Facebook has developed the first machine learning model that can translate between any two of 100 languages without going into English first. Facebook says the new machine translation model was created to help its more than two billion users worldwide. The company is still testing the translation model and hopes to add it to different products in the future.
Angela Fan, a researcher at Facebook, explained the new machine translation model this week on one of the company’s websites. She said the model produces better results than other machine learning systems that depend on English to help in the translation process. The other systems use it as an intermediate step—like a bridge—to translate between two non-English languages.
One example would be a translation from Chinese to French. Fan noted that many machine translation models begin by translating from Chinese to English first, and then from English to French. This is done "because English is the most widely available," she said. But such a way can lead to mistakes in translation.
Facebook says about two-thirds of its users communicate in a language other than English. The company already carries out an average of 20 billion translations every day on its website. But it faces a huge test with many users coming out large numbers of words in more than 160 languages.
The development team trained the new model on a data set of 7.5 billion sentence pairs for 100 languages. In addition, the system was trained on a total of 2,200 language directions. Facebook said this is 10 times the number on the best machine translation models in the past.
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