A Corpus of 21st Century Scots Texts

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Levenshtein Distance

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

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Similar words to bount in Corpus

Levenshtein Double Levenshtein SoundEx MetaPhone Manually curated
bount (0) - 1 freq
brount (1) - 2 freq
bouns (1) - 1 freq
bunt (1) - 6 freq
boun' (1) - 1 freq
bound (1) - 58 freq
count (1) - 45 freq
boult (1) - 1 freq
blunt (1) - 9 freq
brunt (1) - 73 freq
boun (1) - 10 freq
mount (1) - 30 freq
bout (1) - 14 freq
bounty (1) - 10 freq
fount (1) - 2 freq
bouet (1) - 2 freq
coun (2) - 1 freq
aboun (2) - 1 freq
blurt (2) - 1 freq
daunt (2) - 3 freq
souns (2) - 52 freq
doukt (2) - 3 freq
doune (2) - 3 freq
boure (2) - 1 freq
lunt (2) - 5 freq
bount (0) - 1 freq
bunt (1) - 6 freq
bounty (1) - 10 freq
bouet (2) - 2 freq
fount (2) - 2 freq
bunty (2) - 12 freq
bint (2) - 10 freq
boonty (2) - 1 freq
bent (2) - 104 freq
mount (2) - 30 freq
baint (2) - 1 freq
bout (2) - 14 freq
bound (2) - 58 freq
boun' (2) - 1 freq
bouns (2) - 1 freq
brount (2) - 2 freq
boult (2) - 1 freq
count (2) - 45 freq
boun (2) - 10 freq
blunt (2) - 9 freq
brunt (2) - 73 freq
bund (3) - 12 freq
bot (3) - 437 freq
cunt (3) - 447 freq
rounit (3) - 1 freq
SoundEx code - B530
boomed - 8 freq
bendie - 2 freq
bendy - 3 freq
bent - 104 freq
bunnet - 113 freq
bandy - 13 freq
bend - 102 freq
bound - 58 freq
beneath - 35 freq
band - 181 freq
bind - 20 freq
bonnie-die - 1 freq
bounty - 10 freq
behind - 261 freq
beamed - 6 freq
bund - 12 freq
beyond - 102 freq
bunnet' - 2 freq
bammed - 1 freq
baund - 21 freq
boond - 9 freq
bummed - 11 freq
bonnet - 34 freq
boannet - 1 freq
bunt - 6 freq
binweed - 1 freq
bond - 17 freq
banned - 35 freq
beyont - 7 freq
boned - 2 freq
behint - 5 freq
bannit - 2 freq
baint - 1 freq
bint - 10 freq
banty - 5 freq
bunty - 12 freq
baundy - 2 freq
bondie - 3 freq
baand - 13 freq
bantie - 3 freq
bundie - 1 freq
bumed - 1 freq
bumt - 1 freq
bouned - 3 freq
boonty - 1 freq
'behind' - 1 freq
bunnit - 1 freq
behiynd - 1 freq
bayonet - 6 freq
bonnieheid - 1 freq
beand - 1 freq
binwuid - 1 freq
'beyond - 1 freq
beande - 1 freq
bennett - 6 freq
behynde - 1 freq
bonnie-ee'd - 1 freq
bount - 1 freq
buoyant - 2 freq
bannid - 1 freq
bend-o - 1 freq
boyndie - 6 freq
bennite - 1 freq
€˜band - 2 freq
bmd - 1 freq
bnto - 1 freq
byamat - 1 freq
bannet - 1 freq
bond” - 1 freq
bantu - 1 freq
bindie - 1 freq
binned - 1 freq
bunnet” - 1 freq
MetaPhone code - BNT
bendie - 2 freq
bendy - 3 freq
bent - 104 freq
bunnet - 113 freq
bandy - 13 freq
bend - 102 freq
bound - 58 freq
band - 181 freq
bind - 20 freq
bonnie-die - 1 freq
bounty - 10 freq
bund - 12 freq
bunnet' - 2 freq
baund - 21 freq
boond - 9 freq
bonnet - 34 freq
boannet - 1 freq
bunt - 6 freq
bond - 17 freq
banned - 35 freq
boned - 2 freq
bannit - 2 freq
baint - 1 freq
bint - 10 freq
banty - 5 freq
bunty - 12 freq
baundy - 2 freq
bondie - 3 freq
baand - 13 freq
bantie - 3 freq
bundie - 1 freq
bouned - 3 freq
boonty - 1 freq
bunnit - 1 freq
beand - 1 freq
beande - 1 freq
bennett - 6 freq
behynde - 1 freq
bonnie-ee'd - 1 freq
bount - 1 freq
bannid - 1 freq
bend-o - 1 freq
boyndie - 6 freq
bennite - 1 freq
€˜band - 2 freq
bnto - 1 freq
bannet - 1 freq
bond” - 1 freq
bantu - 1 freq
bindie - 1 freq
binned - 1 freq
bunnet” - 1 freq
BOUNT
Time to execute Levenshtein function - 0.322239 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 - 0.592629 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 - 0.027628 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 - 0.070889 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 - 0.000887 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.