PHPCLANCHILDES with regular expressions

7 matches in 6 utterances

4.51 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (348 utterances, 1,551 words searched).

  1. Auntie Elenore # look . MOT · eng_USA_Brown/sarah052.cha, line 885 · Sarah 3;03
  2. see it # Auntie Elenore and Auntie xxx . MOT · eng_USA_Brown/sarah052.cha, line 892 · Sarah 3;03
  3. see it # Auntie Elenore and Auntie xxx . MOT · eng_USA_Brown/sarah052.cha, line 892 · Sarah 3;03
  4. Auntie Ellie . MOT · eng_USA_Brown/sarah052.cha, line 906 · Sarah 3;03
  5. you got two Auntie Ellies . MOT · eng_USA_Brown/sarah052.cha, line 908 · Sarah 3;03
  6. where's the other Auntie Ellie live ? MOT · eng_USA_Brown/sarah052.cha, line 912 · Sarah 3;03
  7. besides Grampy # Uncle Georgie # Uncle Walte(r) # (a)n(d) Auntie Elenore ? MOT · eng_USA_Brown/sarah052.cha, line 980 · Sarah 3;03
  1. eng_USA_Brown/sarah052.cha, line 885 · Sarah, 3;3.07
    MOTSarah look who's out here .
    CHIwho ?
    MOT*MOT: Auntie Elenore # look .
    MOTlook .
    MOTright there .
  2. eng_USA_Brown/sarah052.cha, line 892 · Sarah, 3;3.07
    MOTlook .
    MOTright there .
    MOT*MOT: see it # Auntie Elenore and Auntie xxx .
    CHIBonnie # Ken .
    MOTyeah .
  3. eng_USA_Brown/sarah052.cha, line 906 · Sarah, 3;3.07
    MOThuh ?
    CHIwho ?
    MOT*MOT: Auntie Ellie .
    MOTyou got two Auntie Ellies .
    MOThuh ?
  4. eng_USA_Brown/sarah052.cha, line 908 · Sarah, 3;3.07
    CHIwho ?
    MOTAuntie Ellie .
    MOT*MOT: you got two Auntie Ellies .
    MOThuh ?
    MOTwhere's the other Auntie Ellie live ?
  5. eng_USA_Brown/sarah052.cha, line 912 · Sarah, 3;3.07
    MOTyou got two Auntie Ellies .
    MOThuh ?
    MOT*MOT: where's the other Auntie Ellie live ?
    MOTdo you remember ?
    CHIin the cook+out .
  6. eng_USA_Brown/sarah052.cha, line 980 · Sarah, 3;3.07
    MOT(a)n(d) # who else did ya see at the store that day ?
    MOTremember ?
    MOT*MOT: besides Grampy # Uncle Georgie # Uncle Walte(r) # (a)n(d) Auntie Elenore ?
    MOTwho else ?
    CHIxxx mine ?

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_Brown4.51
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_USA_Brown/sarah052.chaSarah 3;3.071,551674.51

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. auntie7 · 100.0%