This pages gives pointers to all the handouts and resources for the course. There is a great website of resources that is a companion to the Manning and Schutze text.
A description of the course is found in the Course Handout. A syllabus will be available shortly.
Lecture 1: Overview and Key Concepts
Lecture 2: A Whirlwind Tour of Probability
Lecture 3: Estimating Probability Distributions
Lecture 4: Estimating with Hold Outs
Lecture 6: Entropy and Information Theory
Lecture 7: Basic Automata Models
Lecture 8: Tagging Applications
Lecture 9: Searching HMM Models
Lecture 10: Learning with Hidden Data: The EM Algorithm
Lecture 12: Approaches to Speech Recognition
Lecture 13: Signal Processing for Speech-
Lecture 14: Building Code Books
Lecture 15: Search and Training for Large Vocabulary Speech Recognition
Lecture 16: Simple Alignment Models
Lecture 17: Using unordered Contexts
Lecture 18: Information Retrieval
Lecture 19: Probabilistic Context Free Grammars
Lectures 20 and 21: Machine Translation (these are notes from Kevin Knight Ð the first 12 sections review work covered earlier in the course. MT starts with section 13)
Lecture 22: Effective CFG Models
Assignment 1, Due September 16. There are two test corpora for the assignment. Here are assignment one solutions.
Assignment 2, Due October 2 . The test corpora can be found at
ftp://ftp.cs.rochester.edu/pub/u/myros/multi_corpora.tgz
Here are assignment two solutions.
Assignment 3: Due November 4th. Here is the data file.
Assignment 4: Due November 25th. Here is the training data.
Makeup Assignment, Due December 9th at start of class. No late assignments accepted.
A copy of the midterm from last time is http://www.cs.rochester.edu/u/james/CSC248/oldmidterm.pdf