DFG funds new research on machine translation from non-parallel data

Artem Sokolov and Stefan Riezler will start a novel attempt at learning machine translations from data that are not strictly parallel, but only weakly supervised by relevance indicators such as citations in patents or hyperlinks in Wikipedia pages.

The research will be conducted in the DFG funded research project
"Weakly Supervised Learning of Cross-Lingual Systems".