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 han in Corpus

Levenshtein Double Levenshtein SoundEx MetaPhone Manually curated
han (0) - 393 freq
hon (1) - 11 freq
havn (1) - 2 freq
hin (1) - 36 freq
hadn (1) - 2 freq
hat (1) - 177 freq
hai (1) - 4 freq
hant (1) - 6 freq
dan (1) - 472 freq
hain (1) - 63 freq
hag (1) - 2 freq
har (1) - 8 freq
hen (1) - 415 freq
hxn (1) - 1 freq
man (1) - 3502 freq
pan (1) - 137 freq
vhan (1) - 1 freq
chan (1) - 2 freq
harn (1) - 5 freq
van (1) - 161 freq
hang (1) - 48 freq
has (1) - 1383 freq
dhan (1) - 1 freq
hand (1) - 319 freq
ran (1) - 451 freq
han (0) - 393 freq
haan (1) - 95 freq
hen (1) - 415 freq
haun (1) - 931 freq
hun (1) - 9 freq
haen (1) - 156 freq
hn (1) - 3 freq
hain (1) - 63 freq
hane (1) - 4 freq
hin (1) - 36 freq
hon (1) - 11 freq
san (2) - 46 freq
kan (2) - 28 freq
heni (2) - 2 freq
shan (2) - 10 freq
hwn (2) - 1 freq
yan (2) - 1 freq
nan (2) - 14 freq
hauna (2) - 5 freq
had (2) - 4994 freq
fan (2) - 1367 freq
ha (2) - 181 freq
hank (2) - 9 freq
haq (2) - 1 freq
wan (2) - 2472 freq
SoundEx code - H500
him - 8459 freq
haun - 931 freq
hame - 2346 freq
hen - 415 freq
haein - 661 freq
hinnie - 24 freq
hyne - 56 freq
hon - 11 freq
'him - 3 freq
hinna - 86 freq
haan - 95 freq
hmm - 22 freq
haen - 156 freq
hyne-awa - 5 freq
haena - 49 freq
hem - 27 freq
hame' - 6 freq
him-how - 1 freq
how'm - 4 freq
-how'm - 1 freq
hain - 63 freq
hum - 45 freq
han - 393 freq
hayin - 5 freq
hm - 13 freq
hawn - 33 freq
'hmm - 1 freq
home - 280 freq
hume - 10 freq
hime - 17 freq
'hum - 2 freq
hinny - 24 freq
ha''in - 1 freq
hymn - 17 freq
'hame - 2 freq
hinnae - 50 freq
hoyon - 1 freq
haim - 39 freq
'ham - 3 freq
heem - 17 freq
him' - 15 freq
han' - 24 freq
ham - 49 freq
haean - 12 freq
hannah - 10 freq
heaney - 4 freq
hin - 36 freq
hoyin - 5 freq
'hen' - 2 freq
hane - 4 freq
hun - 9 freq
haenae - 18 freq
hee'm - 1 freq
'home - 1 freq
hannie - 3 freq
hine - 26 freq
honey - 413 freq
haein' - 6 freq
henna - 7 freq
hayen - 13 freq
hein - 2 freq
heim - 2 freq
heen - 4 freq
hen' - 2 freq
haun' - 2 freq
hyyyyyyyyyaaaaaaawwwn - 1 freq
ha'en - 5 freq
'hmmm - 2 freq
haime - 26 freq
'hen - 4 freq
ha'in - 9 freq
hiein - 1 freq
hennae - 1 freq
hae'in - 6 freq
hawin - 2 freq
heehawin - 1 freq
hunny - 3 freq
hïm - 575 freq
heyin - 1 freq
hyowin - 2 freq
hmmmm - 4 freq
honou' - 1 freq
hae'n - 2 freq
hym - 5 freq
hom - 38 freq
hoween - 1 freq
home' - 2 freq
hann - 23 freq
hummy - 1 freq
hae-in - 1 freq
haem - 53 freq
hemme - 2 freq
'home' - 1 freq
hæm - 2 freq
howan - 1 freq
hewn - 2 freq
hawaiian - 1 freq
hoam - 4 freq
hahn - 2 freq
heine - 3 freq
hyena - 4 freq
hyneawa - 2 freq
'haein - 1 freq
homo - 3 freq
'hame' - 3 freq
haenna - 3 freq
€˜haem - 1 freq
höm - 1 freq
houane - 5 freq
€˜hmm - 3 freq
haimm - 1 freq
hemmi - 1 freq
hanna - 11 freq
hannaa - 1 freq
hinney - 6 freq
hium - 1 freq
hyne-awaw - 1 freq
hayme - 1 freq
hine-awa - 1 freq
hame- - 1 freq
henny - 10 freq
€œhenny - 3 freq
hmi - 2 freq
himm - 1 freq
hammy - 7 freq
him--- - 1 freq
howein - 1 freq
€˜hmi - 1 freq
haun- - 1 freq
hennie - 6 freq
€œhemm - 1 freq
hemm - 12 freq
hima - 4 freq
€œhmm - 1 freq
€œhoney - 1 freq
€˜hame - 1 freq
€œhomo - 1 freq
ha'ein - 1 freq
€™hm - 1 freq
hny - 1 freq
haÂ’en - 1 freq
hn - 3 freq
heni - 2 freq
hwn - 1 freq
hanoi - 1 freq
haain - 1 freq
hina - 2 freq
hameÂ’ - 1 freq
hmmm - 7 freq
hanÂ’ - 2 freq
haÂ’in - 2 freq
heain' - 1 freq
hinn - 1 freq
hmo - 1 freq
hen” - 1 freq
hauna - 5 freq
hame” - 2 freq
“hame - 1 freq
‘hen’ - 2 freq
hunni - 5 freq
hamm - 1 freq
hyme - 6 freq
“home - 1 freq
“hyme - 1 freq
hyme” - 1 freq
hawn' - 2 freq
hanny - 1 freq
MetaPhone code - HN
haun - 931 freq
hen - 415 freq
haein - 661 freq
hinnie - 24 freq
hon - 11 freq
hinna - 86 freq
haan - 95 freq
haen - 156 freq
haena - 49 freq
hain - 63 freq
han - 393 freq
hawn - 33 freq
hinny - 24 freq
ha''in - 1 freq
hinnae - 50 freq
han' - 24 freq
haean - 12 freq
hannah - 10 freq
heaney - 4 freq
hin - 36 freq
'hen' - 2 freq
hane - 4 freq
hun - 9 freq
haenae - 18 freq
hannie - 3 freq
hine - 26 freq
honey - 413 freq
haein' - 6 freq
henna - 7 freq
hein - 2 freq
heen - 4 freq
hen' - 2 freq
haun' - 2 freq
ha'en - 5 freq
'hen - 4 freq
ha'in - 9 freq
hiein - 1 freq
hennae - 1 freq
hae'in - 6 freq
hunny - 3 freq
wwhan - 1 freq
honou' - 1 freq
hae'n - 2 freq
hann - 23 freq
hae-in - 1 freq
hewn - 2 freq
hahn - 2 freq
heine - 3 freq
'haein - 1 freq
haenna - 3 freq
houane - 5 freq
hanna - 11 freq
hannaa - 1 freq
hinney - 6 freq
henny - 10 freq
€œhenny - 3 freq
haun- - 1 freq
hennie - 6 freq
€œhoney - 1 freq
houghin - 1 freq
ha'ein - 1 freq
haÂ’en - 1 freq
heni - 2 freq
hanoi - 1 freq
haain - 1 freq
hina - 2 freq
hanÂ’ - 2 freq
haÂ’in - 2 freq
heain' - 1 freq
hinn - 1 freq
hen” - 1 freq
hauna - 5 freq
heughan - 1 freq
‘hen’ - 2 freq
hunni - 5 freq
hawn' - 2 freq
hanny - 1 freq
HAN
haun - 931 freq
hauns - 526 freq
haund - 384 freq
haunds - 234 freq
haundit - 63 freq
nearhaund - 16 freq
hook-haundit - 17 freq
hand - 319 freq
hands - 175 freq
handed - 49 freq
second-haund - 6 freq
hannit - 20 freq
hans - 206 freq
han - 393 freq
Time to execute Levenshtein function - 0.184904 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 - 0.362398 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 - 0.028107 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 - 0.044322 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 - 0.000938 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.