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The Grammar Processing Program is a set of picture-identification tasks designed to improve language comprehension and processing skills in children who have difficulty processing and/or learning grammatical skills, including those with attention deficit disorders, auditory processing disorders, autism, and cochlear implants. The tasks in Level 1 of the Program are used to pre-teach nouns, pronouns, verbs, adjectives, negative ¿not,¿ prepositions, and conjunctions. The tasks in Level 2 combine the concepts into longer, more complex sentences for concept drilling. The Grammar Processing Program uses Language Webs and the Altered Auditory Input (AAI) technique that are described in the popular, original Processing Programs. The Grammar Processing Program targets seven grammatical areas: Nouns (singular, plural, possessive) Pronouns (subjective, possessive) Verbs (present progressive, third person singular and plural, regular and irregular past tense, future tense) Adjectives (size, color, spotted/striped, comparative, same/different, quantitative) Negative (not) Prepositions (in, on, over, under, beside, above, below, behind, in front of, on top of, off) Conjunctions (and, but, while) 353 pages. Spiral bound, 8½" x 11".
Finite-state devices, such as finite-state automata, graphs, and finite-state transducers, have been present since the emergence of computer science and are extensively used in areas as various as program compilation, hardware modeling, and database management. Although finite-state devices have been known for some time in computational linguistics, more powerful formalisms such as context-free grammars or unification grammars have typically been preferred. Recent mathematical and algorithmic results in the field of finite-state technology have had a great impact on the representation of electronic dictionaries and on natural language processing, resulting in a new technology for language emerging out of both industrial and academic research. This book presents a discussion of fundamental finite-state algorithms, and constitutes an approach from the perspective of natural language processing.
This book offers a highly accessible introduction to natural language processing, the field that supports a variety of language technologies, from predictive text and email filtering to automatic summarization and translation. With it, you'll learn how to write Python programs that work with large collections of unstructured text. You'll access richly annotated datasets using a comprehensive range of linguistic data structures, and you'll understand the main algorithms for analyzing the content and structure of written communication. Packed with examples and exercises, Natural Language Processing with Python will help you: Extract information from unstructured text, either to guess the topic or identify "named entities" Analyze linguistic structure in text, including parsing and semantic analysis Access popular linguistic databases, including WordNet and treebanks Integrate techniques drawn from fields as diverse as linguistics and artificial intelligence This book will help you gain practical skills in natural language processing using the Python programming language and the Natural Language Toolkit (NLTK) open source library. If you're interested in developing web applications, analyzing multilingual news sources, or documenting endangered languages -- or if you're simply curious to have a programmer's perspective on how human language works -- you'll find Natural Language Processing with Python both fascinating and immensely useful.
Part III: Codeswitching and the LF Interface -- 9 The Semantic Interpretation and Syntactic Distribution of Determiner Phrases in Spanish-English Codeswitching -- 10 Codeswitching and the Syntax-Semantics Interface -- Part IV: Codeswitching and Language Processing -- 11 A Minimalist Parsing Model for Codeswitching -- 12 Language Dominance and Codeswitching Asymmetries -- Contributors -- Index