PHPCLANCHILDES with regular expressions

6 matches in 5 utterances

4.69 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (394 utterances, 1,280 words searched).

  1. what about Grampy # want to talk to Grampy on the phone ? MOT · eng_USA_Brown/sarah010.cha, line 279 · Sarah 2;04
  2. what about Grampy # want to talk to Grampy on the phone ? MOT · eng_USA_Brown/sarah010.cha, line 279 · Sarah 2;04
  3. tell Grampy what kind of dress you got on . FAT · eng_USA_Brown/sarah010.cha, line 282 · Sarah 2;04
  4. say hello # Grampy . FAT · eng_USA_Brown/sarah010.cha, line 292 · Sarah 2;04
  5. say hello # Grampy . MOT · eng_USA_Brown/sarah010.cha, line 294 · Sarah 2;04
  6. Uncle [//] what's Grampy got # Cadillac ? FAT · eng_USA_Brown/sarah010.cha, line 334 · Sarah 2;04
  1. eng_USA_Brown/sarah010.cha, line 279 · Sarah, 2;4.19
    CHIfine .
    CHIxxx .
    MOT*MOT: what about Grampy # want to talk to Grampy on the phone ?
    FATtell Grampy what kind of dress you got on .
    CHII <a dress> [?] .
  2. eng_USA_Brown/sarah010.cha, line 282 · Sarah, 2;4.19
    CHIxxx .
    MOTwhat about Grampy # want to talk to Grampy on the phone ?
    FAT*FAT: tell Grampy what kind of dress you got on .
    CHII <a dress> [?] .
    FATgot a pretty dress on .
  3. eng_USA_Brown/sarah010.cha, line 292 · Sarah, 2;4.19
    FATgot a pretty dress on .
    CHII xxx .
    FAT*FAT: say hello # Grampy .
    MOTsay hello # Grampy .
    CHI(hel)lo Grampy .
  4. eng_USA_Brown/sarah010.cha, line 294 · Sarah, 2;4.19
    CHII xxx .
    FATsay hello # Grampy .
    MOT*MOT: say hello # Grampy .
    CHI(hel)lo Grampy .
    CHIxxx .
  5. eng_USA_Brown/sarah010.cha, line 334 · Sarah, 2;4.19
    FATFord ?
    CHIFord .
    FAT*FAT: Uncle [//] what's Grampy got # Cadillac ?
    CHICa(dilla)c .
    MOTxxx trying to get her to say the words today .

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_Brown4.69
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_USA_Brown/sarah010.chaSarah 2;4.191,280564.69

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. grampy6 · 100.0%