PHPCLANCHILDES with regular expressions

6 matches in 6 utterances

3.28 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (595 utterances, 1,830 words searched).

  1. I write it down . INV · eng_british_Manchester_I/becky18a.cha, line 903 · Becky 2;06
  2. don't you normally write it down , Becky ? MOT · eng_british_Manchester_I/becky18a.cha, line 909 · Becky 2;06
  3. what shall I write then ? INV · eng_british_Manchester_I/becky18a.cha, line 924 · Becky 2;06
  4. you want to write some scissors ? INV · eng_british_Manchester_I/becky18a.cha, line 928 · Becky 2;06
  5. to write on . MOT · eng_british_Manchester_I/becky18a.cha, line 1515 · Becky 2;06
  6. we should write your name on that , shouldn't we ? MOT · eng_british_Manchester_I/becky18a.cha, line 1544 · Becky 2;06
  1. eng_british_Manchester_I/becky18a.cha, line 903 · Becky, 2;6.05
    CHIyou write that down .
    INVoh .
    INV*INV: I write it down .
    INVright .
    INVokay .
  2. eng_british_Manchester_I/becky18a.cha, line 909 · Becky, 2;6.05
    INVright .
    INVokay .
    MOT*MOT: don't you normally write it down , Becky ?
    CHIno .
    MOTyes .
  3. eng_british_Manchester_I/becky18a.cha, line 924 · Becky, 2;6.05
    INVokay .
    MOTself prescription .
    INV*INV: what shall I write then ?
    CHIum I write you some scissors .
    INVyou want to write some scissors ?
  4. eng_british_Manchester_I/becky18a.cha, line 928 · Becky, 2;6.05
    INVwhat shall I write then ?
    CHIum I write you some scissors .
    INV*INV: you want to write some scissors ?
    CHIyeah .
    INVokay .
  5. eng_british_Manchester_I/becky18a.cha, line 1515 · Becky, 2;6.05
    MOTbecause you prefer using these [/] these papers , don't you ?
    CHIyes .
    MOT*MOT: to write on .
    CHIyes .
    CHIjust keep it # nice and warm .
  6. eng_british_Manchester_I/becky18a.cha, line 1544 · Becky, 2;6.05
    MOT<that's right> [<] .
    MOTuhhum .
    MOT*MOT: we should write your name on that , shouldn't we ?
    MOTbecause it says this doctor's case belongs to doctor # Dodson .
    CHII can't do it .

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. Becky eng_british_Manchester_I3.28
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_british_Manchester_I/becky18a.chaBecky 2;6.051,830663.28

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. write6 · 100.0%