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Bayesian Natural Language Semantics And Pragmatics
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Book Synopsis Bayesian Natural Language Semantics and Pragmatics by : Henk Zeevat
Download or read book Bayesian Natural Language Semantics and Pragmatics written by Henk Zeevat and published by Springer. This book was released on 2015-06-19 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Bayesian Analysis in Natural Language Processing, Second Edition by : Shay Cohen
Download or read book Bayesian Analysis in Natural Language Processing, Second Edition written by Shay Cohen and published by Springer Nature. This book was released on 2022-05-31 with total page 311 pages. Available in PDF, EPUB and Kindle. Book excerpt: Natural language processing (NLP) went through a profound transformation in the mid-1980s when it shifted to make heavy use of corpora and data-driven techniques to analyze language. Since then, the use of statistical techniques in NLP has evolved in several ways. One such example of evolution took place in the late 1990s or early 2000s, when full-fledged Bayesian machinery was introduced to NLP. This Bayesian approach to NLP has come to accommodate various shortcomings in the frequentist approach and to enrich it, especially in the unsupervised setting, where statistical learning is done without target prediction examples. In this book, we cover the methods and algorithms that are needed to fluently read Bayesian learning papers in NLP and to do research in the area. These methods and algorithms are partially borrowed from both machine learning and statistics and are partially developed "in-house" in NLP. We cover inference techniques such as Markov chain Monte Carlo sampling and variational inference, Bayesian estimation, and nonparametric modeling. In response to rapid changes in the field, this second edition of the book includes a new chapter on representation learning and neural networks in the Bayesian context. We also cover fundamental concepts in Bayesian statistics such as prior distributions, conjugacy, and generative modeling. Finally, we review some of the fundamental modeling techniques in NLP, such as grammar modeling, neural networks and representation learning, and their use with Bayesian analysis.
Book Synopsis Language Production and Interpretation: Linguistics meets Cognition by : Henk Zeevat
Download or read book Language Production and Interpretation: Linguistics meets Cognition written by Henk Zeevat and published by BRILL. This book was released on 2014-01-30 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: An utterance is normally produced by a speaker in linear time and the hearer normally correctly identifies the speaker intention in linear time and incrementally. This is hard to understand in a standard competence grammar since languages are highly ambiguous and context-free parsing is not linear. Deterministic utterance generation from intention and n-best Bayesian interpretation, based on the production grammar and the prior probabilities that need to be assumed for other perception do much better. The proposed model uses symbolic grammar and derives symbolic semantic representations, but treats interpretation as just another form of perception. Removing interpretation from grammar is not only empirically motivated, but also makes linguistics a much more feasible enterprise. The importance of Henk Zeevat's new monograph cannot be overstated. Its combination of breadth, formal rigor, and originality is unparalleled in work on the form-meaning interface in human language...Zeevat's is the first proposal which provides a computationally feasible integrated treatment of production and comprehension for pragmatics, semantics, syntax, and even phonology. I recommend it to anyone who combines interests in language, logic, and computation with a sense of adventure. David Beaver, University of Texas at Austin
Book Synopsis Bayesian Analysis in Natural Language Processing by : Shay Cohen
Download or read book Bayesian Analysis in Natural Language Processing written by Shay Cohen and published by Morgan & Claypool Publishers. This book was released on 2016-06-01 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: Natural language processing (NLP) went through a profound transformation in the mid-1980s when it shifted to make heavy use of corpora and data-driven techniques to analyze language. Since then, the use of statistical techniques in NLP has evolved in several ways. One such example of evolution took place in the late 1990s or early 2000s, when full-fledged Bayesian machinery was introduced to NLP. This Bayesian approach to NLP has come to accommodate for various shortcomings in the frequentist approach and to enrich it, especially in the unsupervised setting, where statistical learning is done without target prediction examples. We cover the methods and algorithms that are needed to fluently read Bayesian learning papers in NLP and to do research in the area. These methods and algorithms are partially borrowed from both machine learning and statistics and are partially developed "in-house" in NLP. We cover inference techniques such as Markov chain Monte Carlo sampling and variational inference, Bayesian estimation, and nonparametric modeling. We also cover fundamental concepts in Bayesian statistics such as prior distributions, conjugacy, and generative modeling. Finally, we cover some of the fundamental modeling techniques in NLP, such as grammar modeling and their use with Bayesian analysis.
Book Synopsis Bayesian Analysis in Natural Language Processing by : Shay Cohen
Download or read book Bayesian Analysis in Natural Language Processing written by Shay Cohen and published by Morgan & Claypool Publishers. This book was released on 2019-04-09 with total page 345 pages. Available in PDF, EPUB and Kindle. Book excerpt: Natural language processing (NLP) went through a profound transformation in the mid-1980s when it shifted to make heavy use of corpora and data-driven techniques to analyze language. Since then, the use of statistical techniques in NLP has evolved in several ways. One such example of evolution took place in the late 1990s or early 2000s, when full-fledged Bayesian machinery was introduced to NLP. This Bayesian approach to NLP has come to accommodate various shortcomings in the frequentist approach and to enrich it, especially in the unsupervised setting, where statistical learning is done without target prediction examples. In this book, we cover the methods and algorithms that are needed to fluently read Bayesian learning papers in NLP and to do research in the area. These methods and algorithms are partially borrowed from both machine learning and statistics and are partially developed "in-house" in NLP. We cover inference techniques such as Markov chain Monte Carlo sampling and variational inference, Bayesian estimation, and nonparametric modeling. In response to rapid changes in the field, this second edition of the book includes a new chapter on representation learning and neural networks in the Bayesian context. We also cover fundamental concepts in Bayesian statistics such as prior distributions, conjugacy, and generative modeling. Finally, we review some of the fundamental modeling techniques in NLP, such as grammar modeling, neural networks and representation learning, and their use with Bayesian analysis.
Book Synopsis Probabilistic Models of Pragmatics for Natural Language by : Reuben Harry Cohn-Gordon
Download or read book Probabilistic Models of Pragmatics for Natural Language written by Reuben Harry Cohn-Gordon and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Grice (1975) puts forward a view of linguistic meaning in which conversational agents enrich the semantic interpretation of linguistic expressions by recourse to pragmatic reasoning about their interlocutors and world knowledge. As a simple example, on hearing my friend tell me that she read some of War and Peace, I reason that, had she read all of it, she would have said as much, and accordingly that she read only part. It turns out that this perspective is well suited to a probabilistic formalization. In these terms, linguistic meaning is fully characterized by a joint probability distribution P(W; U) between states of the world W and linguistic expressions U. The Gricean perspective described above corresponds to a factoring of this enormously complex distribution into a semantics [[u]](w) : U -> (W -> {0, 1}, world knowledge P(W) and a pair of agents which reason about each other on the assumption that both are cooperative and have access to a commonly known semantics. This third component, of back and forth reasoning between agents, originates in work in game-theory (Franke, 2009; Lewis, 1969) and has been formalized in probabilistic terms by a class of models often collectively referred to as the Rational Speech Acts (RSA) framework (Frank and Goodman, 2012). By allowing for the construction of models which explain in precise terms how Gricean pressures like informativity and relevance interact with a semantics, this framework allows us to take an intuitive theory and explore its predictions beyond the limits of intuition. But it should be more than a theoretical tool. To the extent that its characterization of meaning is correct, it should allow for the construction of computational systems capable of reproducing the dynamics of opendomain natural language. For instance, on the assumption that humans produce language pragmatically, one would expect systems which generate natural language to most faithfully reproduce human behavior when aiming to be not only truthful, but also informative to a hypothetical interlocutor. Likewise, systems which interpret language in a human-like way should perform best when they model language as being generated by an informative speaker. Despite this, standard approaches to many natural language processing (NLP) tasks, like image captioning (Farhadi et al., 2010; Vinyals et al., 2015), translation (Brown et al., 1990; Bahdanau et al., 2014) and metaphor interpretation (Shutova et al., 2013), only incorporate pragmatic reasoning implicitly (in the sense that a supervised model trained on human data may learn to replicate pragmatic behavior). The approach of this dissertation is to take models which capture dynamics of pragmatic language use and apply them to open-domain settings. In this respect, my work builds on research in this vein for referential expression generation (Monroe and Potts, 2015; Andreas and Klein, 2016a), image captioning (Vedantam et al., 2017) and instruction following (Fried et al., 2017), as well as work using neural networks as generative models in Bayesian cognitive architectures (Wu et al., 2015; Liu et al., 2018). The content of the dissertation divides into two parts. The first (chapter 2) focuses on the interpretation of language (particularly non-literal language) using a model of non-literal language previously applied to hyperbole and metaphor interpretation in a setting with a hand-specified and idealized semantics. Here, the goal is to instantiate the same model, but with a semantics derived from a vector space model of word meaning. In this setting, the model remains unchanged, but states are points in an abstract word embedding space - a central computational linguistic representation of meaning (Mikolov et al., 2013; Pennington et al., 2014). The core idea here is that points in the space can be viewed as a continuous analogue of possible worlds, and that linear projections of a vector space are a natural way to represent the aspect of the world that is relevant in a conversation. The second part of the dissertation (chapters 3 and 4) focuses on the production of language, in settings where the length of utterances (and consequently the set of all possible utterances) is unbounded. The core idea here is that pragmatic reasoning can take place incrementally, that is, midway through the saying or hearing of an utterance. This incremental approach is applied to neural language generation tasks, producing informative image captions and translations. The result of these investigations is far from a complete picture, but nevertheless a substantial step towards Bayesian models of semantics and pragmatics which can handle the full richness of natural language, and by doing so provide both explanatory models of meaning and computational systems for producing and interpreting language.
Book Synopsis The Philosophy of Theoretical Linguistics by : Ryan M. Nefdt
Download or read book The Philosophy of Theoretical Linguistics written by Ryan M. Nefdt and published by Cambridge University Press. This book was released on 2024-05-02 with total page 245 pages. Available in PDF, EPUB and Kindle. Book excerpt: What is the remit of theoretical linguistics? How are human languages different from animal calls or artificial languages? What philosophical insights about language can be gleaned from phonology, pragmatics, probabilistic linguistics, and deep learning? This book addresses the current philosophical issues at the heart of theoretical linguistics, which are widely debated not only by linguists, but also philosophers, psychologists, and computer scientists. It delves into hitherto uncharted territory, putting philosophy in direct conversation with phonology, sign language studies, supersemantics, computational linguistics, and language evolution. A range of theoretical positions are covered, from optimality theory and autosegmental phonology to generative syntax, dynamic semantics, and natural language processing with deep learning techniques. By both unwinding the complexities of natural language and delving into the nature of the science that studies it, this book ultimately improves our tools of discovery aimed at one of the most essential features of our humanity, our language.
Book Synopsis Bayesian Speech and Language Processing by : Shinji Watanabe
Download or read book Bayesian Speech and Language Processing written by Shinji Watanabe and published by Cambridge University Press. This book was released on 2015-07-15 with total page 447 pages. Available in PDF, EPUB and Kindle. Book excerpt: A practical and comprehensive guide on how to apply Bayesian machine learning techniques to solve speech and language processing problems.
Book Synopsis Rational Approaches in Language Science by : Matthew W. Crocker
Download or read book Rational Approaches in Language Science written by Matthew W. Crocker and published by Frontiers Media SA. This book was released on 2022-03-25 with total page 514 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis The Oxford Handbook of Reference by : Jeanette Gundel
Download or read book The Oxford Handbook of Reference written by Jeanette Gundel and published by Oxford University Press. This book was released on 2019-02-07 with total page 640 pages. Available in PDF, EPUB and Kindle. Book excerpt: This handbook presents an overview of the phenomenon of reference - the ability to refer to and pick out entities - which is an essential part of human language and cognition. In the volume's 21 chapters, international experts in the field offer a critical account of all aspects of reference from a range of theoretical perspectives. Chapters in the first part of the book are concerned with basic questions related to different types of referring expression and their interpretation. They address questions about the role of the speaker - including speaker intentions - and of the addressee, as well as the role played by the semantics of the linguistic forms themselves in establishing reference. This part also explores the nature of such concepts as definite and indefinite reference and specificity, and the conditions under which reference may fail. The second part of the volume looks at implications and applications, with chapters covering such topics as the acquisition of reference by children, the processing of reference both in the human brain and by machines. The volume will be of interest to linguists in a wide range of subfields, including semantics, pragmatics, computational linguistics, and psycho- and neurolinguistics, as well as scholars in related fields such as philosophy and computer science.
Book Synopsis Bounded Meaning by : Matthew Mandelkern
Download or read book Bounded Meaning written by Matthew Mandelkern and published by Oxford University Press. This book was released on 2024-08-20 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bounded Meaning investigates the dynamics of interpretation: how and why the interpretation of the building blocks of human language is sensitive, not just to the context in which the expression is used, but also to the expression's linguistic environment—in other words, how and why interpretation depends not just on global information, but also on local information. Matthew Mandelkern motivates a range of generalizations about the dynamics of interpretation, some known and some novel, involving modals, conditionals, and anaphora, and an overview of the best extant theory of those patterns, dynamic semantics, is provided. After bringing out the striking motivations and successes of that framework, the discussion turns to criticisms of dynamic semantics, focusing on its puzzling predictions about the logic of natural language. In response to these problems, Mandelkern develops a novel framework for explaining dynamic phenomena without dynamic semantics: the bounded theory of meaning. On the bounded theory, dynamic phenomena arise from the interaction of two dimensions of meaning. One dimension is a standard truth-conditional layer, which, relative to a context of use, associates each sentence with a proposition. The second dimension, the dimension of bounds, limits the admissible interpretations of an expression, relative to the expression's context of use and its local information. Bounds thus play an essential role in coordinating on the resolution of context-sensitive language, explaining dynamic effects in natural language while avoiding a variety of problematic predictions of dynamic semantics.
Book Synopsis Achievements, durativity and scales by : Zsofia Gyarmathy
Download or read book Achievements, durativity and scales written by Zsofia Gyarmathy and published by Logos Verlag Berlin GmbH. This book was released on 2015-09-30 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contributes to the growing work on scale-based formal semantic approaches to verbal phenomena. It presents a new scale-based framework for both aspectual classes and grammatical aspect with the aim of offering an analysis of achievements in the progressive. In order to analyse these, the temporal trace function is relativised to a granularity parameter, and the semantics of the progressive operator is assumed to involve partitivity over scales of change. To this end, a novel concept of a scale of change is adopted, building on a bottom-up idea of associating scales with events and characterising verbal predicates via event-level scales. As a crucial departure from former scale-based approaches, predicates like "arrive" are associated with both two-valued and multi-valued scales of change. The new framework can then capture fine-grained aspectual class differences and predict the interpretations of the progressive for different aspectual classes.
Book Synopsis Scalar Implicatures by : Penka Stateva
Download or read book Scalar Implicatures written by Penka Stateva and published by Frontiers Media SA. This book was released on 2019-10-18 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: Scalar implicatures have enjoyed the status of one of the most researched topics in both theoretical and experimental pragmatics in recent years. This Research Topic presents new developments in studying the comprehension, as well as the production of scalar inferences, suggests new testing paradigms that trigger important discussions about the methodology of experimental investigation, explores the effect of prosody and context on inference rates. To a great extent the articles reflect the state of the art in the domain and outline promising paths for future research.
Book Synopsis The Oxford Handbook of Pragmatics by : Yan Huang
Download or read book The Oxford Handbook of Pragmatics written by Yan Huang and published by Oxford University Press. This book was released on 2017-01-19 with total page 800 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume brings together distinguished scholars from all over the world to present an authoritative, thorough, and yet accessible state-of-the-art survey of current issues in pragmatics. Following an introduction by the editor, the volume is divided into five thematic parts. Chapters in Part I are concerned with schools of thought, foundations, and theories, while Part II deals with central topics in pragmatics, including implicature, presupposition, speech acts, deixis, reference, and context. In Part III, the focus is on cognitively-oriented pragmatics, covering topics such as computational, experimental, and neuropragmatics. Part IV takes a look at socially and culturally-oriented pragmatics such as politeness/impoliteness studies, cross- and intercultural, and interlanguage pragmatics. Finally, the chapters in Part V explore the interfaces of pragmatics with semantics, grammar, morphology, the lexicon, prosody, language change, and information structure. The Oxford Handbook of Pragmatics will be an indispensable reference for scholars and students of pragmatics of all theoretical stripes. It will also be a valuable resource for linguists in other fields, including philosophy of language, semantics, morphosyntax, prosody, psycholinguistics, and sociolinguistics, and for researchers and students in the fields of cognitive science, artificial intelligence, computer science, anthropology, and sociology.
Book Synopsis Measurements, Numerals and Scales by : Nicole Gotzner
Download or read book Measurements, Numerals and Scales written by Nicole Gotzner and published by Springer Nature. This book was released on 2022-02-07 with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book brings together chapters on the semantics and pragmatics of measurement, scales, and numerical expressions. The chapters highlight recent developments in measurement theory, the meaning of numerical expressions and the relation between measurement scales and entailment scales. The authors provide explorations in formal and experimental semantics and pragmatics, as well as at the interfaces of this field with others including philosophy of language and sociolinguistics. This book will be of interest to students and scholars in these areas, as well as psychology, psycholinguistics and artificial intelligence.
Book Synopsis New Frontiers in Artificial Intelligence by : Kazuhiro Kojima
Download or read book New Frontiers in Artificial Intelligence written by Kazuhiro Kojima and published by Springer Nature. This book was released on 2019-10-10 with total page 494 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes extended, revised, and selected papers from the 10th International Symposium of Artificial Intelligence supported by the Japanese Society for Artificial Intelligence, JSAI-isAI 2018. It was held in November 2018 in Yokohama, Japan. The 28 paper full papers and 5 short papers were carefully selected from 97 submissions. The papers selected cover topics in Artificial Intelligence, such as AI and law, business intelligence, human intelligence, logic and engineering, and data analytics and applications.
Book Synopsis Experimental Perspectives on Presuppositions by : Florian Schwarz
Download or read book Experimental Perspectives on Presuppositions written by Florian Schwarz and published by Springer. This book was released on 2014-09-12 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume brings together some of the most recent developments in the field of experimental pragmatics, specifically empirical approaches to theoretical issues in presupposition theory. It includes studies of the online processing of presupposed content; investigations of the interpretive properties of presuppositions in various linguistic contexts; comparative perspectives relative to other aspects of meaning, such as asserted content and implicatures; cross-linguistic comparisons of presupposition triggers; and perspectives from language acquisition. Taken together, these novel contributions provide a snapshot of state-of-the art developments in this area and will serve as a point of reference for numerous emerging avenues of future work. It makes for an ideal set of readings for advanced university courses on experimental studies of meaning and is a must-read for anyone interested in experimental research on meaning in natural language.
