A Corpus of 21st Century Scots Texts

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Cartmill, Claire

Punctuation analysis - Fine grain dialect analysis - Basic author info
Total words by this author in corpus - 430
Total unique words used by this author in corpus - 247
Ratio of total words to unique words - 1.741
Top ten most common words - a, the, tae, ir, tha, i, an, o, in, oul,

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.

Lallans
a 512 author per 10,000 261 dialect per 10,000 the 442 author per 10,000 563 dialect per 10,000 tae 302 author per 10,000 220 dialect per 10,000 ir 209 author per 10,000 2 dialect per 10,000 tha 209 author per 10,000 0 dialect per 10,000 i 163 author per 10,000 35 dialect per 10,000 an 163 author per 10,000 219 dialect per 10,000 o 163 author per 10,000 191 dialect per 10,000 in 140 author per 10,000 150 dialect per 10,000 oul 116 author per 10,000 0 dialect per 10,000 but 116 author per 10,000 46 dialect per 10,000 it 116 author per 10,000 122 dialect per 10,000 we 93 author per 10,000 34 dialect per 10,000 €™ 93 author per 10,000 42 dialect per 10,000 is 93 author per 10,000 62 dialect per 10,000 ye 93 author per 10,000 56 dialect per 10,000 dance 93 author per 10,000 1 dialect per 10,000 noo 93 author per 10,000 13 dialect per 10,000 some 93 author per 10,000 14 dialect per 10,000 this 70 author per 10,000 44 dialect per 10,000 €™s 70 author per 10,000 41 dialect per 10,000 they 70 author per 10,000 43 dialect per 10,000 mae 70 author per 10,000 0 dialect per 10,000 think 70 author per 10,000 9 dialect per 10,000 oot 70 author per 10,000 40 dialect per 10,000 young 70 author per 10,000 3 dialect per 10,000 am 70 author per 10,000 3 dialect per 10,000 wid 70 author per 10,000 8 dialect per 10,000 frae 70 author per 10,000 13 dialect per 10,000 my 70 author per 10,000 6 dialect per 10,000 nae 70 author per 10,000 20 dialect per 10,000 yins 70 author per 10,000 1 dialect per 10,000 noo-a-deys 47 author per 10,000 0 dialect per 10,000 canny 47 author per 10,000 1 dialect per 10,000 roon 47 author per 10,000 3 dialect per 10,000 sae 47 author per 10,000 14 dialect per 10,000 say 47 author per 10,000 10 dialect per 10,000 hame 47 author per 10,000 5 dialect per 10,000 aa 47 author per 10,000 9 dialect per 10,000 floor 47 author per 10,000 0 dialect per 10,000 naw 47 author per 10,000 3 dialect per 10,000 robinson 47 author per 10,000 0 dialect per 10,000 for 47 author per 10,000 47 dialect per 10,000 that 47 author per 10,000 118 dialect per 10,000 age 47 author per 10,000 1 dialect per 10,000 sandy 47 author per 10,000 0 dialect per 10,000 side 47 author per 10,000 3 dialect per 10,000 thauts 47 author per 10,000 0 dialect per 10,000 wae 47 author per 10,000 9 dialect per 10,000 thaur 47 author per 10,000 0 dialect per 10,000 them 47 author per 10,000 17 dialect per 10,000 mi 47 author per 10,000 0 dialect per 10,000 had 47 author per 10,000 25 dialect per 10,000 feet 47 author per 10,000 3 dialect per 10,000 at 47 author per 10,000 56 dialect per 10,000 see 47 author per 10,000 16 dialect per 10,000 bae 47 author per 10,000 0 dialect per 10,000 kno 47 author per 10,000 0 dialect per 10,000 far 47 author per 10,000 2 dialect per 10,000 lang 47 author per 10,000 9 dialect per 10,000 get 47 author per 10,000 16 dialect per 10,000 three 47 author per 10,000 5 dialect per 10,000 leevin 47 author per 10,000 0 dialect per 10,000 caa 47 author per 10,000 0 dialect per 10,000 as 47 author per 10,000 60 dialect per 10,000 hear 47 author per 10,000 4 dialect per 10,000 sweet 23 author per 10,000 0 dialect per 10,000 glenarm 23 author per 10,000 0 dialect per 10,000 mony 23 author per 10,000 4 dialect per 10,000 like 23 author per 10,000 28 dialect per 10,000 ago 23 author per 10,000 1 dialect per 10,000 larne 23 author per 10,000 0 dialect per 10,000 october 23 author per 10,000 0 dialect per 10,000 want 23 author per 10,000 7 dialect per 10,000 hired 23 author per 10,000 0 dialect per 10,000 matt 23 author per 10,000 0 dialect per 10,000 message 23 author per 10,000 1 dialect per 10,000 places 23 author per 10,000 1 dialect per 10,000 meharg 23 author per 10,000 0 dialect per 10,000 bl 23 author per 10,000 0 dialect per 10,000 before 23 author per 10,000 3 dialect per 10,000 peak 23 author per 10,000 0 dialect per 10,000 ether 23 author per 10,000 0 dialect per 10,000 met 23 author per 10,000 1 dialect per 10,000 wife 23 author per 10,000 2 dialect per 10,000 twa 23 author per 10,000 9 dialect per 10,000 went 23 author per 10,000 7 dialect per 10,000 week 23 author per 10,000 2 dialect per 10,000 wus 23 author per 10,000 0 dialect per 10,000 when 23 author per 10,000 17 dialect per 10,000 waaked 23 author per 10,000 0 dialect per 10,000 happy 23 author per 10,000 1 dialect per 10,000 €™easton 23 author per 10,000 0 dialect per 10,000 bike 23 author per 10,000 0 dialect per 10,000 was 23 author per 10,000 6 dialect per 10,000 rid 23 author per 10,000 1 dialect per 10,000 so 23 author per 10,000 9 dialect per 10,000 tildarg 23 author per 10,000 0 dialect per 10,000 tappin 23 author per 10,000 0 dialect per 10,000 know 23 author per 10,000 4 dialect per 10,000 rage 23 author per 10,000 0 dialect per 10,000 €™re 23 author per 10,000 5 dialect per 10,000 cute 23 author per 10,000 0 dialect per 10,000 withoot 23 author per 10,000 1 dialect per 10,000 disco 23 author per 10,000 0 dialect per 10,000 date 23 author per 10,000 1 dialect per 10,000 gone 23 author per 10,000 1 dialect per 10,000 live 23 author per 10,000 1 dialect per 10,000 different 23 author per 10,000 3 dialect per 10,000 country 23 author per 10,000 1 dialect per 10,000 gane 23 author per 10,000 1 dialect per 10,000 on 23 author per 10,000 56 dialect per 10,000 best 23 author per 10,000 4 dialect per 10,000 same 23 author per 10,000 6 dialect per 10,000 fir 23 author per 10,000 8 dialect per 10,000 keep 23 author per 10,000 5 dialect per 10,000 ullans 23 author per 10,000 0 dialect per 10,000 very 23 author per 10,000 1 dialect per 10,000 years 23 author per 10,000 3 dialect per 10,000 tv 23 author per 10,000 0 dialect per 10,000 wha 23 author per 10,000 7 dialect per 10,000 knows 23 author per 10,000 1 dialect per 10,000 fifty 23 author per 10,000 1 dialect per 10,000 past 23 author per 10,000 3 dialect per 10,000 partner 23 author per 10,000 0 dialect per 10,000 lancers 23 author per 10,000 0 dialect per 10,000 done 23 author per 10,000 3 dialect per 10,000 setts 23 author per 10,000 0 dialect per 10,000 polka 23 author per 10,000 0 dialect per 10,000 reels 23 author per 10,000 0 dialect per 10,000 more 23 author per 10,000 0 dialect per 10,000 wanted 23 author per 10,000 1 dialect per 10,000 dancin 23 author per 10,000 0 dialect per 10,000 odds 23 author per 10,000 0 dialect per 10,000 last 23 author per 10,000 6 dialect per 10,000 alwyes 23 author per 10,000 0 dialect per 10,000 €˜twas 23 author per 10,000 0 dialect per 10,000 great 23 author per 10,000 3 dialect per 10,000 while 23 author per 10,000 5 dialect per 10,000 came 23 author per 10,000 3 dialect per 10,000 ithers 23 author per 10,000 2 dialect per 10,000 chance 23 author per 10,000 2 dialect per 10,000 their 23 author per 10,000 19 dialect per 10,000 glide 23 author per 10,000 0 dialect per 10,000 watch 23 author per 10,000 2 dialect per 10,000 poocher 23 author per 10,000 0 dialect per 10,000 rattlin 23 author per 10,000 0 dialect per 10,000 soons 23 author per 10,000 0 dialect per 10,000 heels 23 author per 10,000 0 dialect per 10,000 nicht 23 author per 10,000 5 dialect per 10,000 stan 23 author per 10,000 0 dialect per 10,000 diinne 23 author per 10,000 0 dialect per 10,000 why 23 author per 10,000 2 dialect per 10,000 onywye 23 author per 10,000 0 dialect per 10,000 ouler 23 author per 10,000 0 dialect per 10,000 folk 23 author per 10,000 5 dialect per 10,000 unnerstaun 23 author per 10,000 1 dialect per 10,000 kan 23 author per 10,000 0 dialect per 10,000 hes 23 author per 10,000 1 dialect per 10,000 ninety 23 author per 10,000 0 dialect per 10,000 third 23 author per 10,000 1 dialect per 10,000 year 23 author per 10,000 8 dialect per 10,000 geen 23 author per 10,000 0 dialect per 10,000 richtfa 23 author per 10,000 0 dialect per 10,000 whiles 23 author per 10,000 2 dialect per 10,000 mair 23 author per 10,000 19 dialect per 10,000 road 23 author per 10,000 3 dialect per 10,000 nir 23 author per 10,000 0 dialect per 10,000 fore 23 author per 10,000 0 dialect per 10,000 seems 23 author per 10,000 2 dialect per 10,000 place 23 author per 10,000 6 dialect per 10,000 hell 23 author per 10,000 1 dialect per 10,000 leather 23 author per 10,000 0 dialect per 10,000 wye 23 author per 10,000 0 dialect per 10,000 still 23 author per 10,000 8 dialect per 10,000 feyther 23 author per 10,000 0 dialect per 10,000 hae 23 author per 10,000 22 dialect per 10,000 made 23 author per 10,000 8 dialect per 10,000 through 23 author per 10,000 6 dialect per 10,000 score 23 author per 10,000 0 dialect per 10,000 aye 23 author per 10,000 15 dialect per 10,000 dey 23 author per 10,000 0 dialect per 10,000 what 23 author per 10,000 5 dialect per 10,000 big 23 author per 10,000 8 dialect per 10,000 birthday 23 author per 10,000 0 dialect per 10,000 ither 23 author per 10,000 12 dialect per 10,000 ten 23 author per 10,000 2 dialect per 10,000 merker 23 author per 10,000 0 dialect per 10,000 than 23 author per 10,000 11 dialect per 10,000 ustae 23 author per 10,000 0 dialect per 10,000 be 23 author per 10,000 51 dialect per 10,000 bit 23 author per 10,000 16 dialect per 10,000 step 23 author per 10,000 1 dialect per 10,000 slower 23 author per 10,000 0 dialect per 10,000 dae 23 author per 10,000 17 dialect per 10,000 ower 23 author per 10,000 18 dialect per 10,000 richtly 23 author per 10,000 0 dialect per 10,000 gettin 23 author per 10,000 4 dialect per 10,000 onythin 23 author per 10,000 2 dialect per 10,000 else 23 author per 10,000 3 dialect per 10,000
Doric
a 512 author per 10,000 285 dialect per 10,000 the 442 author per 10,000 534 dialect per 10,000 tae 302 author per 10,000 178 dialect per 10,000 ir 209 author per 10,000 1 dialect per 10,000 tha 209 author per 10,000 0 dialect per 10,000 i 163 author per 10,000 54 dialect per 10,000 an 163 author per 10,000 315 dialect per 10,000 o 163 author per 10,000 200 dialect per 10,000 in 140 author per 10,000 136 dialect per 10,000 oul 116 author per 10,000 0 dialect per 10,000 but 116 author per 10,000 15 dialect per 10,000 it 116 author per 10,000 109 dialect per 10,000 we 93 author per 10,000 21 dialect per 10,000 €™ 93 author per 10,000 33 dialect per 10,000 is 93 author per 10,000 41 dialect per 10,000 ye 93 author per 10,000 77 dialect per 10,000 dance 93 author per 10,000 0 dialect per 10,000 noo 93 author per 10,000 20 dialect per 10,000 some 93 author per 10,000 13 dialect per 10,000 this 70 author per 10,000 22 dialect per 10,000 €™s 70 author per 10,000 30 dialect per 10,000 they 70 author per 10,000 40 dialect per 10,000 mae 70 author per 10,000 0 dialect per 10,000 think 70 author per 10,000 10 dialect per 10,000 oot 70 author per 10,000 53 dialect per 10,000 young 70 author per 10,000 3 dialect per 10,000 am 70 author per 10,000 2 dialect per 10,000 wid 70 author per 10,000 18 dialect per 10,000 frae 70 author per 10,000 14 dialect per 10,000 my 70 author per 10,000 11 dialect per 10,000 nae 70 author per 10,000 49 dialect per 10,000 yins 70 author per 10,000 0 dialect per 10,000 noo-a-deys 47 author per 10,000 0 dialect per 10,000 canny 47 author per 10,000 0 dialect per 10,000 roon 47 author per 10,000 12 dialect per 10,000 sae 47 author per 10,000 16 dialect per 10,000 say 47 author per 10,000 12 dialect per 10,000 hame 47 author per 10,000 11 dialect per 10,000 aa 47 author per 10,000 39 dialect per 10,000 floor 47 author per 10,000 0 dialect per 10,000 naw 47 author per 10,000 0 dialect per 10,000 robinson 47 author per 10,000 0 dialect per 10,000 for 47 author per 10,000 40 dialect per 10,000 that 47 author per 10,000 60 dialect per 10,000 age 47 author per 10,000 2 dialect per 10,000 sandy 47 author per 10,000 3 dialect per 10,000 side 47 author per 10,000 5 dialect per 10,000 thauts 47 author per 10,000 0 dialect per 10,000 wae 47 author per 10,000 0 dialect per 10,000 thaur 47 author per 10,000 0 dialect per 10,000 them 47 author per 10,000 31 dialect per 10,000 mi 47 author per 10,000 0 dialect per 10,000 had 47 author per 10,000 2 dialect per 10,000 feet 47 author per 10,000 4 dialect per 10,000 at 47 author per 10,000 57 dialect per 10,000 see 47 author per 10,000 21 dialect per 10,000 bae 47 author per 10,000 0 dialect per 10,000 kno 47 author per 10,000 0 dialect per 10,000 far 47 author per 10,000 14 dialect per 10,000 lang 47 author per 10,000 12 dialect per 10,000 get 47 author per 10,000 14 dialect per 10,000 three 47 author per 10,000 7 dialect per 10,000 leevin 47 author per 10,000 0 dialect per 10,000 caa 47 author per 10,000 1 dialect per 10,000 as 47 author per 10,000 57 dialect per 10,000 hear 47 author per 10,000 3 dialect per 10,000 sweet 23 author per 10,000 2 dialect per 10,000 glenarm 23 author per 10,000 0 dialect per 10,000 mony 23 author per 10,000 4 dialect per 10,000 like 23 author per 10,000 41 dialect per 10,000 ago 23 author per 10,000 1 dialect per 10,000 larne 23 author per 10,000 0 dialect per 10,000 october 23 author per 10,000 0 dialect per 10,000 want 23 author per 10,000 1 dialect per 10,000 hired 23 author per 10,000 0 dialect per 10,000 matt 23 author per 10,000 0 dialect per 10,000 message 23 author per 10,000 0 dialect per 10,000 places 23 author per 10,000 1 dialect per 10,000 meharg 23 author per 10,000 0 dialect per 10,000 bl 23 author per 10,000 0 dialect per 10,000 before 23 author per 10,000 0 dialect per 10,000 peak 23 author per 10,000 0 dialect per 10,000 ether 23 author per 10,000 0 dialect per 10,000 met 23 author per 10,000 1 dialect per 10,000 wife 23 author per 10,000 3 dialect per 10,000 twa 23 author per 10,000 20 dialect per 10,000 went 23 author per 10,000 4 dialect per 10,000 week 23 author per 10,000 1 dialect per 10,000 wus 23 author per 10,000 0 dialect per 10,000 when 23 author per 10,000 2 dialect per 10,000 waaked 23 author per 10,000 0 dialect per 10,000 happy 23 author per 10,000 2 dialect per 10,000 €™easton 23 author per 10,000 0 dialect per 10,000 bike 23 author per 10,000 1 dialect per 10,000 was 23 author per 10,000 4 dialect per 10,000 rid 23 author per 10,000 0 dialect per 10,000 so 23 author per 10,000 12 dialect per 10,000 tildarg 23 author per 10,000 0 dialect per 10,000 tappin 23 author per 10,000 0 dialect per 10,000 know 23 author per 10,000 0 dialect per 10,000 rage 23 author per 10,000 0 dialect per 10,000 €™re 23 author per 10,000 2 dialect per 10,000 cute 23 author per 10,000 0 dialect per 10,000 withoot 23 author per 10,000 1 dialect per 10,000 disco 23 author per 10,000 0 dialect per 10,000 date 23 author per 10,000 0 dialect per 10,000 gone 23 author per 10,000 1 dialect per 10,000 live 23 author per 10,000 1 dialect per 10,000 different 23 author per 10,000 1 dialect per 10,000 country 23 author per 10,000 1 dialect per 10,000 gane 23 author per 10,000 0 dialect per 10,000 on 23 author per 10,000 65 dialect per 10,000 best 23 author per 10,000 4 dialect per 10,000 same 23 author per 10,000 5 dialect per 10,000 fir 23 author per 10,000 16 dialect per 10,000 keep 23 author per 10,000 4 dialect per 10,000 ullans 23 author per 10,000 0 dialect per 10,000 very 23 author per 10,000 2 dialect per 10,000 years 23 author per 10,000 3 dialect per 10,000 tv 23 author per 10,000 1 dialect per 10,000 wha 23 author per 10,000 1 dialect per 10,000 knows 23 author per 10,000 0 dialect per 10,000 fifty 23 author per 10,000 1 dialect per 10,000 past 23 author per 10,000 3 dialect per 10,000 partner 23 author per 10,000 0 dialect per 10,000 lancers 23 author per 10,000 0 dialect per 10,000 done 23 author per 10,000 0 dialect per 10,000 setts 23 author per 10,000 0 dialect per 10,000 polka 23 author per 10,000 0 dialect per 10,000 reels 23 author per 10,000 0 dialect per 10,000 more 23 author per 10,000 0 dialect per 10,000 wanted 23 author per 10,000 1 dialect per 10,000 dancin 23 author per 10,000 0 dialect per 10,000 odds 23 author per 10,000 0 dialect per 10,000 last 23 author per 10,000 6 dialect per 10,000 alwyes 23 author per 10,000 0 dialect per 10,000 €˜twas 23 author per 10,000 0 dialect per 10,000 great 23 author per 10,000 5 dialect per 10,000 while 23 author per 10,000 2 dialect per 10,000 came 23 author per 10,000 5 dialect per 10,000 ithers 23 author per 10,000 1 dialect per 10,000 chance 23 author per 10,000 1 dialect per 10,000 their 23 author per 10,000 23 dialect per 10,000 glide 23 author per 10,000 0 dialect per 10,000 watch 23 author per 10,000 1 dialect per 10,000 poocher 23 author per 10,000 0 dialect per 10,000 rattlin 23 author per 10,000 0 dialect per 10,000 soons 23 author per 10,000 0 dialect per 10,000 heels 23 author per 10,000 0 dialect per 10,000 nicht 23 author per 10,000 12 dialect per 10,000 stan 23 author per 10,000 1 dialect per 10,000 diinne 23 author per 10,000 0 dialect per 10,000 why 23 author per 10,000 1 dialect per 10,000 onywye 23 author per 10,000 2 dialect per 10,000 ouler 23 author per 10,000 0 dialect per 10,000 folk 23 author per 10,000 3 dialect per 10,000 unnerstaun 23 author per 10,000 0 dialect per 10,000 kan 23 author per 10,000 0 dialect per 10,000 hes 23 author per 10,000 0 dialect per 10,000 ninety 23 author per 10,000 0 dialect per 10,000 third 23 author per 10,000 1 dialect per 10,000 year 23 author per 10,000 6 dialect per 10,000 geen 23 author per 10,000 0 dialect per 10,000 richtfa 23 author per 10,000 0 dialect per 10,000 whiles 23 author per 10,000 0 dialect per 10,000 mair 23 author per 10,000 19 dialect per 10,000 road 23 author per 10,000 5 dialect per 10,000 nir 23 author per 10,000 0 dialect per 10,000 fore 23 author per 10,000 1 dialect per 10,000 seems 23 author per 10,000 1 dialect per 10,000 place 23 author per 10,000 6 dialect per 10,000 hell 23 author per 10,000 2 dialect per 10,000 leather 23 author per 10,000 1 dialect per 10,000 wye 23 author per 10,000 13 dialect per 10,000 still 23 author per 10,000 6 dialect per 10,000 feyther 23 author per 10,000 0 dialect per 10,000 hae 23 author per 10,000 18 dialect per 10,000 made 23 author per 10,000 9 dialect per 10,000 through 23 author per 10,000 2 dialect per 10,000 score 23 author per 10,000 0 dialect per 10,000 aye 23 author per 10,000 15 dialect per 10,000 dey 23 author per 10,000 0 dialect per 10,000 what 23 author per 10,000 1 dialect per 10,000 big 23 author per 10,000 5 dialect per 10,000 birthday 23 author per 10,000 1 dialect per 10,000 ither 23 author per 10,000 8 dialect per 10,000 ten 23 author per 10,000 3 dialect per 10,000 merker 23 author per 10,000 0 dialect per 10,000 than 23 author per 10,000 9 dialect per 10,000 ustae 23 author per 10,000 0 dialect per 10,000 be 23 author per 10,000 44 dialect per 10,000 bit 23 author per 10,000 48 dialect per 10,000 step 23 author per 10,000 1 dialect per 10,000 slower 23 author per 10,000 0 dialect per 10,000 dae 23 author per 10,000 4 dialect per 10,000 ower 23 author per 10,000 28 dialect per 10,000 richtly 23 author per 10,000 0 dialect per 10,000 gettin 23 author per 10,000 3 dialect per 10,000 onythin 23 author per 10,000 2 dialect per 10,000 else 23 author per 10,000 2 dialect per 10,000
Shetland
a 512 author per 10,000 235 dialect per 10,000 the 442 author per 10,000 23 dialect per 10,000 tae 302 author per 10,000 60 dialect per 10,000 ir 209 author per 10,000 12 dialect per 10,000 tha 209 author per 10,000 0 dialect per 10,000 i 163 author per 10,000 133 dialect per 10,000 an 163 author per 10,000 349 dialect per 10,000 o 163 author per 10,000 187 dialect per 10,000 in 140 author per 10,000 93 dialect per 10,000 oul 116 author per 10,000 0 dialect per 10,000 but 116 author per 10,000 36 dialect per 10,000 it 116 author per 10,000 59 dialect per 10,000 we 93 author per 10,000 38 dialect per 10,000 €™ 93 author per 10,000 28 dialect per 10,000 is 93 author per 10,000 62 dialect per 10,000 ye 93 author per 10,000 0 dialect per 10,000 dance 93 author per 10,000 2 dialect per 10,000 noo 93 author per 10,000 19 dialect per 10,000 some 93 author per 10,000 14 dialect per 10,000 this 70 author per 10,000 1 dialect per 10,000 €™s 70 author per 10,000 17 dialect per 10,000 they 70 author per 10,000 1 dialect per 10,000 mae 70 author per 10,000 0 dialect per 10,000 think 70 author per 10,000 0 dialect per 10,000 oot 70 author per 10,000 47 dialect per 10,000 young 70 author per 10,000 4 dialect per 10,000 am 70 author per 10,000 6 dialect per 10,000 wid 70 author per 10,000 43 dialect per 10,000 frae 70 author per 10,000 1 dialect per 10,000 my 70 author per 10,000 20 dialect per 10,000 nae 70 author per 10,000 26 dialect per 10,000 yins 70 author per 10,000 0 dialect per 10,000 noo-a-deys 47 author per 10,000 0 dialect per 10,000 canny 47 author per 10,000 0 dialect per 10,000 roon 47 author per 10,000 1 dialect per 10,000 sae 47 author per 10,000 9 dialect per 10,000 say 47 author per 10,000 15 dialect per 10,000 hame 47 author per 10,000 7 dialect per 10,000 aa 47 author per 10,000 57 dialect per 10,000 floor 47 author per 10,000 0 dialect per 10,000 naw 47 author per 10,000 0 dialect per 10,000 robinson 47 author per 10,000 0 dialect per 10,000 for 47 author per 10,000 48 dialect per 10,000 that 47 author per 10,000 4 dialect per 10,000 age 47 author per 10,000 1 dialect per 10,000 sandy 47 author per 10,000 0 dialect per 10,000 side 47 author per 10,000 5 dialect per 10,000 thauts 47 author per 10,000 0 dialect per 10,000 wae 47 author per 10,000 0 dialect per 10,000 thaur 47 author per 10,000 0 dialect per 10,000 them 47 author per 10,000 1 dialect per 10,000 mi 47 author per 10,000 1 dialect per 10,000 had 47 author per 10,000 2 dialect per 10,000 feet 47 author per 10,000 4 dialect per 10,000 at 47 author per 10,000 119 dialect per 10,000 see 47 author per 10,000 22 dialect per 10,000 bae 47 author per 10,000 0 dialect per 10,000 kno 47 author per 10,000 0 dialect per 10,000 far 47 author per 10,000 6 dialect per 10,000 lang 47 author per 10,000 12 dialect per 10,000 get 47 author per 10,000 6 dialect per 10,000 three 47 author per 10,000 0 dialect per 10,000 leevin 47 author per 10,000 0 dialect per 10,000 caa 47 author per 10,000 3 dialect per 10,000 as 47 author per 10,000 78 dialect per 10,000 hear 47 author per 10,000 3 dialect per 10,000 sweet 23 author per 10,000 1 dialect per 10,000 glenarm 23 author per 10,000 0 dialect per 10,000 mony 23 author per 10,000 3 dialect per 10,000 like 23 author per 10,000 2 dialect per 10,000 ago 23 author per 10,000 1 dialect per 10,000 larne 23 author per 10,000 0 dialect per 10,000 october 23 author per 10,000 0 dialect per 10,000 want 23 author per 10,000 5 dialect per 10,000 hired 23 author per 10,000 0 dialect per 10,000 matt 23 author per 10,000 0 dialect per 10,000 message 23 author per 10,000 0 dialect per 10,000 places 23 author per 10,000 0 dialect per 10,000 meharg 23 author per 10,000 0 dialect per 10,000 bl 23 author per 10,000 0 dialect per 10,000 before 23 author per 10,000 0 dialect per 10,000 peak 23 author per 10,000 0 dialect per 10,000 ether 23 author per 10,000 0 dialect per 10,000 met 23 author per 10,000 1 dialect per 10,000 wife 23 author per 10,000 4 dialect per 10,000 twa 23 author per 10,000 11 dialect per 10,000 went 23 author per 10,000 0 dialect per 10,000 week 23 author per 10,000 1 dialect per 10,000 wus 23 author per 10,000 0 dialect per 10,000 when 23 author per 10,000 3 dialect per 10,000 waaked 23 author per 10,000 0 dialect per 10,000 happy 23 author per 10,000 1 dialect per 10,000 €™easton 23 author per 10,000 0 dialect per 10,000 bike 23 author per 10,000 0 dialect per 10,000 was 23 author per 10,000 3 dialect per 10,000 rid 23 author per 10,000 1 dialect per 10,000 so 23 author per 10,000 32 dialect per 10,000 tildarg 23 author per 10,000 0 dialect per 10,000 tappin 23 author per 10,000 0 dialect per 10,000 know 23 author per 10,000 0 dialect per 10,000 rage 23 author per 10,000 0 dialect per 10,000 €™re 23 author per 10,000 1 dialect per 10,000 cute 23 author per 10,000 0 dialect per 10,000 withoot 23 author per 10,000 1 dialect per 10,000 disco 23 author per 10,000 0 dialect per 10,000 date 23 author per 10,000 0 dialect per 10,000 gone 23 author per 10,000 0 dialect per 10,000 live 23 author per 10,000 2 dialect per 10,000 different 23 author per 10,000 5 dialect per 10,000 country 23 author per 10,000 1 dialect per 10,000 gane 23 author per 10,000 0 dialect per 10,000 on 23 author per 10,000 52 dialect per 10,000 best 23 author per 10,000 7 dialect per 10,000 same 23 author per 10,000 1 dialect per 10,000 fir 23 author per 10,000 34 dialect per 10,000 keep 23 author per 10,000 5 dialect per 10,000 ullans 23 author per 10,000 0 dialect per 10,000 very 23 author per 10,000 8 dialect per 10,000 years 23 author per 10,000 2 dialect per 10,000 tv 23 author per 10,000 0 dialect per 10,000 wha 23 author per 10,000 6 dialect per 10,000 knows 23 author per 10,000 0 dialect per 10,000 fifty 23 author per 10,000 0 dialect per 10,000 past 23 author per 10,000 2 dialect per 10,000 partner 23 author per 10,000 0 dialect per 10,000 lancers 23 author per 10,000 0 dialect per 10,000 done 23 author per 10,000 2 dialect per 10,000 setts 23 author per 10,000 0 dialect per 10,000 polka 23 author per 10,000 0 dialect per 10,000 reels 23 author per 10,000 0 dialect per 10,000 more 23 author per 10,000 1 dialect per 10,000 wanted 23 author per 10,000 2 dialect per 10,000 dancin 23 author per 10,000 0 dialect per 10,000 odds 23 author per 10,000 0 dialect per 10,000 last 23 author per 10,000 5 dialect per 10,000 alwyes 23 author per 10,000 0 dialect per 10,000 €˜twas 23 author per 10,000 0 dialect per 10,000 great 23 author per 10,000 0 dialect per 10,000 while 23 author per 10,000 5 dialect per 10,000 came 23 author per 10,000 0 dialect per 10,000 ithers 23 author per 10,000 0 dialect per 10,000 chance 23 author per 10,000 3 dialect per 10,000 their 23 author per 10,000 1 dialect per 10,000 glide 23 author per 10,000 0 dialect per 10,000 watch 23 author per 10,000 3 dialect per 10,000 poocher 23 author per 10,000 0 dialect per 10,000 rattlin 23 author per 10,000 0 dialect per 10,000 soons 23 author per 10,000 0 dialect per 10,000 heels 23 author per 10,000 0 dialect per 10,000 nicht 23 author per 10,000 3 dialect per 10,000 stan 23 author per 10,000 0 dialect per 10,000 diinne 23 author per 10,000 0 dialect per 10,000 why 23 author per 10,000 2 dialect per 10,000 onywye 23 author per 10,000 3 dialect per 10,000 ouler 23 author per 10,000 0 dialect per 10,000 folk 23 author per 10,000 1 dialect per 10,000 unnerstaun 23 author per 10,000 0 dialect per 10,000 kan 23 author per 10,000 0 dialect per 10,000 hes 23 author per 10,000 0 dialect per 10,000 ninety 23 author per 10,000 0 dialect per 10,000 third 23 author per 10,000 1 dialect per 10,000 year 23 author per 10,000 3 dialect per 10,000 geen 23 author per 10,000 4 dialect per 10,000 richtfa 23 author per 10,000 0 dialect per 10,000 whiles 23 author per 10,000 0 dialect per 10,000 mair 23 author per 10,000 18 dialect per 10,000 road 23 author per 10,000 0 dialect per 10,000 nir 23 author per 10,000 0 dialect per 10,000 fore 23 author per 10,000 1 dialect per 10,000 seems 23 author per 10,000 2 dialect per 10,000 place 23 author per 10,000 10 dialect per 10,000 hell 23 author per 10,000 0 dialect per 10,000 leather 23 author per 10,000 0 dialect per 10,000 wye 23 author per 10,000 25 dialect per 10,000 still 23 author per 10,000 8 dialect per 10,000 feyther 23 author per 10,000 0 dialect per 10,000 hae 23 author per 10,000 25 dialect per 10,000 made 23 author per 10,000 2 dialect per 10,000 through 23 author per 10,000 0 dialect per 10,000 score 23 author per 10,000 0 dialect per 10,000 aye 23 author per 10,000 12 dialect per 10,000 dey 23 author per 10,000 74 dialect per 10,000 what 23 author per 10,000 1 dialect per 10,000 big 23 author per 10,000 2 dialect per 10,000 birthday 23 author per 10,000 0 dialect per 10,000 ither 23 author per 10,000 0 dialect per 10,000 ten 23 author per 10,000 2 dialect per 10,000 merker 23 author per 10,000 0 dialect per 10,000 than 23 author per 10,000 0 dialect per 10,000 ustae 23 author per 10,000 0 dialect per 10,000 be 23 author per 10,000 60 dialect per 10,000 bit 23 author per 10,000 32 dialect per 10,000 step 23 author per 10,000 1 dialect per 10,000 slower 23 author per 10,000 0 dialect per 10,000 dae 23 author per 10,000 2 dialect per 10,000 ower 23 author per 10,000 27 dialect per 10,000 richtly 23 author per 10,000 0 dialect per 10,000 gettin 23 author per 10,000 1 dialect per 10,000 onythin 23 author per 10,000 0 dialect per 10,000 else 23 author per 10,000 1 dialect per 10,000
Orkney
a 512 author per 10,000 308 dialect per 10,000 the 442 author per 10,000 525 dialect per 10,000 tae 302 author per 10,000 222 dialect per 10,000 ir 209 author per 10,000 2 dialect per 10,000 tha 209 author per 10,000 0 dialect per 10,000 i 163 author per 10,000 188 dialect per 10,000 an 163 author per 10,000 109 dialect per 10,000 o 163 author per 10,000 182 dialect per 10,000 in 140 author per 10,000 154 dialect per 10,000 oul 116 author per 10,000 0 dialect per 10,000 but 116 author per 10,000 24 dialect per 10,000 it 116 author per 10,000 29 dialect per 10,000 we 93 author per 10,000 40 dialect per 10,000 €™ 93 author per 10,000 26 dialect per 10,000 is 93 author per 10,000 54 dialect per 10,000 ye 93 author per 10,000 19 dialect per 10,000 dance 93 author per 10,000 2 dialect per 10,000 noo 93 author per 10,000 21 dialect per 10,000 some 93 author per 10,000 21 dialect per 10,000 this 70 author per 10,000 37 dialect per 10,000 €™s 70 author per 10,000 32 dialect per 10,000 they 70 author per 10,000 44 dialect per 10,000 mae 70 author per 10,000 0 dialect per 10,000 think 70 author per 10,000 11 dialect per 10,000 oot 70 author per 10,000 52 dialect per 10,000 young 70 author per 10,000 3 dialect per 10,000 am 70 author per 10,000 3 dialect per 10,000 wid 70 author per 10,000 26 dialect per 10,000 frae 70 author per 10,000 0 dialect per 10,000 my 70 author per 10,000 3 dialect per 10,000 nae 70 author per 10,000 1 dialect per 10,000 yins 70 author per 10,000 0 dialect per 10,000 noo-a-deys 47 author per 10,000 0 dialect per 10,000 canny 47 author per 10,000 0 dialect per 10,000 roon 47 author per 10,000 1 dialect per 10,000 sae 47 author per 10,000 1 dialect per 10,000 say 47 author per 10,000 13 dialect per 10,000 hame 47 author per 10,000 2 dialect per 10,000 aa 47 author per 10,000 8 dialect per 10,000 floor 47 author per 10,000 4 dialect per 10,000 naw 47 author per 10,000 0 dialect per 10,000 robinson 47 author per 10,000 0 dialect per 10,000 for 47 author per 10,000 27 dialect per 10,000 that 47 author per 10,000 97 dialect per 10,000 age 47 author per 10,000 2 dialect per 10,000 sandy 47 author per 10,000 0 dialect per 10,000 side 47 author per 10,000 4 dialect per 10,000 thauts 47 author per 10,000 0 dialect per 10,000 wae 47 author per 10,000 25 dialect per 10,000 thaur 47 author per 10,000 0 dialect per 10,000 them 47 author per 10,000 21 dialect per 10,000 mi 47 author per 10,000 0 dialect per 10,000 had 47 author per 10,000 3 dialect per 10,000 feet 47 author per 10,000 4 dialect per 10,000 at 47 author per 10,000 53 dialect per 10,000 see 47 author per 10,000 15 dialect per 10,000 bae 47 author per 10,000 0 dialect per 10,000 kno 47 author per 10,000 0 dialect per 10,000 far 47 author per 10,000 5 dialect per 10,000 lang 47 author per 10,000 1 dialect per 10,000 get 47 author per 10,000 14 dialect per 10,000 three 47 author per 10,000 3 dialect per 10,000 leevin 47 author per 10,000 0 dialect per 10,000 caa 47 author per 10,000 0 dialect per 10,000 as 47 author per 10,000 58 dialect per 10,000 hear 47 author per 10,000 4 dialect per 10,000 sweet 23 author per 10,000 1 dialect per 10,000 glenarm 23 author per 10,000 0 dialect per 10,000 mony 23 author per 10,000 2 dialect per 10,000 like 23 author per 10,000 27 dialect per 10,000 ago 23 author per 10,000 2 dialect per 10,000 larne 23 author per 10,000 0 dialect per 10,000 october 23 author per 10,000 1 dialect per 10,000 want 23 author per 10,000 6 dialect per 10,000 hired 23 author per 10,000 0 dialect per 10,000 matt 23 author per 10,000 0 dialect per 10,000 message 23 author per 10,000 0 dialect per 10,000 places 23 author per 10,000 0 dialect per 10,000 meharg 23 author per 10,000 0 dialect per 10,000 bl 23 author per 10,000 0 dialect per 10,000 before 23 author per 10,000 1 dialect per 10,000 peak 23 author per 10,000 0 dialect per 10,000 ether 23 author per 10,000 1 dialect per 10,000 met 23 author per 10,000 2 dialect per 10,000 wife 23 author per 10,000 8 dialect per 10,000 twa 23 author per 10,000 13 dialect per 10,000 went 23 author per 10,000 1 dialect per 10,000 week 23 author per 10,000 4 dialect per 10,000 wus 23 author per 10,000 0 dialect per 10,000 when 23 author per 10,000 31 dialect per 10,000 waaked 23 author per 10,000 0 dialect per 10,000 happy 23 author per 10,000 3 dialect per 10,000 €™easton 23 author per 10,000 0 dialect per 10,000 bike 23 author per 10,000 1 dialect per 10,000 was 23 author per 10,000 2 dialect per 10,000 rid 23 author per 10,000 0 dialect per 10,000 so 23 author per 10,000 34 dialect per 10,000 tildarg 23 author per 10,000 0 dialect per 10,000 tappin 23 author per 10,000 0 dialect per 10,000 know 23 author per 10,000 1 dialect per 10,000 rage 23 author per 10,000 0 dialect per 10,000 €™re 23 author per 10,000 2 dialect per 10,000 cute 23 author per 10,000 0 dialect per 10,000 withoot 23 author per 10,000 3 dialect per 10,000 disco 23 author per 10,000 0 dialect per 10,000 date 23 author per 10,000 0 dialect per 10,000 gone 23 author per 10,000 1 dialect per 10,000 live 23 author per 10,000 1 dialect per 10,000 different 23 author per 10,000 2 dialect per 10,000 country 23 author per 10,000 2 dialect per 10,000 gane 23 author per 10,000 0 dialect per 10,000 on 23 author per 10,000 80 dialect per 10,000 best 23 author per 10,000 6 dialect per 10,000 same 23 author per 10,000 3 dialect per 10,000 fir 23 author per 10,000 9 dialect per 10,000 keep 23 author per 10,000 5 dialect per 10,000 ullans 23 author per 10,000 0 dialect per 10,000 very 23 author per 10,000 11 dialect per 10,000 years 23 author per 10,000 3 dialect per 10,000 tv 23 author per 10,000 2 dialect per 10,000 wha 23 author per 10,000 4 dialect per 10,000 knows 23 author per 10,000 0 dialect per 10,000 fifty 23 author per 10,000 0 dialect per 10,000 past 23 author per 10,000 2 dialect per 10,000 partner 23 author per 10,000 0 dialect per 10,000 lancers 23 author per 10,000 0 dialect per 10,000 done 23 author per 10,000 1 dialect per 10,000 setts 23 author per 10,000 0 dialect per 10,000 polka 23 author per 10,000 0 dialect per 10,000 reels 23 author per 10,000 0 dialect per 10,000 more 23 author per 10,000 16 dialect per 10,000 wanted 23 author per 10,000 2 dialect per 10,000 dancin 23 author per 10,000 0 dialect per 10,000 odds 23 author per 10,000 0 dialect per 10,000 last 23 author per 10,000 9 dialect per 10,000 alwyes 23 author per 10,000 0 dialect per 10,000 €˜twas 23 author per 10,000 0 dialect per 10,000 great 23 author per 10,000 6 dialect per 10,000 while 23 author per 10,000 8 dialect per 10,000 came 23 author per 10,000 1 dialect per 10,000 ithers 23 author per 10,000 1 dialect per 10,000 chance 23 author per 10,000 4 dialect per 10,000 their 23 author per 10,000 10 dialect per 10,000 glide 23 author per 10,000 0 dialect per 10,000 watch 23 author per 10,000 2 dialect per 10,000 poocher 23 author per 10,000 0 dialect per 10,000 rattlin 23 author per 10,000 0 dialect per 10,000 soons 23 author per 10,000 0 dialect per 10,000 heels 23 author per 10,000 0 dialect per 10,000 nicht 23 author per 10,000 0 dialect per 10,000 stan 23 author per 10,000 0 dialect per 10,000 diinne 23 author per 10,000 0 dialect per 10,000 why 23 author per 10,000 5 dialect per 10,000 onywye 23 author per 10,000 0 dialect per 10,000 ouler 23 author per 10,000 0 dialect per 10,000 folk 23 author per 10,000 14 dialect per 10,000 unnerstaun 23 author per 10,000 0 dialect per 10,000 kan 23 author per 10,000 0 dialect per 10,000 hes 23 author per 10,000 0 dialect per 10,000 ninety 23 author per 10,000 0 dialect per 10,000 third 23 author per 10,000 0 dialect per 10,000 year 23 author per 10,000 5 dialect per 10,000 geen 23 author per 10,000 2 dialect per 10,000 richtfa 23 author per 10,000 0 dialect per 10,000 whiles 23 author per 10,000 0 dialect per 10,000 mair 23 author per 10,000 1 dialect per 10,000 road 23 author per 10,000 5 dialect per 10,000 nir 23 author per 10,000 0 dialect per 10,000 fore 23 author per 10,000 1 dialect per 10,000 seems 23 author per 10,000 3 dialect per 10,000 place 23 author per 10,000 4 dialect per 10,000 hell 23 author per 10,000 1 dialect per 10,000 leather 23 author per 10,000 0 dialect per 10,000 wye 23 author per 10,000 0 dialect per 10,000 still 23 author per 10,000 12 dialect per 10,000 feyther 23 author per 10,000 1 dialect per 10,000 hae 23 author per 10,000 17 dialect per 10,000 made 23 author per 10,000 1 dialect per 10,000 through 23 author per 10,000 9 dialect per 10,000 score 23 author per 10,000 0 dialect per 10,000 aye 23 author per 10,000 9 dialect per 10,000 dey 23 author per 10,000 0 dialect per 10,000 what 23 author per 10,000 2 dialect per 10,000 big 23 author per 10,000 8 dialect per 10,000 birthday 23 author per 10,000 0 dialect per 10,000 ither 23 author per 10,000 8 dialect per 10,000 ten 23 author per 10,000 3 dialect per 10,000 merker 23 author per 10,000 0 dialect per 10,000 than 23 author per 10,000 13 dialect per 10,000 ustae 23 author per 10,000 0 dialect per 10,000 be 23 author per 10,000 48 dialect per 10,000 bit 23 author per 10,000 60 dialect per 10,000 step 23 author per 10,000 1 dialect per 10,000 slower 23 author per 10,000 0 dialect per 10,000 dae 23 author per 10,000 10 dialect per 10,000 ower 23 author per 10,000 15 dialect per 10,000 richtly 23 author per 10,000 0 dialect per 10,000 gettin 23 author per 10,000 0 dialect per 10,000 onythin 23 author per 10,000 0 dialect per 10,000 else 23 author per 10,000 2 dialect per 10,000
Southern
a 512 author per 10,000 239 dialect per 10,000 the 442 author per 10,000 463 dialect per 10,000 tae 302 author per 10,000 206 dialect per 10,000 ir 209 author per 10,000 8 dialect per 10,000 tha 209 author per 10,000 0 dialect per 10,000 i 163 author per 10,000 62 dialect per 10,000 an 163 author per 10,000 302 dialect per 10,000 o 163 author per 10,000 191 dialect per 10,000 in 140 author per 10,000 111 dialect per 10,000 oul 116 author per 10,000 0 dialect per 10,000 but 116 author per 10,000 39 dialect per 10,000 it 116 author per 10,000 60 dialect per 10,000 we 93 author per 10,000 18 dialect per 10,000 €™ 93 author per 10,000 11 dialect per 10,000 is 93 author per 10,000 60 dialect per 10,000 ye 93 author per 10,000 31 dialect per 10,000 dance 93 author per 10,000 3 dialect per 10,000 noo 93 author per 10,000 13 dialect per 10,000 some 93 author per 10,000 12 dialect per 10,000 this 70 author per 10,000 32 dialect per 10,000 €™s 70 author per 10,000 32 dialect per 10,000 they 70 author per 10,000 35 dialect per 10,000 mae 70 author per 10,000 1 dialect per 10,000 think 70 author per 10,000 7 dialect per 10,000 oot 70 author per 10,000 34 dialect per 10,000 young 70 author per 10,000 4 dialect per 10,000 am 70 author per 10,000 2 dialect per 10,000 wid 70 author per 10,000 3 dialect per 10,000 frae 70 author per 10,000 35 dialect per 10,000 my 70 author per 10,000 2 dialect per 10,000 nae 70 author per 10,000 26 dialect per 10,000 yins 70 author per 10,000 2 dialect per 10,000 noo-a-deys 47 author per 10,000 0 dialect per 10,000 canny 47 author per 10,000 1 dialect per 10,000 roon 47 author per 10,000 3 dialect per 10,000 sae 47 author per 10,000 25 dialect per 10,000 say 47 author per 10,000 17 dialect per 10,000 hame 47 author per 10,000 10 dialect per 10,000 aa 47 author per 10,000 13 dialect per 10,000 floor 47 author per 10,000 0 dialect per 10,000 naw 47 author per 10,000 2 dialect per 10,000 robinson 47 author per 10,000 0 dialect per 10,000 for 47 author per 10,000 15 dialect per 10,000 that 47 author per 10,000 61 dialect per 10,000 age 47 author per 10,000 1 dialect per 10,000 sandy 47 author per 10,000 0 dialect per 10,000 side 47 author per 10,000 7 dialect per 10,000 thauts 47 author per 10,000 0 dialect per 10,000 wae 47 author per 10,000 2 dialect per 10,000 thaur 47 author per 10,000 0 dialect per 10,000 them 47 author per 10,000 4 dialect per 10,000 mi 47 author per 10,000 1 dialect per 10,000 had 47 author per 10,000 2 dialect per 10,000 feet 47 author per 10,000 4 dialect per 10,000 at 47 author per 10,000 70 dialect per 10,000 see 47 author per 10,000 6 dialect per 10,000 bae 47 author per 10,000 0 dialect per 10,000 kno 47 author per 10,000 0 dialect per 10,000 far 47 author per 10,000 2 dialect per 10,000 lang 47 author per 10,000 12 dialect per 10,000 get 47 author per 10,000 11 dialect per 10,000 three 47 author per 10,000 2 dialect per 10,000 leevin 47 author per 10,000 2 dialect per 10,000 caa 47 author per 10,000 0 dialect per 10,000 as 47 author per 10,000 52 dialect per 10,000 hear 47 author per 10,000 5 dialect per 10,000 sweet 23 author per 10,000 1 dialect per 10,000 glenarm 23 author per 10,000 0 dialect per 10,000 mony 23 author per 10,000 4 dialect per 10,000 like 23 author per 10,000 7 dialect per 10,000 ago 23 author per 10,000 1 dialect per 10,000 larne 23 author per 10,000 0 dialect per 10,000 october 23 author per 10,000 0 dialect per 10,000 want 23 author per 10,000 3 dialect per 10,000 hired 23 author per 10,000 0 dialect per 10,000 matt 23 author per 10,000 1 dialect per 10,000 message 23 author per 10,000 0 dialect per 10,000 places 23 author per 10,000 1 dialect per 10,000 meharg 23 author per 10,000 0 dialect per 10,000 bl 23 author per 10,000 0 dialect per 10,000 before 23 author per 10,000 0 dialect per 10,000 peak 23 author per 10,000 0 dialect per 10,000 ether 23 author per 10,000 0 dialect per 10,000 met 23 author per 10,000 1 dialect per 10,000 wife 23 author per 10,000 4 dialect per 10,000 twa 23 author per 10,000 3 dialect per 10,000 went 23 author per 10,000 13 dialect per 10,000 week 23 author per 10,000 1 dialect per 10,000 wus 23 author per 10,000 0 dialect per 10,000 when 23 author per 10,000 17 dialect per 10,000 waaked 23 author per 10,000 0 dialect per 10,000 happy 23 author per 10,000 1 dialect per 10,000 €™easton 23 author per 10,000 0 dialect per 10,000 bike 23 author per 10,000 1 dialect per 10,000 was 23 author per 10,000 53 dialect per 10,000 rid 23 author per 10,000 1 dialect per 10,000 so 23 author per 10,000 3 dialect per 10,000 tildarg 23 author per 10,000 0 dialect per 10,000 tappin 23 author per 10,000 0 dialect per 10,000 know 23 author per 10,000 1 dialect per 10,000 rage 23 author per 10,000 0 dialect per 10,000 €™re 23 author per 10,000 1 dialect per 10,000 cute 23 author per 10,000 0 dialect per 10,000 withoot 23 author per 10,000 3 dialect per 10,000 disco 23 author per 10,000 0 dialect per 10,000 date 23 author per 10,000 0 dialect per 10,000 gone 23 author per 10,000 0 dialect per 10,000 live 23 author per 10,000 1 dialect per 10,000 different 23 author per 10,000 2 dialect per 10,000 country 23 author per 10,000 1 dialect per 10,000 gane 23 author per 10,000 1 dialect per 10,000 on 23 author per 10,000 50 dialect per 10,000 best 23 author per 10,000 4 dialect per 10,000 same 23 author per 10,000 6 dialect per 10,000 fir 23 author per 10,000 12 dialect per 10,000 keep 23 author per 10,000 3 dialect per 10,000 ullans 23 author per 10,000 0 dialect per 10,000 very 23 author per 10,000 1 dialect per 10,000 years 23 author per 10,000 4 dialect per 10,000 tv 23 author per 10,000 0 dialect per 10,000 wha 23 author per 10,000 2 dialect per 10,000 knows 23 author per 10,000 0 dialect per 10,000 fifty 23 author per 10,000 0 dialect per 10,000 past 23 author per 10,000 2 dialect per 10,000 partner 23 author per 10,000 0 dialect per 10,000 lancers 23 author per 10,000 0 dialect per 10,000 done 23 author per 10,000 1 dialect per 10,000 setts 23 author per 10,000 0 dialect per 10,000 polka 23 author per 10,000 0 dialect per 10,000 reels 23 author per 10,000 0 dialect per 10,000 more 23 author per 10,000 1 dialect per 10,000 wanted 23 author per 10,000 1 dialect per 10,000 dancin 23 author per 10,000 1 dialect per 10,000 odds 23 author per 10,000 0 dialect per 10,000 last 23 author per 10,000 6 dialect per 10,000 alwyes 23 author per 10,000 0 dialect per 10,000 €˜twas 23 author per 10,000 0 dialect per 10,000 great 23 author per 10,000 3 dialect per 10,000 while 23 author per 10,000 7 dialect per 10,000 came 23 author per 10,000 6 dialect per 10,000 ithers 23 author per 10,000 2 dialect per 10,000 chance 23 author per 10,000 1 dialect per 10,000 their 23 author per 10,000 14 dialect per 10,000 glide 23 author per 10,000 0 dialect per 10,000 watch 23 author per 10,000 3 dialect per 10,000 poocher 23 author per 10,000 0 dialect per 10,000 rattlin 23 author per 10,000 0 dialect per 10,000 soons 23 author per 10,000 0 dialect per 10,000 heels 23 author per 10,000 0 dialect per 10,000 nicht 23 author per 10,000 7 dialect per 10,000 stan 23 author per 10,000 0 dialect per 10,000 diinne 23 author per 10,000 0 dialect per 10,000 why 23 author per 10,000 1 dialect per 10,000 onywye 23 author per 10,000 0 dialect per 10,000 ouler 23 author per 10,000 0 dialect per 10,000 folk 23 author per 10,000 4 dialect per 10,000 unnerstaun 23 author per 10,000 0 dialect per 10,000 kan 23 author per 10,000 3 dialect per 10,000 hes 23 author per 10,000 4 dialect per 10,000 ninety 23 author per 10,000 0 dialect per 10,000 third 23 author per 10,000 0 dialect per 10,000 year 23 author per 10,000 5 dialect per 10,000 geen 23 author per 10,000 0 dialect per 10,000 richtfa 23 author per 10,000 0 dialect per 10,000 whiles 23 author per 10,000 1 dialect per 10,000 mair 23 author per 10,000 16 dialect per 10,000 road 23 author per 10,000 7 dialect per 10,000 nir 23 author per 10,000 0 dialect per 10,000 fore 23 author per 10,000 1 dialect per 10,000 seems 23 author per 10,000 1 dialect per 10,000 place 23 author per 10,000 6 dialect per 10,000 hell 23 author per 10,000 0 dialect per 10,000 leather 23 author per 10,000 0 dialect per 10,000 wye 23 author per 10,000 0 dialect per 10,000 still 23 author per 10,000 8 dialect per 10,000 feyther 23 author per 10,000 0 dialect per 10,000 hae 23 author per 10,000 33 dialect per 10,000 made 23 author per 10,000 6 dialect per 10,000 through 23 author per 10,000 2 dialect per 10,000 score 23 author per 10,000 0 dialect per 10,000 aye 23 author per 10,000 11 dialect per 10,000 dey 23 author per 10,000 0 dialect per 10,000 what 23 author per 10,000 2 dialect per 10,000 big 23 author per 10,000 7 dialect per 10,000 birthday 23 author per 10,000 0 dialect per 10,000 ither 23 author per 10,000 12 dialect per 10,000 ten 23 author per 10,000 2 dialect per 10,000 merker 23 author per 10,000 0 dialect per 10,000 than 23 author per 10,000 9 dialect per 10,000 ustae 23 author per 10,000 0 dialect per 10,000 be 23 author per 10,000 13 dialect per 10,000 bit 23 author per 10,000 18 dialect per 10,000 step 23 author per 10,000 0 dialect per 10,000 slower 23 author per 10,000 0 dialect per 10,000 dae 23 author per 10,000 13 dialect per 10,000 ower 23 author per 10,000 16 dialect per 10,000 richtly 23 author per 10,000 0 dialect per 10,000 gettin 23 author per 10,000 4 dialect per 10,000 onythin 23 author per 10,000 2 dialect per 10,000 else 23 author per 10,000 2 dialect per 10,000
Ulster
a 512 author per 10,000 295 dialect per 10,000 the 442 author per 10,000 229 dialect per 10,000 tae 302 author per 10,000 259 dialect per 10,000 ir 209 author per 10,000 24 dialect per 10,000 tha 209 author per 10,000 388 dialect per 10,000 i 163 author per 10,000 9 dialect per 10,000 an 163 author per 10,000 392 dialect per 10,000 o 163 author per 10,000 220 dialect per 10,000 in 140 author per 10,000 99 dialect per 10,000 oul 116 author per 10,000 16 dialect per 10,000 but 116 author per 10,000 53 dialect per 10,000 it 116 author per 10,000 82 dialect per 10,000 we 93 author per 10,000 17 dialect per 10,000 €™ 93 author per 10,000 19 dialect per 10,000 is 93 author per 10,000 22 dialect per 10,000 ye 93 author per 10,000 94 dialect per 10,000 dance 93 author per 10,000 2 dialect per 10,000 noo 93 author per 10,000 28 dialect per 10,000 some 93 author per 10,000 8 dialect per 10,000 this 70 author per 10,000 27 dialect per 10,000 €™s 70 author per 10,000 15 dialect per 10,000 they 70 author per 10,000 25 dialect per 10,000 mae 70 author per 10,000 20 dialect per 10,000 think 70 author per 10,000 9 dialect per 10,000 oot 70 author per 10,000 58 dialect per 10,000 young 70 author per 10,000 1 dialect per 10,000 am 70 author per 10,000 4 dialect per 10,000 wid 70 author per 10,000 1 dialect per 10,000 frae 70 author per 10,000 38 dialect per 10,000 my 70 author per 10,000 2 dialect per 10,000 nae 70 author per 10,000 26 dialect per 10,000 yins 70 author per 10,000 10 dialect per 10,000 noo-a-deys 47 author per 10,000 0 dialect per 10,000 canny 47 author per 10,000 1 dialect per 10,000 roon 47 author per 10,000 14 dialect per 10,000 sae 47 author per 10,000 30 dialect per 10,000 say 47 author per 10,000 14 dialect per 10,000 hame 47 author per 10,000 11 dialect per 10,000 aa 47 author per 10,000 43 dialect per 10,000 floor 47 author per 10,000 0 dialect per 10,000 naw 47 author per 10,000 13 dialect per 10,000 robinson 47 author per 10,000 0 dialect per 10,000 for 47 author per 10,000 44 dialect per 10,000 that 47 author per 10,000 88 dialect per 10,000 age 47 author per 10,000 2 dialect per 10,000 sandy 47 author per 10,000 0 dialect per 10,000 side 47 author per 10,000 4 dialect per 10,000 thauts 47 author per 10,000 0 dialect per 10,000 wae 47 author per 10,000 11 dialect per 10,000 thaur 47 author per 10,000 1 dialect per 10,000 them 47 author per 10,000 6 dialect per 10,000 mi 47 author per 10,000 0 dialect per 10,000 had 47 author per 10,000 18 dialect per 10,000 feet 47 author per 10,000 4 dialect per 10,000 at 47 author per 10,000 47 dialect per 10,000 see 47 author per 10,000 20 dialect per 10,000 bae 47 author per 10,000 22 dialect per 10,000 kno 47 author per 10,000 0 dialect per 10,000 far 47 author per 10,000 6 dialect per 10,000 lang 47 author per 10,000 14 dialect per 10,000 get 47 author per 10,000 8 dialect per 10,000 three 47 author per 10,000 4 dialect per 10,000 leevin 47 author per 10,000 4 dialect per 10,000 caa 47 author per 10,000 4 dialect per 10,000 as 47 author per 10,000 30 dialect per 10,000 hear 47 author per 10,000 6 dialect per 10,000 sweet 23 author per 10,000 1 dialect per 10,000 glenarm 23 author per 10,000 0 dialect per 10,000 mony 23 author per 10,000 1 dialect per 10,000 like 23 author per 10,000 9 dialect per 10,000 ago 23 author per 10,000 1 dialect per 10,000 larne 23 author per 10,000 1 dialect per 10,000 october 23 author per 10,000 0 dialect per 10,000 want 23 author per 10,000 4 dialect per 10,000 hired 23 author per 10,000 0 dialect per 10,000 matt 23 author per 10,000 0 dialect per 10,000 message 23 author per 10,000 1 dialect per 10,000 places 23 author per 10,000 1 dialect per 10,000 meharg 23 author per 10,000 0 dialect per 10,000 bl 23 author per 10,000 0 dialect per 10,000 before 23 author per 10,000 0 dialect per 10,000 peak 23 author per 10,000 0 dialect per 10,000 ether 23 author per 10,000 1 dialect per 10,000 met 23 author per 10,000 1 dialect per 10,000 wife 23 author per 10,000 3 dialect per 10,000 twa 23 author per 10,000 13 dialect per 10,000 went 23 author per 10,000 15 dialect per 10,000 week 23 author per 10,000 1 dialect per 10,000 wus 23 author per 10,000 93 dialect per 10,000 when 23 author per 10,000 2 dialect per 10,000 waaked 23 author per 10,000 0 dialect per 10,000 happy 23 author per 10,000 1 dialect per 10,000 €™easton 23 author per 10,000 0 dialect per 10,000 bike 23 author per 10,000 1 dialect per 10,000 was 23 author per 10,000 11 dialect per 10,000 rid 23 author per 10,000 2 dialect per 10,000 so 23 author per 10,000 6 dialect per 10,000 tildarg 23 author per 10,000 0 dialect per 10,000 tappin 23 author per 10,000 0 dialect per 10,000 know 23 author per 10,000 13 dialect per 10,000 rage 23 author per 10,000 0 dialect per 10,000 €™re 23 author per 10,000 1 dialect per 10,000 cute 23 author per 10,000 0 dialect per 10,000 withoot 23 author per 10,000 2 dialect per 10,000 disco 23 author per 10,000 0 dialect per 10,000 date 23 author per 10,000 1 dialect per 10,000 gone 23 author per 10,000 1 dialect per 10,000 live 23 author per 10,000 0 dialect per 10,000 different 23 author per 10,000 1 dialect per 10,000 country 23 author per 10,000 1 dialect per 10,000 gane 23 author per 10,000 1 dialect per 10,000 on 23 author per 10,000 72 dialect per 10,000 best 23 author per 10,000 3 dialect per 10,000 same 23 author per 10,000 7 dialect per 10,000 fir 23 author per 10,000 3 dialect per 10,000 keep 23 author per 10,000 4 dialect per 10,000 ullans 23 author per 10,000 2 dialect per 10,000 very 23 author per 10,000 2 dialect per 10,000 years 23 author per 10,000 3 dialect per 10,000 tv 23 author per 10,000 0 dialect per 10,000 wha 23 author per 10,000 12 dialect per 10,000 knows 23 author per 10,000 1 dialect per 10,000 fifty 23 author per 10,000 0 dialect per 10,000 past 23 author per 10,000 1 dialect per 10,000 partner 23 author per 10,000 0 dialect per 10,000 lancers 23 author per 10,000 0 dialect per 10,000 done 23 author per 10,000 1 dialect per 10,000 setts 23 author per 10,000 0 dialect per 10,000 polka 23 author per 10,000 0 dialect per 10,000 reels 23 author per 10,000 0 dialect per 10,000 more 23 author per 10,000 0 dialect per 10,000 wanted 23 author per 10,000 1 dialect per 10,000 dancin 23 author per 10,000 1 dialect per 10,000 odds 23 author per 10,000 0 dialect per 10,000 last 23 author per 10,000 5 dialect per 10,000 alwyes 23 author per 10,000 1 dialect per 10,000 €˜twas 23 author per 10,000 0 dialect per 10,000 great 23 author per 10,000 1 dialect per 10,000 while 23 author per 10,000 6 dialect per 10,000 came 23 author per 10,000 1 dialect per 10,000 ithers 23 author per 10,000 4 dialect per 10,000 chance 23 author per 10,000 1 dialect per 10,000 their 23 author per 10,000 7 dialect per 10,000 glide 23 author per 10,000 0 dialect per 10,000 watch 23 author per 10,000 1 dialect per 10,000 poocher 23 author per 10,000 0 dialect per 10,000 rattlin 23 author per 10,000 0 dialect per 10,000 soons 23 author per 10,000 0 dialect per 10,000 heels 23 author per 10,000 0 dialect per 10,000 nicht 23 author per 10,000 8 dialect per 10,000 stan 23 author per 10,000 4 dialect per 10,000 diinne 23 author per 10,000 0 dialect per 10,000 why 23 author per 10,000 6 dialect per 10,000 onywye 23 author per 10,000 0 dialect per 10,000 ouler 23 author per 10,000 1 dialect per 10,000 folk 23 author per 10,000 5 dialect per 10,000 unnerstaun 23 author per 10,000 0 dialect per 10,000 kan 23 author per 10,000 0 dialect per 10,000 hes 23 author per 10,000 0 dialect per 10,000 ninety 23 author per 10,000 0 dialect per 10,000 third 23 author per 10,000 0 dialect per 10,000 year 23 author per 10,000 2 dialect per 10,000 geen 23 author per 10,000 0 dialect per 10,000 richtfa 23 author per 10,000 0 dialect per 10,000 whiles 23 author per 10,000 3 dialect per 10,000 mair 23 author per 10,000 27 dialect per 10,000 road 23 author per 10,000 3 dialect per 10,000 nir 23 author per 10,000 2 dialect per 10,000 fore 23 author per 10,000 0 dialect per 10,000 seems 23 author per 10,000 1 dialect per 10,000 place 23 author per 10,000 6 dialect per 10,000 hell 23 author per 10,000 1 dialect per 10,000 leather 23 author per 10,000 0 dialect per 10,000 wye 23 author per 10,000 16 dialect per 10,000 still 23 author per 10,000 5 dialect per 10,000 feyther 23 author per 10,000 0 dialect per 10,000 hae 23 author per 10,000 61 dialect per 10,000 made 23 author per 10,000 7 dialect per 10,000 through 23 author per 10,000 3 dialect per 10,000 score 23 author per 10,000 0 dialect per 10,000 aye 23 author per 10,000 15 dialect per 10,000 dey 23 author per 10,000 0 dialect per 10,000 what 23 author per 10,000 13 dialect per 10,000 big 23 author per 10,000 9 dialect per 10,000 birthday 23 author per 10,000 0 dialect per 10,000 ither 23 author per 10,000 17 dialect per 10,000 ten 23 author per 10,000 2 dialect per 10,000 merker 23 author per 10,000 0 dialect per 10,000 than 23 author per 10,000 3 dialect per 10,000 ustae 23 author per 10,000 0 dialect per 10,000 be 23 author per 10,000 45 dialect per 10,000 bit 23 author per 10,000 8 dialect per 10,000 step 23 author per 10,000 0 dialect per 10,000 slower 23 author per 10,000 0 dialect per 10,000 dae 23 author per 10,000 28 dialect per 10,000 ower 23 author per 10,000 20 dialect per 10,000 richtly 23 author per 10,000 0 dialect per 10,000 gettin 23 author per 10,000 2 dialect per 10,000 onythin 23 author per 10,000 0 dialect per 10,000 else 23 author per 10,000 1 dialect per 10,000