PHPCLANCHILDES with regular expressions

6 matches in 6 utterances

6.84 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (219 utterances, 877 words searched).

  1. put it up here (be)cause you xxx . MOT · eng_USA_Brown/sarah134.cha, line 144 · Sarah 5;00
  2. yeah # put the two up first . MOT · eng_USA_Brown/sarah134.cha, line 224 · Sarah 5;00
  3. that add up to seven . MOT · eng_USA_Brown/sarah134.cha, line 228 · Sarah 5;00
  4. I wonder how sometimes how they think think up +... MOT · eng_USA_Brown/sarah134.cha, line 504 · Sarah 5;00
  5. pick it up . MOT · eng_USA_Brown/sarah134.cha, line 685 · Sarah 5;00
  6. y(ou) know to go down to Connecticut (a)n(d) pick him up . MOT · eng_USA_Brown/sarah134.cha, line 882 · Sarah 5;00
  1. eng_USA_Brown/sarah134.cha, line 144 · Sarah, 5;0.02
    MOTthat would be forty minute xxx .
    MOTsee ?
    MOT*MOT: put it up here (be)cause you xxx .
    MOTI got ta call Grampy .
    CHIwhat ?
  2. eng_USA_Brown/sarah134.cha, line 224 · Sarah, 5;0.02
    MOTthat's five .
    CHIno # you didn't put it like that .
    MOT*MOT: yeah # put the two up first .
    MOTtwo and five +...
    MOTthat add up to seven .
  3. eng_USA_Brown/sarah134.cha, line 228 · Sarah, 5;0.02
    MOTyeah # put the two up first .
    MOTtwo and five +...
    MOT*MOT: that add up to seven .
    CHIno # you +...
    MOTsee # look .
  4. eng_USA_Brown/sarah134.cha, line 504 · Sarah, 5;0.02
    CHIhey # remember that I hanged em on like dat ?
    MOTthat's clever # though .
    MOT*MOT: I wonder how sometimes how they think think up +...
    GAImmhm .
    MOTy(ou) know ?
  5. eng_USA_Brown/sarah134.cha, line 685 · Sarah, 5;0.02
    MOTyeah # I guess so .
    CHIthree # yeah .
    MOT*MOT: pick it up .
    CHII'm gonna xxx stay here .
    MOTwhat ?
  6. eng_USA_Brown/sarah134.cha, line 882 · Sarah, 5;0.02
    MOTwe never # never expected to see him .
    MOTwe thought we might get a call this morning from him .
    MOT*MOT: y(ou) know to go down to Connecticut (a)n(d) pick him up .
    GAIyeah .
    CHI0 .

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_Brown6.84
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_USA_Brown/sarah134.chaSarah 5;0.02877666.84

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. up6 · 100.0%