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The fallback machine-training material for these languages consists of religious publications, including the much-translated Bible. They are known as low-resource languages. No such data mountain exists, however, for languages that may be widely spoken but not as prolifically translated. The European Parliament alone produces a data trove of 1.37 billion words in 23 languages over a decade. Their human translators churn out streams of translated transcripts and other documents. There is an abundance of such material for languages like English, French, Spanish and German, thanks to multilingual institutions like the Canadian parliament, the United Nations and the European Union. That's because the algorithms that power these engines learn from human translations – ideally, millions of words of translated text. But many other languages still defy machine translation, including languages spoken by millions of people, such as Wolof, Luganda, Twi and Ewe in Africa. If the message is in French or Spanish, typing it into an automatic translation engine will instantly solve the mystery and produce a solid answer in English. You're not even sure which of the world's thousands of languages it is written in.
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But there's a problem: you don't understand a word. Imagine you come across a message that could contain life-saving information.