PHPCLANCHILDES with regular expressions

4 matches in 4 utterances

2.81 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (350 utterances, 1,423 words searched).

  1. comment on demande ? 234403_240570 MOT · french/lyon_nat35a.cha, line 146 · Nathan 2;07
  2. comment on demande Nat ? MOT · french/lyon_nat35a.cha, line 158 · Nathan 2;07
  3. comment on appelle ça Nanou ? 503573_507443 MOT · french/lyon_nat35a.cha, line 324 · Nathan 2;07
  4. tu t(e) rappelles comment c'est ? 1487905_1490740 MOT · french/lyon_nat35a.cha, line 1198 · Nathan 2;07
  1. MOTça arrive hein ! 218935_221603
    MOTencore un autre ? 221603_234403
    MOT*MOT: comment on demande ? 234403_240570
    MOTqu'est-ce qu'on +...
    MOTah !
  2. MOTmoi qui ai passé le balai . 240570_241590
    MOTbon tant_pis . 241590_247097
    MOT*MOT: comment on demande Nat ?
    CHIyyy si_il_te_plaît .
    MOTsi_il_te_plaît . 247097_248043
  3. MOTben oui .
    MOTqu'est-ce qu'il a sur son tee_shirt@s:eng ?
    MOT*MOT: comment on appelle ça Nanou ? 503573_507443
    MOTtu sais ?
    CHIyyy yyy . 507443_510793
  4. MOTtu t(e) souviens Nanou de chez papy Ala ?
    CHIoui . 1487097_1487905
    MOT*MOT: tu t(e) rappelles comment c'est ? 1487905_1490740
    CHImhm . 1490740_1504312
    CHIyyy .

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 french2.81
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
french/lyon_nat35a.chaNathan 2;7.61,423442.81

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.

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