CS 5/662, Winter 2023

Natural Language Processing

Overview

This course covers key algorithms and modeling techniques for processing human language sequences, which are needed for applications such as Automatic Speech Recognition and Machine Translation. Both statistical and symbolic approaches to modeling natural language phonology, morphology, and syntax are presented, along with widely used algorithms for efficiently learning and applying different kinds of natural language grammars. There is an emphasis on algorithms and data structures that scale up to handle very large real-world data sets, such as newswire text. The course includes several challenging hands-on programming assignments. Suggested prerequisite: CSE 560 or equivalent. Python programming experience is highly recommended, as is familiarity with regular expressions.

Textbooks & Resources

Two of the textbooks we will be using are available electronically from the OHSU Library, and both of the others are available in draft form online.

If possible, I do encourage you to buy a copy of at least the Eisenstein book, so as to support the publishing of high-quality NLP texts.

Course goals

By the end of the course, students will:

Logistics

When & Where?

Tuesdays & Thursdays, 15:00 – 16:30, mostly in BICC 124

Starts: January 10

Ends: March 23

Who?

Instructor: Steven Bedrick

Office Location: Gaines Hall, 21

Office Hours: Wednesday and Friday 13:00 – 18:00; By appointment otherwise. Note that I will not necessarily be on campus during those times (in which case I will be available via Webex), so before schlepping all the way to Gaines you’ll want to check in with me.


Page last updated: 2023-12-15 10:25