Machine learning has significantly boosted automatic translation in recent years. Systems such as 2016’s GNMT (Google’s Neural Machine Translation System) have improved translation performance in over 100 languages. However, even today’s most advanced translation systems still lag behind human performance in almost all respects. For languages with high usage rates, plentiful data resources make it easy to improve technical capabilities. Translation improvements for low-resource languages however have not nearly come as quickly.

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