PHPCLANCHILDES with regular expressions

8 matches in 8 utterances

9.47 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (221 utterances, 845 words searched).

  1. who did we see yesterday ? MOT · eng_USA_Brown/sarah011.cha, line 285 · Sarah 2;04
  2. who was the man that we saw ? MOT · eng_USA_Brown/sarah011.cha, line 289 · Sarah 2;04
  3. Mr who ? MOT · eng_USA_Brown/sarah011.cha, line 441 · Sarah 2;04
  4. who's that ? MOT · eng_USA_Brown/sarah011.cha, line 696 · Sarah 2;04
  5. who ? MOT · eng_USA_Brown/sarah011.cha, line 700 · Sarah 2;04
  6. know who's comin(g) today ? MOT · eng_USA_Brown/sarah011.cha, line 787 · Sarah 2;04
  7. know who's coming over Nana's today ? MOT · eng_USA_Brown/sarah011.cha, line 791 · Sarah 2;04
  8. yeah # Teppy's over Nana's # but who's coming over Nana's today ? MOT · eng_USA_Brown/sarah011.cha, line 798 · Sarah 2;04
  1. CHIa Jo_Ann .
    MOTyeah # you went with Jo_Ann # but where'd we go ?
    MOT*MOT: who did we see yesterday ?
    CHIxxx .
    MOTwho was the man that we saw ?
  2. MOTwho did we see yesterday ?
    CHIxxx .
    MOT*MOT: who was the man that we saw ?
    MOTwhat was his name ?
    CHIxxx .
  3. CHImonkey here .
    MOTmonkey # yeah # what's his name ?
    MOT*MOT: Mr who ?
    CHIMister Ear .
    MOTMister Ears # yeah .
  4. CHIprincess ?
    CHIyyy .
    MOT*MOT: who's that ?
    CHIxxx .
    MOTwho ?
  5. MOTwho's that ?
    CHIxxx .
    MOT*MOT: who ?
    CHIxxx .
    CHIhorsie .
  6. CHIno Mike .
    CHIxxx .
    MOT*MOT: know who's comin(g) today ?
    CHI(wh)o .
    MOTknow who's coming over Nana's today ?
  7. MOTknow who's comin(g) today ?
    CHI(wh)o .
    MOT*MOT: know who's coming over Nana's today ?
    MOTxxx .
    CHITeppy !
  8. MOTxxx .
    CHITeppy !
    MOT*MOT: yeah # Teppy's over Nana's # but who's coming over Nana's today ?
    CHIxxx .
    MOTRobert and Richard .

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_Brown9.47
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_USA_Brown/sarah011.chaSarah 2;4.26845889.47

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. who8 · 100.0%