PHPCLANCHILDES with regular expressions

13 matches in 13 utterances

7.39 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (485 utterances, 1,760 words searched).

  1. well . MOT · eng_british_Manchester_I/becky14a.cha, line 24 · Becky 2;04
  2. and these are yours as well , aren't they ? MOT · eng_british_Manchester_I/becky14a.cha, line 62 · Becky 2;04
  3. that's good as well . INV · eng_british_Manchester_I/becky14a.cha, line 93 · Becky 2;04
  4. well . INV · eng_british_Manchester_I/becky14a.cha, line 134 · Becky 2;04
  5. well . MOT · eng_british_Manchester_I/becky14a.cha, line 178 · Becky 2;04
  6. well . MOT · eng_british_Manchester_I/becky14a.cha, line 436 · Becky 2;04
  7. well . MOT · eng_british_Manchester_I/becky14a.cha, line 495 · Becky 2;04
  8. well . MOT · eng_british_Manchester_I/becky14a.cha, line 794 · Becky 2;04
  9. shall we take Sukie_cat as well ? MOT · eng_british_Manchester_I/becky14a.cha, line 866 · Becky 2;04
  10. well . INV · eng_british_Manchester_I/becky14a.cha, line 900 · Becky 2;04
  11. well . MOT · eng_british_Manchester_I/becky14a.cha, line 1247 · Becky 2;04
  12. well . MOT · eng_british_Manchester_I/becky14a.cha, line 1429 · Becky 2;04
  13. well . MOT · eng_british_Manchester_I/becky14a.cha, line 1538 · Becky 2;04
  1. MOTit doesn't work ?
    MOTno .
    MOT*MOT: well .
    MOTthe thing is , Becky .
    MOTwhen we did that owl before that was when we were painting , wasn't it ?
  2. INVexcellent .
    INVI like that .
    MOT*MOT: and these are yours as well , aren't they ?
    CHIthese 0are [*] mine .
    CHIthese are mine .
  3. CHIyeah .
    INVoh .
    INV*INV: that's good as well .
    CHIyeah .
    CHIthese are mine .
  4. INVoh .
    CHIthere's some dots there .
    INV*INV: well .
    INVI think +//.
    INVI don't think those are dots .
  5. MOTyou want to draw a christmas tree ?
    CHImmhm .
    MOT*MOT: well .
    MOTmaybe later on .
    MOTthat's not christmas tree .
  6. CHIhe's red .
    MOThe's red , isn't he ?
    MOT*MOT: well .
    MOTwhat does he have on his chin ?
    CHII don't know .
  7. CHICaroline's toys .
    MOTyou want Caroline's toys ?
    MOT*MOT: well .
    MOTwe have to play with your toys first .
    MOTthen we'll bring them in .
  8. MOTcan I ?
    CHImmhm .
    MOT*MOT: well .
    MOTshall we go in the car then ?
    MOThmm ?
  9. CHIdo you want to come in car ?
    INVokay .
    MOT*MOT: shall we take Sukie_cat as well ?
    CHIyes please .
    CHItake Sukie_cat .
  10. MOTthank you .
    CHIdo you wanna sit my # seat ?
    INV*INV: well .
    INVMummy's sitting in your seat .
    INVshall I sit next to Mummy ?
  11. MOToh .
    MOTI'm sorry .
    MOT*MOT: well .
    MOTwe've lost the [/] the little boy .
    CHII just xxx .
  12. MOToh .
    MOTI'm sorry .
    MOT*MOT: well .
    MOTit doesn't matter if they're upsidedown .
    MOTalright .
  13. CHI<is it um it um> [/] is it Charlie_Chalk ?
    MOTno .
    MOT*MOT: well .
    MOTthat is but that isn't .
    MOTwho's this ?

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_I7.39
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_british_Manchester_I/becky14a.chaBecky 2;4.281,76013137.39

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. well13 · 100.0%