Sequoyah foreign language translation system business case analysis

• Main Author: Ong, Wing Shan Shirley.
• Other Authors: Nussbaum, Dan
• Published: Monterey, California. Naval Postgraduate School 2012
• Online Access: http://hdl.handle.net/10945/3123

Sequoyah, which is the Department of Defense (DoD)'s Program of Record for automated foreign language translation, is to identify current and developing technologies to meet warfighter requirements for foreign language support. Sequoyah aspires to have MLT capability embedded in other systems, such as Soldier as a System (SaaS) and Future Combat System (FCS), so as to provide automated capability to meet the warfighters' foreign language translation needs when a human linguist is unavailable. The purpose of this thesis is to analyze the potential cost savings and benefits of utilizing MLT systems as a complement to the host nation linguists required to be hired to support military operations. This thesis will develop a Business case for the following purposes: Analyze the best circumstances in military operations that MLT systems can be used to complement human linguists or when human linguist is not available. Determine the comparative costs of MLT systems vs. host nation linguists using techniques from the field of cost estimation. Although the use of computers is very prevalent in today's society, they simply cannot replace human beings in performing some of the tasks that require thinking and understanding. Bar-Hillel, an early machine translation researcher, used a seemingly simple sentence "The box is in the pen" to point out that "to decide whether the sentence is talking about a writing instrument pen or a child's play pen, it would be necessary for a computer to know about the relative sizes of objects in the real world. The point is that accurate translation requires an understanding of the text, which includes an understanding of the situation and an enormous variety of facts about the world in which we live." Hence, this study does not advocate replacing human linguists with MLT systems but rather to explore the circumstances that MLT systems can be used to complement host nation linguists or when there is no linguist available.