CSCE 771 Natural Language Processsing
Computer Processing of Natural Language. (3) (Prereq: CSCE 580) Computational models for the analysis and synthesis of natural language; representations for syntax and semantics; applications to text-to-speech conversion, speech recognition, and language understanding.
Speech and Language Processing,
2nd edition by Jurafsky & Martin, (Prentice Hall Series in Artificial Intelligence), 2008.
Time and Location
TTh 11:00-12:15 SWGN 2A11
The goal for this course is for you to understand
various models of the syntax and semantics of natural language and their use in software systems.
In particular you should be able to:
- Demonstrate mastery of python for crawling the web and extracting knowledge,
- Demonstrate mastery of parsing of natural languages and knowledge representation languages,
- Demonstrate mastery of Hidden Markov Models (HMM) for choosing the best matching sequence.
- Demonstrate mastery of knowledge representation for semantics, and
- Demonstrate mastery of python and the Natural Language Toolkit for processing natural languages,
- Demonstrate the ability to formulate a research proposal.
|Jan 10 ||classes begin |
| Monday, Feb 28, 2011 ||Last day to withdraw without WF |
|TBA ||Final Exam
Assignments will be handled through dropbox https://dropbox.cse.sc.edu/ .
No late homework or projects will be accepted.
If you cannot make it to class due to other commitments,
you can hand in your homework the day before it is due.
The final grade will be based on 6-8 assignments
and the final exam, according to the following weights:
- Projects: 60%
- Midterm and Final: 40%
The homework and programs
you submit for this class must be entirely your own.
If this policy is not absolutely clear, then please contact me.
Any other collaboration of any type on any assignment is not permitted.
It is also your responsibility to protect your work
from unauthorized access.
You are reminded that you are expected to know and follow the academic
code of responsibility that appears in
Carolina Community: Student
Handbook & Policy Guide,
(Link to actual section)
In particular all work submitted
for this course must be your own. Violations of this code can result in
actions varying from a failing grade to expulsion from the university.
Solutions to midterms will be distributed when the exams are returned,
usually within one week of the exam.
Questions about grading of midterms and assignments must be presented
to the instructor within one week after the tests or assignments have been