PHPCLANCHILDES with regular expressions

6 matches in 6 utterances

3.84 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (354 utterances, 1,562 words searched).

  1. Sarah's not a name that lends itself to nicknames very much . MEL · eng_USA_Brown/sarah095.cha, line 527 · Sarah 4;02
  2. not when you're tired . FAT · eng_USA_Brown/sarah095.cha, line 741 · Sarah 4;02
  3. it's not cotton # is it ? MOT · eng_USA_Brown/sarah095.cha, line 986 · Sarah 4;02
  4. no # not from New_York . FAT · eng_USA_Brown/sarah095.cha, line 1072 · Sarah 4;02
  5. Tommy White # not the baby . MOT · eng_USA_Brown/sarah095.cha, line 1329 · Sarah 4;02
  6. not his legs ? MOT · eng_USA_Brown/sarah095.cha, line 1368 · Sarah 4;02
  1. eng_USA_Brown/sarah095.cha, line 527 · Sarah, 4;2.09
    MELyou could call him Dan # instead of Danny .
    MOTyou had a stop and think # huh ?
    MEL*MEL: Sarah's not a name that lends itself to nicknames very much .
    MOTshe's on an eatin(g) kick too .
    MOTshe's been eatin(g) xxx .
  2. eng_USA_Brown/sarah095.cha, line 741 · Sarah, 4;2.09
    FATno # you don't .
    CHIyes # I do .
    FAT*FAT: not when you're tired .
    FATdoes she # Mommy ?
    MOTwell # she has her moments # we'll put it that way .
  3. eng_USA_Brown/sarah095.cha, line 986 · Sarah, 4;2.09
    FATwhat have you got in there ?
    FATtwo cottons .
    MOT*MOT: it's not cotton # is it ?
    CHIboth cotton .
    CHIlook .
  4. eng_USA_Brown/sarah095.cha, line 1072 · Sarah, 4;2.09
    FATwhere'd we just come from ?
    CHIfrom New_York .
    FAT*FAT: no # not from New_York .
    FATwhere were &w xxx .
    FATwhere'd we go ?
  5. eng_USA_Brown/sarah095.cha, line 1329 · Sarah, 4;2.09
    MOThe was born without tonsils too .
    FATwhat little Tommy # Tommy White ?
    MOT*MOT: Tommy White # not the baby .
    CHIsometimes you forget .
    FATforget what ?
  6. eng_USA_Brown/sarah095.cha, line 1368 · Sarah, 4;2.09
    MOThe moved his arms ?
    CHInot his legs .
    MOT*MOT: not his legs ?
    CHIno .
    CHIthe water made his # uh # hands float .

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_Brown3.84
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_USA_Brown/sarah095.chaSarah 4;2.091,562663.84

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. not6 · 100.0%