PHPCLANCHILDES with regular expressions

5 matches in 5 utterances

2.70 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (504 utterances, 1,851 words searched).

  1. put the curlers in it ? MOT · eng_USA_Brown/sarah037.cha, line 324 · Sarah 2;11
  2. haven't we got some curlers somewhere ? MOT · eng_USA_Brown/sarah037.cha, line 328 · Sarah 2;11
  3. where's all your curlers ? MOT · eng_USA_Brown/sarah037.cha, line 330 · Sarah 2;11
  4. here's some curlers . MOT · eng_USA_Brown/sarah037.cha, line 338 · Sarah 2;11
  5. with her hair all up in curlers ? MOT · eng_USA_Brown/sarah037.cha, line 632 · Sarah 2;11
  1. MOTI think she's kind of a lost cause # really .
    CHIxxx .
    MOT*MOT: put the curlers in it ?
    CHIonce .
    MOThaven't we got some curlers somewhere ?
  2. MOTput the curlers in it ?
    CHIonce .
    MOT*MOT: haven't we got some curlers somewhere ?
    MOTwhere's all your curlers ?
    MOTwant to put curls in ?
  3. CHIonce .
    MOThaven't we got some curlers somewhere ?
    MOT*MOT: where's all your curlers ?
    MOTwant to put curls in ?
    CHIum .
  4. CHIum .
    MOTthere .
    MOT*MOT: here's some curlers .
    MOTI don't know whether the other ones are .
    COUhey # can the doll wear earrings ?
  5. MOTthere # how's she look ?
    MOTall ready for bed ?
    MOT*MOT: with her hair all up in curlers ?
    MOThmm ?
    CHIyeah .

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_Brown2.70
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_USA_Brown/sarah037.chaSarah 2;11.171,851552.70

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. curlers5 · 100.0%