PHPCLANCHILDES with regular expressions

6 matches in 6 utterances

4.63 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (374 utterances, 1,296 words searched).

  1. did you have your Wheaties this mornin(g) ? FAT · eng_USA_Brown/sarah090.cha, line 250 · Sarah 4;01
  2. what do you have in the other one ? MEL · eng_USA_Brown/sarah090.cha, line 439 · Sarah 4;01
  3. boys don't have bangs . FAT · eng_USA_Brown/sarah090.cha, line 573 · Sarah 4;01
  4. they have Dutch cuts . FAT · eng_USA_Brown/sarah090.cha, line 575 · Sarah 4;01
  5. Beatles have bangs . MEL · eng_USA_Brown/sarah090.cha, line 577 · Sarah 4;01
  6. we decided to make a big pattern milk by saying you'll have hair on your chest when you grow up . MEL · eng_USA_Brown/sarah090.cha, line 987 · Sarah 4;01
  1. CHI(be)cause .
    MELmust be pretty full .
    FAT*FAT: did you have your Wheaties this mornin(g) ?
    CHIWheaties .
    CHIbut I don't have xxx .
  2. CHIMelissa I get a piggie+bank and now I got two piggie+banks .
    CHIone is a doggie # one is a pig .
    MEL*MEL: what do you have in the other one ?
    CHImoney [?] .
    MEL<more pennies> [?] ?
  3. CHIwant me make your bangs ?
    FATno # no # not for me .
    FAT*FAT: boys don't have bangs .
    FATthey have Dutch cuts .
    MELBeatles have bangs .
  4. FATno # no # not for me .
    FATboys don't have bangs .
    FAT*FAT: they have Dutch cuts .
    MELBeatles have bangs .
    CHIyou have bangs ?
  5. FATboys don't have bangs .
    FATthey have Dutch cuts .
    MEL*MEL: Beatles have bangs .
    CHIyou have bangs ?
    MELsort of .
  6. FATlike me ?
    CHIyou have +...
    MEL*MEL: we decided to make a big pattern milk by saying you'll have hair on your chest when you grow up .
    CHIyou have hair on your chest ?
    MELnope .

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_Brown4.63
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_USA_Brown/sarah090.chaSarah 4;1.041,296664.63

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. have6 · 100.0%