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cs.CL2021
Comparing Feature-Engineering and Feature-Learning Approaches for Multilingual Translationese Classification
Daria Pylypenko, Kwabena Amponsah-Kaakyire, Koel Dutta Chowdhury +2
Traditional hand-crafted linguistically-informed features have often been used for distinguishing between translated and original non-translated texts. By contrast, to date, neural…
cs.CL2021
Leveraging Neural Machine Translation for Word Alignment
Vilém Zouhar, Daria Pylypenko
The most common tools for word-alignment rely on a large amount of parallel sentences, which are then usually processed according to one of the IBM model algorithms. The training d…