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Lost in Transliteration: Making America a Place Where Everybody Knows Your Name

Aug 22, 2018 @ 1:00 pm - 2:30 pm

Lost in Transliteration: Making America a Place Where Everybody Knows Your Name


Jared Stegall and Richard Tait



Have you ever come across someone from another country at either a business meeting or a social outing, and when you try and pronounce their name you completely mess it up? It leaves everyone in the scenario feeling bad and is the ultimate precursor to a poor first impression.

For the past year and a half, Jared Stegall, Richard Tait, and Jon Stallrich have been working to combat this problem, along with several others, by analyzing how well native English speaking American citizens pronounce common Korean names that have been transliterated into English. They combined their linguistic and technical expertise to scientifically assess the effectiveness of not only the current IC standard transliteration method, but also methods developed by the South Korean Government and academia to determine which one yielded the best pronunciation performance from native English speaking American citizens.

In this WRM, Stegall, an LAS Research Specialist, and Tait, an LAS Korean Language Analyst, will take you through the origins of the project, experiments that were conducted, results found, and ongoing supplemental research efforts.


WEB/CONFERENCE CALL 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 downloaded directly from Cisco. Also, it should work on iPhones and iPads via the WebExApp. A good internet connection is recommended. For better audio, please join via computer and then have the meeting call your number or call in directly using one of the numbers below. When not speaking, please mute your phone to avoid background noise. When it’s time, join the WebEx meeting from here:




919-513-9329 (WolfMeeting)

Access Code: 996 474 981



Aug 22, 2018
1:00 pm - 2:30 pm


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



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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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