PHPCLANCHILDES with regular expressions

7 matches in 7 utterances

3.58 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (452 utterances, 1,957 words searched).

  1. la neve . MOT · italian/mart03.cha, line 589 · Martina 1;08
  2. hai visto la neve ? MOT · italian/mart03.cha, line 590 · Martina 1;08
  3. come si fa sulla neve ? MOT · italian/mart03.cha, line 591 · Martina 1;08
  4. quanta neve ! MOT · italian/mart03.cha, line 600 · Martina 1;08
  5. la neve . MOT · italian/mart03.cha, line 612 · Martina 1;08
  6. hai visto la neve ? MOT · italian/mart03.cha, line 613 · Martina 1;08
  7. come si fa sulla neve ? MOT · italian/mart03.cha, line 614 · Martina 1;08
  1. MOT# oh .
    CHIla neve .
    MOT*MOT: la neve .
    MOThai visto la neve ?
    MOTcome si fa sulla neve ?
  2. CHIla neve .
    MOTla neve .
    MOT*MOT: hai visto la neve ?
    MOTcome si fa sulla neve ?
    CHIsc@o .
  3. MOTla neve .
    MOThai visto la neve ?
    MOT*MOT: come si fa sulla neve ?
    CHIsc@o .
    MOTsc, chi è che fa così, sc ?
  4. MOTme lo dici come fa quando scia babbo ?
    MOTguarda qua !
    MOT*MOT: quanta neve !
    CHI0d bimba .
    MOTfa la pipì, sì, dove la fa ?
  5. MOToh oh .
    CHIla neve .
    MOT*MOT: la neve .
    MOThai visto la neve ?
    MOTcome si fa sulla neve ?
  6. CHIla neve .
    MOTla neve .
    MOT*MOT: hai visto la neve ?
    MOTcome si fa sulla neve ?
    CHIscc@o .
  7. MOTla neve .
    MOThai visto la neve ?
    MOT*MOT: come si fa sulla neve ?
    CHIscc@o .
    MOTsc .

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. Martina italian3.58
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
italian/mart03.chaMartina 1;8.21,957773.58

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. neve7 · 100.0%