PHPCLANCHILDES with regular expressions

5 matches in 5 utterances

3.87 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (283 utterances, 1,293 words searched).

  1. c(o)me on xxx . MOT · eng_USA_Brown/sarah098.cha, line 165 · Sarah 4;02
  2. c@l . MOT · eng_USA_Brown/sarah098.cha, line 274 · Sarah 4;02
  3. c@l # a@l what # for cat ? MOT · eng_USA_Brown/sarah098.cha, line 419 · Sarah 4;02
  4. I knew that was a@l natural when she said c@l a@l . MOT · eng_USA_Brown/sarah098.cha, line 718 · Sarah 4;02
  5. spellery@c ? GAI · eng_USA_Brown/sarah098.cha, line 1040 · Sarah 4;02
  1. MOTif it's so easy how_come you make all the mistakes ?
    MOThmm ?
    MOT*MOT: c(o)me on xxx .
    CHIsee ?
    CHIc@l .
  2. MOToh .
    CHIsee c@l .
    MOT*MOT: c@l .
    CHIsee .
    MOTmmhm .
  3. CHIa@l .
    MELthat's the middle letter .
    MOT*MOT: c@l # a@l what # for cat ?
    MELit's the letter you just learned how to make # the next letter .
    CHII saw it # uh .
  4. MELno .
    CHIdog # cat .
    MOT*MOT: I knew that was a@l natural when she said c@l a@l .
    MELit spells jam .
    MELjam .
  5. GAIwhat do you think it spells ?
    CHIspellery@c .
    GAI*GAI: spellery@c ?
    CHIspellery@c .
    GAIis that what it spells ?

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. Sarah eng_USA_Brown3.87
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_USA_Brown/sarah098.chaSarah 4;2.281,293553.87

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. c5 · 100.0%