Translation Memory in Context: What Makes Transit Different?
The sentence is the basic unit of language. However, it is not necessarily the basic unit of meaning. Translators read sentences in the source text but are only able to do an effective job of translating them if they are able to derive and understand their meaning from the context. This is a principle which was taken into account in the first version of Transit, over 20 years ago. In contrast to other translation memory systems, Transit does away with a database that is exclusively sentence-based. Instead, the full breadth of the context contained in a document remains available in the Transit reference material.
Transit NXT provides information ‘on the fly’.
Bubble windows, which provide a dynamic representation of fuzzy matches, allows you to make even more efficient use of the Transit editor. The Fuzzy window is only displayed when there are translation suggestions and then disappears again from the interface after the suggestion has been accepted.
TermStar NXT – Fuzzy Term catches on every time.
Transit’s tried-and-tested ‘Fuzzy logic’ is now also available in TermStar NXT. Fuzzy search in TermStar NXT not only finds items which precisely correspond to your search term but also all similar entries contained in the dictionary.
Your reference material now has even more value. Dual Fuzzy logic in Transit NXT not only takes account of the source text when searching for translation suggestions, it now also looks at the target text.
Transit NXT suggests sentences from existing translations. The innovation here is the Dual Fuzzy principle, which means that Transit NXT searches both the source and the target language for similar sentences. This means that two sentences which have the same basic meaning but are differently formulated can be assigned a single translation. If no matches are found in the source text, Transit NXT searches the target text for similar sentences while the translation is being entered.