Introduction to Computational Linguistics
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Introduction to computational linguistics (also known as natural-language processing) including the related mathematics and several programming projects. Particular topics include: language modeling (as used in e.g., speech recognition, machine translation), machine translation, part-of-speech labeling, syntactic parsing, and pronoun resolution. Mathematical techniques include basic probability, noisy channel models, the EM (Expectation-Maximization) algorithm, hidden Markov models, probabilistic context-free grammars, and the forward-backward algorithm.
Prerequisites are CSCI1410 or permission of instructor. Permission will be given to all students with a solid background in programming (which programming language is secondary) and either basic probability, or enough mathematical background to quickly absorb the latter.