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Transwolf: Statistical Machine Translation of North Korean Propaganda

Jun 27 @ 1:00 pm - 2:30 pm

Transwolf: Statistical Machine Translation of North Korean Propaganda

SPEAKER:

Richard Tait, James Campbell, and Dr. Natalie Smith

 

ABSTRACT:

Interested in Transwolf, a popular public bus system in Brazil? Then you would be coming to the wrong place, because 27 June’s WRM (weekly research meeting) will be spent introducing an effort called Transwolf: Domain-Specific Machine Translation Research. This will all happen on Wednesday, 27 June 1:00-2:30 pm in rm. 205, the large conference room on the second floor of the Poulton Innovation Center. A small team of LAS experts, including Korean language analyst Richard Tait, data science expert James Campbell, and key analyst Dr. Natalie Smith, have worked together to develop tailored, domain-specific translation models using the popular Moses machine translation system. Come learn about what has been accomplished as well as future plans. We look forward to seeing you there!

 

 

WEB/CONFERENCECALL INFO: We are going to use the NC State WebEx for the web conference.Please note that this WebEx belongs to NC State and can not be downloadeddirectly from Cisco. Also, it should work on iPhones and iPads via the WebExApp. A good internet connection is recommended. For better audio, please joinvia computer and then have the meeting call your number or call in directlyusing one of the numbers below. When not speaking, please mute your phone toavoid background noise. When it’s time, join the WebEx meeting from here:

https://wolfmeeting.ncsu.edu/orion/joinmeeting.do?MTID=53061696754dc38d42cda2489fef5701

 

 

Audio Connection:  919-513-9329(WolfMeeting)

Access Code:  999 199 621

 

Details

Date:
Jun 27
Time:
1:00 pm - 2:30 pm

Venue

Partners I, 1017 Main Campus Dr, Raleigh, NC 27606, USA
800 Main Campus Dr
Raleigh, NC United States

Organizer

lascalendar@ncsu.edu
Email:
lascalendar@ncsu.edu

Connect With Us

LAS aims to bring together a multi-disciplinary group of academic, industry, and government researchers, analysts and managers together to re-engineer the intelligence analysis process to promote predictive analysis. LAS will do this by conducting both classified and unclassified research in a variety of areas of research. The research done in this area will serve as the foundation for mission effects and integrated back into the enterprise.

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