A Corpus of 21st Century Scots Texts

Intro a b c d e f g h i j k l m n o p q r s t u v w x y z Texts Writers Statistics Top200 Search Compare

Levenshtein Distance

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

- basic concord - pre-sorted concord - post-sorted concord - map and chronology - chronogrid - fine-grain concord -

Similar words to amiss in Corpus

Levenshtein Double Levenshtein SoundEx MetaPhone Manually curated
amiss (0) - 16 freq
amids (1) - 1 freq
aiss (1) - 3 freq
'miss (1) - 23 freq
a-miss (1) - 1 freq
miss (1) - 956 freq
wiss (2) - 72 freq
piss (2) - 72 freq
ais (2) - 18 freq
am's (2) - 2 freq
kyiss (2) - 1 freq
eiss (2) - 31 freq
mids (2) - 70 freq
muss (2) - 7 freq
ameise (2) - 1 freq
mists (2) - 8 freq
damies (2) - 1 freq
uiss (2) - 132 freq
amico (2) - 1 freq
yuiss (2) - 16 freq
mess (2) - 103 freq
riss (2) - 2 freq
aisse (2) - 4 freq
swiss (2) - 26 freq
amigo (2) - 3 freq
amiss (0) - 16 freq
miss (1) - 956 freq
mess (2) - 103 freq
moss (2) - 99 freq
mss (2) - 2 freq
missa (2) - 1 freq
mass (2) - 70 freq
muss (2) - 7 freq
missy (2) - 3 freq
aiss (2) - 3 freq
amids (2) - 1 freq
'miss (2) - 23 freq
a-miss (2) - 1 freq
miss' (3) - 2 freq
abyss (3) - 11 freq
oiss (3) - 1 freq
mics (3) - 2 freq
'iss (3) - 1 freq
fiss (3) - 5 freq
amigos (3) - 2 freq
yiss (3) - 22 freq
kiss (3) - 123 freq
aless (3) - 26 freq
acoss (3) - 1 freq
hiss (3) - 21 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 - AMS
amuse - 8 freq
awmous - 4 freq
aims - 14 freq
a-miss - 1 freq
amaze - 4 freq
aums - 1 freq
amiss - 16 freq
amos - 3 freq
am's - 2 freq
aamos - 5 freq
amboise - 3 freq
ameise - 1 freq
ameuse - 1 freq
aimee's - 1 freq
amys - 1 freq
ammys - 1 freq
AMISS
Time to execute Levenshtein function - 0.270116 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 - 0.431583 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 - 0.028745 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 - 0.037272 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 - 0.000935 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.