Linguistics Department

Computational Linguistics

The Computational Linguistics concentration area educates the student in the theory, technologies and applications of Computational Linguistics and Natural Language Processing (NLP).  Computational Linguistics is an interdisciplinary field addressing human languages by applying methods of both Linguistics and Computer Science.  One can distinguish two major subdisciplines:

  1. Research in Computational Linguistics addresses the computational properties of linguistic models of natural language and develops algorithms and computational implementations of such linguistic models;
  2. Research in NLP emphasizes the goal of developing systems that can deal effectively with natural language data in an application context.

The Computational Linguistics concentration area at the UT Linguistics department is structured as follows. In their first year, graduate students interested in computational linguistics usually take the required courses related to syntax and semantics (some students opt to take Semantics I in their second year).

Research in Computational Linguistics is taken in both semesters of the first year, and all subsequent years.

  • LIN 380M: Semantics I.
  • LIN 380L: Syntax I.
  • LIN 389C, Research in Computational Linguistics

Beginning in their second year, students interested in continuing in computational linguistics choose courses from the following:

  • Natural Language Processing (Ray Mooney, Computer Science)
  • Applied Natural Language Processing (Jason Baldridge)
  • Concepts of Information Retrieval (Matt Lease, ISchool)
  • Courses offered by the Department of Statistics and Data Sciences
  • Machine Learning (Computer Science)

Advanced courses and seminars in computational linguistics are offered as LIN 386/LIN 392. They are typically taught in the spring semester. Past topics have included:

  • Computational semantics
  • Grounded models of meaning
  • Applied text analysis
  • Data-Intensive Computing for Text Analysis
  • Semisupervised Learning for Computational Linguistics
  • Natural language learning

Students in computational linguistics are also expected to participate in the cross-departmental biweekly reading group “NLL” (Natural Language Learning). Students are asked to contact computational linguistics faculty to get on the mailing list.

Depending on the student's focus, advanced courses from other concentration areas in Linguistics will tie in very well with the Computational Linguistics concentration area.  For example, a student focusing on computational syntax and semantics will benefit greatly from advanced syntax courses such as Lexical-Functional Grammar, or Head-driven Phrase Structure Grammar.

In general, students in computational linguistics are greatly encouraged to take courses in the UT Computer Science department, the iSchool, and the Department of Statistics and Data Sciences.

For more information on the UT Computational Linguistics concentration, including research focus and a list of computational linguistics faculty across UT departments, please see the computational linguistics web page.