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Computational Linguistics Courses

The Computational Linguistics MA Program involves coursework from both Computer Science and Linguistics. The following is a list of CL courses offered in the current Fall 2010 term. For full information regarding courses, including descriptions and offerings, please visit the Brandeis Course Bulletin entries for Computer Science and Linguistics.

An introduction to the process of syntactic analysis, to generative syntactic theory, and to many major syntactic phenomena of English and other languages, including the clausal architecture, the lexicon, and various types of syntactic movement. Offered every year.

LING 131a Programming for Linguistics
This is an upper-level course on the computational properties of natural languages and the fundamental algorithms used for processing them. The main objectives of the course are to develop a through understanding of the principles and formal methods used in the design and analysis of language processing algorithms, and to provide an in-depth presentation of these algorithms as they are applied to Lexical, Morphological, Syntactic, and Semantic analysis. Offered every year.

LING 140a Architecture of Conversation: Discourse and Pragmatics
Assuming a theory of sentence-level linguistic competence, what phenomena are still to be accounted for in the explication of language knowledge? The class explores topics in language use in context, including anaphora, deixis, implicature, speech acts, information packaging, and pragmatics of dialogue. Usually offered every year.

LING 160b Mathematical Methods in Linguistics
An introduction to fundamental mathematical concepts needed for advanced work in linguistics and computational linguistics. Topics include: set theory, theory of relations, fundamentals of logic, formal systems, lambda calculus, formal language theory, theory of automata, basics of probability and statistics, game theory, and decision theory. Offered every year.

COSI 112a Modal, Temporal, and Spacial Logic for Language
Examines the formal and computational properties of logical systems that are used in AI and linguistics. This includes (briefly) propositional logic and first order logic, and then an in-depth study of modal logic, temporal logic, spatial logic, and dynamic logic. Throughout the analyses of these systems, focuses on how they are used in the modeling of linguistic data. Usually offered every second year.

COSI 134a Statistical Approaches to Natural Language Processing
An introductory graduate-level course covering fundamental concepts in statistical Natural Language Processing (NLP). Provides an in-depth view of the statistical models and machine-learning methods used in NLP, including methods used in morphological, syntactic, and semantic analysis. Offered every year.

COSI 216a Topics in NLP: Automatic Speech Recognition Systems
This course covers the core components of a speech recognizer and the algorithms that underlie them. Topics include phonetics, Hidden Markov Models, finite state grammars, statistical language models, and industry standards for implementing applications, such as VXML. We will survey real applications to look at where speech works well and where it falls short. Students will work with a variety of toolkits to build and analyze simple applications.