A Corpus of 21st Century Scots Texts

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Levenshtein Distance

Enter a word to find nearest neighbouring words, for example ahint

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Similar words to baitur in Corpus

Levenshtein Double Levenshtein SoundEx MetaPhone Manually curated
baitur (0) - 4 freq
battur (1) - 1 freq
baiturr (1) - 1 freq
naitur (1) - 75 freq
pastur (2) - 5 freq
naitir (2) - 1 freq
bait (2) - 32 freq
eraitur (2) - 1 freq
baiyun (2) - 1 freq
caiptur (2) - 1 freq
maiur (2) - 1 freq
basturt (2) - 17 freq
maiter (2) - 71 freq
bait's (2) - 1 freq
natur (2) - 25 freq
craitur (2) - 126 freq
baitin (2) - 1 freq
waatur (2) - 1 freq
baitic (2) - 1 freq
baiker (2) - 1 freq
naiture (2) - 4 freq
bettur (2) - 3 freq
bantu (2) - 1 freq
aftur (2) - 1 freq
matur (2) - 1 freq
baitur (0) - 4 freq
bator (2) - 1 freq
battur (2) - 1 freq
naitur (2) - 75 freq
baiturr (2) - 1 freq
biter (2) - 1 freq
baited (3) - 1 freq
artur (3) - 1 freq
raitir (3) - 1 freq
naiter (3) - 2 freq
baur (3) - 67 freq
baitert (3) - 1 freq
watur (3) - 1 freq
baits (3) - 3 freq
baiters (3) - 2 freq
baithe (3) - 3 freq
laiter (3) - 4 freq
baitter (3) - 1 freq
beater (3) - 11 freq
beter (3) - 1 freq
bair (3) - 1 freq
barter (3) - 3 freq
batter (3) - 74 freq
baither (3) - 2 freq
baith (3) - 1601 freq
SoundEx code - B360
bother - 329 freq
better - 1704 freq
bitter - 112 freq
batter - 74 freq
butter - 134 freq
'better - 9 freq
bather - 59 freq
baitur - 4 freq
baiturr - 1 freq
baither - 2 freq
badder - 5 freq
battery - 25 freq
betray - 10 freq
bator - 1 freq
buther - 11 freq
baitter - 1 freq
biter - 1 freq
batthrie - 1 freq
bettér - 4 freq
bittér - 1 freq
butterie - 7 freq
bathir - 2 freq
biether - 1 freq
'butterie' - 1 freq
bettèr - 32 freq
bethray - 2 freq
boather - 5 freq
boathir - 3 freq
better' - 3 freq
budder - 47 freq
bither - 12 freq
bettir - 12 freq
betther - 18 freq
bowder - 1 freq
battur - 1 freq
bettur - 3 freq
be-etter - 2 freq
be-e-e-etter - 1 freq
betaware - 1 freq
€˜betaware - 1 freq
buttery - 24 freq
buttir - 2 freq
bidder - 1 freq
beter - 1 freq
byde-ower - 1 freq
behauder - 2 freq
boathur - 1 freq
buddir - 3 freq
beater - 11 freq
buttrie - 4 freq
b-u-tt-r-ie - 1 freq
betterÂ’ - 1 freq
betterawa - 3 freq
“better - 1 freq
MetaPhone code - BTR
better - 1704 freq
bitter - 112 freq
batter - 74 freq
butter - 134 freq
'better - 9 freq
baitur - 4 freq
baiturr - 1 freq
badder - 5 freq
battery - 25 freq
betray - 10 freq
bator - 1 freq
baitter - 1 freq
biter - 1 freq
batthrie - 1 freq
bettér - 4 freq
bittér - 1 freq
butterie - 7 freq
'butterie' - 1 freq
bettèr - 32 freq
better' - 3 freq
budder - 47 freq
bettir - 12 freq
betther - 18 freq
bowder - 1 freq
battur - 1 freq
bettur - 3 freq
be-etter - 2 freq
be-e-e-etter - 1 freq
buttery - 24 freq
buttir - 2 freq
bidder - 1 freq
beter - 1 freq
buddir - 3 freq
beater - 11 freq
buttrie - 4 freq
b-u-tt-r-ie - 1 freq
betterÂ’ - 1 freq
“better - 1 freq
BAITUR
Time to execute Levenshtein function - 0.171812 milliseconds
The Levenshtein distance is the number of characters you have to replace, insert or delete to transform one word into another, its useful for detecting typos and alternative spellings
Time to execute Double Levenshtein function - 0.328647 milliseconds
In a stroke of genius, this runs the Levenshtein function twice, once without vowels and adds the distance together, giving double weight to consonants.
Time to execute SoundEx function - 0.027761 milliseconds
Soundex is a phonetic algorithm for indexing names by sound, as pronounced in English. The goal is for homophones to be encoded to the same representation so that they can be matched despite minor differences in spelling.
Time to execute MetaPhone function - 0.037354 milliseconds
Metaphone is a phonetic algorithm, published by Lawrence Philips in 1990, for indexing words by their English pronunciation.[1] It fundamentally improves on the Soundex algorithm by using information about variations and inconsistencies in English spelling and pronunciation to produce a more accurate encoding, which does a better job of matching words and names which sound similar.
Time to execute Manually curated function - 0.000884 milliseconds
Manual Curation uses a lookup table / lexicon which has been created by hand which links words to their lemmas, and includes obvious typos and spelling variations. Not all words are covered.