This is the traditional approach, involving dictionary look-up and syntactical analysis. It is capable of continuing gradual improvement, which is going on at the same centres. Knowledge-based machine translation. Statistically-based machine translation. The approach has been pioneered in the USA, especially at IBM .
Technical texts are an important area where translation is often necessary.
However, they are often written in specialized language which is not available in bilingual dictionaries. It therefore becomes necessary, and cost-efficient, to compile special lists of terms and their equivalents in foreign languages. These lists are typically much longer than general-language dictionaries. Memory-based machine translation. This approach, like the statistically-based, relies on records of previous translation, but is deterministic, providing automatic access to translation equivalents which have already been selected in a translator's past work.