PHPCLANCHILDES with regular expressions

2 matches in 2 utterances

2.20 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (327 utterances, 909 words searched).

  1. <si tu xxx un petit rongeur mordeur> [/] [= ! lu] . 27342_30752 MOT · french/lyon_nat06a.cha, line 34 · Nathan 1;02
  2. xxx l(e) petit www [= ! li] oeil . 144700_146902 MOT · french/lyon_nat06a.cha, line 184 · Nathan 1;02
  1. french/lyon_nat06a.cha, line 34 · Nathan, 1;2.26
    MOTdis [= ! lu] ! 21675_25190
    MOT<ouh va t(e) laver> [= ! lu] ! 25190_27342
    MOT*MOT: <si tu xxx un petit rongeur mordeur> [/] [= ! lu] . 27342_30752
    MOTdis [= ! lu] ! 30752_34553
    MOT<si tu vois des limaces pleines de baves> [= ! lu] . 34553_39463
  2. french/lyon_nat06a.cha, line 184 · Nathan, 1;2.26
    MOTregarde l'éléphant ! 142048_143038
    MOTtu le vois l'éléphant ? 143038_144700
    MOT*MOT: xxx l(e) petit www [= ! li] oeil . 144700_146902
    JEA+< avec ses grandes dents .
    CHIyyy . 146902_147863

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 french2.20
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
french/lyon_nat06a.chaNathan 1;2.26909222.20

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. petit2 · 100.0%