Bryn Mawr College
CMSC 325: Computational Linguistics
Fall 2018
Course Materials
Prof. Deepak Kumar

Information
Texts  Important Dates  Assignments  Lectures Course Policies Links

 

Instructor: Deepak Kumar
Office: 201 Park Science Building
Phone: 526-7485
e-mail: dkumar at brynmawr dot edu
web: http://cs.brynmawr.edu/~dkumar

Lecture Hours: Mondays & Wednesdays, 10:10 a.m. to 11:30 a.m.
Office Hours:Tuesdays 1:30 to 2:30p and during Lab Hours
Lecture Room: 349 PSB
Lab: All labs will meet in Room 230 PSB. Students should register for the lab shown below:

Laboratories:

Texts & Software

TEXTS:

Speech & language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition by Daniel Jurafsky & James H. Martin, 2nd Edition, Pearson Prentice Hall 2008.

NOTE: The authors are currently updating the text for a Third Edition. Updates are available electronically at Prof. Jurafsky's website. More details on accessing its content will be provided in the First Week.

Natural Language processing with Python - Analyzing Text with the Natural Language Toolkit (NLTK) by Steven Bird, Ewan Klein, and Edward Loper. Available under Creative Commons License at NLTK Book Site.

SOFTWARE:

Python 3.0+NLTK
This software is installed on all computers in the CS Lab. It can also be installed on your computers. Await instructions in the lectures/labs about installing on your own computers.

 

 

Syllabus

Course Description: Class Number: 2201
Introduction to computational models of understanding and processing human languages. How elements of linguistics, computer science, and artificial intelligence can be combined to help computers process human language and to help linguists understand language through computer models. Topics covered: syntax, semantics, pragmatics, generation and knowledge representation techniques. Prerequisite: CMSC 206 , or H106 and CMSC 231 or permission of instructor. Haverford: Natural Science (NA)
Enrollment Limit; 24.

Lab Attendance: Attendance in Lab is optional, but will be required during specific weeks. Look for announcements below during the semester. Prof. Kumar will be available in the Lab during all Lab times throughout the semester.

Important Dates

September 5: First lecture
October 1: Exam 1
November 7: Exam 2
December 10: Last lecture
December 12: Exam 3

Assignments

  1. Assignment#1 (Due on Wednesday, September 19) is posted. Click here for details.
  2. Assignment#2 (Due on Wednesday, October 3) is posted.Click here for details.
  3. Assignment#3 (Due on Wednesday, October 24): Click here for details.
  4. Assignment#4 (Due on Wednesday, November 7):Click here for details.
  5. Assignment#5 (Due on Monday, December 10):Click here for deatils.

Lectures

Course Policies

Communication

Attendance and active participation are expected in every class. Participation includes asking questions, contributing answers, proposing ideas, and providing constructive comments.

As you will discover, we are proponents of two-way communication and we welcome feedback during the semester about the course. We are available to answer student questions, listen to concerns, and talk about any course-related topic (or otherwise!). Come to office hours! This helps us get to know you. You are welcome to stop by and chat. There are many more exciting topics to talk about that we won't have time to cover in-class.

Although computer science work can be intense and solitary, please stay in touch with us, particularly if you feel stuck on a topic or project and can't figure out how to proceed. Often a quick e-mail, phone call or face-to-face conference can reveal solutions to problems and generate renewed creative and scholarly energy. It is essential that you begin assignments early, since we will be covering a variety of challenging topics in this course.

Grading

All graded work will receive a grade, 4.0, 3.7, 3.3, 3.0, 2.7, 2.3, 2.0, 1.7, 1.3, 1.0, or 0.0. At the end of the semester, final grades will be calculated as a weighted average of all grades according to the following weights:

Exam 1: 20%
Exam 2: 20%
Exam 3: 20%
Labs & Written Work: 40%
Total: 100%

Incomplete grades will be given only for verifiable medical illness or other such dire circumstances.

Submission and Late Policy

All work must be turned in either in hard-copy or electronic submission, depending on the instructions given in the assignment.  E-mail submissions, when permitted, should request a "delivery receipt" to document time and date of submission.  Extensions will be given only in the case of verifiable medical excuses or other such dire circumstances, if requested in advance and supported by your Academic Dean.

No assignment will be accepted after it is past due.

No past work can be "made up" after it is due.

No regrade requests will be entertained one week after the graded work is returned in class.

Exams

There will be three exams in this course.  The exams will be closed-book and closed-notes.  The exams will cover material from lectures, homeworks, and assigned readings (including topics not discussed in class).

Links (To be updated)

The Association for Computational Linguistics (ACL)

The Language Computer Q&A demo

An online version of ELIZA

NLTK Home page

NLTK LITE Tutorials

NLTK LITE API Documentation

 

Created on May 4, 2018.