Simon Fraser University
Engaging the World

Course Outlines

Fall 2022 - LING 450 D100

Computational Linguistics (3)

Class Number: 3609

Delivery Method: In Person

Overview

  • Course Times + Location:

    Sep 7 – Dec 6, 2022: Fri, 9:30 a.m.–12:20 p.m.
    Burnaby

  • Prerequisites:

    LING 250 or SDA 250.

Description

CALENDAR DESCRIPTION:

Introduction to theoretical and applied issues in the computational processing of natural language.

COURSE DETAILS:

This course is an introduction to theoretical and applied issues in computational linguistics. Computational Linguistics (or Natural Language Processing) refers to the processing of human languages through computers, which is mostly an applied venture. It also covers theoretical aspects, such as the computational modeling of language processing phenomena, and it overlaps with research in psychology and neurolinguistics.

In this course, we will survey the field and study a few specific applications. Classes will consist of lectures, drawing on material from the main textbooks, but also from other sources (to be distributed throughout the semester). In each class, there will also be a practical part, where we will test and implement algorithms in the Natural Language Processing Tool Kit, and will experiment with existing natural language processing systems.

MODE OF INSTRUCTION: In person

MODE OF DELIVERY: In person

PLATFORMS USED: Canvas

TECHNOLOGY REQUIRED: Computer for checking Canvas and doing class assignments and projects. Computer capable of running python and where new software can be installed.

Grading

  • Attendance and participation 20%
  • Assignments 40%
  • Project 20%
  • Term paper 20%
  • No Final Exam

NOTES:

Students requiring accommodations as a result of a disability must contact the Centre for Accessible Learning (caladmin@sfu.ca).

Materials

REQUIRED READING:

Bird, S., E. Klein and E. Loper (2009) Natural Language Processing with Python, O’Reilly Media. Related web page, and full online book: http://www.nltk.org/book

Eisenstein, Jacob (2019) Natural Language Processing. Cambridge, MA: MIT Press (forthcoming). Current draft: https://github.com/jacobeisenstein/gt-nlp-class/tree/master/notes

Jurafsky, Dan and James H. Martin (2019/2021) Speech and Language Processing. Current draft: https://web.stanford.edu/~jurafsky/slp3/

REQUIRED READING NOTES:

Your personalized Course Material list, including digital and physical textbooks, are available through the SFU Bookstore website by simply entering your Computing ID at: shop.sfu.ca/course-materials/my-personalized-course-materials.

Department Undergraduate Notes:

Students should familiarize themselves with the Department's Standards on Class Management and Student Responsibilities.

Please note that a grade of “FD” (Failed-Dishonesty) may be assigned as a penalty for academic dishonesty.

All student requests for accommodations for their religious practices must be made in writing by the end of the first week of classes or no later than one week after a student adds a course.

Registrar Notes:

ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS

SFU’s Academic Integrity website http://www.sfu.ca/students/academicintegrity.html is filled with information on what is meant by academic dishonesty, where you can find resources to help with your studies and the consequences of cheating. Check out the site for more information and videos that help explain the issues in plain English.

Each student is responsible for his or her conduct as it affects the university community. Academic dishonesty, in whatever form, is ultimately destructive of the values of the university. Furthermore, it is unfair and discouraging to the majority of students who pursue their studies honestly. Scholarly integrity is required of all members of the university. http://www.sfu.ca/policies/gazette/student/s10-01.html