Course Description
Computer techniques for processing human languages (e.g., English, Spanish, German), covering applied topics such as text normalization and named entity recognition, as well as theoretical matters, such as the implementation of syntactic and semantic theories.
Additional Requirements for Graduate Students:
The final project for graduate students will involve original research and must include a full, formal write-up in the style of a paper that could be published in the proceedings of the Association of Computational Linguistics.
Athena Title
Natural Language Processing
Undergraduate Prerequisite
(LING 2100 or LING 2100E or LING 2100H) and (CSCI 1300-1300L or CSCI 1360 or CSCI 1360E)
Graduate Prerequisite
Permission of department
Grading System
A - F (Traditional)
Course Objectives
Students will understand basic principles and techniques of natural language processing and will be able to apply these to specific linguistic projects. In addition to regular programming assignments, all students will complete a final project that involves building some kind of natural language system using available tools and corpora (see also the additional requirements for graduate students listed above). Students will gain an understanding of natural language processing as a computational form of linguistics, with its own traditions, favored approaches, and well-studied problems.
Topical Outline
Topics will include fundamental concepts and techniques in natural language processing, such as finite state technology, sequence labeling, grammar engineering, parsing in various formalisms, and deep learning as applied to text. The choice and sequencing of topics may vary.
Syllabus