LING 224/424 Spring 2026

Introduction to Computational Linguistics

University of Rochester · Department of Linguistics

Overview

Instructor Aaron Steven White
Office 511A Lattimore Hall
Meetings Monday & Wednesday, 12:30 PM - 1:45 PM
Location Lattimore 513
Workshop Friday 9:00 AM - 10:15 AM · Helena Feng
Communication Zulip
Course Notes View notes
Office Hours By appointment

This course covers foundational concepts in computational linguistics. Major focus is placed on the use of formal languages as a tool for understanding natural language as well as on developing students' ability to implement foundational algorithms pertaining to those formal languages. Topics include basic formal language theory, finite state phonological and morphological parsing, and syntactic parsing for context free grammars and mildly context sensitive formalisms.

Prerequisites: LIN110 (Introduction to Linguistic Analysis); CSC161 (Introduction To Programming) or equivalent

Materials

Assessment

Component
Weekly Assignments 80%70%
Participation 20%
Project 30%

Schedule

Week Dates Topic Due
The role of computation in linguistics
Developing the notion of strings and
languages as formal objects
Grammars as languages that describe languages
Grammars as languages that describe languages (continued)
Uncertainty about languages
Uncertainty about languages (continued)
Describing languages in terms of strings
Describing languages in terms of strings (continued)
The relationship between languages
The relationship between languages and their use
The nature of phonological patterns
Recognizing well-formed words
Analyzing well-formed words
No class (spring break)
No class (spring break)
Describing phonological rules
Mapping between rule descriptions
The nature of morphological patterns
Recognizing well-formed words (redux)
Analyzing well-formed words (redux)
Predicting upcoming morphemes in a word
Word and sentence analysis as deduction
The nature of syntactic patterns
Alternative formalizations of
the notion of a gap
Recognizing well-formed sentences
Recognizing well-formed sentences (continued)
Recognizing well-formed sentences (continued)
Recognizing well-formed sentences (continued)

Policies

Late Work

Homeworks should be submitted before the workshop each week -- i.e. by the start of the recitation (9am on Fridays). Because homeworks are discussed in workshop, no late work will be accepted unless I have given you an extension prior to the deadline. You must ask for an extension at least 48 hours before the deadline, unless you are asking because it is an emergency.

Academic Integrity

All assignments and activities associated with this course must be performed in accordance with the University of Rochester's Academic Honesty Policy. More information is available at: http://www.rochester.edu/college/honesty/

Ai Policy

Accessibility

Any student who needs special accommodations due to a disability should let me know privately, at the start of the semester.

Exceptions

Students will not be penalized because of important civic, ethnic, family or religious obligations, or university service. You will have a chance, whenever feasible, to make up within a reasonable time any assignment that is missed for these reasons. Absences for these reasons will count as excused for the sake of the participation grade. But it is your job to inform me of any expected absences in advance, as soon as possible.

Credit Hour

This course follows the College credit hour policy for four-credit courses, which stipulates that students are expected to complete a 'fourth period' in addition to the course instructional time of two class periods per week. In this course, students will use this 'fourth period' for enriched independent study using readings and other class materials, including those associated with the course project.

References

  1. Chandlee, J. 2017. Computational locality in morphological maps. Morphology 27, 599-641.
  2. Clark, A. 2014. An introduction to multiple context free grammars for linguists.
  3. Gorman, K., & Sproat, R. 2022. Finite-State Text Processing. Morgan & Claypool.
  4. Heinz, J. 2018. The computational nature of phonological generalizations. In Larry Hyman and Frans Plank, editors, Phonological Typology, Phonetics and Phonology, chapter 5, pages 126-195. De Gruyter Mouton.
  5. Hunter, T. to appear. Competence and Performance. In K. Grohmann & E. Leivada (eds.), The Cambridge Handbook of Minimalism.
  6. Kallmeyer, L. 2013. Linear Context-Free Rewriting Systems. Language and Linguistics Compass 7/1: 22-38.
  7. de Marneffe, M.-C. & Potts, C. 2017. Developing Linguistic Theories Using Annotated Corpora. In Handbook of Linguistic Annotation (pp. 411-438). Springer Netherlands.
  8. Oseki, Y. & Marantz, A. 2020. Modeling Human Morphological Competence. Frontiers in Psychology 11.
  9. Piantadosi, S.T. 2014. Zipf's word frequency law in natural language: A critical review and future directions. Psychonomic Bulletin & Review 21, 1112-1130.
  10. Shieber, S., Y. Schabes, & F. Pereira. 1993. Principles and implementation of deductive parsing. The Journal of Logic Programming, 3-36.