PHPCLANCHILDES with regular expressions

5 matches in 5 utterances

2.52 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (454 utterances, 1,986 words searched).

  1. would you like to be a doctor ? FAT · eng_USA_Brown/sarah127.cha, line 791 · Sarah 4;10
  2. you had a lady doctor . MOT · eng_USA_Brown/sarah127.cha, line 809 · Sarah 4;10
  3. sure # remember when you # that lady doctor gave you a needle ? FAT · eng_USA_Brown/sarah127.cha, line 813 · Sarah 4;10
  4. she [//] # that was a lady doctor . FAT · eng_USA_Brown/sarah127.cha, line 820 · Sarah 4;10
  5. that was a lady doctor . MOT · eng_USA_Brown/sarah127.cha, line 822 · Sarah 4;10
  1. eng_USA_Brown/sarah127.cha, line 791 · Sarah, 4;10.06
    FATyou don't get +...
    FATthat's the shoulder .
    FAT*FAT: would you like to be a doctor ?
    FATwould ya ?
    CHIno .
  2. eng_USA_Brown/sarah127.cha, line 809 · Sarah, 4;10.06
    FATno # they make girl doctors .
    FATgirls can be doctors .
    MOT*MOT: you had a lady doctor .
    MOTremember when you had the cold ?
    FATsure # remember when you # that lady doctor gave you a needle ?
  3. eng_USA_Brown/sarah127.cha, line 813 · Sarah, 4;10.06
    MOTyou had a lady doctor .
    MOTremember when you had the cold ?
    FAT*FAT: sure # remember when you # that lady doctor gave you a needle ?
    MOTremember up the hospital # thanksgivin(g) .
    FAThuh ?
  4. eng_USA_Brown/sarah127.cha, line 820 · Sarah, 4;10.06
    MOTremember up the hospital # thanksgivin(g) .
    FAThuh ?
    FAT*FAT: she [//] # that was a lady doctor .
    MOTthat was a lady doctor .
    MOTthat wasn't a man .
  5. eng_USA_Brown/sarah127.cha, line 822 · Sarah, 4;10.06
    FAThuh ?
    FATshe [//] # that was a lady doctor .
    MOT*MOT: that was a lady doctor .
    MOTthat wasn't a man .
    MOTno # the nurse gave her the shot .

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_Brown2.52
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_USA_Brown/sarah127.chaSarah 4;10.061,986552.52

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. doctor5 · 100.0%