PHPCLANCHILDES with regular expressions

4 matches in 4 utterances

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

  1. no # that spells car # c@l a@l r@l . MOT · eng_USA_Brown/sarah113.cha, line 1003
  2. are you gonna make that red car now ? MEL · eng_USA_Brown/sarah113.cha, line 1108
  3. c@l a@l r@l # car . MOT · eng_USA_Brown/sarah113.cha, line 1118
  4. have you seen a red car ? MEL · eng_USA_Brown/sarah113.cha, line 1181
  1. eng_USA_Brown/sarah113.cha, line 1003
    MOTc@l a@l what ?
    CHIc@l a@l r@l ?
    MOT*MOT: no # that spells car # c@l a@l r@l .
    CHIoh I know how to spell car now # huh ?
    MELmmhm .
  2. eng_USA_Brown/sarah113.cha, line 1108
    CHIis this red or orange ?
    MOTred .
    MEL*MEL: are you gonna make that red car now ?
    CHIdoes it have glass over it ?
    MOTxxx .
  3. eng_USA_Brown/sarah113.cha, line 1118
    MOTxxx .
    CHInow how you write a car ?
    MOT*MOT: c@l a@l r@l # car .
    CHIno # a [/] a # car that moves # like Uncle_Buster's .
    MOTI don't know what you mean .
  4. eng_USA_Brown/sarah113.cha, line 1181
    CHIno .
    MELI think there are such things .
    MEL*MEL: have you seen a red car ?
    CHIyep .
    CHIle(t) me make # a nest ?

Matches by child

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

  1. Sarah eng_USA_Brown4.01
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_USA_Brown/sarah113.chaSarah 997444.01

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. car4 · 100.0%