What is Neural Transfer?
Neural transfer is a method which, like the human brain, uses associations for selecting translation alternatives.
It helps in choosing the correct translation if there are several possible translations available.
The central idea is: What do humans do in such cases to find the correct translation?
The next question is: How do humans come to this conclusion?
These terms are extracted and saved in an associative memory (a neural network). The information held here would indicate, for example, that "plant" is probably translated as "Pflanze" if used in the context of "flower", "water", etc., but is probably translated as "Werk" if used in the context of "electrical", "chemical", "workforce", etc.
This neural network is activated if the system encounters a term with several meanings:
This makes it possible to find translation alternatives which have so far not been possible to identify in machine translations because previous systems a) only analyze the individual sentence (instead of the entire context), and b) do not have this associative knowledge capability.
Of course, no system is perfect and the intelligent human can always find cases in which the ignorant machine chooses the wrong option, for example, if the "parliament" "pays" its "phone" "bill".