PHPCLANCHILDES with regular expressions

3 matches in 3 utterances

2.30 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (392 utterances, 1,303 words searched).

  1. tu veux encore y aller ? 186615_189877 MOT · french/lyon_tim32a.cha, line 321 · Tim 2;05
  2. tu veux qu'on joue au garage ? 1135400_1137748 AME · french/lyon_tim32a.cha, line 1616 · Tim 2;05
  3. veux y aller tout_de_suite . 1697253_1699282 AME · french/lyon_tim32a.cha, line 2110 · Tim 2;05
  1. MOTwww [= ! rit] . 182518_186615
    CHI<yyy aller> [/] ‹aller [/]› <aller encore la neige> [/] ‹www [= ! rit]› .
    MOT*MOT: tu veux encore y aller ? 186615_189877
    CHIouais .
    MOT+< bah oui .
  2. CHIwww [= ! souffle] .
    CHI‹micro [= ! mumuré]› .
    AME*AME: tu veux qu'on joue au garage ? 1135400_1137748
    CHImon livre . 1162853_1165283
    CHI‹(..) regarde› ‹mes [?]› yyy . 1174783_1182538
  3. CHIdemain . 1695013_1697253
    MOTwww [= ! rit] .
    AME*AME: veux y aller tout_de_suite . 1697253_1699282
    AMEj(e) suis pressée .
    MOToui . 1699282_1701532

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. Tim french2.30
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
french/lyon_tim32a.chaTim 2;5.201,303332.30

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. veux3 · 100.0%