University of Chicago: Computer Science: CMSC 35100: Winter 2006: Course Description

CMSC 35100 - Natural Language Processing
Winter 2006
Course Description

Description

An introduction to the theory and practice of natural language processing, with applications to both text and speech. Topics to be covered include: regular expressions, finite state automata, morphology, part of speech tagging, context free grammars, parsing, semantics, discourse, and dialogue. Symbolic and probabilitistic models will be presented. Techniques for automatic acquisition of linguistic knowledge will be emphasized.

Goals

Analyze, evaluate, and apply symbolic and stochastic techniques for a variety of tasks in speech and language processing.
Compare automatic processing techniques to theoretical and linguistic explanations of human language processing capabilities.

Instructional Staff

	Instructor	Teaching Assistant
Name	Gina Levow
Email	levow@cs.uchicago.edu
Office	Ry 166
Office Phone	x2-5680

Course Mechanics

A syllabus that summarizes what we will cover each week and gives a preview of the homework assignments and a reading list showing the reading for each week can be found on the class web page.

The instructors' office hours are for discussing material from class. Students wishing to discuss accommodations for unusual circumstances should also come see me, and should do so at the earliest possible time. I will also be happy to meet with students either after class or by appointment. Electronic mail is the best way to reach me to set up an appointment, and it is also a good way to get a quick answer to a simple question.

Course Materials

The class web site at http://www.classes.cs.uchicago.edu/archive/2006/winter/cs35100-1/ contains the most recent copies of all material produced for this course. This course description (which contains a number of useful links), the syllabus, lecture notes and homework solutions can be found there.

The required text is Jurafsky and Martin's Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition, available from the Seminary Co-op Bookstore.

Grading

Course grades will be assigned based on in-class participation, homework, and a final project. Scores on each component will be combined to produce a single overall score for each student as follows:

Component	Percentage
Class Participation	20%
Homework	40%
Final Project	40%

Scores for each course requirement (homework assignment, project ) will be assigned on a 100 point scale.

Homework is due before the start of class. Credit for partial work will be given.

Students may work together on the assignments, but all of the material which is turned in for grading must be produced individually. For example, students may form study groups and work out solutions together on a chalkboard, but it would not be permissible for one student to create a computer file containing the answers and then for other students to copy that file and submit it as their own work. The goal of this policy is to encourage the use of homework as a learning aid. Credit should be given for help on the homework by identifying one's collaborators on the first page of the submitted homework assignment.