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 aneuch in Corpus

Levenshtein Double Levenshtein SoundEx MetaPhone Manually curated
aneuch (0) - 31 freq
eneuch (1) - 751 freq
aneoch (1) - 2 freq
aneugh (1) - 15 freq
beuch (2) - 2 freq
anyoch (2) - 25 freq
heuch (2) - 6 freq
yeuch (2) - 5 freq
reuch (2) - 17 freq
aneuch's (2) - 1 freq
enouch (2) - 4 freq
an-ugh (2) - 1 freq
bleuch (2) - 2 freq
pleuch (2) - 12 freq
eneugh (2) - 49 freq
wreuch (2) - 1 freq
cheuch (2) - 2 freq
aneith (2) - 8 freq
feuch (2) - 2 freq
eneoch (2) - 2 freq
eneuch- (2) - 1 freq
euch (2) - 1 freq
auch (2) - 3 freq
tyeuch (2) - 1 freq
abeich (2) - 6 freq
aneuch (0) - 31 freq
aneoch (1) - 2 freq
eneuch (1) - 751 freq
eneoch (2) - 2 freq
enuch (2) - 89 freq
enouch (2) - 4 freq
aneugh (2) - 15 freq
anyoch (2) - 25 freq
an-och (3) - 1 freq
aneath (3) - 106 freq
'yeuch (3) - 1 freq
abeich (3) - 6 freq
tyeuch (3) - 1 freq
unich (3) - 1 freq
aneth (3) - 178 freq
eheuch (3) - 1 freq
noch (3) - 2 freq
auch (3) - 3 freq
leuch (3) - 96 freq
enyoch (3) - 36 freq
eneueh (3) - 2 freq
teuch (3) - 31 freq
eneuch- (3) - 1 freq
enoch (3) - 17 freq
inch (3) - 51 freq
SoundEx code - A520
aince - 459 freq
ang - 8 freq
aneugh - 15 freq
aneuch - 31 freq
anes - 222 freq
ain-och - 1 freq
an---och - 1 freq
anyweys - 1 freq
ance - 72 freq
awns - 17 freq
angie - 36 freq
'angie - 5 freq
anxi - 4 freq
anas - 9 freq
anyways - 12 freq
amuse - 8 freq
awmous - 4 freq
ane's - 11 freq
annoys - 4 freq
amok - 1 freq
aims - 14 freq
a-miss - 1 freq
annie's - 8 freq
aeons - 1 freq
amyoose - 1 freq
ains - 15 freq
amaze - 4 freq
anna's - 3 freq
amoco - 1 freq
annnnngggggggeeeeeewwwahhh - 1 freq
anq - 2 freq
aums - 1 freq
aeneas - 3 freq
anes' - 2 freq
'aince - 1 freq
an-och - 1 freq
amiss - 16 freq
anagh - 1 freq
an-ugh - 1 freq
ann's - 4 freq
anne's - 2 freq
annas - 2 freq
amos - 3 freq
am's - 2 freq
an's - 4 freq
amnesia - 1 freq
ank - 1 freq
anyoch - 25 freq
aamos - 5 freq
annies - 1 freq
ameise - 1 freq
aence - 8 freq
ameuse - 1 freq
annexe - 1 freq
anso - 1 freq
amuck - 1 freq
ans - 2 freq
aa'hing - 5 freq
anse - 4 freq
aneoch - 2 freq
an'-qh - 1 freq
ain's - 3 freq
aans - 1 freq
annays - 1 freq
'anus' - 1 freq
€œaneugh - 1 freq
annex - 4 freq
€œaince - 4 freq
amico - 1 freq
a-muigh - 1 freq
ange - 1 freq
anzio - 1 freq
aeyhing - 1 freq
€™ang - 2 freq
aines - 2 freq
ahing - 1 freq
anns - 1 freq
awmox - 1 freq
angieh - 1 freq
aÂ’hinÂ’s - 1 freq
aneÂ’s - 1 freq
aimee's - 1 freq
anyhoos - 13 freq
aeonmag - 1 freq
a'hing - 4 freq
annjj - 1 freq
aewing - 1 freq
ayoung - 1 freq
amigo - 3 freq
amys - 1 freq
amc - 1 freq
annec - 3 freq
ammys - 1 freq
MetaPhone code - ANX
aneuch - 31 freq
ain-och - 1 freq
an---och - 1 freq
an-och - 1 freq
aneoch - 2 freq
ANEUCH
Time to execute Levenshtein function - 0.186328 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 - 0.320152 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 - 0.028065 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 - 0.036970 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 - 0.000939 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.