A Corpus of 21st Century Scots Texts

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Gauld, Ilene


Total words by this author in corpus - 914
Total unique words used by this author in corpus - 411
Ratio of total words to unique words - 2.224
Top ten most common words - a, i, the, we, €™, €™s, tae, an, fit, ma,

Word frequency analysis

For these graphs we normalise the words used by the author to occurrences per million, and we calculate a similar normalised number of occurrences for the same word in each dialect. The author's norm is plotted against each dialect's norm in each graph.
If the dots line up with the diagonal line then the author is using words found in that dialect in about the typical frequency expected.
If the dots are below the dotted line, then the author's words are not found in the dialect as often as expected.
If the dots are along the y-axis, the words are not found in that dialect.
To save memory only the most frequent 200 words of the author's work are plotted.

Central
a 460 author per 10,000 262 dialect per 10,000 i 317 author per 10,000 38 dialect per 10,000 the 295 author per 10,000 564 dialect per 10,000 we 208 author per 10,000 34 dialect per 10,000 €™ 197 author per 10,000 45 dialect per 10,000 €™s 197 author per 10,000 36 dialect per 10,000 tae 186 author per 10,000 212 dialect per 10,000 an 175 author per 10,000 215 dialect per 10,000 fit 164 author per 10,000 2 dialect per 10,000 ma 164 author per 10,000 51 dialect per 10,000 in 142 author per 10,000 148 dialect per 10,000 he 131 author per 10,000 90 dialect per 10,000 o 131 author per 10,000 187 dialect per 10,000 that 120 author per 10,000 108 dialect per 10,000 it 109 author per 10,000 119 dialect per 10,000 hiv 109 author per 10,000 2 dialect per 10,000 wis 109 author per 10,000 99 dialect per 10,000 ees 98 author per 10,000 0 dialect per 10,000 for 88 author per 10,000 46 dialect per 10,000 on 77 author per 10,000 54 dialect per 10,000 wi 77 author per 10,000 64 dialect per 10,000 €™d 77 author per 10,000 7 dialect per 10,000 us 66 author per 10,000 15 dialect per 10,000 and 66 author per 10,000 104 dialect per 10,000 them 66 author per 10,000 18 dialect per 10,000 fin 55 author per 10,000 1 dialect per 10,000 €™ll 55 author per 10,000 5 dialect per 10,000 or 55 author per 10,000 29 dialect per 10,000 so 55 author per 10,000 10 dialect per 10,000 see 55 author per 10,000 17 dialect per 10,000 be 55 author per 10,000 49 dialect per 10,000 up 55 author per 10,000 40 dialect per 10,000 canna 55 author per 10,000 3 dialect per 10,000 jist 55 author per 10,000 22 dialect per 10,000 at 55 author per 10,000 58 dialect per 10,000 she 55 author per 10,000 57 dialect per 10,000 well 55 author per 10,000 5 dialect per 10,000 zyne 44 author per 10,000 0 dialect per 10,000 magic 44 author per 10,000 1 dialect per 10,000 €™m 44 author per 10,000 6 dialect per 10,000 get 44 author per 10,000 15 dialect per 10,000 ken 44 author per 10,000 14 dialect per 10,000 lang 44 author per 10,000 9 dialect per 10,000 nae 44 author per 10,000 22 dialect per 10,000 tractor 44 author per 10,000 0 dialect per 10,000 been 44 author per 10,000 19 dialect per 10,000 dinna 33 author per 10,000 4 dialect per 10,000 €¦ 33 author per 10,000 1 dialect per 10,000 auld 33 author per 10,000 13 dialect per 10,000 bob 33 author per 10,000 0 dialect per 10,000 there 33 author per 10,000 24 dialect per 10,000 dad 33 author per 10,000 1 dialect per 10,000 is 33 author per 10,000 61 dialect per 10,000 day 33 author per 10,000 14 dialect per 10,000 these 33 author per 10,000 4 dialect per 10,000 her 33 author per 10,000 45 dialect per 10,000 ye 33 author per 10,000 60 dialect per 10,000 bit 33 author per 10,000 17 dialect per 10,000 as 33 author per 10,000 60 dialect per 10,000 tartan 33 author per 10,000 0 dialect per 10,000 will 33 author per 10,000 11 dialect per 10,000 sean 33 author per 10,000 0 dialect per 10,000 noo 33 author per 10,000 13 dialect per 10,000 special 33 author per 10,000 1 dialect per 10,000 zynes 33 author per 10,000 0 dialect per 10,000 dunlop 33 author per 10,000 0 dialect per 10,000 rose 33 author per 10,000 1 dialect per 10,000 €™ve 33 author per 10,000 4 dialect per 10,000 sash 33 author per 10,000 0 dialect per 10,000 caad 33 author per 10,000 0 dialect per 10,000 beets 22 author per 10,000 0 dialect per 10,000 fairies 22 author per 10,000 0 dialect per 10,000 pit 22 author per 10,000 9 dialect per 10,000 dress 22 author per 10,000 0 dialect per 10,000 tinkerbell 22 author per 10,000 0 dialect per 10,000 camouflage 22 author per 10,000 0 dialect per 10,000 oot 22 author per 10,000 40 dialect per 10,000 me 22 author per 10,000 40 dialect per 10,000 only 22 author per 10,000 5 dialect per 10,000 invited 22 author per 10,000 0 dialect per 10,000 brilliant 22 author per 10,000 0 dialect per 10,000 kin 22 author per 10,000 5 dialect per 10,000 hubby 22 author per 10,000 0 dialect per 10,000 breeks 22 author per 10,000 0 dialect per 10,000 am 22 author per 10,000 3 dialect per 10,000 kilt 22 author per 10,000 0 dialect per 10,000 telt 22 author per 10,000 5 dialect per 10,000 lik 22 author per 10,000 5 dialect per 10,000 say 22 author per 10,000 10 dialect per 10,000 said 22 author per 10,000 44 dialect per 10,000 gings 22 author per 10,000 0 dialect per 10,000 ee 22 author per 10,000 2 dialect per 10,000 hear 22 author per 10,000 4 dialect per 10,000 bonnie 22 author per 10,000 2 dialect per 10,000 ae 22 author per 10,000 24 dialect per 10,000 wird 22 author per 10,000 1 dialect per 10,000 bade 22 author per 10,000 0 dialect per 10,000 een 22 author per 10,000 5 dialect per 10,000 name 22 author per 10,000 4 dialect per 10,000 yer 22 author per 10,000 18 dialect per 10,000 mine 22 author per 10,000 1 dialect per 10,000 lobby 22 author per 10,000 0 dialect per 10,000 didna 22 author per 10,000 5 dialect per 10,000 him 22 author per 10,000 29 dialect per 10,000 flat 22 author per 10,000 1 dialect per 10,000 macintyre 22 author per 10,000 0 dialect per 10,000 weel 22 author per 10,000 9 dialect per 10,000 his 22 author per 10,000 56 dialect per 10,000 abody 22 author per 10,000 0 dialect per 10,000 back 22 author per 10,000 20 dialect per 10,000 afore 22 author per 10,000 9 dialect per 10,000 has 22 author per 10,000 5 dialect per 10,000 wee 22 author per 10,000 28 dialect per 10,000 this 22 author per 10,000 43 dialect per 10,000 time 22 author per 10,000 17 dialect per 10,000 off 22 author per 10,000 1 dialect per 10,000 my 22 author per 10,000 6 dialect per 10,000 sang 22 author per 10,000 2 dialect per 10,000 doric 22 author per 10,000 0 dialect per 10,000 syne 22 author per 10,000 6 dialect per 10,000 which 22 author per 10,000 5 dialect per 10,000 wir 22 author per 10,000 4 dialect per 10,000 but 22 author per 10,000 47 dialect per 10,000 to 22 author per 10,000 9 dialect per 10,000 bairns 22 author per 10,000 5 dialect per 10,000 sufferers 11 author per 10,000 0 dialect per 10,000 tartans 11 author per 10,000 0 dialect per 10,000 zing 11 author per 10,000 0 dialect per 10,000 suggested 11 author per 10,000 0 dialect per 10,000 zilence 11 author per 10,000 0 dialect per 10,000 zit 11 author per 10,000 0 dialect per 10,000 same 11 author per 10,000 6 dialect per 10,000 hid 11 author per 10,000 2 dialect per 10,000 thocht 11 author per 10,000 8 dialect per 10,000 wrang 11 author per 10,000 2 dialect per 10,000 check 11 author per 10,000 1 dialect per 10,000 chappie 11 author per 10,000 0 dialect per 10,000 fa 11 author per 10,000 0 dialect per 10,000 exactly 11 author per 10,000 1 dialect per 10,000 stock 11 author per 10,000 0 dialect per 10,000 shock 11 author per 10,000 0 dialect per 10,000 min 11 author per 10,000 0 dialect per 10,000 nelly 11 author per 10,000 0 dialect per 10,000 tee 11 author per 10,000 0 dialect per 10,000 put 11 author per 10,000 1 dialect per 10,000 come 11 author per 10,000 9 dialect per 10,000 happy 11 author per 10,000 1 dialect per 10,000 fellow 11 author per 10,000 0 dialect per 10,000 kent 11 author per 10,000 6 dialect per 10,000 sing 11 author per 10,000 1 dialect per 10,000 intil 11 author per 10,000 2 dialect per 10,000 eradicate 11 author per 10,000 0 dialect per 10,000 their 11 author per 10,000 18 dialect per 10,000 straight 11 author per 10,000 1 dialect per 10,000 blog 11 author per 10,000 0 dialect per 10,000 upon 11 author per 10,000 1 dialect per 10,000 asweel 11 author per 10,000 0 dialect per 10,000 post 11 author per 10,000 1 dialect per 10,000 gie 11 author per 10,000 7 dialect per 10,000 sign 11 author per 10,000 1 dialect per 10,000 web 11 author per 10,000 0 dialect per 10,000 meal 11 author per 10,000 0 dialect per 10,000 fits 11 author per 10,000 0 dialect per 10,000 of 11 author per 10,000 10 dialect per 10,000 sake 11 author per 10,000 1 dialect per 10,000 nicht 11 author per 10,000 5 dialect per 10,000 supper 11 author per 10,000 0 dialect per 10,000 burn 11 author per 10,000 1 dialect per 10,000 bard 11 author per 10,000 0 dialect per 10,000 bash 11 author per 10,000 0 dialect per 10,000 hire 11 author per 10,000 0 dialect per 10,000 nor 11 author per 10,000 6 dialect per 10,000 left 11 author per 10,000 5 dialect per 10,000 efter 11 author per 10,000 10 dialect per 10,000 salesman 11 author per 10,000 0 dialect per 10,000 skweel 11 author per 10,000 0 dialect per 10,000 sirs 11 author per 10,000 0 dialect per 10,000 went 11 author per 10,000 7 dialect per 10,000 educate 11 author per 10,000 0 dialect per 10,000 black 11 author per 10,000 2 dialect per 10,000 fine 11 author per 10,000 3 dialect per 10,000 new 11 author per 10,000 7 dialect per 10,000 resort 11 author per 10,000 0 dialect per 10,000 violence 11 author per 10,000 0 dialect per 10,000 zilly 11 author per 10,000 0 dialect per 10,000 not 11 author per 10,000 2 dialect per 10,000 shade 11 author per 10,000 0 dialect per 10,000 if 11 author per 10,000 18 dialect per 10,000 s 11 author per 10,000 2 dialect per 10,000 one 11 author per 10,000 2 dialect per 10,000 primary 11 author per 10,000 1 dialect per 10,000 pulls 11 author per 10,000 0 dialect per 10,000 green 11 author per 10,000 2 dialect per 10,000 definitely 11 author per 10,000 0 dialect per 10,000 si 11 author per 10,000 0 dialect per 10,000 years 11 author per 10,000 4 dialect per 10,000 conveniently 11 author per 10,000 0 dialect per 10,000 brings 11 author per 10,000 0 dialect per 10,000 sun 11 author per 10,000 2 dialect per 10,000 sin 11 author per 10,000 1 dialect per 10,000
Doric
a 460 author per 10,000 300 dialect per 10,000 i 317 author per 10,000 71 dialect per 10,000 the 295 author per 10,000 469 dialect per 10,000 we 208 author per 10,000 21 dialect per 10,000 €™ 197 author per 10,000 12 dialect per 10,000 €™s 197 author per 10,000 23 dialect per 10,000 tae 186 author per 10,000 164 dialect per 10,000 an 175 author per 10,000 307 dialect per 10,000 fit 164 author per 10,000 41 dialect per 10,000 ma 164 author per 10,000 46 dialect per 10,000 in 142 author per 10,000 135 dialect per 10,000 he 131 author per 10,000 97 dialect per 10,000 o 131 author per 10,000 181 dialect per 10,000 that 120 author per 10,000 51 dialect per 10,000 it 109 author per 10,000 104 dialect per 10,000 hiv 109 author per 10,000 9 dialect per 10,000 wis 109 author per 10,000 104 dialect per 10,000 ees 98 author per 10,000 0 dialect per 10,000 for 88 author per 10,000 45 dialect per 10,000 on 77 author per 10,000 67 dialect per 10,000 wi 77 author per 10,000 82 dialect per 10,000 €™d 77 author per 10,000 11 dialect per 10,000 us 66 author per 10,000 6 dialect per 10,000 and 66 author per 10,000 43 dialect per 10,000 them 66 author per 10,000 25 dialect per 10,000 fin 55 author per 10,000 19 dialect per 10,000 €™ll 55 author per 10,000 4 dialect per 10,000 or 55 author per 10,000 25 dialect per 10,000 so 55 author per 10,000 14 dialect per 10,000 see 55 author per 10,000 22 dialect per 10,000 be 55 author per 10,000 46 dialect per 10,000 up 55 author per 10,000 45 dialect per 10,000 canna 55 author per 10,000 8 dialect per 10,000 jist 55 author per 10,000 35 dialect per 10,000 at 55 author per 10,000 70 dialect per 10,000 she 55 author per 10,000 73 dialect per 10,000 well 55 author per 10,000 2 dialect per 10,000 zyne 44 author per 10,000 0 dialect per 10,000 magic 44 author per 10,000 1 dialect per 10,000 €™m 44 author per 10,000 3 dialect per 10,000 get 44 author per 10,000 15 dialect per 10,000 ken 44 author per 10,000 23 dialect per 10,000 lang 44 author per 10,000 14 dialect per 10,000 nae 44 author per 10,000 50 dialect per 10,000 tractor 44 author per 10,000 0 dialect per 10,000 been 44 author per 10,000 13 dialect per 10,000 dinna 33 author per 10,000 18 dialect per 10,000 €¦ 33 author per 10,000 1 dialect per 10,000 auld 33 author per 10,000 8 dialect per 10,000 bob 33 author per 10,000 1 dialect per 10,000 there 33 author per 10,000 23 dialect per 10,000 dad 33 author per 10,000 1 dialect per 10,000 is 33 author per 10,000 42 dialect per 10,000 day 33 author per 10,000 28 dialect per 10,000 these 33 author per 10,000 2 dialect per 10,000 her 33 author per 10,000 69 dialect per 10,000 ye 33 author per 10,000 94 dialect per 10,000 bit 33 author per 10,000 41 dialect per 10,000 as 33 author per 10,000 55 dialect per 10,000 tartan 33 author per 10,000 0 dialect per 10,000 will 33 author per 10,000 10 dialect per 10,000 sean 33 author per 10,000 0 dialect per 10,000 noo 33 author per 10,000 21 dialect per 10,000 special 33 author per 10,000 1 dialect per 10,000 zynes 33 author per 10,000 0 dialect per 10,000 dunlop 33 author per 10,000 0 dialect per 10,000 rose 33 author per 10,000 1 dialect per 10,000 €™ve 33 author per 10,000 2 dialect per 10,000 sash 33 author per 10,000 0 dialect per 10,000 caad 33 author per 10,000 2 dialect per 10,000 beets 22 author per 10,000 1 dialect per 10,000 fairies 22 author per 10,000 0 dialect per 10,000 pit 22 author per 10,000 9 dialect per 10,000 dress 22 author per 10,000 0 dialect per 10,000 tinkerbell 22 author per 10,000 0 dialect per 10,000 camouflage 22 author per 10,000 0 dialect per 10,000 oot 22 author per 10,000 48 dialect per 10,000 me 22 author per 10,000 31 dialect per 10,000 only 22 author per 10,000 6 dialect per 10,000 invited 22 author per 10,000 0 dialect per 10,000 brilliant 22 author per 10,000 0 dialect per 10,000 kin 22 author per 10,000 3 dialect per 10,000 hubby 22 author per 10,000 0 dialect per 10,000 breeks 22 author per 10,000 0 dialect per 10,000 am 22 author per 10,000 3 dialect per 10,000 kilt 22 author per 10,000 0 dialect per 10,000 telt 22 author per 10,000 8 dialect per 10,000 lik 22 author per 10,000 3 dialect per 10,000 say 22 author per 10,000 15 dialect per 10,000 said 22 author per 10,000 39 dialect per 10,000 gings 22 author per 10,000 1 dialect per 10,000 ee 22 author per 10,000 10 dialect per 10,000 hear 22 author per 10,000 4 dialect per 10,000 bonnie 22 author per 10,000 4 dialect per 10,000 ae 22 author per 10,000 8 dialect per 10,000 wird 22 author per 10,000 2 dialect per 10,000 bade 22 author per 10,000 1 dialect per 10,000 een 22 author per 10,000 19 dialect per 10,000 name 22 author per 10,000 4 dialect per 10,000 yer 22 author per 10,000 35 dialect per 10,000 mine 22 author per 10,000 2 dialect per 10,000 lobby 22 author per 10,000 1 dialect per 10,000 didna 22 author per 10,000 10 dialect per 10,000 him 22 author per 10,000 33 dialect per 10,000 flat 22 author per 10,000 1 dialect per 10,000 macintyre 22 author per 10,000 0 dialect per 10,000 weel 22 author per 10,000 18 dialect per 10,000 his 22 author per 10,000 72 dialect per 10,000 abody 22 author per 10,000 1 dialect per 10,000 back 22 author per 10,000 22 dialect per 10,000 afore 22 author per 10,000 14 dialect per 10,000 has 22 author per 10,000 2 dialect per 10,000 wee 22 author per 10,000 19 dialect per 10,000 this 22 author per 10,000 18 dialect per 10,000 time 22 author per 10,000 20 dialect per 10,000 off 22 author per 10,000 2 dialect per 10,000 my 22 author per 10,000 11 dialect per 10,000 sang 22 author per 10,000 2 dialect per 10,000 doric 22 author per 10,000 2 dialect per 10,000 syne 22 author per 10,000 12 dialect per 10,000 which 22 author per 10,000 1 dialect per 10,000 wir 22 author per 10,000 5 dialect per 10,000 but 22 author per 10,000 25 dialect per 10,000 to 22 author per 10,000 8 dialect per 10,000 bairns 22 author per 10,000 4 dialect per 10,000 sufferers 11 author per 10,000 0 dialect per 10,000 tartans 11 author per 10,000 0 dialect per 10,000 zing 11 author per 10,000 0 dialect per 10,000 suggested 11 author per 10,000 0 dialect per 10,000 zilence 11 author per 10,000 0 dialect per 10,000 zit 11 author per 10,000 0 dialect per 10,000 same 11 author per 10,000 5 dialect per 10,000 hid 11 author per 10,000 34 dialect per 10,000 thocht 11 author per 10,000 13 dialect per 10,000 wrang 11 author per 10,000 3 dialect per 10,000 check 11 author per 10,000 0 dialect per 10,000 chappie 11 author per 10,000 0 dialect per 10,000 fa 11 author per 10,000 9 dialect per 10,000 exactly 11 author per 10,000 0 dialect per 10,000 stock 11 author per 10,000 0 dialect per 10,000 shock 11 author per 10,000 0 dialect per 10,000 min 11 author per 10,000 2 dialect per 10,000 nelly 11 author per 10,000 0 dialect per 10,000 tee 11 author per 10,000 3 dialect per 10,000 put 11 author per 10,000 1 dialect per 10,000 come 11 author per 10,000 14 dialect per 10,000 happy 11 author per 10,000 2 dialect per 10,000 fellow 11 author per 10,000 0 dialect per 10,000 kent 11 author per 10,000 8 dialect per 10,000 sing 11 author per 10,000 1 dialect per 10,000 intil 11 author per 10,000 1 dialect per 10,000 eradicate 11 author per 10,000 0 dialect per 10,000 their 11 author per 10,000 20 dialect per 10,000 straight 11 author per 10,000 0 dialect per 10,000 blog 11 author per 10,000 0 dialect per 10,000 upon 11 author per 10,000 1 dialect per 10,000 asweel 11 author per 10,000 0 dialect per 10,000 post 11 author per 10,000 0 dialect per 10,000 gie 11 author per 10,000 7 dialect per 10,000 sign 11 author per 10,000 2 dialect per 10,000 web 11 author per 10,000 0 dialect per 10,000 meal 11 author per 10,000 1 dialect per 10,000 fits 11 author per 10,000 0 dialect per 10,000 of 11 author per 10,000 8 dialect per 10,000 sake 11 author per 10,000 1 dialect per 10,000 nicht 11 author per 10,000 12 dialect per 10,000 supper 11 author per 10,000 2 dialect per 10,000 burn 11 author per 10,000 1 dialect per 10,000 bard 11 author per 10,000 0 dialect per 10,000 bash 11 author per 10,000 0 dialect per 10,000 hire 11 author per 10,000 0 dialect per 10,000 nor 11 author per 10,000 6 dialect per 10,000 left 11 author per 10,000 5 dialect per 10,000 efter 11 author per 10,000 11 dialect per 10,000 salesman 11 author per 10,000 0 dialect per 10,000 skweel 11 author per 10,000 1 dialect per 10,000 sirs 11 author per 10,000 0 dialect per 10,000 went 11 author per 10,000 5 dialect per 10,000 educate 11 author per 10,000 0 dialect per 10,000 black 11 author per 10,000 3 dialect per 10,000 fine 11 author per 10,000 12 dialect per 10,000 new 11 author per 10,000 6 dialect per 10,000 resort 11 author per 10,000 0 dialect per 10,000 violence 11 author per 10,000 0 dialect per 10,000 zilly 11 author per 10,000 0 dialect per 10,000 not 11 author per 10,000 1 dialect per 10,000 shade 11 author per 10,000 0 dialect per 10,000 if 11 author per 10,000 17 dialect per 10,000 s 11 author per 10,000 1 dialect per 10,000 one 11 author per 10,000 2 dialect per 10,000 primary 11 author per 10,000 0 dialect per 10,000 pulls 11 author per 10,000 0 dialect per 10,000 green 11 author per 10,000 3 dialect per 10,000 definitely 11 author per 10,000 0 dialect per 10,000 si 11 author per 10,000 0 dialect per 10,000 years 11 author per 10,000 2 dialect per 10,000 conveniently 11 author per 10,000 0 dialect per 10,000 brings 11 author per 10,000 0 dialect per 10,000 sun 11 author per 10,000 2 dialect per 10,000 sin 11 author per 10,000 8 dialect per 10,000
Shetland
a 460 author per 10,000 280 dialect per 10,000 i 317 author per 10,000 143 dialect per 10,000 the 295 author per 10,000 18 dialect per 10,000 we 208 author per 10,000 43 dialect per 10,000 €™ 197 author per 10,000 17 dialect per 10,000 €™s 197 author per 10,000 16 dialect per 10,000 tae 186 author per 10,000 86 dialect per 10,000 an 175 author per 10,000 330 dialect per 10,000 fit 164 author per 10,000 4 dialect per 10,000 ma 164 author per 10,000 0 dialect per 10,000 in 142 author per 10,000 105 dialect per 10,000 he 131 author per 10,000 103 dialect per 10,000 o 131 author per 10,000 177 dialect per 10,000 that 120 author per 10,000 4 dialect per 10,000 it 109 author per 10,000 58 dialect per 10,000 hiv 109 author per 10,000 1 dialect per 10,000 wis 109 author per 10,000 161 dialect per 10,000 ees 98 author per 10,000 0 dialect per 10,000 for 88 author per 10,000 35 dialect per 10,000 on 77 author per 10,000 52 dialect per 10,000 wi 77 author per 10,000 95 dialect per 10,000 €™d 77 author per 10,000 2 dialect per 10,000 us 66 author per 10,000 0 dialect per 10,000 and 66 author per 10,000 15 dialect per 10,000 them 66 author per 10,000 1 dialect per 10,000 fin 55 author per 10,000 7 dialect per 10,000 €™ll 55 author per 10,000 5 dialect per 10,000 or 55 author per 10,000 32 dialect per 10,000 so 55 author per 10,000 26 dialect per 10,000 see 55 author per 10,000 20 dialect per 10,000 be 55 author per 10,000 55 dialect per 10,000 up 55 author per 10,000 42 dialect per 10,000 canna 55 author per 10,000 9 dialect per 10,000 jist 55 author per 10,000 0 dialect per 10,000 at 55 author per 10,000 112 dialect per 10,000 she 55 author per 10,000 7 dialect per 10,000 well 55 author per 10,000 1 dialect per 10,000 zyne 44 author per 10,000 0 dialect per 10,000 magic 44 author per 10,000 1 dialect per 10,000 €™m 44 author per 10,000 5 dialect per 10,000 get 44 author per 10,000 6 dialect per 10,000 ken 44 author per 10,000 14 dialect per 10,000 lang 44 author per 10,000 11 dialect per 10,000 nae 44 author per 10,000 23 dialect per 10,000 tractor 44 author per 10,000 0 dialect per 10,000 been 44 author per 10,000 16 dialect per 10,000 dinna 33 author per 10,000 0 dialect per 10,000 €¦ 33 author per 10,000 1 dialect per 10,000 auld 33 author per 10,000 1 dialect per 10,000 bob 33 author per 10,000 0 dialect per 10,000 there 33 author per 10,000 1 dialect per 10,000 dad 33 author per 10,000 2 dialect per 10,000 is 33 author per 10,000 81 dialect per 10,000 day 33 author per 10,000 18 dialect per 10,000 these 33 author per 10,000 1 dialect per 10,000 her 33 author per 10,000 64 dialect per 10,000 ye 33 author per 10,000 0 dialect per 10,000 bit 33 author per 10,000 38 dialect per 10,000 as 33 author per 10,000 79 dialect per 10,000 tartan 33 author per 10,000 0 dialect per 10,000 will 33 author per 10,000 9 dialect per 10,000 sean 33 author per 10,000 0 dialect per 10,000 noo 33 author per 10,000 19 dialect per 10,000 special 33 author per 10,000 1 dialect per 10,000 zynes 33 author per 10,000 0 dialect per 10,000 dunlop 33 author per 10,000 0 dialect per 10,000 rose 33 author per 10,000 0 dialect per 10,000 €™ve 33 author per 10,000 1 dialect per 10,000 sash 33 author per 10,000 0 dialect per 10,000 caad 33 author per 10,000 3 dialect per 10,000 beets 22 author per 10,000 0 dialect per 10,000 fairies 22 author per 10,000 0 dialect per 10,000 pit 22 author per 10,000 6 dialect per 10,000 dress 22 author per 10,000 0 dialect per 10,000 tinkerbell 22 author per 10,000 0 dialect per 10,000 camouflage 22 author per 10,000 0 dialect per 10,000 oot 22 author per 10,000 42 dialect per 10,000 me 22 author per 10,000 41 dialect per 10,000 only 22 author per 10,000 5 dialect per 10,000 invited 22 author per 10,000 0 dialect per 10,000 brilliant 22 author per 10,000 0 dialect per 10,000 kin 22 author per 10,000 1 dialect per 10,000 hubby 22 author per 10,000 0 dialect per 10,000 breeks 22 author per 10,000 0 dialect per 10,000 am 22 author per 10,000 4 dialect per 10,000 kilt 22 author per 10,000 0 dialect per 10,000 telt 22 author per 10,000 7 dialect per 10,000 lik 22 author per 10,000 10 dialect per 10,000 say 22 author per 10,000 11 dialect per 10,000 said 22 author per 10,000 61 dialect per 10,000 gings 22 author per 10,000 1 dialect per 10,000 ee 22 author per 10,000 11 dialect per 10,000 hear 22 author per 10,000 4 dialect per 10,000 bonnie 22 author per 10,000 0 dialect per 10,000 ae 22 author per 10,000 1 dialect per 10,000 wird 22 author per 10,000 8 dialect per 10,000 bade 22 author per 10,000 0 dialect per 10,000 een 22 author per 10,000 20 dialect per 10,000 name 22 author per 10,000 4 dialect per 10,000 yer 22 author per 10,000 0 dialect per 10,000 mine 22 author per 10,000 1 dialect per 10,000 lobby 22 author per 10,000 0 dialect per 10,000 didna 22 author per 10,000 10 dialect per 10,000 him 22 author per 10,000 47 dialect per 10,000 flat 22 author per 10,000 1 dialect per 10,000 macintyre 22 author per 10,000 0 dialect per 10,000 weel 22 author per 10,000 18 dialect per 10,000 his 22 author per 10,000 52 dialect per 10,000 abody 22 author per 10,000 0 dialect per 10,000 back 22 author per 10,000 18 dialect per 10,000 afore 22 author per 10,000 15 dialect per 10,000 has 22 author per 10,000 3 dialect per 10,000 wee 22 author per 10,000 0 dialect per 10,000 this 22 author per 10,000 1 dialect per 10,000 time 22 author per 10,000 21 dialect per 10,000 off 22 author per 10,000 0 dialect per 10,000 my 22 author per 10,000 23 dialect per 10,000 sang 22 author per 10,000 2 dialect per 10,000 doric 22 author per 10,000 0 dialect per 10,000 syne 22 author per 10,000 1 dialect per 10,000 which 22 author per 10,000 1 dialect per 10,000 wir 22 author per 10,000 49 dialect per 10,000 but 22 author per 10,000 28 dialect per 10,000 to 22 author per 10,000 8 dialect per 10,000 bairns 22 author per 10,000 10 dialect per 10,000 sufferers 11 author per 10,000 0 dialect per 10,000 tartans 11 author per 10,000 0 dialect per 10,000 zing 11 author per 10,000 0 dialect per 10,000 suggested 11 author per 10,000 0 dialect per 10,000 zilence 11 author per 10,000 0 dialect per 10,000 zit 11 author per 10,000 0 dialect per 10,000 same 11 author per 10,000 0 dialect per 10,000 hid 11 author per 10,000 1 dialect per 10,000 thocht 11 author per 10,000 0 dialect per 10,000 wrang 11 author per 10,000 3 dialect per 10,000 check 11 author per 10,000 0 dialect per 10,000 chappie 11 author per 10,000 0 dialect per 10,000 fa 11 author per 10,000 0 dialect per 10,000 exactly 11 author per 10,000 1 dialect per 10,000 stock 11 author per 10,000 0 dialect per 10,000 shock 11 author per 10,000 0 dialect per 10,000 min 11 author per 10,000 0 dialect per 10,000 nelly 11 author per 10,000 0 dialect per 10,000 tee 11 author per 10,000 0 dialect per 10,000 put 11 author per 10,000 1 dialect per 10,000 come 11 author per 10,000 19 dialect per 10,000 happy 11 author per 10,000 1 dialect per 10,000 fellow 11 author per 10,000 0 dialect per 10,000 kent 11 author per 10,000 10 dialect per 10,000 sing 11 author per 10,000 1 dialect per 10,000 intil 11 author per 10,000 0 dialect per 10,000 eradicate 11 author per 10,000 0 dialect per 10,000 their 11 author per 10,000 1 dialect per 10,000 straight 11 author per 10,000 1 dialect per 10,000 blog 11 author per 10,000 0 dialect per 10,000 upon 11 author per 10,000 0 dialect per 10,000 asweel 11 author per 10,000 0 dialect per 10,000 post 11 author per 10,000 0 dialect per 10,000 gie 11 author per 10,000 9 dialect per 10,000 sign 11 author per 10,000 1 dialect per 10,000 web 11 author per 10,000 0 dialect per 10,000 meal 11 author per 10,000 0 dialect per 10,000 fits 11 author per 10,000 0 dialect per 10,000 of 11 author per 10,000 11 dialect per 10,000 sake 11 author per 10,000 1 dialect per 10,000 nicht 11 author per 10,000 3 dialect per 10,000 supper 11 author per 10,000 0 dialect per 10,000 burn 11 author per 10,000 2 dialect per 10,000 bard 11 author per 10,000 0 dialect per 10,000 bash 11 author per 10,000 0 dialect per 10,000 hire 11 author per 10,000 0 dialect per 10,000 nor 11 author per 10,000 3 dialect per 10,000 left 11 author per 10,000 5 dialect per 10,000 efter 11 author per 10,000 9 dialect per 10,000 salesman 11 author per 10,000 0 dialect per 10,000 skweel 11 author per 10,000 0 dialect per 10,000 sirs 11 author per 10,000 0 dialect per 10,000 went 11 author per 10,000 0 dialect per 10,000 educate 11 author per 10,000 0 dialect per 10,000 black 11 author per 10,000 3 dialect per 10,000 fine 11 author per 10,000 7 dialect per 10,000 new 11 author per 10,000 8 dialect per 10,000 resort 11 author per 10,000 0 dialect per 10,000 violence 11 author per 10,000 0 dialect per 10,000 zilly 11 author per 10,000 0 dialect per 10,000 not 11 author per 10,000 2 dialect per 10,000 shade 11 author per 10,000 0 dialect per 10,000 if 11 author per 10,000 25 dialect per 10,000 s 11 author per 10,000 2 dialect per 10,000 one 11 author per 10,000 1 dialect per 10,000 primary 11 author per 10,000 0 dialect per 10,000 pulls 11 author per 10,000 0 dialect per 10,000 green 11 author per 10,000 2 dialect per 10,000 definitely 11 author per 10,000 0 dialect per 10,000 si 11 author per 10,000 0 dialect per 10,000 years 11 author per 10,000 4 dialect per 10,000 conveniently 11 author per 10,000 0 dialect per 10,000 brings 11 author per 10,000 0 dialect per 10,000 sun 11 author per 10,000 3 dialect per 10,000 sin 11 author per 10,000 0 dialect per 10,000
Orkney
a 460 author per 10,000 296 dialect per 10,000 i 317 author per 10,000 156 dialect per 10,000 the 295 author per 10,000 581 dialect per 10,000 we 208 author per 10,000 30 dialect per 10,000 €™ 197 author per 10,000 14 dialect per 10,000 €™s 197 author per 10,000 18 dialect per 10,000 tae 186 author per 10,000 222 dialect per 10,000 an 175 author per 10,000 179 dialect per 10,000 fit 164 author per 10,000 1 dialect per 10,000 ma 164 author per 10,000 1 dialect per 10,000 in 142 author per 10,000 147 dialect per 10,000 he 131 author per 10,000 88 dialect per 10,000 o 131 author per 10,000 199 dialect per 10,000 that 120 author per 10,000 75 dialect per 10,000 it 109 author per 10,000 23 dialect per 10,000 hiv 109 author per 10,000 13 dialect per 10,000 wis 109 author per 10,000 79 dialect per 10,000 ees 98 author per 10,000 1 dialect per 10,000 for 88 author per 10,000 24 dialect per 10,000 on 77 author per 10,000 73 dialect per 10,000 wi 77 author per 10,000 48 dialect per 10,000 €™d 77 author per 10,000 2 dialect per 10,000 us 66 author per 10,000 6 dialect per 10,000 and 66 author per 10,000 191 dialect per 10,000 them 66 author per 10,000 17 dialect per 10,000 fin 55 author per 10,000 0 dialect per 10,000 €™ll 55 author per 10,000 2 dialect per 10,000 or 55 author per 10,000 30 dialect per 10,000 so 55 author per 10,000 29 dialect per 10,000 see 55 author per 10,000 16 dialect per 10,000 be 55 author per 10,000 42 dialect per 10,000 up 55 author per 10,000 33 dialect per 10,000 canna 55 author per 10,000 3 dialect per 10,000 jist 55 author per 10,000 3 dialect per 10,000 at 55 author per 10,000 53 dialect per 10,000 she 55 author per 10,000 8 dialect per 10,000 well 55 author per 10,000 1 dialect per 10,000 zyne 44 author per 10,000 0 dialect per 10,000 magic 44 author per 10,000 0 dialect per 10,000 €™m 44 author per 10,000 4 dialect per 10,000 get 44 author per 10,000 10 dialect per 10,000 ken 44 author per 10,000 15 dialect per 10,000 lang 44 author per 10,000 2 dialect per 10,000 nae 44 author per 10,000 3 dialect per 10,000 tractor 44 author per 10,000 1 dialect per 10,000 been 44 author per 10,000 18 dialect per 10,000 dinna 33 author per 10,000 4 dialect per 10,000 €¦ 33 author per 10,000 4 dialect per 10,000 auld 33 author per 10,000 1 dialect per 10,000 bob 33 author per 10,000 1 dialect per 10,000 there 33 author per 10,000 18 dialect per 10,000 dad 33 author per 10,000 1 dialect per 10,000 is 33 author per 10,000 73 dialect per 10,000 day 33 author per 10,000 21 dialect per 10,000 these 33 author per 10,000 2 dialect per 10,000 her 33 author per 10,000 48 dialect per 10,000 ye 33 author per 10,000 17 dialect per 10,000 bit 33 author per 10,000 48 dialect per 10,000 as 33 author per 10,000 48 dialect per 10,000 tartan 33 author per 10,000 0 dialect per 10,000 will 33 author per 10,000 9 dialect per 10,000 sean 33 author per 10,000 0 dialect per 10,000 noo 33 author per 10,000 27 dialect per 10,000 special 33 author per 10,000 0 dialect per 10,000 zynes 33 author per 10,000 0 dialect per 10,000 dunlop 33 author per 10,000 0 dialect per 10,000 rose 33 author per 10,000 1 dialect per 10,000 €™ve 33 author per 10,000 1 dialect per 10,000 sash 33 author per 10,000 0 dialect per 10,000 caad 33 author per 10,000 2 dialect per 10,000 beets 22 author per 10,000 0 dialect per 10,000 fairies 22 author per 10,000 0 dialect per 10,000 pit 22 author per 10,000 5 dialect per 10,000 dress 22 author per 10,000 0 dialect per 10,000 tinkerbell 22 author per 10,000 0 dialect per 10,000 camouflage 22 author per 10,000 0 dialect per 10,000 oot 22 author per 10,000 51 dialect per 10,000 me 22 author per 10,000 111 dialect per 10,000 only 22 author per 10,000 7 dialect per 10,000 invited 22 author per 10,000 0 dialect per 10,000 brilliant 22 author per 10,000 0 dialect per 10,000 kin 22 author per 10,000 1 dialect per 10,000 hubby 22 author per 10,000 0 dialect per 10,000 breeks 22 author per 10,000 1 dialect per 10,000 am 22 author per 10,000 6 dialect per 10,000 kilt 22 author per 10,000 0 dialect per 10,000 telt 22 author per 10,000 4 dialect per 10,000 lik 22 author per 10,000 0 dialect per 10,000 say 22 author per 10,000 10 dialect per 10,000 said 22 author per 10,000 15 dialect per 10,000 gings 22 author per 10,000 0 dialect per 10,000 ee 22 author per 10,000 1 dialect per 10,000 hear 22 author per 10,000 4 dialect per 10,000 bonnie 22 author per 10,000 2 dialect per 10,000 ae 22 author per 10,000 1 dialect per 10,000 wird 22 author per 10,000 2 dialect per 10,000 bade 22 author per 10,000 1 dialect per 10,000 een 22 author per 10,000 4 dialect per 10,000 name 22 author per 10,000 3 dialect per 10,000 yer 22 author per 10,000 7 dialect per 10,000 mine 22 author per 10,000 3 dialect per 10,000 lobby 22 author per 10,000 0 dialect per 10,000 didna 22 author per 10,000 9 dialect per 10,000 him 22 author per 10,000 21 dialect per 10,000 flat 22 author per 10,000 1 dialect per 10,000 macintyre 22 author per 10,000 0 dialect per 10,000 weel 22 author per 10,000 18 dialect per 10,000 his 22 author per 10,000 63 dialect per 10,000 abody 22 author per 10,000 0 dialect per 10,000 back 22 author per 10,000 27 dialect per 10,000 afore 22 author per 10,000 13 dialect per 10,000 has 22 author per 10,000 1 dialect per 10,000 wee 22 author per 10,000 1 dialect per 10,000 this 22 author per 10,000 35 dialect per 10,000 time 22 author per 10,000 18 dialect per 10,000 off 22 author per 10,000 6 dialect per 10,000 my 22 author per 10,000 4 dialect per 10,000 sang 22 author per 10,000 1 dialect per 10,000 doric 22 author per 10,000 0 dialect per 10,000 syne 22 author per 10,000 0 dialect per 10,000 which 22 author per 10,000 1 dialect per 10,000 wir 22 author per 10,000 27 dialect per 10,000 but 22 author per 10,000 28 dialect per 10,000 to 22 author per 10,000 9 dialect per 10,000 bairns 22 author per 10,000 4 dialect per 10,000 sufferers 11 author per 10,000 0 dialect per 10,000 tartans 11 author per 10,000 0 dialect per 10,000 zing 11 author per 10,000 0 dialect per 10,000 suggested 11 author per 10,000 0 dialect per 10,000 zilence 11 author per 10,000 0 dialect per 10,000 zit 11 author per 10,000 0 dialect per 10,000 same 11 author per 10,000 3 dialect per 10,000 hid 11 author per 10,000 93 dialect per 10,000 thocht 11 author per 10,000 0 dialect per 10,000 wrang 11 author per 10,000 0 dialect per 10,000 check 11 author per 10,000 0 dialect per 10,000 chappie 11 author per 10,000 0 dialect per 10,000 fa 11 author per 10,000 0 dialect per 10,000 exactly 11 author per 10,000 1 dialect per 10,000 stock 11 author per 10,000 0 dialect per 10,000 shock 11 author per 10,000 0 dialect per 10,000 min 11 author per 10,000 1 dialect per 10,000 nelly 11 author per 10,000 0 dialect per 10,000 tee 11 author per 10,000 0 dialect per 10,000 put 11 author per 10,000 0 dialect per 10,000 come 11 author per 10,000 10 dialect per 10,000 happy 11 author per 10,000 3 dialect per 10,000 fellow 11 author per 10,000 0 dialect per 10,000 kent 11 author per 10,000 5 dialect per 10,000 sing 11 author per 10,000 1 dialect per 10,000 intil 11 author per 10,000 0 dialect per 10,000 eradicate 11 author per 10,000 0 dialect per 10,000 their 11 author per 10,000 7 dialect per 10,000 straight 11 author per 10,000 1 dialect per 10,000 blog 11 author per 10,000 0 dialect per 10,000 upon 11 author per 10,000 1 dialect per 10,000 asweel 11 author per 10,000 0 dialect per 10,000 post 11 author per 10,000 1 dialect per 10,000 gie 11 author per 10,000 2 dialect per 10,000 sign 11 author per 10,000 2 dialect per 10,000 web 11 author per 10,000 0 dialect per 10,000 meal 11 author per 10,000 0 dialect per 10,000 fits 11 author per 10,000 0 dialect per 10,000 of 11 author per 10,000 6 dialect per 10,000 sake 11 author per 10,000 0 dialect per 10,000 nicht 11 author per 10,000 0 dialect per 10,000 supper 11 author per 10,000 1 dialect per 10,000 burn 11 author per 10,000 1 dialect per 10,000 bard 11 author per 10,000 0 dialect per 10,000 bash 11 author per 10,000 0 dialect per 10,000 hire 11 author per 10,000 0 dialect per 10,000 nor 11 author per 10,000 1 dialect per 10,000 left 11 author per 10,000 6 dialect per 10,000 efter 11 author per 10,000 6 dialect per 10,000 salesman 11 author per 10,000 0 dialect per 10,000 skweel 11 author per 10,000 0 dialect per 10,000 sirs 11 author per 10,000 0 dialect per 10,000 went 11 author per 10,000 1 dialect per 10,000 educate 11 author per 10,000 0 dialect per 10,000 black 11 author per 10,000 6 dialect per 10,000 fine 11 author per 10,000 6 dialect per 10,000 new 11 author per 10,000 10 dialect per 10,000 resort 11 author per 10,000 0 dialect per 10,000 violence 11 author per 10,000 0 dialect per 10,000 zilly 11 author per 10,000 0 dialect per 10,000 not 11 author per 10,000 2 dialect per 10,000 shade 11 author per 10,000 0 dialect per 10,000 if 11 author per 10,000 15 dialect per 10,000 s 11 author per 10,000 1 dialect per 10,000 one 11 author per 10,000 1 dialect per 10,000 primary 11 author per 10,000 0 dialect per 10,000 pulls 11 author per 10,000 0 dialect per 10,000 green 11 author per 10,000 5 dialect per 10,000 definitely 11 author per 10,000 0 dialect per 10,000 si 11 author per 10,000 0 dialect per 10,000 years 11 author per 10,000 3 dialect per 10,000 conveniently 11 author per 10,000 0 dialect per 10,000 brings 11 author per 10,000 0 dialect per 10,000 sun 11 author per 10,000 3 dialect per 10,000 sin 11 author per 10,000 0 dialect per 10,000
Southern
a 460 author per 10,000 223 dialect per 10,000 i 317 author per 10,000 78 dialect per 10,000 the 295 author per 10,000 438 dialect per 10,000 we 208 author per 10,000 10 dialect per 10,000 €™ 197 author per 10,000 15 dialect per 10,000 €™s 197 author per 10,000 37 dialect per 10,000 tae 186 author per 10,000 203 dialect per 10,000 an 175 author per 10,000 310 dialect per 10,000 fit 164 author per 10,000 6 dialect per 10,000 ma 164 author per 10,000 59 dialect per 10,000 in 142 author per 10,000 106 dialect per 10,000 he 131 author per 10,000 11 dialect per 10,000 o 131 author per 10,000 214 dialect per 10,000 that 120 author per 10,000 64 dialect per 10,000 it 109 author per 10,000 58 dialect per 10,000 hiv 109 author per 10,000 0 dialect per 10,000 wis 109 author per 10,000 58 dialect per 10,000 ees 98 author per 10,000 0 dialect per 10,000 for 88 author per 10,000 22 dialect per 10,000 on 77 author per 10,000 56 dialect per 10,000 wi 77 author per 10,000 71 dialect per 10,000 €™d 77 author per 10,000 7 dialect per 10,000 us 66 author per 10,000 5 dialect per 10,000 and 66 author per 10,000 15 dialect per 10,000 them 66 author per 10,000 4 dialect per 10,000 fin 55 author per 10,000 1 dialect per 10,000 €™ll 55 author per 10,000 2 dialect per 10,000 or 55 author per 10,000 22 dialect per 10,000 so 55 author per 10,000 1 dialect per 10,000 see 55 author per 10,000 5 dialect per 10,000 be 55 author per 10,000 12 dialect per 10,000 up 55 author per 10,000 41 dialect per 10,000 canna 55 author per 10,000 2 dialect per 10,000 jist 55 author per 10,000 12 dialect per 10,000 at 55 author per 10,000 74 dialect per 10,000 she 55 author per 10,000 97 dialect per 10,000 well 55 author per 10,000 1 dialect per 10,000 zyne 44 author per 10,000 0 dialect per 10,000 magic 44 author per 10,000 0 dialect per 10,000 €™m 44 author per 10,000 5 dialect per 10,000 get 44 author per 10,000 10 dialect per 10,000 ken 44 author per 10,000 18 dialect per 10,000 lang 44 author per 10,000 13 dialect per 10,000 nae 44 author per 10,000 25 dialect per 10,000 tractor 44 author per 10,000 1 dialect per 10,000 been 44 author per 10,000 10 dialect per 10,000 dinna 33 author per 10,000 2 dialect per 10,000 €¦ 33 author per 10,000 1 dialect per 10,000 auld 33 author per 10,000 20 dialect per 10,000 bob 33 author per 10,000 1 dialect per 10,000 there 33 author per 10,000 16 dialect per 10,000 dad 33 author per 10,000 0 dialect per 10,000 is 33 author per 10,000 65 dialect per 10,000 day 33 author per 10,000 18 dialect per 10,000 these 33 author per 10,000 2 dialect per 10,000 her 33 author per 10,000 16 dialect per 10,000 ye 33 author per 10,000 19 dialect per 10,000 bit 33 author per 10,000 15 dialect per 10,000 as 33 author per 10,000 50 dialect per 10,000 tartan 33 author per 10,000 0 dialect per 10,000 will 33 author per 10,000 1 dialect per 10,000 sean 33 author per 10,000 0 dialect per 10,000 noo 33 author per 10,000 11 dialect per 10,000 special 33 author per 10,000 0 dialect per 10,000 zynes 33 author per 10,000 0 dialect per 10,000 dunlop 33 author per 10,000 1 dialect per 10,000 rose 33 author per 10,000 1 dialect per 10,000 €™ve 33 author per 10,000 4 dialect per 10,000 sash 33 author per 10,000 0 dialect per 10,000 caad 33 author per 10,000 0 dialect per 10,000 beets 22 author per 10,000 0 dialect per 10,000 fairies 22 author per 10,000 0 dialect per 10,000 pit 22 author per 10,000 2 dialect per 10,000 dress 22 author per 10,000 0 dialect per 10,000 tinkerbell 22 author per 10,000 0 dialect per 10,000 camouflage 22 author per 10,000 0 dialect per 10,000 oot 22 author per 10,000 35 dialect per 10,000 me 22 author per 10,000 14 dialect per 10,000 only 22 author per 10,000 8 dialect per 10,000 invited 22 author per 10,000 0 dialect per 10,000 brilliant 22 author per 10,000 0 dialect per 10,000 kin 22 author per 10,000 1 dialect per 10,000 hubby 22 author per 10,000 0 dialect per 10,000 breeks 22 author per 10,000 0 dialect per 10,000 am 22 author per 10,000 1 dialect per 10,000 kilt 22 author per 10,000 1 dialect per 10,000 telt 22 author per 10,000 6 dialect per 10,000 lik 22 author per 10,000 18 dialect per 10,000 say 22 author per 10,000 18 dialect per 10,000 said 22 author per 10,000 70 dialect per 10,000 gings 22 author per 10,000 0 dialect per 10,000 ee 22 author per 10,000 57 dialect per 10,000 hear 22 author per 10,000 5 dialect per 10,000 bonnie 22 author per 10,000 2 dialect per 10,000 ae 22 author per 10,000 73 dialect per 10,000 wird 22 author per 10,000 0 dialect per 10,000 bade 22 author per 10,000 9 dialect per 10,000 een 22 author per 10,000 2 dialect per 10,000 name 22 author per 10,000 3 dialect per 10,000 yer 22 author per 10,000 10 dialect per 10,000 mine 22 author per 10,000 1 dialect per 10,000 lobby 22 author per 10,000 0 dialect per 10,000 didna 22 author per 10,000 2 dialect per 10,000 him 22 author per 10,000 11 dialect per 10,000 flat 22 author per 10,000 0 dialect per 10,000 macintyre 22 author per 10,000 0 dialect per 10,000 weel 22 author per 10,000 4 dialect per 10,000 his 22 author per 10,000 37 dialect per 10,000 abody 22 author per 10,000 1 dialect per 10,000 back 22 author per 10,000 20 dialect per 10,000 afore 22 author per 10,000 16 dialect per 10,000 has 22 author per 10,000 1 dialect per 10,000 wee 22 author per 10,000 23 dialect per 10,000 this 22 author per 10,000 35 dialect per 10,000 time 22 author per 10,000 13 dialect per 10,000 off 22 author per 10,000 9 dialect per 10,000 my 22 author per 10,000 1 dialect per 10,000 sang 22 author per 10,000 1 dialect per 10,000 doric 22 author per 10,000 0 dialect per 10,000 syne 22 author per 10,000 5 dialect per 10,000 which 22 author per 10,000 7 dialect per 10,000 wir 22 author per 10,000 1 dialect per 10,000 but 22 author per 10,000 38 dialect per 10,000 to 22 author per 10,000 1 dialect per 10,000 bairns 22 author per 10,000 8 dialect per 10,000 sufferers 11 author per 10,000 0 dialect per 10,000 tartans 11 author per 10,000 0 dialect per 10,000 zing 11 author per 10,000 0 dialect per 10,000 suggested 11 author per 10,000 0 dialect per 10,000 zilence 11 author per 10,000 0 dialect per 10,000 zit 11 author per 10,000 0 dialect per 10,000 same 11 author per 10,000 6 dialect per 10,000 hid 11 author per 10,000 0 dialect per 10,000 thocht 11 author per 10,000 14 dialect per 10,000 wrang 11 author per 10,000 1 dialect per 10,000 check 11 author per 10,000 0 dialect per 10,000 chappie 11 author per 10,000 0 dialect per 10,000 fa 11 author per 10,000 1 dialect per 10,000 exactly 11 author per 10,000 1 dialect per 10,000 stock 11 author per 10,000 0 dialect per 10,000 shock 11 author per 10,000 0 dialect per 10,000 min 11 author per 10,000 0 dialect per 10,000 nelly 11 author per 10,000 0 dialect per 10,000 tee 11 author per 10,000 0 dialect per 10,000 put 11 author per 10,000 6 dialect per 10,000 come 11 author per 10,000 7 dialect per 10,000 happy 11 author per 10,000 0 dialect per 10,000 fellow 11 author per 10,000 0 dialect per 10,000 kent 11 author per 10,000 11 dialect per 10,000 sing 11 author per 10,000 1 dialect per 10,000 intil 11 author per 10,000 11 dialect per 10,000 eradicate 11 author per 10,000 0 dialect per 10,000 their 11 author per 10,000 13 dialect per 10,000 straight 11 author per 10,000 0 dialect per 10,000 blog 11 author per 10,000 0 dialect per 10,000 upon 11 author per 10,000 0 dialect per 10,000 asweel 11 author per 10,000 0 dialect per 10,000 post 11 author per 10,000 1 dialect per 10,000 gie 11 author per 10,000 13 dialect per 10,000 sign 11 author per 10,000 1 dialect per 10,000 web 11 author per 10,000 0 dialect per 10,000 meal 11 author per 10,000 0 dialect per 10,000 fits 11 author per 10,000 0 dialect per 10,000 of 11 author per 10,000 9 dialect per 10,000 sake 11 author per 10,000 0 dialect per 10,000 nicht 11 author per 10,000 7 dialect per 10,000 supper 11 author per 10,000 0 dialect per 10,000 burn 11 author per 10,000 5 dialect per 10,000 bard 11 author per 10,000 0 dialect per 10,000 bash 11 author per 10,000 0 dialect per 10,000 hire 11 author per 10,000 0 dialect per 10,000 nor 11 author per 10,000 5 dialect per 10,000 left 11 author per 10,000 5 dialect per 10,000 efter 11 author per 10,000 14 dialect per 10,000 salesman 11 author per 10,000 0 dialect per 10,000 skweel 11 author per 10,000 0 dialect per 10,000 sirs 11 author per 10,000 0 dialect per 10,000 went 11 author per 10,000 13 dialect per 10,000 educate 11 author per 10,000 0 dialect per 10,000 black 11 author per 10,000 1 dialect per 10,000 fine 11 author per 10,000 1 dialect per 10,000 new 11 author per 10,000 7 dialect per 10,000 resort 11 author per 10,000 0 dialect per 10,000 violence 11 author per 10,000 0 dialect per 10,000 zilly 11 author per 10,000 0 dialect per 10,000 not 11 author per 10,000 0 dialect per 10,000 shade 11 author per 10,000 0 dialect per 10,000 if 11 author per 10,000 16 dialect per 10,000 s 11 author per 10,000 0 dialect per 10,000 one 11 author per 10,000 0 dialect per 10,000 primary 11 author per 10,000 0 dialect per 10,000 pulls 11 author per 10,000 0 dialect per 10,000 green 11 author per 10,000 2 dialect per 10,000 definitely 11 author per 10,000 0 dialect per 10,000 si 11 author per 10,000 0 dialect per 10,000 years 11 author per 10,000 3 dialect per 10,000 conveniently 11 author per 10,000 0 dialect per 10,000 brings 11 author per 10,000 0 dialect per 10,000 sun 11 author per 10,000 3 dialect per 10,000 sin 11 author per 10,000 7 dialect per 10,000
Ulster
a 460 author per 10,000 284 dialect per 10,000 i 317 author per 10,000 10 dialect per 10,000 the 295 author per 10,000 296 dialect per 10,000 we 208 author per 10,000 18 dialect per 10,000 €™ 197 author per 10,000 16 dialect per 10,000 €™s 197 author per 10,000 11 dialect per 10,000 tae 186 author per 10,000 259 dialect per 10,000 an 175 author per 10,000 364 dialect per 10,000 fit 164 author per 10,000 4 dialect per 10,000 ma 164 author per 10,000 21 dialect per 10,000 in 142 author per 10,000 120 dialect per 10,000 he 131 author per 10,000 63 dialect per 10,000 o 131 author per 10,000 210 dialect per 10,000 that 120 author per 10,000 72 dialect per 10,000 it 109 author per 10,000 71 dialect per 10,000 hiv 109 author per 10,000 0 dialect per 10,000 wis 109 author per 10,000 1 dialect per 10,000 ees 98 author per 10,000 0 dialect per 10,000 for 88 author per 10,000 33 dialect per 10,000 on 77 author per 10,000 54 dialect per 10,000 wi 77 author per 10,000 61 dialect per 10,000 €™d 77 author per 10,000 2 dialect per 10,000 us 66 author per 10,000 4 dialect per 10,000 and 66 author per 10,000 10 dialect per 10,000 them 66 author per 10,000 7 dialect per 10,000 fin 55 author per 10,000 5 dialect per 10,000 €™ll 55 author per 10,000 2 dialect per 10,000 or 55 author per 10,000 36 dialect per 10,000 so 55 author per 10,000 5 dialect per 10,000 see 55 author per 10,000 16 dialect per 10,000 be 55 author per 10,000 40 dialect per 10,000 up 55 author per 10,000 31 dialect per 10,000 canna 55 author per 10,000 0 dialect per 10,000 jist 55 author per 10,000 9 dialect per 10,000 at 55 author per 10,000 58 dialect per 10,000 she 55 author per 10,000 13 dialect per 10,000 well 55 author per 10,000 2 dialect per 10,000 zyne 44 author per 10,000 0 dialect per 10,000 magic 44 author per 10,000 0 dialect per 10,000 €™m 44 author per 10,000 1 dialect per 10,000 get 44 author per 10,000 8 dialect per 10,000 ken 44 author per 10,000 4 dialect per 10,000 lang 44 author per 10,000 12 dialect per 10,000 nae 44 author per 10,000 23 dialect per 10,000 tractor 44 author per 10,000 0 dialect per 10,000 been 44 author per 10,000 2 dialect per 10,000 dinna 33 author per 10,000 0 dialect per 10,000 €¦ 33 author per 10,000 0 dialect per 10,000 auld 33 author per 10,000 1 dialect per 10,000 bob 33 author per 10,000 0 dialect per 10,000 there 33 author per 10,000 6 dialect per 10,000 dad 33 author per 10,000 0 dialect per 10,000 is 33 author per 10,000 19 dialect per 10,000 day 33 author per 10,000 15 dialect per 10,000 these 33 author per 10,000 5 dialect per 10,000 her 33 author per 10,000 7 dialect per 10,000 ye 33 author per 10,000 79 dialect per 10,000 bit 33 author per 10,000 10 dialect per 10,000 as 33 author per 10,000 29 dialect per 10,000 tartan 33 author per 10,000 0 dialect per 10,000 will 33 author per 10,000 2 dialect per 10,000 sean 33 author per 10,000 0 dialect per 10,000 noo 33 author per 10,000 23 dialect per 10,000 special 33 author per 10,000 0 dialect per 10,000 zynes 33 author per 10,000 0 dialect per 10,000 dunlop 33 author per 10,000 0 dialect per 10,000 rose 33 author per 10,000 0 dialect per 10,000 €™ve 33 author per 10,000 0 dialect per 10,000 sash 33 author per 10,000 0 dialect per 10,000 caad 33 author per 10,000 4 dialect per 10,000 beets 22 author per 10,000 0 dialect per 10,000 fairies 22 author per 10,000 0 dialect per 10,000 pit 22 author per 10,000 11 dialect per 10,000 dress 22 author per 10,000 0 dialect per 10,000 tinkerbell 22 author per 10,000 0 dialect per 10,000 camouflage 22 author per 10,000 0 dialect per 10,000 oot 22 author per 10,000 51 dialect per 10,000 me 22 author per 10,000 24 dialect per 10,000 only 22 author per 10,000 3 dialect per 10,000 invited 22 author per 10,000 0 dialect per 10,000 brilliant 22 author per 10,000 0 dialect per 10,000 kin 22 author per 10,000 1 dialect per 10,000 hubby 22 author per 10,000 0 dialect per 10,000 breeks 22 author per 10,000 1 dialect per 10,000 am 22 author per 10,000 3 dialect per 10,000 kilt 22 author per 10,000 0 dialect per 10,000 telt 22 author per 10,000 1 dialect per 10,000 lik 22 author per 10,000 6 dialect per 10,000 say 22 author per 10,000 10 dialect per 10,000 said 22 author per 10,000 29 dialect per 10,000 gings 22 author per 10,000 0 dialect per 10,000 ee 22 author per 10,000 3 dialect per 10,000 hear 22 author per 10,000 5 dialect per 10,000 bonnie 22 author per 10,000 0 dialect per 10,000 ae 22 author per 10,000 0 dialect per 10,000 wird 22 author per 10,000 0 dialect per 10,000 bade 22 author per 10,000 0 dialect per 10,000 een 22 author per 10,000 6 dialect per 10,000 name 22 author per 10,000 6 dialect per 10,000 yer 22 author per 10,000 38 dialect per 10,000 mine 22 author per 10,000 9 dialect per 10,000 lobby 22 author per 10,000 0 dialect per 10,000 didna 22 author per 10,000 0 dialect per 10,000 him 22 author per 10,000 9 dialect per 10,000 flat 22 author per 10,000 0 dialect per 10,000 macintyre 22 author per 10,000 0 dialect per 10,000 weel 22 author per 10,000 13 dialect per 10,000 his 22 author per 10,000 19 dialect per 10,000 abody 22 author per 10,000 0 dialect per 10,000 back 22 author per 10,000 3 dialect per 10,000 afore 22 author per 10,000 12 dialect per 10,000 has 22 author per 10,000 1 dialect per 10,000 wee 22 author per 10,000 26 dialect per 10,000 this 22 author per 10,000 28 dialect per 10,000 time 22 author per 10,000 13 dialect per 10,000 off 22 author per 10,000 0 dialect per 10,000 my 22 author per 10,000 2 dialect per 10,000 sang 22 author per 10,000 2 dialect per 10,000 doric 22 author per 10,000 0 dialect per 10,000 syne 22 author per 10,000 1 dialect per 10,000 which 22 author per 10,000 0 dialect per 10,000 wir 22 author per 10,000 1 dialect per 10,000 but 22 author per 10,000 42 dialect per 10,000 to 22 author per 10,000 2 dialect per 10,000 bairns 22 author per 10,000 0 dialect per 10,000 sufferers 11 author per 10,000 0 dialect per 10,000 tartans 11 author per 10,000 0 dialect per 10,000 zing 11 author per 10,000 0 dialect per 10,000 suggested 11 author per 10,000 0 dialect per 10,000 zilence 11 author per 10,000 0 dialect per 10,000 zit 11 author per 10,000 0 dialect per 10,000 same 11 author per 10,000 5 dialect per 10,000 hid 11 author per 10,000 0 dialect per 10,000 thocht 11 author per 10,000 11 dialect per 10,000 wrang 11 author per 10,000 3 dialect per 10,000 check 11 author per 10,000 0 dialect per 10,000 chappie 11 author per 10,000 0 dialect per 10,000 fa 11 author per 10,000 0 dialect per 10,000 exactly 11 author per 10,000 0 dialect per 10,000 stock 11 author per 10,000 0 dialect per 10,000 shock 11 author per 10,000 0 dialect per 10,000 min 11 author per 10,000 0 dialect per 10,000 nelly 11 author per 10,000 0 dialect per 10,000 tee 11 author per 10,000 0 dialect per 10,000 put 11 author per 10,000 1 dialect per 10,000 come 11 author per 10,000 9 dialect per 10,000 happy 11 author per 10,000 1 dialect per 10,000 fellow 11 author per 10,000 0 dialect per 10,000 kent 11 author per 10,000 1 dialect per 10,000 sing 11 author per 10,000 2 dialect per 10,000 intil 11 author per 10,000 1 dialect per 10,000 eradicate 11 author per 10,000 0 dialect per 10,000 their 11 author per 10,000 6 dialect per 10,000 straight 11 author per 10,000 0 dialect per 10,000 blog 11 author per 10,000 0 dialect per 10,000 upon 11 author per 10,000 1 dialect per 10,000 asweel 11 author per 10,000 0 dialect per 10,000 post 11 author per 10,000 0 dialect per 10,000 gie 11 author per 10,000 17 dialect per 10,000 sign 11 author per 10,000 1 dialect per 10,000 web 11 author per 10,000 0 dialect per 10,000 meal 11 author per 10,000 0 dialect per 10,000 fits 11 author per 10,000 0 dialect per 10,000 of 11 author per 10,000 2 dialect per 10,000 sake 11 author per 10,000 0 dialect per 10,000 nicht 11 author per 10,000 6 dialect per 10,000 supper 11 author per 10,000 0 dialect per 10,000 burn 11 author per 10,000 1 dialect per 10,000 bard 11 author per 10,000 0 dialect per 10,000 bash 11 author per 10,000 0 dialect per 10,000 hire 11 author per 10,000 0 dialect per 10,000 nor 11 author per 10,000 12 dialect per 10,000 left 11 author per 10,000 4 dialect per 10,000 efter 11 author per 10,000 5 dialect per 10,000 salesman 11 author per 10,000 0 dialect per 10,000 skweel 11 author per 10,000 0 dialect per 10,000 sirs 11 author per 10,000 0 dialect per 10,000 went 11 author per 10,000 12 dialect per 10,000 educate 11 author per 10,000 0 dialect per 10,000 black 11 author per 10,000 0 dialect per 10,000 fine 11 author per 10,000 1 dialect per 10,000 new 11 author per 10,000 8 dialect per 10,000 resort 11 author per 10,000 0 dialect per 10,000 violence 11 author per 10,000 0 dialect per 10,000 zilly 11 author per 10,000 0 dialect per 10,000 not 11 author per 10,000 1 dialect per 10,000 shade 11 author per 10,000 0 dialect per 10,000 if 11 author per 10,000 13 dialect per 10,000 s 11 author per 10,000 1 dialect per 10,000 one 11 author per 10,000 0 dialect per 10,000 primary 11 author per 10,000 0 dialect per 10,000 pulls 11 author per 10,000 0 dialect per 10,000 green 11 author per 10,000 1 dialect per 10,000 definitely 11 author per 10,000 1 dialect per 10,000 si 11 author per 10,000 0 dialect per 10,000 years 11 author per 10,000 2 dialect per 10,000 conveniently 11 author per 10,000 0 dialect per 10,000 brings 11 author per 10,000 1 dialect per 10,000 sun 11 author per 10,000 1 dialect per 10,000 sin 11 author per 10,000 3 dialect per 10,000