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. this way . MOT · eng_USA_Brown/sarah131.cha, line 676 · Sarah 4;11
  2. it goes this way # here . MOT · eng_USA_Brown/sarah131.cha, line 703 · Sarah 4;11
  3. (be)cause that's the way you make a two . MOT · eng_USA_Brown/sarah131.cha, line 747 · Sarah 4;11
  4. see you go the wrong way . MOT · eng_USA_Brown/sarah131.cha, line 790 · Sarah 4;11
  5. no # the other way . MOT · eng_USA_Brown/sarah131.cha, line 807 · Sarah 4;11
  6. down # (a)n(d) around that way # towards Gail . MOT · eng_USA_Brown/sarah131.cha, line 923 · Sarah 4;11
  7. now we'll be able to save all our pennies that way # and then buy things we really need . MEL · eng_USA_Brown/sarah131.cha, line 1090 · Sarah 4;11
  1. MOTa problem's here # huh ?
    MOTwell make a nice two .
    MOT*MOT: this way .
    CHIyou makes a two for me .
    MOTwhy don't you make a two ?
  2. MOTthat's backwards .
    MOTit goes over this side # the loop .
    MOT*MOT: it goes this way # here .
    CHIhow_come they # they always make it like this ?
    MOTthat's how you make a two .
  3. 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 .
  4. CHIlike this you make a two ?
    MOTno .
    MOT*MOT: see you go the wrong way .
    CHIto Melissa ?
    MOTmake it towards Gail .
  5. MOTnow go around .
    MOTtowards the microphone .
    MOT*MOT: no # the other way .
    CHII am .
    MOTno # <no # no> [/] .
  6. MOTwhere ?
    MOTno # the other side .
    MOT*MOT: down # (a)n(d) around that way # towards Gail .
    MOTsee you're goin(g) towards Melissa .
    MOTyou have to go towards Gail .
  7. MOTlet Gail # let Melissa open it .
    MOTGail's next .
    MEL*MEL: now we'll be able to save all our pennies that way # and then buy things we really need .
    CHIso I got lots of piggie+banks # do you ?
    MELdo we get lots ?

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. way7 · 100.0%