The reuse of text segments that have been previously translated in the past is part of the basic functionality of translation memory systems (TMS), and the reason the systems have this name. The underlying principle is to save every translated sentence in a database and to compare each new sentence that needs to be translated with this database.
Upon introduction of the system, the translation memory (TM) is initially filled by importing existing data or by performing an "alignment" in which source and target text pairs are analyzed and matching sentences are transferred into the translation memory. After that, the translation memory, which is a learning system, grows with each new translation, i.e., the new sentences contained in the translation are directly accepted in the translation memory either automatically or after a prior quality check.
The translation memory can also be used and accessed in various ways:
The basic difference from conventional translation memory systems is that the Across Language Server acts as the central platform for all involved individuals inside and outside the company. From the in-house translator to the freelancer to the translation agency that, for its part, passes on individual target languages to external workers, everyone is working on the basis of the same consistent data.
As a complement to the translation memory crossTank, with crossMining and algorithms from statistical machine translation, Across generates additional benefit from your language resources. One of the most important applications is intelligent automatic completion of sentences during translation, based on the source text and the keystrokes entered by the translator. This feature not only saves time, but also prevents errors.
The result is that the quality of the translations rises at the same time as significant cost reductions are achieved; depending on the redundancy of the texts in question, these cost reductions can be up to 80%.
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