PHPCLANCHILDES with regular expressions

5 matches in 5 utterances

2.71 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (383 utterances, 1,848 words searched).

  1. Ann_Marie has a belt but you have no belt . MOT · eng_USA_Brown/sarah125.cha, line 763 · Sarah 4;09
  2. that would be very nice but I don't have one for you . GAI · eng_USA_Brown/sarah125.cha, line 826 · Sarah 4;09
  3. it shouldn't be but it's awful cold . MOT · eng_USA_Brown/sarah125.cha, line 1031 · Sarah 4;09
  4. you have to make that same line # but you have to make it right close to the edge # here . GAI · eng_USA_Brown/sarah125.cha, line 1039 · Sarah 4;09
  5. yeah # but it was on tv . ANN · eng_USA_Brown/sarah125.cha, line 1088 · Sarah 4;09
  1. eng_USA_Brown/sarah125.cha, line 763 · Sarah, 4;9.19
    CHIgirls (sup)posed to have belts ?
    MOTbelts ?
    MOT*MOT: Ann_Marie has a belt but you have no belt .
    ANNI got a boy's belt on .
    ANNsee ?
  2. eng_USA_Brown/sarah125.cha, line 826 · Sarah, 4;9.19
    CHIoops # made it the wrong side .
    CHII think you brought a toy for me me today .
    GAI*GAI: that would be very nice but I don't have one for you .
    CHIaah .
    CHInot today ?
  3. eng_USA_Brown/sarah125.cha, line 1031 · Sarah, 4;9.19
    MOTit's too early for an all white dress # huh ?
    MELit shouldn't be .
    MOT*MOT: it shouldn't be but it's awful cold .
    CHIlike dat ?
    CHIlike dat ?
  4. eng_USA_Brown/sarah125.cha, line 1039 · Sarah, 4;9.19
    CHIlike dat ?
    CHIlike dat ?
    GAI*GAI: you have to make that same line # but you have to make it right close to the edge # here .
    GAIstart here and do it this way .
    CHIoh .
  5. eng_USA_Brown/sarah125.cha, line 1088 · Sarah, 4;9.19
    ANNit was a [//] a whale .
    CHIreally # Ann_Marie ?
    ANN*ANN: yeah # but it was on tv .
    CHIhuh ?
    ANNhow_come it was on tv ?

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_Brown2.71
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_USA_Brown/sarah125.chaSarah 4;9.191,848552.71

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. but5 · 100.0%