Improving machine translation output of German compound and multiword financial terms: comparison with cross-linguistic data

Abstract

The present application translates German financial terms to the Greek language aiming to maximize the translation quality. The demand for better translation increases the need for more MT systems; journalists or professionals in the banking sector require accurate translations. A novel statistical method of MT is presented, where we use a probability distribution over sentence pairs from a parallel corpus (German-Greek). Both the MT system and the parallel corpus were built from scratch. The present application combines parameters in a new way and estimates the probabilities that extract the best translation.