PHPCLANCHILDES with regular expressions

9 matches in 9 utterances

5.43 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (338 utterances, 1,658 words searched).

  1. did you make one before ever ? MEL · eng_USA_Brown/sarah131.cha, line 378 · Sarah 4;11
  2. make sure you knew what you wrote . MOT · eng_USA_Brown/sarah131.cha, line 443 · Sarah 4;11
  3. well make a nice two . MOT · eng_USA_Brown/sarah131.cha, line 673 · Sarah 4;11
  4. why don't you make a two ? MOT · eng_USA_Brown/sarah131.cha, line 682 · Sarah 4;11
  5. that's how you make a two . MOT · eng_USA_Brown/sarah131.cha, line 708 · Sarah 4;11
  6. that's why you make your twos wrong . MOT · eng_USA_Brown/sarah131.cha, line 718 · Sarah 4;11
  7. (be)cause that's the way you make a two . MOT · eng_USA_Brown/sarah131.cha, line 747 · Sarah 4;11
  8. make it towards Gail . MOT · eng_USA_Brown/sarah131.cha, line 794 · Sarah 4;11
  9. what would you like to make ? MOT · eng_USA_Brown/sarah131.cha, line 852 · Sarah 4;11
  1. eng_USA_Brown/sarah131.cha, line 378 · Sarah, 4;11.13
    CHIhow you make a six ?
    MELlike that .
    MEL*MEL: did you make one before ever ?
    MELI'll do one for you to copy .
    MELoops .
  2. eng_USA_Brown/sarah131.cha, line 443 · Sarah, 4;11.13
    MOTuhhuh .
    MOTjust wonderin(g) .
    MOT*MOT: make sure you knew what you wrote .
    CHInow # which one I was startin(g) on # this one ?
    MELum # I think this one maybe .
  3. eng_USA_Brown/sarah131.cha, line 673 · Sarah, 4;11.13
    CHIgettin(g) problems here .
    MOTa problem's here # huh ?
    MOT*MOT: well make a nice two .
    MOTthis way .
    CHIyou makes a two for me .
  4. eng_USA_Brown/sarah131.cha, line 682 · Sarah, 4;11.13
    MOTthis way .
    CHIyou makes a two for me .
    MOT*MOT: why don't you make a two ?
    CHIhey # let's do another page .
    CHIoh # this one .
  5. eng_USA_Brown/sarah131.cha, line 708 · Sarah, 4;11.13
    MOTit goes this way # here .
    CHIhow_come they # they always make it like this ?
    MOT*MOT: that's how you make a two .
    MOTno # start at the top .
    MOTsee # you start up here .
  6. eng_USA_Brown/sarah131.cha, line 718 · Sarah, 4;11.13
    MOTcome down # (a)n(d) around .
    MOTsee you start backwards .
    MOT*MOT: that's why you make your twos wrong .
    MOT<you start> [//] you do it backwards .
    CHIlook what +...
  7. eng_USA_Brown/sarah131.cha, line 747 · Sarah, 4;11.13
    GAIjust like this # and then down .
    CHIhow_come I always make it like this ?
    MOT*MOT: (be)cause that's the way you make a two .
    MOTthat's why .
    CHIwell I can make it like this .
  8. eng_USA_Brown/sarah131.cha, line 794 · Sarah, 4;11.13
    MOTsee you go the wrong way .
    CHIto Melissa ?
    MOT*MOT: make it towards Gail .
    CHII did .
    CHII maked it like this .
  9. eng_USA_Brown/sarah131.cha, line 852 · Sarah, 4;11.13
    CHII'm goin(g) make somethin(g) else .
    CHIwhat do you think I should make ?
    MOT*MOT: what would you like to make ?
    CHII'm goin(g) make a d@l .
    CHIsee how I make a d@l right .

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. Sarah eng_USA_Brown5.43
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_USA_Brown/sarah131.chaSarah 4;11.131,658995.43

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. make9 · 100.0%