PHPCLANCHILDES with regular expressions

7 matches in 7 utterances

4.56 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (447 utterances, 1,534 words searched).

  1. it's a fence. MOT · downs-flusberg/charles1.cha, line 497
  2. the cow by the fence. MOT · downs-flusberg/charles1.cha, line 501
  3. should we put all the cows by the fence? MOT · downs-flusberg/charles1.cha, line 515
  4. let's put all the cows by the fence. MOT · downs-flusberg/charles1.cha, line 516
  5. now all the fence is up. MOT · downs-flusberg/charles1.cha, line 524
  6. can you put the fence in here? MOT · downs-flusberg/charles1.cha, line 662
  7. put the fence in the barn. MOT · downs-flusberg/charles1.cha, line 664
  1. downs-flusberg/charles1.cha, line 497
    CHIhammer.
    MOTthat's not a hammer.
    MOT*MOT: it's a fence.
    MOTlet's set that up there.
    MOTwanna stand the cow here?
  2. downs-flusberg/charles1.cha, line 501
    MOTlet's set that up there.
    MOTwanna stand the cow here?
    MOT*MOT: the cow by the fence.
    CHImom?
    MOTwhat?
  3. downs-flusberg/charles1.cha, line 515
    MOTok?
    CHIxxx.
    MOT*MOT: should we put all the cows by the fence?
    MOTlet's put all the cows by the fence.
    MOTis there another cow?
  4. downs-flusberg/charles1.cha, line 516
    CHIxxx.
    MOTshould we put all the cows by the fence?
    MOT*MOT: let's put all the cows by the fence.
    MOTis there another cow?
    MOTwhere's another cow?
  5. downs-flusberg/charles1.cha, line 524
    MOTthere.
    MOTalright.
    MOT*MOT: now all the fence is up.
    MOTfind a cow.
    MOTmake another cow stand with this cow.
  6. downs-flusberg/charles1.cha, line 662
    MOTwhat about that?
    MOTput away the fences +/.
    MOT*MOT: can you put the fence in here?
    CHI<huh> [/?]?
    MOTput the fence in the barn.
  7. downs-flusberg/charles1.cha, line 664
    MOTcan you put the fence in here?
    CHI<huh> [/?]?
    MOT*MOT: put the fence in the barn.
    MOTI'll put the cow in.
    MOTand the trough, and the horse.

Matches by child

Matches per 1,000 words, all transcripts of each child together, highest first.

  1. Charles downs-flusberg4.56
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
downs-flusberg/charles1.chaCharles 1,534774.56

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. fence7 · 100.0%