Hi and welcome!
This can be automated, one can compute expected counts of bigrams given character frequencies and then compare with actual numbers. For example, I'm attaching a filtered transliteration file (based on #=IVTFF Eva- 1.7 with some simplifications) where some of the rarest bigrams made of common characters are highlighted. Then it's possible to take it one step further and look for rare bigram clusters, etc, etc.
rarebigrams.txt (Size: 14.78 KB / Downloads: 31)
This can be automated, one can compute expected counts of bigrams given character frequencies and then compare with actual numbers. For example, I'm attaching a filtered transliteration file (based on #=IVTFF Eva- 1.7 with some simplifications) where some of the rarest bigrams made of common characters are highlighted. Then it's possible to take it one step further and look for rare bigram clusters, etc, etc.
rarebigrams.txt (Size: 14.78 KB / Downloads: 31)