These results are less accurate than Google Translate. But they are far faster to get, and far less expensive to generate:
https://cloud.google.com/translate/pricing — our goal is here is speed. We want to search through many possibilities as quickly as possible.
The word vectors have been aligned in multiple languages. Using an approximate nearest neighbor search we are able to find the nearest vector to the input in multiple languages very quickly.
To keep the example simple, we did not try to filter the data through hand-built language dictionaries. In fact, we simply drop words in other languages that also appear in the English .vec file. Words like "ciao" appear frequently enough in otherwise English sentences that the example code drops it from Italian, and so is not shown in the results:
% curl -s "https://dl.fbaipublicfiles.com/fasttext/vectors-aligned/wiki..." | grep -n ciao
50393:ciao 0.0120 ...
One improvement would be to filter out any words that do not appear in a hand-curated dictionary instead of filtering out words that already appear in English. We decided not to show how to do this because we'd already introduced a few concepts, like aligned word vectors, approximate nearest neighbour searches, and wanted to keep the example as simple as possible.