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

The papers in this volume are intended to exemplify the state of experimental psycho linguistics in the middle to later 1980s. Our over riding impression is that the field has come a long way since the earlier work of the 1950s and 1960s, and that the field has emerged with a renewed strength from a difficult period in the 1970s. Not only are the theoretical issues more sharply defined and integrated with existing issues from other domains ("modularity" being one such example), but the experimental techniques employed are much more sophisticated, thanks to the work of numerous psychologists not necessarily interested in psycholinguistics, and thanks to improving technologies unavailable a few years ago (for instance, eye-trackers). We selected papers that provide a coherent, overall picture of existing techniques and issues. The volume is organized much as one might organize an introductory linguistics course - beginning with sound and working "up" to mean ing. Indeed, the first paper, Rebecca Treiman's, begins with considera tion of syllable structure, a phonological consideration, and the last, Alan Garnham's, exemplifies some work on the interpretation of pro nouns, a semantic matter. In between are found works concentrating on morphemes, lexical structures, and syntax. The cross-section represented in this volume is by necessity incom plete, since we focus only on experimental work directed at under standing how adults comprehend and produce language. We do not include any works on language acquisition, first or second.

Many NLP tasks have at their core a subtask of extracting the dependencies—who did what to whom—from natural language sentences. This task can be understood as the inverse of the problem solved in different ways by diverse human languages, namely, how to indicate the relationship between different parts of a sentence. Understanding how languages solve the problem can be extremely useful in both feature design and error analysis in the application of machine learning to NLP. Likewise, understanding cross-linguistic variation can be important for the design of MT systems and other multilingual applications. The purpose of this book is to present in a succinct and accessible fashion information about the morphological and syntactic structure of human languages that can be useful in creating more linguistically sophisticated, more language-independent, and thus more successful NLP systems. Table of Contents: Acknowledgments / Introduction/motivation / Morphology: Introduction / Morphophonology / Morphosyntax / Syntax: Introduction / Parts of speech / Heads, arguments, and adjuncts / Argument types and grammatical functions / Mismatches between syntactic position and semantic roles / Resources / Bibliography / Author's Biography / General Index / Index of Languages

Meaning is a fundamental concept in Natural Language Processing (NLP), in the tasks of both Natural Language Understanding (NLU) and Natural Language Generation (NLG). This is because the aims of these fields are to build systems that understand what people mean when they speak or write, and that can produce linguistic strings that successfully express to people the intended content. In order for NLP to scale beyond partial, task-specific solutions, researchers in these fields must be informed by what is known about how humans use language to express and understand communicative intents. The purpose of this book is to present a selection of useful information about semantics and pragmatics, as understood in linguistics, in a way that's accessible to and useful for NLP practitioners with minimal (or even no) prior training in linguistics.

A work that reveals the profound links between the evolution, acquisition, and processing of language, and proposes a new integrative framework for the language sciences. Language is a hallmark of the human species; the flexibility and unbounded expressivity of our linguistic abilities is unique in the biological world. In this book, Morten Christiansen and Nick Chater argue that to understand this astonishing phenomenon, we must consider how language is created: moment by moment, in the generation and understanding of individual utterances; year by year, as new language learners acquire language skills; and generation by generation, as languages change, split, and fuse through the processes of cultural evolution. Christiansen and Chater propose a revolutionary new framework for understanding the evolution, acquisition, and processing of language, offering an integrated theory of how language creation is intertwined across these multiple timescales. Christiansen and Chater argue that mainstream generative approaches to language do not provide compelling accounts of language evolution, acquisition, and processing. Their own account draws on important developments from across the language sciences, including statistical natural language processing, learnability theory, computational modeling, and psycholinguistic experiments with children and adults. Christiansen and Chater also consider some of the major implications of their theoretical approach for our understanding of how language works, offering alternative accounts of specific aspects of language, including the structure of the vocabulary, the importance of experience in language processing, and the nature of recursive linguistic structure.

No detailed description available for "Syntactic Structures".