PHPCLANCHILDES with regular expressions

3 matches in 3 utterances

2.54 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (274 utterances, 1,180 words searched).

  1. Sarah # now make your xxx . MOT · eng_USA_Brown/sarah114.cha, line 313 · Sarah 4;06
  2. that's how you make one kind . MEL · eng_USA_Brown/sarah114.cha, line 555 · Sarah 4;06
  3. after supper we'll make Jello for tomorrow # huh ? MOT · eng_USA_Brown/sarah114.cha, line 1109 · Sarah 4;06
  1. eng_USA_Brown/sarah114.cha, line 313 · Sarah, 4;6.17
    CHIxxx # did you say xxx ?
    MOTd@l .
    MOT*MOT: Sarah # now make your xxx .
    CHIdat's a xxx .
    MOToh [/] oh yeah # I see # d@l o@l g@l .
  2. eng_USA_Brown/sarah114.cha, line 555 · Sarah, 4;6.17
    MELthank+you .
    CHIthat's how you make it ?
    MEL*MEL: that's how you make one kind .
    CHIit looks like a sink to me .
    CHIcan't you draw a sink ?
  3. eng_USA_Brown/sarah114.cha, line 1109 · Sarah, 4;6.17
    MOTit's too late for puddin(g) .
    MOTI tell you what .
    MOT*MOT: after supper we'll make Jello for tomorrow # huh ?
    CHIno # I want puddin(g) always .
    MOTalways # always # always .

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_Brown2.54
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_USA_Brown/sarah114.chaSarah 4;6.171,180332.54

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. make3 · 100.0%