Demonstration of a Neural Machine Translation System with Online Learning for Translators
[EN] We introduce a demonstration of our system, which implements online learning for neural machine translation in a production environment. These techniques allow the system to continuously learn from the corrections provided by the translators. We implemented an end-to-end platform integrating our machine translation servers to one of the most common user interfaces for professional translators: SDL Trados Studio. Our objective was to save post-editing effort as the machine is continuously learning from human choices and adapting the models to a specific domain or user style. ; The research leading to these results has received funding from the Spanish Centre for Technological and Industrial Development (Centro para el Desarrollo Tecnologico Industrial) (CDTI) and ¿ the European Union through Programa Operativo de Crecimiento Inteligente (Project IDI20170964). We gratefully acknowledge the support of NVIDIA Corporation with the donation of a GPU used for part of this research. ; Domingo-Ballester, M.; García-Martínez, M.; Estela, A.; Bié, L.; Helle, A.; Peris, Á.; Casacuberta Nolla, F. (2019). Demonstration of a Neural Machine Translation System with Online Learning for Translators. Association for Computational Linguistics. 70-74. http://hdl.handle.net/10251/180931 ; S ; 70 ; 74