Machine Translation vs Human

Been reexamining he process of language translation, especially as it relates to real time assistant interaction.  This points out that full document translations still are better using humans, which implies document-contextual elements. I saw this in starting my own look at assistant translations,  the context introduces a clearer focus   This could be provided by using intelligent followup questions.

Human translators are still on top—for now

Machine translation works well for sentences but turns out to falter at the document level, computational linguists have found.  by Emerging Technology from the arXiv  September 5, 2018

You may have missed the popping of champagne corks and the shower of ticker tape, but in recent months computational linguists have begun to claim that neural machine translation now matches the performance of human translators.

The technique of using a neural network to translate text from one language into another has improved by leaps and bounds in recent years, thanks to the ongoing breakthroughs in machine learning and artificial intelligence. So it is not really a surprise that machines have approached the performance of humans. Indeed, computational linguists have good evidence to back up this claim.

But today, Samuel Laubli at the University of Zurich and a couple of colleagues say the champagne should go back on ice. They do not dispute their colleagues’ results but say the testing protocol fails to take account of the way humans read entire documents. When this is assessed, machines lag significantly behind humans, they say. .... "