PHPCLANCHILDES with regular expressions

7 matches in 7 utterances

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

  1. it doesn't xxx as an owl because the paint's dry . MOT · eng_british_Manchester_I/becky14a.cha, line 38 · Becky 2;04
  2. next time we do painting we'll do an owl again . MOT · eng_british_Manchester_I/becky14a.cha, line 45 · Becky 2;04
  3. next time we do painting we'll do an owl again . MOT · eng_british_Manchester_I/becky14a.cha, line 81 · Becky 2;04
  4. you should have said yesterday you wanted to do an owl . MOT · eng_british_Manchester_I/becky14a.cha, line 86 · Becky 2;04
  5. it's an owl . INV · eng_british_Manchester_I/becky14a.cha, line 270 · Becky 2;04
  6. an owl . INV · eng_british_Manchester_I/becky14a.cha, line 286 · Becky 2;04
  7. should get an elastic band for them , shouldn't we really ? MOT · eng_british_Manchester_I/becky14a.cha, line 1864 · Becky 2;04
  1. MOTand then we folded the paper .
    MOTand we made owl because the paint was wet .
    MOT*MOT: it doesn't xxx as an owl because the paint's dry .
    CHIyeah .
    CHIit's owl .
  2. CHIyeah .
    CHIit's owl .
    MOT*MOT: next time we do painting we'll do an owl again .
    MOTokay ?
    CHImmhm .
  3. MOTbut it willn't work , Becky .
    MOTbecause the paint's not wet .
    MOT*MOT: next time we do painting we'll do an owl again .
    MOTokay ?
    MOTyou should have said yesterday you wanted to do an owl .
  4. MOTnext time we do painting we'll do an owl again .
    MOTokay ?
    MOT*MOT: you should have said yesterday you wanted to do an owl .
    CHIyeah .
    INVoh .
  5. CHIxxx .
    CHIwhat is it ?
    INV*INV: it's an owl .
    CHIa [*] owl .
    CHIit's a [*] owl .
  6. CHIwhat is this ?
    CHIa [*] owl .
    INV*INV: an owl .
    CHImmhm .
    CHIin there .
  7. CHIxxx .
    MOTyou've got one more here , look .
    MOT*MOT: should get an elastic band for them , shouldn't we really ?
    MOTput them together .
    MOTI'll see if we've got one xxx .

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_I3.98
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_british_Manchester_I/becky14a.chaBecky 2;4.281,760773.98

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. an7 · 100.0%