Applying Automated Machine Translation to Educational Video Courses
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We studied the capability of automated machine translation in the online video education space by automatically translating Khan Academy videos with state of the art translation models and applying Text-to-Speech synthesis to build engaging videos in target languages. We also analyzed and established a reliable translation confidence estimator based on round-trip translations in order to efficiently manage translation quality and reduce human translation effort. Finally, we developed a deployable system to deliver translated videos to end users and collect user corrections for iterative improvement.
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