Automatic Detection of Machine Translated Text and Translation Quality Estimation

Roee Aharoni, Moshe Koppel, Yoav Goldberg

Abstract: We show that it is possible to automatically detect machine translated text at sentence level from monolingual corpora, using text classification methods. We show further that the accuracy with which a learned classifier can detect text as machine translated is strongly correlated with the translation quality of the machine translation system that generated it. Finally, we offer a generic machine translation quality estimation technique based on this approach, which does not require reference sentences.