PHPCLANCHILDES with regular expressions

3 matches in 3 utterances

3.36 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (215 utterances, 892 words searched).

  1. tu veux mettre les chaussons ? MOT · french/lyon_nat35b.cha, line 481 · Nathan 2;07
  2. on va s(e) mettre en pyj(ama) . 769855_771175 MOT · french/lyon_nat35b.cha, line 733 · Nathan 2;07
  3. viens on va s(e) mettre en pyjama . 816962_823790 MOT · french/lyon_nat35b.cha, line 746 · Nathan 2;07
  1. CHIoui . 579223_580028
    MOTmais tiens . 580028_581938
    MOT*MOT: tu veux mettre les chaussons ?
    CHInon ! 581938_583178
    MOTtu veux rester pieds nu ? 583178_585935
  2. CHIyyy . 766250_768650
    MOTallez . 768650_769855
    MOT*MOT: on va s(e) mettre en pyj(ama) . 769855_771175
    MOTet on vient regarder Némo . 771175_783267
    MOTtu veux aller au pipi Nanou ? 783267_811553
  3. MOT(il) y a plus d(e) bonbons .
    MOTtiens Nanou tiens . 811553_816962
    MOT*MOT: viens on va s(e) mettre en pyjama . 816962_823790
    MOToh pardon . 823790_827415
    CHIécraser ‹doigts [/]› doigts de pieds ! 827415_832867

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 french3.36
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
french/lyon_nat35b.chaNathan 2;7.6892333.36

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%