PHPCLANCHILDES with regular expressions

6 matches in 6 utterances

4.36 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (335 utterances, 1,375 words searched).

  1. can Bugs snap his fingers ? KEN · eng_USA_Brown/sarah051.cha, line 613 · Sarah 3;03
  2. Petunia # isn't that his girl+friend's name . MOT · eng_USA_Brown/sarah051.cha, line 659 · Sarah 3;03
  3. look # his claws on the table . MOT · eng_USA_Brown/sarah051.cha, line 907 · Sarah 3;03
  4. looked somebody was gonna xxx # the cat turned his head now . MOT · eng_USA_Brown/sarah051.cha, line 911 · Sarah 3;03
  5. what's his name ? MOT · eng_USA_Brown/sarah051.cha, line 1047 · Sarah 3;03
  6. hey # don't write on his paper . MOT · eng_USA_Brown/sarah051.cha, line 1353 · Sarah 3;03
  1. eng_USA_Brown/sarah051.cha, line 613 · Sarah, 3;3.07
    MOTsee ?
    MOTlike that .
    KEN*KEN: can Bugs snap his fingers ?
    CHIhe can't .
    KENwhy ?
  2. eng_USA_Brown/sarah051.cha, line 659 · Sarah, 3;3.07
    KENtell me about her .
    CHIyyy .
    MOT*MOT: Petunia # isn't that his girl+friend's name .
    CHIno <&e> [//] Yuna .
    MOTI think Petunia's the little skunk .
  3. eng_USA_Brown/sarah051.cha, line 907 · Sarah, 3;3.07
    CHIwhere .
    MOTI it was somebody's head on the window .
    MOT*MOT: look # his claws on the table .
    MOTxxx not doin(g) it .
    MOTlooked somebody was gonna xxx # the cat turned his head now .
  4. eng_USA_Brown/sarah051.cha, line 911 · Sarah, 3;3.07
    MOTlook # his claws on the table .
    MOTxxx not doin(g) it .
    MOT*MOT: looked somebody was gonna xxx # the cat turned his head now .
    MOTbefore the head was # the cat's head was down .
    CHIlet's see .
  5. eng_USA_Brown/sarah051.cha, line 1047 · Sarah, 3;3.07
    MOT<what's> [/] what's Auntie Katz poodle's name ?
    CHIhmm # French .
    MOT*MOT: what's his name ?
    CHIFrench .
    MOTnope .
  6. eng_USA_Brown/sarah051.cha, line 1353 · Sarah, 3;3.07
    MOTthat's right .
    CHIxxx .
    MOT*MOT: hey # don't write on his paper .
    CHIwhy ?
    MOT(be)cause its not nice .

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_Brown4.36
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_USA_Brown/sarah051.chaSarah 3;3.071,375664.36

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. his6 · 100.0%