Instructor:	Dr. Eun-Joo Lee
Email Address:	elee [at] po-box.esu.edu
Office Location:	SciTech 327
Office Phone:	570-422-2740

Course Description

This course is designed to introduce students to the fundamental concepts and ideas in natural language processing (NLP), and to get them up to speed with current research in the area. It develops an in-depth understanding of both the algorithms available for the processing of linguistic information and the underlying computational properties of natural languages. Word-level, syntactic, and semantic processing from both a linguistic and an algorithmic perspective are considered. The focus is on modern quantitative techniques in NLP: using large corpora, statistical models for acquisition, disambiguation, and parsing. Also, it examines and constructs representative systems.

Prerequisites

CPSC 111, 141, 251, 330

Intended Audience

Graduate students and advanced undergraduates specializing in computer science, linguistics, or symbolic systems.

Textbook and Readings

The required text is:

Daniel Jurafsky and James H. Martin. 2008. Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics and Speech Recognition. Second Edition. Prentice Hall.

Other useful reference texts for NLP are:

James Allen. 1995. Natural Language Understanding. Benjamin/Cummings, 2ed.
Gerald Gazdar and Chris Mellish. 1989. Natural Language Processing in X. Addison-Wesley. [Where X = Prolog, Lisp, or, I think, Snobol.
Frederick Jelinek. 1998. Statistical Methods for Speech Recognition. MIT Press.

Other papers with relevant material will be posted on the syllabus, as will lecture slides.