PHPCLANCHILDES with regular expressions

6 matches in 6 utterances

3.62 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (338 utterances, 1,658 words searched).

  1. five take away two . MEL · eng_USA_Brown/sarah131.cha, line 217 · Sarah 4;11
  2. you have five # and you take away two # and how many do you have ? MEL · eng_USA_Brown/sarah131.cha, line 219 · Sarah 4;11
  3. six take away two ? MEL · eng_USA_Brown/sarah131.cha, line 256 · Sarah 4;11
  4. six take away six is two ? MEL · eng_USA_Brown/sarah131.cha, line 299 · Sarah 4;11
  5. your scar went # your vaccination went away ? MEL · eng_USA_Brown/sarah131.cha, line 328 · Sarah 4;11
  6. your # sore place all went away . MEL · eng_USA_Brown/sarah131.cha, line 333 · Sarah 4;11
  1. eng_USA_Brown/sarah131.cha, line 217 · Sarah, 4;11.13
    MELthat's five xxx two .
    CHIhuh ?
    MEL*MEL: five take away two .
    MELyou have five # and you take away two # and how many do you have ?
    CHIone # two # three !
  2. eng_USA_Brown/sarah131.cha, line 219 · Sarah, 4;11.13
    CHIhuh ?
    MELfive take away two .
    MEL*MEL: you have five # and you take away two # and how many do you have ?
    CHIone # two # three !
    MELsee ?
  3. eng_USA_Brown/sarah131.cha, line 256 · Sarah, 4;11.13
    CHI(a)n(d) that's four .
    MELwhat did you start out with ?
    MEL*MEL: six take away two ?
    CHI0 .
    MELand you got four .
  4. eng_USA_Brown/sarah131.cha, line 299 · Sarah, 4;11.13
    CHIand one # two .
    CHIisn't it ?
    MEL*MEL: six take away six is two ?
    CHIisn't it ?
    MELno .
  5. eng_USA_Brown/sarah131.cha, line 328 · Sarah, 4;11.13
    CHIum # I don't know .
    CHII have to do somethin(g) .
    MEL*MEL: your scar went # your vaccination went away ?
    CHIhuh ?
    MELyour # sore place all went away .
  6. eng_USA_Brown/sarah131.cha, line 333 · Sarah, 4;11.13
    MELyour scar went # your vaccination went away ?
    CHIhuh ?
    MEL*MEL: your # sore place all went away .
    CHIoh this is nice one .
    CHII have to make a n@l to do it .

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_Brown3.62
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_USA_Brown/sarah131.chaSarah 4;11.131,658663.62

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. away6 · 100.0%