PHPCLANCHILDES with regular expressions

8 matches in 7 utterances

2.52 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (813 utterances, 3,173 words searched).

  1. Racketyboom you gonna read Racketyboom ? MOT · eng_USA_Brown/eve02.cha, line 508 · Eve 1;06
  2. Racketyboom you gonna read Racketyboom ? MOT · eng_USA_Brown/eve02.cha, line 508 · Eve 1;06
  3. is that Racketyboom . MOT · eng_USA_Brown/eve02.cha, line 832 · Eve 1;06
  4. lay down here # you look at Racketyboom while Mommy changes your diaper . MOT · eng_USA_Brown/eve02.cha, line 996 · Eve 1;06
  5. <now you sit there and look at Racketyboom> [>] [?] . MOT · eng_USA_Brown/eve02.cha, line 1094 · Eve 1;06
  6. shall we read Racketyboom ? MOT · eng_USA_Brown/eve02.cha, line 1119 · Eve 1;06
  7. okay # this is Racketyboom . MOT · eng_USA_Brown/eve02.cha, line 1300 · Eve 1;06
  8. Racketyboom # alright . COL · eng_USA_Brown/eve02.cha, line 4067 · Eve 1;06
  1. MOToh that's a pretty hat .
    CHIRacketyboom .
    MOT*MOT: Racketyboom you gonna read Racketyboom ?
    CHIyeah .
    MOTalright .
  2. MOThad enough .
    CHIcup Racketyboom .
    MOT*MOT: is that Racketyboom .
    CHIread .
    MOTno # Mommy's busy .
  3. MOTone more minute .
    MOTlay down .
    MOT*MOT: lay down here # you look at Racketyboom while Mommy changes your diaper .
    MOTfor just one more minute .
    CHIpotty .
  4. MOT(e)xcuse me .
    MOTMommy will read in just a minute .
    MOT*MOT: <now you sit there and look at Racketyboom> [>] [?] .
    CHIRacketyboom .
    MOTyes .
  5. MOTyou hold very still while I put your diaper on .
    MOTwe've got to put your leotard on .
    MOT*MOT: shall we read Racketyboom ?
    CHIoh # yeah .
    MOThere # hold the book and turn the pages .
  6. MOTlet me put the fire on the coffee .
    CHIfire coffee .
    MOT*MOT: okay # this is Racketyboom .
    MOTyou're turning too many pages .
    MOTnow # Mommy's gonna go get lunch .
  7. COLwhat are you going to read ?
    CHIRacketyboom .
    COL*COL: Racketyboom # alright .
    FAThi # Eve .
    FATis that the best you can do ?

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. Eve eng_USA_Brown2.52
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_USA_Brown/eve02.chaEve 1;6.3,173782.52

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. racketyboom8 · 100.0%