PHPCLANCHILDES with regular expressions

4 matches in 4 utterances

3.13 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (394 utterances, 1,280 words searched).

  1. Nana wants to know how you are ? FAT · eng_USA_Brown/sarah010.cha, line 266 · Sarah 2;04
  2. I know it's your coat . MOT · eng_USA_Brown/sarah010.cha, line 911 · Sarah 2;04
  3. I'm talkin(g) to you # you know . FAT · eng_USA_Brown/sarah010.cha, line 1452 · Sarah 2;04
  4. yeah # I know it's hard # but you can do it . MOT · eng_USA_Brown/sarah010.cha, line 1677 · Sarah 2;04
  1. eng_USA_Brown/sarah010.cha, line 266 · Sarah, 2;4.19
    CHICarol .
    FATok .
    FAT*FAT: Nana wants to know how you are ?
    FATare you fine ?
    CHI0 .
  2. eng_USA_Brown/sarah010.cha, line 911 · Sarah, 2;4.19
    MOTum .
    CHImy coat .
    MOT*MOT: I know it's your coat .
    CHImy coat .
    CHIxxx .
  3. eng_USA_Brown/sarah010.cha, line 1452 · Sarah, 2;4.19
    FATwhat's your name ?
    FATyou Sarah ?
    FAT*FAT: I'm talkin(g) to you # you know .
    CHIxxx .
    FATwho are you ?
  4. eng_USA_Brown/sarah010.cha, line 1677 · Sarah, 2;4.19
    MOTyeah .
    CHII wan(t) [=? hard] two ri(bbo)n head .
    MOT*MOT: yeah # I know it's hard # but you can do it .
    CHIo:h .
    MOTxxx .

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_Brown3.13
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_USA_Brown/sarah010.chaSarah 2;4.191,280443.13

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. know4 · 100.0%