PHPCLANCHILDES with regular expressions

7 matches in 7 utterances

3.00 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (538 utterances, 2,330 words searched).

  1. is that big enough ? MOT · eng_british_Manchester_II/warr06a.cha, line 693 · Warren 2;00
  2. oh: I've not done it big enough . MOT · eng_british_Manchester_II/warr06a.cha, line 1158 · Warren 2;00
  3. not big enough . MOT · eng_british_Manchester_II/warr06a.cha, line 1162 · Warren 2;00
  4. I think there's enough for two . MOT · eng_british_Manchester_II/warr06a.cha, line 1229 · Warren 2;00
  5. Mummy make it big enough for the sheep . MOT · eng_british_Manchester_II/warr06a.cha, line 1251 · Warren 2;00
  6. now I think we've got enough for one more . MOT · eng_british_Manchester_II/warr06a.cha, line 1433 · Warren 2;00
  7. we haven't got enough soft stuff . MOT · eng_british_Manchester_II/warr06a.cha, line 1590 · Warren 2;00
  1. MOTright .
    MOTyou put the +//.
    MOT*MOT: is that big enough ?
    MOTlet's make that a bit bigger .
    MOTyou put the monkey on there .
  2. CHII make a +...
    MOTright you make that animal then .
    MOT*MOT: oh: I've not done it big enough .
    MOTjust a minute .
    MOTnot big enough .
  3. MOToh: I've not done it big enough .
    MOTjust a minute .
    MOT*MOT: not big enough .
    MOTthat's better .
    CHIMummy help .
  4. MOTwe're going to run out of this stuff in a minute .
    CHIMummy .
    MOT*MOT: I think there's enough for two .
    CHIme .
    CHII make a sheep please .
  5. MOTWarren do some rolling .
    MOTshall Mummy finish off ?
    MOT*MOT: Mummy make it big enough for the sheep .
    MOTthere we go .
    MOTjust a second .
  6. CHIxxx .
    MOTshall we put the elephant next to the sheep ?
    MOT*MOT: now I think we've got enough for one more .
    MOTwe've already done that [/] that one .
    MOTfind one from there and we'll do one more .
  7. MOTand there's one that we couldn't make .
    CHIput on there .
    MOT*MOT: we haven't got enough soft stuff .
    CHImore .
    MOTthat's all we've got .

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. Warren eng_british_Manchester_II3.00
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_british_Manchester_II/warr06a.chaWarren 2;0.032,330773.00

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. enough7 · 100.0%