This course is designed to introduce students to the current statistical techniques for the automatic analysis of natural (human) language data. It develops an in-depth understanding of both the algorithms available for the processing of linguistic information and the underlying computational properties of natural languages. Potential topics include language modeling, finite state models, stochastic grammars, latent semantic analysis, log-linear models in natural language processing. We will explore how these core techniques can be applied to user applications such as information extraction, question answering, automatic speech recognition, statistical machine translation.
Time: Monday/Wednesday 8:00 pm -9:15 pm; Location: Russ Center 155
Shaojun Wang
428, Russ Engineering Center Building
shaojun.wang(at)wright.edu
(937) 775-5140
Office hours: Monday/Wednesday 2:00PM-3:30PM
Jurafksy, D. and Martin, J.
Speech and Language Processing, 2nd Edtion
Prentice Hall, 2008.
Manning, C. and Schuetze, H.
Foundations of Statistical Natural Language Processing
MIT Press, 1999.
Attendance 10%
Final Project 90%