TRA 301 / COS 401 Graded A-F, P/D/F, Audit
Introduction to Machine Translation
This course will provide an in-depth study of the MT paradigms (direct, transfer, statistical/example, and interlingual) used in state-of-the-art speech-to-speech and text-based MT systems, from computational and linguistic perspectives. Machine-learning techniques for processing human languages (morphological analysis, tagging, syntactic and semantic parsing, and language generation) will be discussed in detail. Linguistic variation across languages and its impact on computational models will be presented. Projects will involve implementing speech/text translation components, identifying their limitations and suggesting improvements.
Sample reading list:
S. Nirenberg, H. Somers & Y. Wilks, Readings in Machine Translation
Arturo Trujillo, Translation Engines: Techniques for Machine Translation
Jurafsky and Martin, Speech and Language Processing
W. John Hutchins & Harold L. Somers, An Introduction to Machine Translation
Carl and Way, Recent Advances in Example-Based Machine Translation
Dorr, Bonnie J, Machine Translation Divergences
See instructor for complete list
The course will involve some programming exercises.
Mid Term Exam - 20%
Paper in lieu of Final - 35%
Oral Presentation(s) - 10%
Class/Precept Participation - 10%
Problem set(s) - 25%
Not Open to Freshmen.
Prerequisites and Restrictions:
Students are required to have programming experience or should have completed COS126 (Introduction to Computer Science). TRA 200 is recommended (may be taken simultaneously)..
|41146||C01||1:30 pm - 4:20 pm||Th||Aaron Burr Hall 216||Enrolled:14 Limit:18|