PHPCLANCHILDES with regular expressions

10 matches in 10 utterances

6.56 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (370 utterances, 1,524 words searched).

  1. <Sarah # what's my Daddy's name> [?] ? GLO · eng_USA_Brown/sarah047.cha, line 106 · Sarah 3;02
  2. what's my Mommy's name ? GLO · eng_USA_Brown/sarah047.cha, line 115 · Sarah 3;02
  3. what's your Mommy's name ? GLO · eng_USA_Brown/sarah047.cha, line 123 · Sarah 3;02
  4. what's your Daddy's name ? GLO · eng_USA_Brown/sarah047.cha, line 130 · Sarah 3;02
  5. <what's your name> [?] ? MOT · eng_USA_Brown/sarah047.cha, line 573 · Sarah 3;02
  6. <what's my doggie's name> [?] ? MOT · eng_USA_Brown/sarah047.cha, line 754 · Sarah 3;02
  7. yeah # and what's Bam_Bam's doggie's name ? MOT · eng_USA_Brown/sarah047.cha, line 762 · Sarah 3;02
  8. what's Bam_Bam's doggie's name ? MOT · eng_USA_Brown/sarah047.cha, line 776 · Sarah 3;02
  9. what's his animal's name ? MOT · eng_USA_Brown/sarah047.cha, line 780 · Sarah 3;02
  10. what's her name ? MOT · eng_USA_Brown/sarah047.cha, line 1470 · Sarah 3;02
  1. eng_USA_Brown/sarah047.cha, line 106 · Sarah, 3;2.02
    GLOok ?
    CHIhey # I go ge(t) two pencils .
    GLO*GLO: <Sarah # what's my Daddy's name> [?] ?
    CHIuh # Flintstone .
    GLO<that's right # Flintstone> [?] .
  2. eng_USA_Brown/sarah047.cha, line 115 · Sarah, 3;2.02
    CHIuh # Flintstone .
    GLO<that's right # Flintstone> [?] .
    GLO*GLO: what's my Mommy's name ?
    CHIum # Be(tt)y .
    GLOthat's right .
  3. eng_USA_Brown/sarah047.cha, line 123 · Sarah, 3;2.02
    GLOthat's right .
    GLOthat's right # Betty .
    GLO*GLO: what's your Mommy's name ?
    CHIuh .
    CHICarol .
  4. eng_USA_Brown/sarah047.cha, line 130 · Sarah, 3;2.02
    CHIuh .
    CHICarol .
    GLO*GLO: what's your Daddy's name ?
    CHIuh # my Daddy name # Donny .
    GLOthat's # yes that's right .
  5. eng_USA_Brown/sarah047.cha, line 573 · Sarah, 3;2.02
    CHIhi [/] hi .
    GLOhi .
    MOT*MOT: <what's your name> [?] ?
    CHIwho me ?
    MOT<who you> [?] ?
  6. eng_USA_Brown/sarah047.cha, line 754 · Sarah, 3;2.02
    GLOp@l # r@l # e@l # i@l # huh ?
    CHIgot it twisted .
    MOT*MOT: <what's my doggie's name> [?] ?
    CHIhuh .
    CHIuh # Beeno .
  7. eng_USA_Brown/sarah047.cha, line 762 · Sarah, 3;2.02
    CHIhuh .
    CHIuh # Beeno .
    MOT*MOT: yeah # and what's Bam_Bam's doggie's name ?
    CHIshe get my own .
    MOThuh ?
  8. eng_USA_Brown/sarah047.cha, line 776 · Sarah, 3;2.02
    CHIyyy .
    CHIheh .
    MOT*MOT: what's Bam_Bam's doggie's name ?
    CHIuh .
    MOTwhat's his animal's name ?
  9. eng_USA_Brown/sarah047.cha, line 780 · Sarah, 3;2.02
    MOTwhat's Bam_Bam's doggie's name ?
    CHIuh .
    MOT*MOT: what's his animal's name ?
    MOTit's a friend .
    CHIPeeno .
  10. eng_USA_Brown/sarah047.cha, line 1470 · Sarah, 3;2.02
    MOTsometimes it sort of runs away with her .
    MOToh # look who's here .
    MOT*MOT: what's her name ?
    CHITickles .
    GLOTickles # that's right .

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_Brown6.56
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_USA_Brown/sarah047.chaSarah 3;2.021,52410106.56

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. name10 · 100.0%