks, as well as studies that provide new insights by approaching language from an interdisciplinary perspective. TRENDS IN LINGUISTICS considers itself a forum for cutting-edge research based on solid empirical data on language in its various manifestations, including sign languages. It regards linguistic variation in its synchronic and diachronic dimensions as well as in its social contexts as important sources of insight for a better understanding of the design of linguistic systems and the ecology and evolution of language. TRENDS IN LINGUISTICS publishes monographs and outstanding dissertations as well as edited volumes, which provide the opportunity to address controversial topics from different empirical and theoretical viewpoints. High quality standards are ensured through anonymous reviewing. To discuss your book idea or submit a proposal, please contact Birgit Sievert.
Book Synopsis Hidden Markov Models for Time Series by : Walter Zucchini
Download or read book Hidden Markov Models for Time Series written by Walter Zucchini and published by CRC Press. This book was released on 2017-12-19 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hidden Markov Models for Time Series: An Introduction Using R, Second Edition illustrates the great flexibility of hidden Markov models (HMMs) as general-purpose models for time series data. The book provides a broad understanding of the models and their uses. After presenting the basic model formulation, the book covers estimation, forecasting, decoding, prediction, model selection, and Bayesian inference for HMMs. Through examples and applications, the authors describe how to extend and generalize the basic model so that it can be applied in a rich variety of situations. The book demonstrates how HMMs can be applied to a wide range of types of time series: continuous-valued, circular, multivariate, binary, bounded and unbounded counts, and categorical observations. It also discusses how to employ the freely available computing environment R to carry out the computations. Features Presents an accessible overview of HMMs Explores a variety of applications in ecology, finance, epidemiology, climatology, and sociology Includes numerous theoretical and programming exercises Provides most of the analysed data sets online New to the second edition A total of five chapters on extensions, including HMMs for longitudinal data, hidden semi-Markov models and models with continuous-valued state process New case studies on animal movement, rainfall occurrence and capture-recapture data
Book Synopsis Formal Grammars in Linguistics and Psycholinguistics by : Willem J.M. Levelt
Download or read book Formal Grammars in Linguistics and Psycholinguistics written by Willem J.M. Levelt and published by John Benjamins Publishing. This book was released on 2008-12-19 with total page 594 pages. Available in PDF, EPUB and Kindle. Book excerpt: Almost four decades have passed since Formal Grammars first appeared in 1974. At that time it was still possible to rather comprehensively review for (psycho)linguists the relevant literature on the theory of formal languages and automata, on their applications in linguistic theory and in the psychology of language. That is no longer feasible. In all three areas developments have been substantial, if not breathtaking. Nowadays, an interested linguist or psycholinguist opening any text on formal languages can no longer see the wood for the trees, as it is by no means evident which formal, mathematical tools are really required for natural language applications. An historical perspective can be helpful here. There are paths through the wood that have been beaten since decades; they can still provide useful orientation. The origins of these paths can be traced in the three volumes of Formal Grammars, brought together in the present re-edition. In a newly added postscript the author has sketched what has become, after all these years, of formal grammars in linguistics and psycholinguistics, or at least some of the core developments. This chapter may provide further motivation for the reader to make a trip back to some of the historical sources.
