1 code implementation • 25 May 2023 • Sebastian Vincent, Robert Flynn, Carolina Scarton
This work introduces MTCue, a novel neural machine translation (NMT) framework that interprets all context (including discrete variables) as text.
1 code implementation • 29 Mar 2023 • Sebastian Vincent, Alice Dowek, Rowanne Sumner, Charlotte Blundell, Emily Preston, Chris Bayliss, Chris Oakley, Carolina Scarton
Our results suggest that the degree to which professional translations in our domain are context-specific can be preserved to a better extent by a contextual machine translation model than a non-contextual model, which is also reflected in the contextual model's superior reference-based scores.
no code implementations • EACL 2021 • Sebastian Vincent
State-of-the-art (SOTA) neural machine translation (NMT) systems translate texts at sentence level, ignoring context: intra-textual information, like the previous sentence, and extra-textual information, like the gender of the speaker.