A Corpus of 21st Century Scots Texts

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Levenshtein Distance

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

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Similar words to sensors in Corpus

Levenshtein Double Levenshtein SoundEx MetaPhone Manually curated
sensors (0) - 1 freq
sensory (1) - 4 freq
censors (1) - 1 freq
seniors (1) - 2 freq
sensored (2) - 1 freq
censor (2) - 3 freq
sensins (2) - 1 freq
sectors (2) - 13 freq
senior (2) - 40 freq
senses (2) - 56 freq
seasons (2) - 39 freq
senders (2) - 1 freq
tenors (2) - 1 freq
sentor (2) - 1 freq
bentos (3) - 1 freq
benson (3) - 1 freq
ensures (3) - 3 freq
snore (3) - 6 freq
snorl (3) - 21 freq
sensit (3) - 1 freq
mennirs (3) - 1 freq
sponsor (3) - 3 freq
stressors (3) - 1 freq
jonsars (3) - 3 freq
shoors (3) - 34 freq
sensors (0) - 1 freq
seniors (2) - 2 freq
censors (2) - 1 freq
sensory (2) - 4 freq
senses (3) - 56 freq
senders (3) - 1 freq
sensins (3) - 1 freq
sensored (3) - 1 freq
senatours (4) - 1 freq
sinners (4) - 8 freq
sneers (4) - 2 freq
snpers (4) - 2 freq
singers (4) - 55 freq
saasers (4) - 1 freq
sinses (4) - 2 freq
awnsers (4) - 1 freq
pansers (4) - 2 freq
unnsers (4) - 1 freq
jonsars (4) - 3 freq
sanners (4) - 2 freq
sinders (4) - 4 freq
yessers (4) - 2 freq
tenors (4) - 1 freq
sentor (4) - 1 freq
seasons (4) - 39 freq
SoundEx code - S526
snickerin - 5 freq
smacher - 2 freq
singers - 55 freq
singer - 47 freq
singer's - 2 freq
snocherin - 7 freq
smokers' - 4 freq
sincerely - 8 freq
sincere - 13 freq
sneegart - 1 freq
sneegert - 1 freq
sniggerin - 6 freq
sincerity - 3 freq
snochert - 1 freq
snickert - 1 freq
smoker - 2 freq
smasher - 4 freq
sanquhar - 9 freq
semi-circles - 1 freq
smickered - 1 freq
smickert - 1 freq
snicheren - 2 freq
smokers - 8 freq
sing-greet - 1 freq
sniggers - 5 freq
smugger - 1 freq
smickerin - 2 freq
sangria - 2 freq
snichered - 2 freq
snicher - 3 freq
skincare - 1 freq
smachrie - 2 freq
sniggered - 4 freq
singers' - 2 freq
sniggern - 9 freq
sniggert - 5 freq
smoker's - 2 freq
snooker - 16 freq
synchronised - 1 freq
snocher - 6 freq
snochered - 1 freq
smackaroonies - 2 freq
snicker - 1 freq
shae-makker - 1 freq
shae-maakers - 1 freq
smaikrie - 1 freq
sensory-seutid - 1 freq
sneegired - 1 freq
sneegirs - 1 freq
sanger - 1 freq
sheanchara - 1 freq
snicheran - 1 freq
snicherin - 1 freq
snickered - 1 freq
snigger' - 1 freq
snichert - 2 freq
sanchar - 1 freq
smacker - 3 freq
syncretism - 1 freq
snashers - 1 freq
snickerin' - 1 freq
shoemaker-levy - 1 freq
smacherie - 1 freq
synchronise - 1 freq
snookert - 1 freq
sensoryattachmentintervention - 1 freq
sensory - 4 freq
snochrie - 12 freq
singer-sangwriters - 1 freq
sanskrit - 1 freq
semi-circle - 1 freq
somequhaar - 1 freq
smicker - 1 freq
€œsincerely - 1 freq
synchronically - 1 freq
smacherry - 2 freq
sunscreem - 6 freq
smokiered - 16 freq
samcornwell - 1 freq
skinnycortado - 1 freq
sincerest - 1 freq
shingaurds - 1 freq
smoocher - 3 freq
shaunwkearney - 1 freq
sunnygradio - 1 freq
sensored - 1 freq
sonjahern - 1 freq
sinker - 1 freq
samgray - 29 freq
seanmccrory - 1 freq
snookers - 1 freq
sensors - 1 freq
snickers - 1 freq
sammgreer - 14 freq
suncream - 1 freq
MetaPhone code - SNSRS
censors - 1 freq
sensors - 1 freq
SENSORS
Time to execute Levenshtein function - 0.196310 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 - 0.365998 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 - 0.027309 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 - 0.037035 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 - 0.000932 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.