PHPCLANCHILDES with regular expressions

9 matches in 9 utterances

5.11 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (485 utterances, 1,760 words searched).

  1. right . MOT · eng_british_Manchester_I/becky14a.cha, line 351 · Becky 2;04
  2. oh right . INV · eng_british_Manchester_I/becky14a.cha, line 410 · Becky 2;04
  3. that's right . MOT · eng_british_Manchester_I/becky14a.cha, line 1027 · Becky 2;04
  4. oh right . MOT · eng_british_Manchester_I/becky14a.cha, line 1195 · Becky 2;04
  5. right . MOT · eng_british_Manchester_I/becky14a.cha, line 1341 · Becky 2;04
  6. right . MOT · eng_british_Manchester_I/becky14a.cha, line 1353 · Becky 2;04
  7. right . MOT · eng_british_Manchester_I/becky14a.cha, line 1450 · Becky 2;04
  8. that's right . MOT · eng_british_Manchester_I/becky14a.cha, line 1582 · Becky 2;04
  9. put them all the right way round . MOT · eng_british_Manchester_I/becky14a.cha, line 1712 · Becky 2;04
  1. MOTis it ?
    CHIthis .
    MOT*MOT: right .
    CHIlook .
    CHIit's a # lion .
  2. MOThe was in Sainsburys , wasn't he ?
    CHISainsburys .
    INV*INV: oh right .
    CHIhe's [*] was out of Sainsburys .
    MOThe was outside , wasn't he ?
  3. CHIit's Charlie_Chalk .
    MOTCharleie_Chalk .
    MOT*MOT: that's right .
    CHIgoing to go +//.
    CHIwe go swimming pool and the splash+pool .
  4. CHIhe's run away .
    MOThas he ?
    MOT*MOT: oh right .
    CHIwe find him again .
    MOTwill we ?
  5. CHImmhm .
    MOTI don't think you've grasped the concept of Snap yet , have you ?
    MOT*MOT: right .
    MOTsit down then .
    MOTthere you are .
  6. CHImmhm .
    MOTthese are Mummy's .
    MOT*MOT: right .
    MOTso I turn one over .
    CHImmhm .
  7. MOToh .
    MOTput William on top .
    MOT*MOT: right .
    MOTare you ready ?
    CHII said Snap .
  8. MOTso what do we say ?
    CHIum snap .
    MOT*MOT: that's right .
    MOTgo on then .
    MOTtake them all .
  9. MOTlet's play something else .
    MOTshall I <put the> [//] stack the cards together for you ?
    MOT*MOT: put them all the right way round .
    MOTbecause they're the wrong way , aren't they ?
    CHIno .

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. Becky eng_british_Manchester_I5.11
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_british_Manchester_I/becky14a.chaBecky 2;4.281,760995.11

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. right9 · 100.0%