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.
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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 F. C. N. Pereira, S. M. Shieber - Center for the Study of Language
A concise introduction to logic programming and the logic-programming language Prolog both as vehicles for understanding elementary computational linguistics and as tools for implementing the basic components of natural-language-processing systems.
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.
by Daniël de Kok, Harm Brouwer
We will go into many of the techniques that so-called computational linguists use to analyze the structure of human language, and transform it into a form that computers work with. We chose Haskell as the main programming language for this book.