PHPCLANCHILDES with regular expressions

21 matches in 21 utterances

17.89 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (308 utterances, 1,174 words searched).

  1. oh dear . MOT · eng_british_Manchester_I/becky30b.cha, line 120 · Becky 2;10
  2. oh . MOT · eng_british_Manchester_I/becky30b.cha, line 178 · Becky 2;10
  3. oh . MOT · eng_british_Manchester_I/becky30b.cha, line 233 · Becky 2;10
  4. oh . MOT · eng_british_Manchester_I/becky30b.cha, line 244 · Becky 2;10
  5. oh . MOT · eng_british_Manchester_I/becky30b.cha, line 331 · Becky 2;10
  6. oh . MOT · eng_british_Manchester_I/becky30b.cha, line 421 · Becky 2;10
  7. oh , Becky . MOT · eng_british_Manchester_I/becky30b.cha, line 525 · Becky 2;10
  8. oh . MOT · eng_british_Manchester_I/becky30b.cha, line 594 · Becky 2;10
  9. oh . MOT · eng_british_Manchester_I/becky30b.cha, line 699 · Becky 2;10
  10. oh . MOT · eng_british_Manchester_I/becky30b.cha, line 714 · Becky 2;10
  11. oh . MOT · eng_british_Manchester_I/becky30b.cha, line 765 · Becky 2;10
  12. oh . MOT · eng_british_Manchester_I/becky30b.cha, line 779 · Becky 2;10
  13. oh . MOT · eng_british_Manchester_I/becky30b.cha, line 971 · Becky 2;10
  14. oh . MOT · eng_british_Manchester_I/becky30b.cha, line 1123 · Becky 2;10
  15. oh dear . MOT · eng_british_Manchester_I/becky30b.cha, line 1144 · Becky 2;10
  16. oh well . MOT · eng_british_Manchester_I/becky30b.cha, line 1158 · Becky 2;10
  17. oh right . MOT · eng_british_Manchester_I/becky30b.cha, line 1174 · Becky 2;10
  18. oh well . MOT · eng_british_Manchester_I/becky30b.cha, line 1288 · Becky 2;10
  19. oh . MOT · eng_british_Manchester_I/becky30b.cha, line 1384 · Becky 2;10
  20. oh good . MOT · eng_british_Manchester_I/becky30b.cha, line 1428 · Becky 2;10
  21. oh good . MOT · eng_british_Manchester_I/becky30b.cha, line 1499 · Becky 2;10
  1. MOTno mouth ?
    CHIno .
    MOT*MOT: oh dear .
    CHIxxx .
    MOTwell .
  2. CHIyes .
    MOTalright .
    MOT*MOT: oh .
    MOTcheer up .
    CHIoh .
  3. CHIthis .
    CHIxxx this on me .
    MOT*MOT: oh .
    MOTwhat else do we need in that picture ?
    MOTanything ?
  4. MOTwhat about some teeth ?
    CHIyes .
    MOT*MOT: oh .
    MOTteeth .
    MOTthere .
  5. MOTthere we are .
    MOTpink cheeks .
    MOT*MOT: oh .
    MOTand eyebrows as well .
    MOTthere .
  6. MOToctopus .
    CHIyou did that .
    MOT*MOT: oh .
    MOTand what was that one ?
    CHIyou did that one .
  7. MOTput some on the paper .
    MOTcome +//.
    MOT*MOT: oh , Becky .
    MOTwhat a mess you're making .
    MOThere .
  8. CHImy hand .
    MOTnever mind .
    MOT*MOT: oh .
    MOTdoes it need wiping again ?
    CHIyeah .
  9. CHIxxx .
    CHIxxx .
    MOT*MOT: oh .
    MOTcareful .
    MOTyou're gonna [: going to] drip it on me as well .
  10. CHIyou do that .
    CHIblack .
    MOT*MOT: oh .
    MOTwhat's happened ?
    MOTI think you need some clean water , don't you ?
  11. CHIMummy .
    CHIlook .
    MOT*MOT: oh .
    MOTyou've got yellow water now .
    CHIxxx .
  12. CHIdo that .
    CHIwhat's that ?
    MOT*MOT: oh .
    MOTit's running .
    MOTit's running .
  13. CHIthe caterpillar's coming .
    CHIthe caterpillar's coming .
    MOT*MOT: oh .
    CHIthat one .
    CHIthere's xxx now .
  14. MOTwhoops .
    CHIoh .
    MOT*MOT: oh .
    CHIyellow in the paper .
    CHItread on it .
  15. CHIlook .
    CHIlook , Mum .
    MOT*MOT: oh dear .
    CHIwhat is it ?
    CHIxxx , Mum ?
  16. CHIthis [/] this hasn't xxx .
    MOThasn't it ?
    MOT*MOT: oh well .
    MOTthat's good , isn't it ?
    MOTdo you like this monster then ?
  17. MOTMr_Monster ?
    CHIyes .
    MOT*MOT: oh right .
    CHIthank you , Mum .
    CHIhave you finished yet ?
  18. MOTwhat ?
    CHIthere .
    MOT*MOT: oh well .
    MOTnever mind .
    CHIlook .
  19. MOTdon't put that in .
    MOTBecky .
    MOT*MOT: oh .
    MOTfor goodness sake .
    CHIxxx .
  20. CHII done red .
    CHIlook .
    MOT*MOT: oh good .
    CHIoh no .
    CHIit's brown .
  21. CHIit is dry .
    CHIit is dry .
    MOT*MOT: oh good .
    CHImove it for me .
    MOTdo you want me to wipe that and you do [/] do some more coloring ?

Matches by age

One dot per transcript: matches per 1,000 words of everyone but CHI. Dots of the same child are joined.

Matches by child

Matches per 1,000 words, all transcripts of each child together, highest first.

  1. Becky eng_british_Manchester_I17.89
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_british_Manchester_I/becky30b.chaBecky 2;10.121,174212117.89

What the pattern matched

1 different forms (lowercased). Useful to see what a pattern really catches: unexpected forms here usually mean the pattern is too broad.

  1. oh21 · 100.0%