PHPCLANCHILDES with regular expressions

6 matches in 6 utterances

14.05 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (88 utterances, 427 words searched).

  1. we're going to have to move it even more # huh ? MOT · eng_USA_Bates/nan28.cha, line 27 · Nan 2;04
  2. I don't know if we'll have enough people for all of them . MOT · eng_USA_Bates/nan28.cha, line 121 · Nan 2;04
  3. oh # we have three more . MOT · eng_USA_Bates/nan28.cha, line 207 · Nan 2;04
  4. oh # we have four more . MOT · eng_USA_Bates/nan28.cha, line 210 · Nan 2;04
  5. do we have four more people ? MOT · eng_USA_Bates/nan28.cha, line 213 · Nan 2;04
  6. you have one with a hat like that # don't you ? MOT · eng_USA_Bates/nan28.cha, line 232 · Nan 2;04
  1. eng_USA_Bates/nan28.cha, line 27 · Nan, 2;4.
    CHIxxx .
    MOTmove some of that ?
    MOT*MOT: we're going to have to move it even more # huh ?
    CHIthis one .
    CHIone ?
  2. eng_USA_Bates/nan28.cha, line 121 · Nan, 2;4.
    CHIyeah .
    MOTthere's a person .
    MOT*MOT: I don't know if we'll have enough people for all of them .
    CHIno !
    MOTno # you don't think so ?
  3. eng_USA_Bates/nan28.cha, line 207 · Nan, 2;4.
    MOTok .
    CHIcome .
    MOT*MOT: oh # we have three more .
    MOToh # we have four more .
    MOTdo we have four more people ?
  4. eng_USA_Bates/nan28.cha, line 210 · Nan, 2;4.
    CHIcome .
    MOToh # we have three more .
    MOT*MOT: oh # we have four more .
    MOTdo we have four more people ?
    CHIxxx .
  5. eng_USA_Bates/nan28.cha, line 213 · Nan, 2;4.
    MOToh # we have three more .
    MOToh # we have four more .
    MOT*MOT: do we have four more people ?
    CHIxxx .
    MOThow many more people ?
  6. eng_USA_Bates/nan28.cha, line 232 · Nan, 2;4.
    MOTxxx .
    CHIdo_do_do@wp that side .
    MOT*MOT: you have one with a hat like that # don't you ?
    CHIdo_do_do@wp that side .
    MOTthat side ?

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. Nan eng_USA_Bates14.05
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_USA_Bates/nan28.chaNan 2;4.4276614.05

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. have6 · 100.0%