  In previous work, it has been shown that BERT can adequately align
cross-lingual sentences on the word level. Here we investigate whether BERT can
also operate as a char-level aligner. The languages examined are English,
Fake-English, German and Greek. We show that the closer two languages are, the
better BERT can align them on the character level. BERT indeed works well in
English to Fake-English alignment, but this does not generalize to natural
languages to the same extent. Nevertheless, the proximity of two languages does
seem to be a factor. English is more related to German than to Greek and this
is reflected in how well BERT aligns them; English to German is better than
English to Greek. We examine multiple setups and show that the similarity
matrices for natural languages show weaker relations the further apart two
languages are.
