Syllabus
CS 601R: Statistical Natural Language Processing
Winter Semester 2003
Irene Langkilde Geary
Office: 3334 TMCB, Email: irenelg@cs.byu.edu, Phone:
2-3020 , Hours: ???
Objectives:
- become familiar with prominent applications and techniques used in
SNLP
- appreciate real-world computational complexity of natural language
Prerequisites: some ability to program
Textbook: Foundations of Statistical Natural Language Processing,
by Christopher D. Manning and Hinrich Schutze, MIT Press, 1999.
Other Sources:
Jurafsky, Daniel and James H. Martin, Speech and Language Processing,
(2000) Prentice-Hall.
http://nlp.standford.edu/fsnlp
http://www.cs.colorado.edu/~martin/slp.html
Grading Policy:
25% Lectures
10% Quizzes
50% Homework
15% Final Project
Last Day of Class: Monday, April 14th
Final Exam Date: Monday, April 21st, 11am-2pm
Tentative Schedule:
Week 1: Intro, linguistic basics (Ch 1&3)
Week 2: Corpora, Perl (Ch 4)
Week 3: Math Foundations (Ch 2)
Week 4: Words (Ch 5&6)
Topics:
Applications:
machine translation
dialogue
information retrieval
information extraction
text categorization
question answering
summarization
speech recognition
speech synthesis
Subtasks:
tagging
parsing
generation
word sense disambiguation
alignment
clustering
Linguistic theory basics:
morphology
phonology
syntax
semantics
discourse
Grammar theories
categorial
systemic-functional
meaning-text
tree-adjoining
hpsg
Techniques/Models:
ngrams and HMMs
FSAs and FSTs
dynamic programming
unification
Tools:
taggers/parsers
machine learners
CMU Statistical Language Modeling Toolkit
Carmel Finite State Transducer
Languages:
LISP
Perl
Prolog