PHPCLANCHILDES with regular expressions

3 matches in 3 utterances

2.10 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (527 utterances, 1,427 words searched).

  1. bon . 1223508_1225533 MOT · french/lyon_nat02b.cha, line 1008 · Nathan 1;00
  2. c'est bon ? 1334548_1339913 MOT · french/lyon_nat02b.cha, line 1125 · Nathan 1;00
  3. bon va falloir que je l(e) nettoie c(el)ui là . 1743893_1746228 MOT · french/lyon_nat02b.cha, line 1589 · Nathan 1;00
  1. MOT(a)ttention . 1220165_1221863
    MOTwww [= ! souffle] . 1221863_1223508
    MOT*MOT: bon . 1223508_1225533
    MOTtant qu(e) tu l'envois pas valser . 1225533_1242192
    MOTnon [/] non . 1242192_1248750
  2. MOTassis sur un pot d(e) talc c'est pas: +...
    CHIyyy . 1331345_1334548
    MOT*MOT: c'est bon ? 1334548_1339913
    MOTt(u) es sec de partout ?
    MOTqu'est-c(e) tu +//?
  3. MOTsuper .
    MOTbravo . 1742278_1743893
    MOT*MOT: bon va falloir que je l(e) nettoie c(el)ui là . 1743893_1746228
    MOTwww [= ! souffle] . 1746228_1755520
    MOTnon mais +...

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 french2.10
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
french/lyon_nat02b.chaNathan 1;0.241,427332.10

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. bon3 · 100.0%