75 citations · 168 across the 13 of their papers we have counts for
5 papers · 1 filter
Domain specialization: a post-training domain adaptation for Neural Machine Translation
Christophe Servan, Josep Crego, Jean Senellart
Domain adaptation is a key feature in Machine Translation. It generally encompasses terminology, domain and style adaptation, especially for human post-editing workflows in Compute…
Neural Machine Translation from Simplified Translations
Josep Crego, Jean Senellart
Text simplification aims at reducing the lexical, grammatical and structural complexity of a text while keeping the same meaning. In the context of machine translation, we introduc…
Domain Control for Neural Machine Translation
Catherine Kobus, Josep Crego, Jean Senellart
Machine translation systems are very sensitive to the domains they were trained on. Several domain adaptation techniques have been deeply studied. We propose a new technique for ne…
Boosting Neural Machine Translation
Dakun Zhang, Jungi Kim, Josep Crego +1
Training efficiency is one of the main problems for Neural Machine Translation (NMT). Deep networks need for very large data as well as many training iterations to achieve state-of…
SYSTRAN's Pure Neural Machine Translation Systems
Josep Crego, Jungi Kim, Guillaume Klein +27
Since the first online demonstration of Neural Machine Translation (NMT) by LISA, NMT development has recently moved from laboratory to production systems as demonstrated by severa…