This post is an addendum to our original post on 1/10/2017 entitled 2017 Machine Translation Quality Evaluation. Experimental Design We evaluate all machine translation systems for English-French and English-German. We report case-insensitive BLEU-4 , which is computed by the mteval scoring script from the Stanford University open source toolkit Phrasal. NIST tokenization was applied to both the system outputs and the reference translations.
In the last few decades, machine translation has become more and more common as a tool to improve speed and reduce cost for companies scaling localization programs. The process itself has helped to make large amounts of the world’s content available for people outside of the target language audience.