PHPCLANCHILDES with regular expressions

3 matches in 3 utterances

1.95 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (459 utterances, 1,539 words searched).

  1. là y doit y avoir (.) dessous . MOT · french/lyon_tim30a.cha, line 1805 · Tim 2;04
  2. +< et i(ls) vont avoir des petits camions ? MOT · french/lyon_tim30a.cha, line 2266 · Tim 2;04
  3. i(l) faut avoir des petits doigts hein . 1482942_1485630 MOT · french/lyon_tim30a.cha, line 2592 · Tim 2;04
  1. MOTfais voir là ! 1029083_1030488
    MOTdonc euh elle , elle est d(e)ssus .
    MOT*MOT: là y doit y avoir (.) dessous .
    MOTy en a des voitures non ? 1030488_1036350
    CHIah si . 1036350_1038080
  2. MOTah: . 1304303_1306142
    CHIlà yyy yyy . 1306142_1308692
    MOT*MOT: +< et i(ls) vont avoir des petits camions ?
    CHIoui . 1308692_1309430
    MOTxxx des bébés camions ? 1309430_1311153
  3. CHIoui . 1480182_1481547
    MOTah: . 1481547_1482942
    MOT*MOT: i(l) faut avoir des petits doigts hein . 1482942_1485630
    CHIoui . 1485630_1486618
    MOTt(u) as mis ton doigt d(e)dans ? 1486618_1489378

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 french1.95
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
french/lyon_tim30a.chaTim 2;4.221,539331.95

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. avoir3 · 100.0%