Probabilistic Models in the Study of Language
by Roger Levy
Publisher: University of California, San Diego 2012
Number of pages: 274
A textbook on the topic of using probabilistic models in scientific work on language ranging from experimental data analysis to corpus work to cognitive modeling. The intended audience is graduate students in linguistics, psychology, cognitive science, and computer science who are interested in using probabilistic models to study language.
Home page url
Download or read it online for free here:
by Shuly Wintner - ESSLLI
This text is a mild introduction to Formal Language Theory for students with little or no background in formal systems. The motivation is Natural Language Processing, and the presentation is geared towards NLP applications, with extensive examples.
by Michael A. Covington - Prentice-Hall
Designed to bridge the gap for those who know Prolog but have no background in linguistics, this book concentrates on turning theories into practical techniques. Coverage includes template and keyword systems, definite clause grammars, and more.
by Doug Arnold, at al. - Blackwell Pub
This introductory book looks at all aspects of Machine Translation: covering questions of what it is like to use a modern Machine Translation system, through questions about how it is done, to questions of evaluating systems, and more.
by Dan Jurafsky, James H. Martin - Stanford University
This text takes an empirical approach to the subject, based on applying statistical and machine-learning algorithms to large corporations. The authors describe a unified vision of speech and language processing. Emphasis is on practical applications.