Project in detail

Asking MOSES to help with translation verification

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Our aim is to perform translation verification efficiently within the constraints of budget and limited manpower. This project describes our approach to translation verification. We built up a program that reads the outcome provided by translators, stores translation and metadata, performs sanity checks, i.e. empty field or wrong indexation, and a content related check. For the latter we rely on the use of a statistical machine translation system (Moses) to provide back translations. Moses uses a corpus of approved pairs of translations and a calibrated model to provide the most likely back-translation. As a last step our program evaluates text similarity comparing the back translation provided by Moses and the original English version. The final outcome of our program is a report on the quality of the translations, flagging text to be re-checked. Our approach processes high volume of data/text efficiently. In this paper we measure the incidence of the false positives, i.e. flagged items that were translated properly. This program still needs further improvement to be reliable for long sentences and out-of-the context situations.

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