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 hunde in Corpus

Levenshtein Double Levenshtein SoundEx MetaPhone Manually curated
hunde (0) - 1 freq
hunds (1) - 3 freq
hunda (1) - 1 freq
hunder (1) - 96 freq
hund (1) - 1 freq
hende (1) - 1 freq
hulme (2) - 1 freq
hindi (2) - 2 freq
hunkie (2) - 20 freq
hunky (2) - 2 freq
honds (2) - 1 freq
gundge (2) - 1 freq
handen (2) - 1 freq
bund (2) - 12 freq
hunt (2) - 62 freq
hurd (2) - 2 freq
suede (2) - 2 freq
hudnae (2) - 62 freq
hunxed (2) - 1 freq
gundy (2) - 4 freq
chunse (2) - 15 freq
hure (2) - 12 freq
hunch (2) - 3 freq
hundret (2) - 2 freq
fundy (2) - 1 freq
hunde (0) - 1 freq
hende (1) - 1 freq
hund (1) - 1 freq
hunda (1) - 1 freq
handee (2) - 4 freq
handie (2) - 3 freq
handy (2) - 56 freq
hind (2) - 14 freq
haundy (2) - 18 freq
hindu (2) - 8 freq
haund (2) - 384 freq
hynd (2) - 1 freq
haundie (2) - 1 freq
hound (2) - 11 freq
hnd (2) - 3 freq
hunder (2) - 96 freq
hond (2) - 3 freq
hand (2) - 319 freq
hindi (2) - 2 freq
hunds (2) - 3 freq
hung (3) - 159 freq
haand (3) - 104 freq
hinge (3) - 5 freq
mundie (3) - 4 freq
hundog (3) - 1 freq
SoundEx code - H530
haund - 384 freq
hummed - 10 freq
handy - 56 freq
haundie - 1 freq
haunt - 28 freq
hin't - 1 freq
haunit - 2 freq
hint - 78 freq
hoond - 2 freq
hand - 319 freq
hant - 6 freq
hunt - 62 freq
honed - 5 freq
him-it - 1 freq
hent - 6 freq
haundy - 18 freq
hannit - 20 freq
hantie - 4 freq
hamewith - 9 freq
hained - 27 freq
honey-dew - 1 freq
haunmaid - 1 freq
handee - 4 freq
handie - 3 freq
hind - 14 freq
haun't - 4 freq
hemmed - 3 freq
'haund - 3 freq
hem't - 1 freq
hannet - 2 freq
hummit - 1 freq
haand - 104 freq
hindu - 8 freq
him-hit - 1 freq
honeyed - 1 freq
hunda - 1 freq
haun-med - 1 freq
hainit - 6 freq
him-id - 1 freq
houmit - 1 freq
hunde - 1 freq
hinnied - 1 freq
hamada - 1 freq
haint - 3 freq
haunnit - 2 freq
hende - 1 freq
heymouthe - 1 freq
hynd - 1 freq
€œhunty - 1 freq
hound - 11 freq
€œhand - 1 freq
hnd - 3 freq
hindi - 2 freq
hond - 3 freq
henwudie - 1 freq
henwuddie - 3 freq
haun-made - 1 freq
hammett - 1 freq
heymooth - 1 freq
huntie - 1 freq
heynd - 1 freq
hmt - 1 freq
‘hand - 1 freq
hnuty - 1 freq
hmdt - 1 freq
honeat - 1 freq
hund - 1 freq
hnid - 1 freq
hunt' - 1 freq
handw - 1 freq
MetaPhone code - HNT
haund - 384 freq
handy - 56 freq
haundie - 1 freq
haunt - 28 freq
hin't - 1 freq
haunit - 2 freq
hint - 78 freq
hoond - 2 freq
hand - 319 freq
hant - 6 freq
hunt - 62 freq
honed - 5 freq
hent - 6 freq
haundy - 18 freq
hannit - 20 freq
hantie - 4 freq
hained - 27 freq
honey-dew - 1 freq
handee - 4 freq
handie - 3 freq
hind - 14 freq
haun't - 4 freq
'haund - 3 freq
hannet - 2 freq
haand - 104 freq
hindu - 8 freq
hunda - 1 freq
hainit - 6 freq
hunde - 1 freq
hinnied - 1 freq
haint - 3 freq
haunnit - 2 freq
hende - 1 freq
€œhunty - 1 freq
hound - 11 freq
€œhand - 1 freq
hindi - 2 freq
hond - 3 freq
huntie - 1 freq
heynd - 1 freq
‘hand - 1 freq
honeat - 1 freq
hund - 1 freq
hunt' - 1 freq
handw - 1 freq
HUNDE
Time to execute Levenshtein function - 0.216326 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 - 0.353171 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 - 0.027793 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 - 0.037551 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 - 0.000884 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.