Introduction of Automation for the Production of Bilingual, Parallel-aligned Text

Report No. ARL-TR-5798
Authors: Will Tanenbaum, Steve LaRocca, John Morgan, and Ghulam Hazrat Jahed
Date/Pages: October 2011; 18 pages
Abstract: As the study and application of statistical machine translation (SMT) grows, progress is often circumscribed by a lack of data. The statistical models that govern SMT engines rely on many large bilingual text corpora, each comprised of vast numbers of bilingual text segments. For certain languages, corpora already exist and help to power translation engines. Regrettably, this is not the case for every language the Army is interested in, making the creation or acquisition of such data a priority. To this end, a language expert in Dari and Pashto was hired, who collected, prepared, and ensured the quality of bilingual text. To explore ways to aid the expert, a variety of the steps performed by the expert and necessary to the process were automated. The hypothesis was that automation of selected processes would improve efficiency, measured in terms of both speed of production, and quantity of data produced, even when time to correct automation-caused errors was accounted for. As predicted, the net result of introducing automation was an increase in both the rate of producing correct bilingual segments and the number produced. The implications of these results for improving larger bilingual data creation and acquisition efforts are discussed.
Distribution: Approved for public release
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Last Update / Reviewed: October 1, 2011