From the Google Blog comes the announcement that Google’s system placed first in the annual Machine Translation evaluation by the National Institute of Standards and Technology (NIST). The tests involved translating from Arabic and Chinese into English.

According to Google’s engineer Franz Och, their “approach was to use statistical translation models learned from parallel text, that is, sets of documents and their translations. The system learns a model automatically from the parallel data. This approach differs from the rule-based approach used by many existing commercial machine translation companies which is based on large sets of handwritten translation rules. We’re very pleased with the results of this evaluation. Our computing infrastructure allows us to do a lot of experiments and work with huge data sets very easily.”