PHPCLANCHILDES with regular expressions

3 matches in 3 utterances

3.92 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (244 utterances, 766 words searched).

  1. allez viens ! MOT · french/lyon_nat01b.cha, line 23 · Nathan 1;00
  2. tu te déshabilles et tu viens au bain maintenant ! 28468_33827 MOT · french/lyon_nat01b.cha, line 39 · Nathan 1;00
  3. viens [= ! chuchote] xxx c'est normal ! 473805_477955 MOT · french/lyon_nat01b.cha, line 401 · Nathan 1;00
  1. MOTwww [= ! rigole] . 15127_17008
    JEAwww [= ! rigole] . 17008_22387
    MOT*MOT: allez viens !
    MOTenlève tes chaussures Jea .
    MOTet la prochaine fois tu xxx . 22387_26517
  2. MOTdis oh oh oh chu:t . 26517_28467
    MOTtu enlève tes chaussures hein .
    MOT*MOT: tu te déshabilles et tu viens au bain maintenant ! 28468_33827
    CHImhm ! 38020_41852
    MOTbing . 41858_48700
  3. MOTben dis_don(c) (.) t(u) as l'oreille fine hein ! 469172_472635
    MOTallez on www [= ! li] y va . 472645_473805
    MOT*MOT: viens [= ! chuchote] xxx c'est normal ! 473805_477955
    CHIyyy ! 490245_491957
    MOTeuhah@u . 491965_493797

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 french3.92
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
french/lyon_nat01b.chaNathan 1;0.12766333.92

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. viens3 · 100.0%