A Comparison of Transformer and Recurrent Neural Networks on Multilingual Neural Machine Translation

Understand

Recently, neural machine translation (NMT) has been extended to multilinguality, that is to handle more than one translation direction with a single system.

• Multilingual NMT showed competitive performance against pure bilingual systems.
• Notably, in low-resource settings, it proved to work effectively and efficiently, thanks to shared representation space that is forced across languages and induces a sort of transfer-learning.
• Furthermore, multilingual NMT enables so-called zero-shot inference across language pairs never seen at training time.