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Graduate Program

Master of Science in Computational Linguistics

The Computational Linguistics MS program at Rochester trains students to be conversant both in the analysis of language and in 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 MS program will be prepared for both further training at the PhD level in Computer Science and Linguistics and Computational Linguistics positions in industry. A growing number companies such as Google, Amazon.com, Nuance, LexisNexis, Oracle and many others 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.

Coursework

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 further requires a culminating special written project on a topic relevant to the student's interest and in consultation with individual advisors. The degree can typically be completed in three full-time semesters.

Linguistics Courses

Prerequisite

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

    • LIN 110: Introduction to Linguistic Analysis

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

  • 1. Sound structure (LIN 410, 427, 510)
  • 2. Grammatical structure (LIN 420, 460, 461, 462, 520)
  • 3. Meaning (425, 465, 466, 468, 525, 535)

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

Required

At least one of the following:

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

Plus at least two from the following:

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

Computer Science Courses

Prerequisites

Students are required to have completed the following prerequisite courses, or its equivalents, for the MS in Computational Linguistics. 

 

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

Required

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

    • LIN 424: Introduction to Computational Linguistics
    • CS 447: Natural Language Processing
    • CS 448: Statistical Speech and Language Processing

Plus at least two of the following:

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

Program Faculty

Linguistics:

Computer Science: