approaches. Original versions of Google Translate were based on a method called statistical machine translation, and more specifically, on research by Och who won the DARPA contest for speed machine translation in 2003. Och was the head of Google's machine translation group until leaving to join Human Longevity, Inc. in July 2014. Google Translate does not translate from one language to another (L1 → L2). Instead, it often translates first to English and then to the target language (L1 → EN → L2). However, because English, like all human languages, is ambiguous and depends on context, this can cause translation errors. For example, translating from French to Russian gives → you → OR . If Google were using an unambiguous, artificial language as the intermediary, it would be → you → OR → thou → . Such a suffixing of words disambiguates their different meanings. Hence, publishing in English, using unambiguous words, providing context, using expressions such as "you all" may or may not make a better one-step translation depending on the target language. The following languages do not have a direct Google translation to or from English. These languages are translated through the indicated intermediate language (which in most cases is closely related to the desired language but more widely spoken) in addition to through English: Belarusian (be ↔ ru ↔ en ↔ other); Catalan (ca ↔ es ↔ en ↔ other); Galician (gl ↔ pt ↔ en ↔ other); Haitian Creole (ht ↔ fr ↔ en ↔ other); Korean (ko ↔ ja ↔ en ↔ other); Slovak (sk ↔ cs ↔ en ↔ other); Ukrainian (uk ↔ ru ↔ en ↔ other); Urdu (ur ↔ hi ↔ en ↔ other). According to Och, a solid base for developing a usable statistical machine translation system for a new pair of languages from scratch would consist of a bilingual text corpus (or parallel collection) of more than 150-200 million words, and two monolingual corpora each of more than a billion words. Statistical models from these data are then used to translate between those languages. To acquire this huge amount of linguistic data, Google used United Nations and European Parliament documents and transcripts. The UN typically publishes documents in all six official UN languages, which has produced a very large 6-language corpus. Google representatives have been involved with domestic conferences in Japan where it has solicited bilingual data from researchers. When