PHPCLANCHILDES with regular expressions

3 matches in 3 utterances

3.56 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (222 utterances, 843 words searched).

  1. petit Nanou on va lui mettre ses feutres . MOT · french/lyon_nat22b.cha, line 21 · Nathan 2;05
  2. i(l) fond et puis tu vas en mettre partout . MOT · french/lyon_nat22b.cha, line 219 · Nathan 2;05
  3. tu as oublié de mettre le bouchon . 1053335_1055657 MOT · french/lyon_nat22b.cha, line 733 · Nathan 2;05
  1. MOTqu'est-ce que tu veux None ? 0_7460
    MOTalors petit None .
    MOT*MOT: petit Nanou on va lui mettre ses feutres .
    MOTj'entends un nez qui m'a l'air bien pris là . 7460_44285
    CHI‹yyy [= ! babillage]› .
  2. MOTnon [/] non [/] non Nat .
    MOTça tu le manges le chocolat .
    MOT*MOT: i(l) fond et puis tu vas en mettre partout .
    CHIwww [= ! chante] .
    MOTregarde None tu t'en mets partout . 326012_333148
  3. CHI‹mhm [= ! babillage]› !
    MOTNat ?
    MOT*MOT: tu as oublié de mettre le bouchon . 1053335_1055657
    MOToù il est le bouchon ? 1055657_1067913
    CHImhm !

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. Nathan french3.56
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
french/lyon_nat22b.chaNathan 2;5.18843333.56

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. mettre3 · 100.0%