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 mairrit in Corpus

Levenshtein Double Levenshtein SoundEx MetaPhone Manually curated
mairrit (0) - 59 freq
mairmit (1) - 1 freq
mairit (1) - 11 freq
mairkit (1) - 4 freq
'mairrit (1) - 1 freq
eairrit (1) - 3 freq
cairrit (1) - 27 freq
mairret (1) - 17 freq
marrit (1) - 1 freq
mairrie (1) - 7 freq
hairrit (1) - 1 freq
mairriet (1) - 55 freq
cairryit (2) - 2 freq
mairiet (2) - 4 freq
marriet (2) - 15 freq
marlit (2) - 1 freq
nairrie (2) - 1 freq
cairryt (2) - 1 freq
cairtit (2) - 11 freq
mairried (2) - 40 freq
mairry (2) - 43 freq
mairries (2) - 8 freq
mairnt (2) - 1 freq
marit (2) - 1 freq
cairit (2) - 6 freq
mairrit (0) - 59 freq
mairret (1) - 17 freq
marrit (1) - 1 freq
mairriet (1) - 55 freq
hairrit (2) - 1 freq
marriet (2) - 15 freq
muirret (2) - 1 freq
marriot (2) - 1 freq
mairrie (2) - 7 freq
merrit (2) - 6 freq
mairkit (2) - 4 freq
mairit (2) - 11 freq
'mairrit (2) - 1 freq
mairmit (2) - 1 freq
cairrit (2) - 27 freq
eairrit (2) - 3 freq
nairriet (3) - 1 freq
varrit (3) - 1 freq
mairryin (3) - 12 freq
magrit (3) - 1 freq
midrit (3) - 1 freq
cairriet (3) - 70 freq
mirdit (3) - 1 freq
merriet (3) - 39 freq
mairket (3) - 20 freq
SoundEx code - M630
mairrit - 59 freq
mort - 3 freq
mairried - 40 freq
mairiet - 4 freq
married - 29 freq
mairriet - 55 freq
marred - 5 freq
mired - 2 freq
mirth - 10 freq
merit - 16 freq
moored - 2 freq
merriet - 39 freq
mairret - 17 freq
marta - 1 freq
'mairrit - 1 freq
mart - 25 freq
merried - 14 freq
mird - 6 freq
mardi - 2 freq
martha - 7 freq
mairied - 10 freq
mairie't - 1 freq
moort - 4 freq
mayritt - 1 freq
mairit - 11 freq
myriad - 11 freq
mairt - 5 freq
marriet - 15 freq
merde - 1 freq
mairtha - 3 freq
muirret - 1 freq
moorit - 8 freq
merrried - 1 freq
mert - 1 freq
mereat - 1 freq
murdo - 18 freq
merrit - 6 freq
murriet - 1 freq
marrit - 1 freq
marit - 1 freq
mairead - 5 freq
maerried - 1 freq
marriot - 1 freq
moretti - 1 freq
morde - 1 freq
merida - 1 freq
muirhead - 1 freq
MetaPhone code - MRT
mairrit - 59 freq
mort - 3 freq
mairried - 40 freq
mairiet - 4 freq
married - 29 freq
mairriet - 55 freq
marred - 5 freq
mired - 2 freq
merit - 16 freq
moored - 2 freq
merriet - 39 freq
mairret - 17 freq
marta - 1 freq
'mairrit - 1 freq
mart - 25 freq
merried - 14 freq
mird - 6 freq
mardi - 2 freq
mairied - 10 freq
mairie't - 1 freq
moort - 4 freq
mayritt - 1 freq
mairit - 11 freq
myriad - 11 freq
mairt - 5 freq
marriet - 15 freq
merde - 1 freq
muirret - 1 freq
moorit - 8 freq
merrried - 1 freq
mert - 1 freq
mereat - 1 freq
murdo - 18 freq
merrit - 6 freq
murriet - 1 freq
marrit - 1 freq
marit - 1 freq
mairead - 5 freq
maerried - 1 freq
marriot - 1 freq
moretti - 1 freq
morde - 1 freq
merida - 1 freq
MAIRRIT
Time to execute Levenshtein function - 0.223879 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 - 0.346813 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 - 0.027003 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 - 0.036971 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 - 0.000780 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.