Sep 28, 2024  
2024-2025 Academic Catalog 
    
2024-2025 Academic Catalog

Computational Linguistics, MS


The MS Computational Linguistics program, jointly offered by the Department of Linguistics and Language Development  and the Department of Computer Science , prepares students with advanced knowledge and skills for Computational Linguistics careers. It features a computing-based curriculum and instructs students in the theory and practice of language, linguistics and applied linguistics, and computer science to prepare students for job careers in automated text analysis, machine translation, grammar checking, speech synthesis & recognition, artificial intelligence, machine learning, web search, information retrieval, big data analytics, and more. The program also prepares students for entry into doctoral programs in a wide variety of interdisciplinary fields such as computational linguistics, natural language processing, computer science, artificial intelligence, information research, media studies, and human-computer interaction. Its integrated coursework provides students with strong computing, analytical, and linguistics skills to understand and solve problems for business and research, with strong societal and cultural implications.

Admission Requirements

Candidates must meet all of the university admission requirements . Students can be admitted in either classified or conditionally classified standing. While the expectation is that (at least at first) most students will enter the MS in Computational Linguistics after finishing the BS Computer Science and Linguistics , some may come from other backgrounds and therefore need prerequisites.

To be admitted to classified standing, applicants must have earned a Bachelor’s degree in linguistics, science, or engineering (e.g., applied math, statistics, computer science, and software engineering) from a regionally accredited institution with a minimum GPA of 3.0 (based on a 4.0 scale), and have completed all program prerequisites listed below. Two to three letters of recommendation are also required. 

To enter this program with classified standing, a student must have passed the following prerequisites courses (with the listed required grades in some cases): 

  • A two-semester series of calculus courses covering integration and partial derivation (e.g. MATH 30  and MATH 31  at SJSU), with a grade of B or better
  • A linear algebra course (e.g., MATH 39  at SJSU), with a grade of B or better
  • A discrete mathematics course (e.g. MATH 42  at SJSU) with a grade of B or better
  • A statistics and probability theory course (e.g., MATH 105  or MATH 161A  at SJSU) 
  • A course on Python programming (e.g. CS 22A  at SJSU)
  • A course on object-oriented programming (e.g. CS 46A  at SJSU)
  • An introductory data structures course (e.g. CS 46B  at SJSU)
  • An introductory linguistics course (e.g. LING 101  at SJSU)
  • A Natural Language Processing or computational linguistics course (e.g. LING 165  at SJSU)

Applicants from countries in which the native language is not English must submit TOEFL scores. Minimum TOEFL scores acceptable for admission are 600 (paper-based), 250 (computer-based), or 100 (internet-based).

Advancement to Candidacy

The student must obtain a grade of B or better in each of LING 220  and LING 221 , complete at least 15 units towards the degree with at least a 3.0 GPA, and meet all other university requirements, including the Graduation Writing Assessment Requirement (GWAR), before being advanced to candidacy. 

Students must maintain an overall grade point average (GPA) of 3.0 at all times, otherwise they will be placed on academic notice and required to raise the overall GPA above the 3.0 minimum during the subsequent semester (failing to do so will result in disqualification from the program). 

Graduation Requirements

University Graduation Requirements

Students must complete all residency, curriculum, unit, GPA, and culminating experience requirements as outlined in the Graduation Requirements  section of the Graduate Policies and Procedures .

Graduation Writing Assessment Requirement

At SJSU, students must pass the Graduation Writing Assessment Requirement (GWAR) .This requirement is satisfied by taking CS 200W  or LLD 250W  in the MS Computational Linguistics program.

Culminating Experience

MS Computational Linguistics students must complete one of the following two options: 

  • Plan A (Linguistics-focused project):LING 298  and/or LING 299  (2 semesters)
  • Plan B (Natural Language Processing-focused project): CS 297  and CS 298  or CS 299  

Both plans require two semesters of enrollment in 6-unit coursework in order to conduct the proposed project or thesis study. The student is responsible for securing the commitment of a full-time tenured or tenure-track faculty member in either Department of Linguistics and Language Development or Department of Computer Science who agrees to serve as their primary advisor. The student must also secure the commitments of two additional members, one of whom must be a full-time tenured or tenure-track faculty member at SJSU. Either plan requires writing a manuscript in a formal format describing original computational linguistics research, which is submitted for review by the student’s committee. In addition, the student must successfully pass a comprehensive oral examination, according to the standard assessment used in the home department of the primary advisor, by the student’s committee based on the conducted project or thesis study.

Master’s Requirements (30 units)


Graduation Writing Assessment Requirement


Complete one course:

Culminating Experience (6 units)


Complete one option (Plan A or Plan B)

Plan A (Linguistics-focused project)


Plan B (Natural Language Processing-focused project)


Total Units Required (30 units)


The maximum number of upper-division undergraduate units that can be applied toward the master’s degree is 15.

Upon completion of the degree requirements, the student must have achieved minimum candidacy and SJSU Cumulative grade point averages of 3.0 in order to graduate.