PHPCLANCHILDES with regular expressions

8 matches in 8 utterances

4.98 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (414 utterances, 1,606 words searched).

  1. I better send for that doll . MOT · eng_USA_Brown/sarah054.cha, line 580 · Sarah 3;03
  2. it's a doll . MOT · eng_USA_Brown/sarah054.cha, line 586 · Sarah 3;03
  3. that's xxx doll . MOT · eng_USA_Brown/sarah054.cha, line 590 · Sarah 3;03
  4. let me see your new doll # Sarah . GLO · eng_USA_Brown/sarah054.cha, line 672 · Sarah 3;03
  5. let's see how your doll is doing . GLO · eng_USA_Brown/sarah054.cha, line 954 · Sarah 3;03
  6. Momma had ta give her that doll . MOT · eng_USA_Brown/sarah054.cha, line 1013 · Sarah 3;03
  7. what a good little doll . GLO · eng_USA_Brown/sarah054.cha, line 1201 · Sarah 3;03
  8. what a good little doll . GLO · eng_USA_Brown/sarah054.cha, line 1203 · Sarah 3;03
  1. MOTxxx .
    CHII want Tressa .
    MOT*MOT: I better send for that doll .
    CHII want Tressa .
    GLOwhat's Tressa ?
  2. CHII want Tressa .
    GLOwhat's Tressa ?
    MOT*MOT: it's a doll .
    GLOoh .
    MOTthat's xxx doll .
  3. MOTit's a doll .
    GLOoh .
    MOT*MOT: that's xxx doll .
    GLOd(o) you have a picture of her ?
    CHIhuh ?
  4. MOTyeah .
    CHI<Tressa # Tressa> [/] # Tressa # <red blue> [/] # red blue # <Tressa # Tressa # Tressa> [/] # Tressa .
    GLO*GLO: let me see your new doll # Sarah .
    GLOSarah .
    GLOyoohoo # Sarah .
  5. MOToh # it is huh ?
    CHIhuh .
    GLO*GLO: let's see how your doll is doing .
    GLOdid she wet ?
    CHIuhuh .
  6. MOTnothin(g) made her happy .
    GLOoh # dear .
    MOT*MOT: Momma had ta give her that doll .
    MOTwhere'd you get it ?
    GLOwhere'd you get it ?
  7. GLOstill dry ?
    MOTstill dry .
    GLO*GLO: what a good little doll .
    GLOwhat a good little doll .
    MOTI wish you were that good when you were a baby .
  8. MOTstill dry .
    GLOwhat a good little doll .
    GLO*GLO: what a good little doll .
    MOTI wish you were that good when you were a baby .
    CHII know 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. Sarah eng_USA_Brown4.98
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_USA_Brown/sarah054.chaSarah 3;3.201,606884.98

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. doll8 · 100.0%