Abstract
Abstract : This memorandum report outlines the Human in the Loop Translation process, which strives to increase translators' productivity using statistical machine translation (SMT). In this process, U.S. Army Research Laboratory (ARL) systems trained by open source SMT toolkits were placed in a feedback loop with human translators in Afghanistan to incrementally improve Dari translations of English medical training manuals and to create bilingual glossaries in the medical domain. Anecdotal evidence indicates that the quality of the machine translation drafts produced using this feedback loop process is high enough to assist human translators in translating training manuals in the medical domain. Automatic scores showed large improvements in translation quality as the loop progressed for a very narrow task, providing indirect evidence that SMT can benefit human translators even with small amounts of training data.
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