Master of Science in Computational Linguistics

The computational linguistics master's program at Rochester trains students to be conversant both in language analysis and computational techniques applied to natural language. The curriculum consists of courses in linguistics and computer science for a total of 32 credit hours.

Graduates from the computational linguistics program will be prepared for both further training at the PhD level in computer science and linguistics, as well as industry positions. A number companies such as Google, Amazon, Nuance, LexisNexis, and Oracle are searching for employees with advanced degrees in computational linguistics for positions ranging from speech recognition technology to improving translation systems to developing better models of language understanding.


The curriculum consists of courses in linguistics and computer science, in roughly a 50/50 mix, for a total of 32 credit hours. Four courses (16 credits) are required in linguistics and four courses (16 credits) in computer science. The degree also requires a culminating special written project on a topic relevant to the student's interest and in consultation with individual advisors.

This program’s coursework can typically be completed in three full-time semesters. A fourth semester is for students to prepare their program’s final assignment, project, or thesis.

Linguistics Courses


Students are required to have completed the following prerequisite course, or its equivalent.

  • LING 110: Introduction to Linguistic Analysis
Track Courses

Within linguistics, students will work with an advisor to create a “track” for their coursework in one of three areas:

  • Sound structure (LING 410, 427, 510)
  • Grammatical structure (LING 420, 460, 461, 462, 520)
  • Meaning (LING 425, 465, 466, 468, 525, 535)

Students will be encouraged to take LING 450 and LING 501 as it suits their programs.


At least one of the following:

  • LING 410: Introduction to Language Sound Systems
  • LING 420: Introduction to Grammatical Systems
  • LING 425: Introduction to Semantic Analysis

Plus at least two from the following:

  • LING 427: Topics in Phonetics and Phonology
  • LING 450: Data Science for Linguistics
  • LING 460: Syntactic Theory
  • LING 461: Phrase Structure Grammar
  • LING 462: Topics in Experimental Syntax
  • LING 465: Formal Semantics
  • LING 466: Pragmatics
  • LING 468: Computational Semantics
  • LING 481: Statistical and Neural Computational Linguistics
  • LING 501: Linguistics Graduate Proseminar
  • LING 520: Syntax
  • LING 525: Graduate Semantics
  • LING 527: Topics in Phonetics and Phonology
  • LING 535: Formal Pragmatics

Computer Science Courses


Students are required to have completed the following prerequisite courses, or its equivalents: 

  • CSC 171: The Science of Programming
  • CSC 172: The Science of Data Structures
  • CSC 173: Computation and Formal Systems
  • MATH 150: Discrete Math
  • MATH 165: Linear Algebra with Differential Equations 

Students must take two of the following three courses for the MS in Computational Linguistics.

  • LING 424: Introduction to Computational Linguistics
  • CSC 447: Natural Language Processing
  • CSC 448: Statistical Speech and Language Processing

Plus at least two of the following:

  • CSC 440: Data Mining
  • CSC 442: Artificial Intelligence
  • CSC 444: Logical Foundations of Artificial Intelligence
  • CSC 446: Machine Learning


Program Faculty


Computer science: