Linguistic Structure In Language Processing
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Speech and Language Processing
This book takes an empirical approach to language processing, based on applying statistical and other machine-learning algorithms to large corpora.Methodology boxes are included in each chapter. Each chapter is built around one or more worked examples to demonstrate the main idea of the chapter. Covers the fundamental algorithms of various fields, whether originally proposed for spoken or written language to demonstrate how the same algorithm can be used for speech recognition and word-sense disambiguation. Emphasis on web and other practical applications. Emphasis on scientific evaluation. Useful as a reference for professionals in any of the areas of speech and language processing.
Linguistic Structure in Language Processing
Author: G.N. Carlson
language: en
Publisher: Springer Science & Business Media
Release Date: 2012-12-06
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.
Linguistic Structure Prediction
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