PHPCLANCHILDES with regular expressions

7 matches in 7 utterances

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

  1. how are you ? MEL · eng_USA_Brown/sarah131.cha, line 21 · Sarah 4;11
  2. do you know how much that is ? MEL · eng_USA_Brown/sarah131.cha, line 199 · Sarah 4;11
  3. 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
  4. how do you look in it ? MEL · eng_USA_Brown/sarah131.cha, line 577 · Sarah 4;11
  5. that's how you make a two . MOT · eng_USA_Brown/sarah131.cha, line 708 · Sarah 4;11
  6. see how you write your name lately . MOT · eng_USA_Brown/sarah131.cha, line 841 · Sarah 4;11
  7. oh how pretty . MEL · eng_USA_Brown/sarah131.cha, line 1241 · Sarah 4;11
  1. CHIhi # Melissa .
    MELhi # Sarah .
    MEL*MEL: how are you ?
    CHInow where's that present ?
    MOToh # big mouth .
  2. MELwhat is that ?
    CHIfive [/] five plus two .
    MEL*MEL: do you know how much that is ?
    CHI0 .
    MELcan you do it on your fingers ?
  3. 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 ?
  4. CHItwo piece .
    MELwow !
    MEL*MEL: how do you look in it ?
    CHImm # good .
    GAIwhat does it look like # Sarah ?
  5. 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 .
  6. MOTwell # last year I think you're <doing better> [//] did better than you're doin(g) this year .
    MOTyou're not doin(g) # let me see you write your name .
    MOT*MOT: see how you write your name lately .
    CHII'm goin(g) make somethin(g) else .
    CHIwhat do you think I should make ?
  7. MELthank+you .
    CHII jumping .
    MEL*MEL: oh how pretty .
    MELoh .
    MELa cup and saucer .

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_Brown4.22
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_USA_Brown/sarah131.chaSarah 4;11.131,658774.22

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. how7 · 100.0%