In-context translation

Context matters in every language. In-context translation uses context-aware Machine translation (MT) models and integrated workflows to interpret the relationships between words, sentences and documents.

Instead of translating phrases in isolation, it considers elements such as domain, tone, formatting, layout and even visual cues from the interface or document structure. This improves accuracy and fluency – particularly for idioms, polysemous terms and culturally sensitive expressions. In-context translation is also used within CAT tools (Computer-assisted translation) and content management environments, where translators see text within its real-world setting (for example, in a webpage, app or video subtitle). By seeing how content will appear, linguists can make better lexical and stylistic decisions.

At RWS, in-context translation is how we bring meaning and nuance into AI translation. Through Language Weaver, our context-aware MT platform, we combine neural attention models with real-world deployment in tools such as Trados and Tridion.

Language Weaver’s context-aware architecture interprets sentence- and document-level relationships to produce translations that reflect intent, tone and domain. When paired with human linguists in the loop, it delivers both precision and authenticity – at enterprise scale. This Human + Technology approach ensures every translation reflects not just the words on the page but the purpose behind them. In-context translation helps organizations communicate naturally, maintaining brand voice and meaning across every interaction.