no code implementations • EAMT 2022 • Pedro Mota, Vera Cabarrão, Eduardo Farah
In this work, we propose a Named Entity handling approach to improve translation quality within an existing Natural Language Processing (NLP) pipeline without modifying the Neural Machine Translation (NMT) component.
no code implementations • LREC 2020 • Julia Ive, Lucia Specia, Sara Szoc, Tom Vanallemeersch, Joachim Van den Bogaert, Eduardo Farah, Christine Maroti, Artur Ventura, Maxim Khalilov
We introduce a machine translation dataset for three pairs of languages in the legal domain with post-edited high-quality neural machine translation and independent human references.