The gap between human and machine translators could be narrowing as researchers find a new way to improve the learning capabilities of Google Translate’s neural network.
On the same day that Google announced its translation services were now operating with its Neural Machine Translation (NMT) system, a team of researchers released a paper on arXiv showing how its NMT could be pushed one step further.
An NMT is a large single neural network that learns to translate by being trained on a pair of languages. Google Translate has been around for ten years, and before an NMT was used, it often provided a clumsy attempt at translation. Sentences could be lost in translation because individual phrases were translated together instead of whole sentences.