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Course Details

Spring 2017-2018
TRA 301 / COS 401 / LIN 304   Graded A-F, P/D/F, Audit

Introduction to Machine Translation

Srinivas Bangalore

This course will provide an in-depth study of the Machine Translation paradigms (direct, transfer, statistical/example, interlingua and neural network) used in state-of-the-art speech-to-speech and text-based MT systems, from computational and linguistic perspectives. Techniques for processing human languages (morphological analysis, tagging, syntactic and semantic parsing, and language generation) will be discussed. 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

Reading/Writing assignments:
The course will involve some programming exercises.

Requirements/Grading:
Mid Term Exam - 20%
Paper in lieu of Final - 35%
Oral Presentation(s) - 10%
Class/Precept Participation - 10%
Problem set(s) - 25%

Other Requirements:
Not Open to Freshmen.

Prerequisites and Restrictions:
Students are required to have programming experience or should have completed COS 226 (Algorithms and Data Structures). TRA 200 is recommended (may be taken simultaneously)..

Schedule/Classroom assignment:

Class numberSectionTimeDaysRoomEnrollmentStatus
42144 C01 1:30 pm - 4:20 pm F        Enrolled:19 Limit:25