PHPCLANCHILDES with regular expressions

8 matches in 8 utterances

4.36 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (453 utterances, 1,834 words searched).

  1. he is going to bite your nose . MOT · eng_british_Manchester_I/becky05b.cha, line 977 · Becky 2;01
  2. are you ready for him to bite your nose ? MOT · eng_british_Manchester_I/becky05b.cha, line 982 · Becky 2;01
  3. he's bitten your nose . MOT · eng_british_Manchester_I/becky05b.cha, line 991 · Becky 2;01
  4. it's gone now your nose has . MOT · eng_british_Manchester_I/becky05b.cha, line 995 · Becky 2;01
  5. he's eaten your nose . MOT · eng_british_Manchester_I/becky05b.cha, line 1005 · Becky 2;01
  6. he's eaten your nose . MOT · eng_british_Manchester_I/becky05b.cha, line 1013 · Becky 2;01
  7. your nose is gone . MOT · eng_british_Manchester_I/becky05b.cha, line 1097 · Becky 2;01
  8. he pecks your nose ? MOT · eng_british_Manchester_I/becky05b.cha, line 1326 · Becky 2;01
  1. CHIno .
    MOThe does .
    MOT*MOT: he is going to bite your nose .
    CHIno .
    MOTare you ready for him to bite your nose ?
  2. MOThe is going to bite your nose .
    CHIno .
    MOT*MOT: are you ready for him to bite your nose ?
    CHIno .
    MOTyou are .
  3. MOTyou are .
    MOTthere .
    MOT*MOT: he's bitten your nose .
    CHIno .
    MOTit's gone now your nose has .
  4. MOThe's bitten your nose .
    CHIno .
    MOT*MOT: it's gone now your nose has .
    CHIno .
    MOTwhere's it gone ?
  5. MOTwhere's it gone ?
    CHImine .
    MOT*MOT: he's eaten your nose .
    CHIno .
    MOThe has .
  6. MOThe has .
    CHIno .
    MOT*MOT: he's eaten your nose .
    CHIno .
    MOT<he's going to eat your> [/] he's going to cheeks next .
  7. CHIit's gone .
    MOTyour ears have gone .
    MOT*MOT: your nose is gone .
    MOTyour cheeks have gone .
    MOTyour legs have gone .
  8. MOTand what's the bird doing ?
    CHIpeck your nose .
    MOT*MOT: he pecks your nose ?
    CHIyeah .
    MOTdoes he ?

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_I4.36
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_british_Manchester_I/becky05b.chaBecky 2;1.241,834884.36

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. nose8 · 100.0%