[akdor1154]

I think ML approaches are not well suited here - or at least there are still huge problems between non-germanic/Latin languages that have yet to be approached. (My background: white Australian, not a linguist, know a little Vietnamese, know a very tiny bit about indigenous Australian languages based on chatting with friends who studied that area)

I continually see consumer-facing ml approaches (FB, Google) give terrible Vietnamese translations because they assume all of the context needed for a translation is available in the text. In general this is not the case. In Vietnamese this is hugely obvious because their pronoun system is largely based on 3rd person relationships ("sister walks down the street", "boyfriend loves girlfriend"), which is impossible to map to/from English 2nd person ("you walk down the street", "I love you") without basically a full conscious intelligence. Even FB, which is in a unique circumstance of actually having a lot of the requisite relationship data between people available to it, does a terrible job at this.

My (tiny) understanding of the incredibly rich kinship systems in indigenous Australian cultures suggests that this would be a huge issue there as well, assuming these complexities are also present in their languages. (...OP? :) )