PHPCLANCHILDES with regular expressions

6 matches in 6 utterances

5.08 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (274 utterances, 1,180 words searched).

  1. not +... MEL · eng_USA_Brown/sarah114.cha, line 25 · Sarah 4;06
  2. not xxx . MOT · eng_USA_Brown/sarah114.cha, line 222 · Sarah 4;06
  3. that's not a xxx # that's an xxx . MOT · eng_USA_Brown/sarah114.cha, line 252 · Sarah 4;06
  4. I'm not gonna have any # thanks . GAI · eng_USA_Brown/sarah114.cha, line 887 · Sarah 4;06
  5. hey # not on the table . MOT · eng_USA_Brown/sarah114.cha, line 1196 · Sarah 4;06
  6. no # no # no # no # no # no # not on the # table . MOT · eng_USA_Brown/sarah114.cha, line 1198 · Sarah 4;06
  1. eng_USA_Brown/sarah114.cha, line 25 · Sarah, 4;6.17
    MELyeah .
    MELyou wanna talk for it ?
    MEL*MEL: not +...
    MELyou can talk right here and it goes right in .
    CHI<&h> [//] did <my breath> [/] my breath went in there ?
  2. eng_USA_Brown/sarah114.cha, line 222 · Sarah, 4;6.17
    MOT+" dog .
    CHIxxx .
    MOT*MOT: not xxx .
    MOTxxx .
    CHImmhm # a xxx # too ?
  3. eng_USA_Brown/sarah114.cha, line 252 · Sarah, 4;6.17
    MOTyou don't think so ?
    CHIhey # dat one a xxx !
    MOT*MOT: that's not a xxx # that's an xxx .
    CHIuh # I was makin(g) it wrong ?
    MOTguess so .
  4. eng_USA_Brown/sarah114.cha, line 887 · Sarah, 4;6.17
    MELa fan ?
    CHIyeah .
    GAI*GAI: I'm not gonna have any # thanks .
    GAII had some just before .
    MELum # I think so # yeah .
  5. eng_USA_Brown/sarah114.cha, line 1196 · Sarah, 4;6.17
    CHI0 .
    GAIhey # paper +...
    MOT*MOT: hey # not on the table .
    MOTno # no # no # no # no # no # not on the # table .
    CHII can (e)rase it off .
  6. eng_USA_Brown/sarah114.cha, line 1198 · Sarah, 4;6.17
    GAIhey # paper +...
    MOThey # not on the table .
    MOT*MOT: no # no # no # no # no # no # not on the # table .
    CHII can (e)rase it off .
    MOTyou're gettin(g) xxx .

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_Brown5.08
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_USA_Brown/sarah114.chaSarah 4;6.171,180665.08

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%