PHPCLANCHILDES with regular expressions

7 matches in 6 utterances

4.46 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (468 utterances, 1,571 words searched).

  1. we said it was Percy_pig . MOT · eng_british_Manchester_I/becky13b.cha, line 177 · Becky 2;04
  2. do you remember those cars <that we> [/] that we had out ? MOT · eng_british_Manchester_I/becky13b.cha, line 304 · Becky 2;04
  3. do you remember those cars <that we> [/] that we had out ? MOT · eng_british_Manchester_I/becky13b.cha, line 304 · Becky 2;04
  4. all the little matchbox cars we found in the cupboard . MOT · eng_british_Manchester_I/becky13b.cha, line 322 · Becky 2;04
  5. there we are . MOT · eng_british_Manchester_I/becky13b.cha, line 384 · Becky 2;04
  6. I don't think we've got cherrys . MOT · eng_british_Manchester_I/becky13b.cha, line 918 · Becky 2;04
  7. I think tomatos are as near as we're gonna [: going to] get . MOT · eng_british_Manchester_I/becky13b.cha, line 920 · Becky 2;04
  1. CHIis that +...
    CHIwhat's this pig called ?
    MOT*MOT: we said it was Percy_pig .
    CHIwhat's this dog called ?
    MOTum can't remember what the dog xxx .
  2. MOTdo you remember that , Becky ?
    CHImmhm .
    MOT*MOT: do you remember those cars <that we> [/] that we had out ?
    CHImmhm .
    MOTthey were good , weren't they ?
  3. MOTthey were my cars when I was little .
    INVwere they ?
    MOT*MOT: all the little matchbox cars we found in the cupboard .
    MOThere you are .
    INVwww .
  4. MOTgoing to make him come under the tunnel ?
    MOTmake him come under here , look .
    MOT*MOT: there we are .
    MOTyou go round the other way .
    MOTshall I push him through back to you ?
  5. CHIwhere's cherry on top ?
    MOTwell .
    MOT*MOT: I don't think we've got cherrys .
    MOTI think tomatos are as near as we're gonna [: going to] get .
    MOTdoes that look like one of Grandma's cakes now ?
  6. MOTwell .
    MOTI don't think we've got cherrys .
    MOT*MOT: I think tomatos are as near as we're gonna [: going to] get .
    MOTdoes that look like one of Grandma's cakes now ?
    CHIyeah .

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_I4.46
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_british_Manchester_I/becky13b.chaBecky 2;4.191,571674.46

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. we7 · 100.0%