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. that was fast . MEL · eng_USA_Brown/sarah131.cha, line 110 · Sarah 4;11
  2. well # what was it ? MOT · eng_USA_Brown/sarah131.cha, line 658 · Sarah 4;11
  3. it was a two ! MOT · eng_USA_Brown/sarah131.cha, line 662 · Sarah 4;11
  4. I was wondering about that xxx . MEL · eng_USA_Brown/sarah131.cha, line 1022 · Sarah 4;11
  5. I thought that was cute # his # hers # and ours . MOT · eng_USA_Brown/sarah131.cha, line 1101 · Sarah 4;11
  6. I thought it was a little cake icing maybe . MEL · eng_USA_Brown/sarah131.cha, line 1125 · Sarah 4;11
  1. eng_USA_Brown/sarah131.cha, line 110 · Sarah, 4;11.13
    CHId@l o@l g@l .
    MELsay # you're really getting good .
    MEL*MEL: that was fast .
    CHIuh # I know how to spell cat .
    CHIc@l # now what's that other word ?
  2. eng_USA_Brown/sarah131.cha, line 658 · Sarah, 4;11.13
    GAIwhy don't you like fat sixes ?
    CHIthat ain't a six .
    MOT*MOT: well # what was it ?
    CHItwo .
    MOTit was a two !
  3. eng_USA_Brown/sarah131.cha, line 662 · Sarah, 4;11.13
    MOTwell # what was it ?
    CHItwo .
    MOT*MOT: it was a two !
    CHII made it wrong .
    MOTheavens !
  4. eng_USA_Brown/sarah131.cha, line 1022 · Sarah, 4;11.13
    MELdid you wrap it yourself ?
    MELit looks like it though .
    MEL*MEL: I was wondering about that xxx .
    MOTI hide all the scotch+tape (a)n(d) everything # ya know .
    MOTI had to use the # then I had to start usin(g) that crazy glue .
  5. eng_USA_Brown/sarah131.cha, line 1101 · Sarah, 4;11.13
    MELdo we get lots ?
    MELwell # we've got lots here .
    MOT*MOT: I thought that was cute # his # hers # and ours .
    MELthat's neat .
    MELthank+you very much # Sarah .
  6. eng_USA_Brown/sarah131.cha, line 1125 · Sarah, 4;11.13
    MELnow I can smell it .
    MOTyeah .
    MEL*MEL: I thought it was a little cake icing maybe .
    MOTit could be if she did it up # believe me .
    MELdo you know what this is # Sarah ?

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. was6 · 100.0%