PHPCLANCHILDES with regular expressions

6 matches in 5 utterances

6.02 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (259 utterances, 997 words searched).

  1. a what (a)n(d) a p@l ? MEL · eng_USA_Brown/sarah113.cha, line 482
  2. paper begins with a p@l . MOT · eng_USA_Brown/sarah113.cha, line 891
  3. no # p@l . MOT · eng_USA_Brown/sarah113.cha, line 895
  4. p@l . MOT · eng_USA_Brown/sarah113.cha, line 910
  5. p@l a@l p@l e@l r@l . MOT · eng_USA_Brown/sarah113.cha, line 914
  6. p@l a@l p@l e@l r@l . MOT · eng_USA_Brown/sarah113.cha, line 914
  1. eng_USA_Brown/sarah113.cha, line 482
    MELthat's right .
    CHI(a)n(d) I can make # r@l r@l (a)n(d) a p@l .
    MEL*MEL: a what (a)n(d) a p@l ?
    CHIr@l # r@l .
    CHIsee .
  2. eng_USA_Brown/sarah113.cha, line 891
    MOT(a)n(d) you wrote war .
    CHI<&pape> [/] paper .
    MOT*MOT: paper begins with a p@l .
    CHI(a)n(d) d@l-s too ?
    MOTno # p@l .
  3. eng_USA_Brown/sarah113.cha, line 895
    MOTpaper begins with a p@l .
    CHI(a)n(d) d@l-s too ?
    MOT*MOT: no # p@l .
    CHII know how to write # somethin(g) .
    CHII did # p@l .
  4. eng_USA_Brown/sarah113.cha, line 910
    MOTwell that's a different word .
    CHIhow ?
    MOT*MOT: p@l .
    CHIlike +...
    MOTp@l a@l p@l e@l r@l .
  5. eng_USA_Brown/sarah113.cha, line 914
    MOTp@l .
    CHIlike +...
    MOT*MOT: p@l a@l p@l e@l r@l .
    CHII'm gonna do +...
    CHInow what does this spell ?

Matches by child

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

  1. Sarah eng_USA_Brown6.02
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_USA_Brown/sarah113.chaSarah 997566.02

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. p6 · 100.0%