Introduction

This course will introduce you to a broad range of topics in the area of natural language processing including language modeling, part of speech tagging, spelling correction, morphology, syntactic parsing, semantics and machine translation. If time permits, we may also cover speech recognition, natural language generation or discourse systems.

Class information

Professor: Richard Wicentowski
Office: Science Center 251
Phone: (610) 690-5643
Office hours: Monday 1:00-3:30 pm and by appointment

Room: Science Center 181
Class Time: Tuesday, Thursday 2:40pm–3:55pm
Lab Times: Wednesday 2:40pm–3:55pm; Wednesday 1:00m–2:30pm
Text: Jurafsky and Martin, Speech and Language Processing, 2nd edition (Recommended)

Schedule

(tentative)

Grading

Your overall grade in the course will be determined as follows:

65%	Labs and projects
30%	Exams
5%	Class pariticipation and Attendance

Turning in Assignments

You will submit your assignments electronically using the handin65 program. You may submit your assignment multiple times, but each submission overwrites the previous one and only the final submission will be graded. Normally, late assignments will not be accepted; however, special exceptions can be made if you contact me well in advance of the deadline. Even if you do not fully complete an assignment, submit what you have done in order to receive partial credit.

Some assignments may take a considerable amount of time. You are strongly encouraged to begin working on assignments well before the due date.

Programming Language

Assignments will presuppose knowledge of Python. You will almost certainly end up learning some Perl and bash scripting, but you are not expected to know this (yet).

Please make sure that each program/script you turn in has:

• A comment at the top of the program that includes
  • Program authors
  • A brief description of what the program does
• Concise comments that summarize major sections of your code
• Meaningful variable and function names
• Well organized code
• White space to improve legibility
• Lines whose width is less than 80 characters wide (whenever possible)

Academic Integrity

Academic honesty is required in all work you submit to be graded. With the exception of your partner on assignments, you may not submit work done with (or by) someone else, or examine or use work done by others to complete your own work.

You may discuss assignment specifications and requirements with others in the class to be sure you understand the problem. In addition, you are allowed to work with others to help learn the course material. However, with the exception of your lab partner, you may not work with others on your assignments in any capacity.

All code you submit must be your own with the following permissible exceptions: code distributed by me as part of the class, code found in the course text book, and code worked on with your assignment partner. You should always include detailed comments that indicates which parts of the assignment you received help on, and what your sources were. If you believe a particular 3rd party library would be useful in solving the problem at hand, please ask me to be sure it's ok to proceed.

Please see me if there are any questions about what is permissible.

Academic Accomodations

If you believe that you need accommodations for a disability, please contact Leslie Hempling in the Office of Student Disability Services (Parrish 130) or e-mail lhempli1@swarthmore.edu to set up an appointment to discuss your needs. Leslie Hempling is responsible for reviewing and approving disability-related accommodation requests. As appropriate, she will issue students with documented disabilities an Accommodation Authorization Letter. Since accommodations require early planning and are not retroactive, please contact her as soon as possible. For details about the Student Disabilities Service and the accomodations process, visit their website. You are also welcome to contact me privately to discuss your academic needs. However, all disability-related accommodations must be arranged through Leslie Hempling in the Office Of Student Disability Services.

External Links

Jurafsky and Martin, Speech and Language Processing (2/e), 2008
Manning, Raghavan and Schütze, Introduction to Information Retrieval, 2008
Manning and Schutze, Foundations of Statistical Natural Language Processing, 1999
Mertz, Text Processing in Python, 2003
NLTK: Natural Language Toolkit
The ACL Anthology
Python Documentation
Think Python: How To Think Like a Computer Scientist