Papers with statistical and neural machine translation systems

2 papers
English-Basque Statistical and Neural Machine Translation (L18-1)

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Challenge: Neural machine translation (NMT) requires large training corpora, which is problematic for low-resource languages.
Approach: They propose to use an open-domain and an IT-domain corpora to train machine translations in English-Basque.
Outcome: The proposed systems outperform OpenNMT, Moses SMT and Google Translate in English-Basque translation.
Benchmarking Neural and Statistical Machine Translation on Low-Resource African Languages (2020.lrec-1)

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Challenge: a recent study has focused on languages where large amounts of resources are available.
Approach: They benchmark state of the art statistical and neural machine translation systems on Somali and Swahili languages . they find that statistical machine translation and neural translation can perform similarly in low-resource scenarios .
Outcome: The results show that statistical machine translation and neural machine translation perform similarly in low-resource scenarios.

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