PHPCLANCHILDES with regular expressions

13 matches in 13 utterances

7.84 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (338 utterances, 1,658 words searched).

  1. two thirty ? MEL · eng_USA_Brown/sarah131.cha, line 69 · Sarah 4;11
  2. that's five xxx two . MEL · eng_USA_Brown/sarah131.cha, line 213 · Sarah 4;11
  3. five take away two . MEL · eng_USA_Brown/sarah131.cha, line 217 · Sarah 4;11
  4. you have five # and you take away two # and how many do you have ? MEL · eng_USA_Brown/sarah131.cha, line 219 · Sarah 4;11
  5. six take away two ? MEL · eng_USA_Brown/sarah131.cha, line 256 · Sarah 4;11
  6. six take away six is two ? MEL · eng_USA_Brown/sarah131.cha, line 299 · Sarah 4;11
  7. a two piece bathing+suit ? MEL · eng_USA_Brown/sarah131.cha, line 571 · Sarah 4;11
  8. it was a two ! MOT · eng_USA_Brown/sarah131.cha, line 662 · Sarah 4;11
  9. well make a nice two . MOT · eng_USA_Brown/sarah131.cha, line 673 · Sarah 4;11
  10. why don't you make a two ? MOT · eng_USA_Brown/sarah131.cha, line 682 · Sarah 4;11
  11. yeah # that's a good lookin(g) two # isn't it ? MOT · eng_USA_Brown/sarah131.cha, line 688 · Sarah 4;11
  12. that's how you make a two . MOT · eng_USA_Brown/sarah131.cha, line 708 · Sarah 4;11
  13. (be)cause that's the way you make a two . MOT · eng_USA_Brown/sarah131.cha, line 747 · Sarah 4;11
  1. eng_USA_Brown/sarah131.cha, line 69 · Sarah, 4;11.13
    MELwhy don't you come up and sit down ?
    CHIis it too dirty ?
    MEL*MEL: two thirty ?
    CHIno # I said +"/.
    CHI+" too dirty .
  2. eng_USA_Brown/sarah131.cha, line 213 · Sarah, 4;11.13
    MELit's three ?
    CHIthree ?
    MEL*MEL: that's five xxx two .
    CHIhuh ?
    MELfive take away two .
  3. eng_USA_Brown/sarah131.cha, line 217 · Sarah, 4;11.13
    MELthat's five xxx two .
    CHIhuh ?
    MEL*MEL: five take away two .
    MELyou have five # and you take away two # and how many do you have ?
    CHIone # two # three !
  4. eng_USA_Brown/sarah131.cha, line 219 · Sarah, 4;11.13
    CHIhuh ?
    MELfive take away two .
    MEL*MEL: you have five # and you take away two # and how many do you have ?
    CHIone # two # three !
    MELsee ?
  5. eng_USA_Brown/sarah131.cha, line 256 · Sarah, 4;11.13
    CHI(a)n(d) that's four .
    MELwhat did you start out with ?
    MEL*MEL: six take away two ?
    CHI0 .
    MELand you got four .
  6. eng_USA_Brown/sarah131.cha, line 299 · Sarah, 4;11.13
    CHIand one # two .
    CHIisn't it ?
    MEL*MEL: six take away six is two ?
    CHIisn't it ?
    MELno .
  7. eng_USA_Brown/sarah131.cha, line 571 · Sarah, 4;11.13
    MELa top and bottom ?
    CHItwo piece .
    MEL*MEL: a two piece bathing+suit ?
    CHItwo piece .
    MELwow !
  8. eng_USA_Brown/sarah131.cha, line 662 · Sarah, 4;11.13
    MOTwell # what was it ?
    CHItwo .
    MOT*MOT: it was a two !
    CHII made it wrong .
    MOTheavens !
  9. eng_USA_Brown/sarah131.cha, line 673 · Sarah, 4;11.13
    CHIgettin(g) problems here .
    MOTa problem's here # huh ?
    MOT*MOT: well make a nice two .
    MOTthis way .
    CHIyou makes a two for me .
  10. eng_USA_Brown/sarah131.cha, line 682 · Sarah, 4;11.13
    MOTthis way .
    CHIyou makes a two for me .
    MOT*MOT: why don't you make a two ?
    CHIhey # let's do another page .
    CHIoh # this one .
  11. eng_USA_Brown/sarah131.cha, line 688 · Sarah, 4;11.13
    CHIhey # let's do another page .
    CHIoh # this one .
    MOT*MOT: yeah # that's a good lookin(g) two # isn't it ?
    MOThuh ?
    CHIyeah .
  12. eng_USA_Brown/sarah131.cha, line 708 · Sarah, 4;11.13
    MOTit goes this way # here .
    CHIhow_come they # they always make it like this ?
    MOT*MOT: that's how you make a two .
    MOTno # start at the top .
    MOTsee # you start up here .
  13. eng_USA_Brown/sarah131.cha, line 747 · Sarah, 4;11.13
    GAIjust like this # and then down .
    CHIhow_come I always make it like this ?
    MOT*MOT: (be)cause that's the way you make a two .
    MOTthat's why .
    CHIwell I can make it like this .

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. Sarah eng_USA_Brown7.84
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_USA_Brown/sarah131.chaSarah 4;11.131,65813137.84

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. two13 · 100.0%