Addressing context in machine translation development
The second day of the conference began with a keynote titled “Machine Translation Using Context Information”, presented by Marcello Federico of AWS AI Labs.
Federico emphasizes that the output of machine translation may look correct out of context, but there are many external factors that may show them to be incorrect. These may include gender, speech registers, topic or domain of discourse, among other things that define the context in which the original text, and by extension the translation, operates within.
Machine translation has yet to solve these problems, howeve bosnia and herzegovina mobile database there is already a lot of research on how generic data can be annotated to control for some of these factors and analyze past translations to provide better output.
In line with the theme of context, the next panel we were able to attend discussed a specific context-related problem in “Fixed Language Units and Machine Translation: Pragmatemes in Machine-Translated Subtitles” presented by Judyta Mężyk.
Mężyk defines pragmatemes as “autonomous, polylexical, semantically compositional utterances constrained in their signified by the situation of communication in which they are produced”.