Alignment technology automatically matches source segments with their corresponding translations with the help of statistical and/or lexical algorithms, creating a bi-text that can be imported into a translation memory. This technology is useful to translators to recycle legacy translations, to teachers in translation training, to researchers to feed and train machine translation engines.

Although most traditional CAT tools incorporate an alignment tool, the resulting bi-text is not perfect as the alignment algorithm is usually based mostly on formal criteria of the texts (length, formatting, …). Since recently, the alignment technology has also been used to align the initial source segments with their revised translations.

How can alignment tools be improved? Is there a need for more linguistically based algorithms?

Last updated: 02 Nov 2017 13:43, by: Iulianna van der Lek