no code implementations • WS 2018 • Daria Pylypenko, Raphael Rubino
This paper presents the Automatic Post-editing (APE) systems submitted by the DFKI-MLT group to the WMT{'}18 APE shared task.
no code implementations • 31 Mar 2021 • 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.
no code implementations • EMNLP 2021 • Daria Pylypenko, Kwabena Amponsah-Kaakyire, Koel Dutta Chowdhury, Josef van Genabith, Cristina España-Bonet
Traditional hand-crafted linguistically-informed features have often been used for distinguishing between translated and original non-translated texts.
no code implementations • 24 Oct 2022 • Kwabena Amponsah-Kaakyire, Daria Pylypenko, Josef van Genabith, Cristina España-Bonet
Previous research did not show $(i)$ whether the difference is because of the features, the classifiers or both, and $(ii)$ what the neural classifiers actually learn.
1 code implementation • 25 Aug 2023 • Angana Borah, Daria Pylypenko, Cristina Espana-Bonet, Josef van Genabith
Translationese signals are subtle (especially for professional translation) and compete with many other signals in the data such as genre, style, author, and, in particular, topic.