PHPCLANCHILDES with regular expressions

14 matches in 13 utterances

4.52 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (725 utterances, 3,097 words searched).

  1. and you had an orange Fizzie ? MOT · eng_USA_Brown/eve20.cha, line 101 · Eve 2;03
  2. and here's an eyebrow and here's another eyebrow and here's an eye . MOT · eng_USA_Brown/eve20.cha, line 1096 · Eve 2;03
  3. and here's an eyebrow and here's another eyebrow and here's an eye . MOT · eng_USA_Brown/eve20.cha, line 1096 · Eve 2;03
  4. and let's put an ice cube in . MOT · eng_USA_Brown/eve20.cha, line 1208 · Eve 2;03
  5. that's an ice cube . MOT · eng_USA_Brown/eve20.cha, line 1214 · Eve 2;03
  6. xxx be like an exercise . MOT · eng_USA_Brown/eve20.cha, line 2787 · Eve 2;03
  7. is that an exercise ? MOT · eng_USA_Brown/eve20.cha, line 2797 · Eve 2;03
  8. an eggnog ? MOT · eng_USA_Brown/eve20.cha, line 3061 · Eve 2;03
  9. now let's see, how can we make an eggnog . FAT · eng_USA_Brown/eve20.cha, line 3188 · Eve 2;03
  10. now what do we need for an eggnog, Eve ? MOT · eng_USA_Brown/eve20.cha, line 3208 · Eve 2;03
  11. an egg . MOT · eng_USA_Brown/eve20.cha, line 3216 · Eve 2;03
  12. goodness+sakes, what an eggnog drinker . MOT · eng_USA_Brown/eve20.cha, line 4022 · Eve 2;03
  13. goodness+sakes, what an eggnog drinker . MOT · eng_USA_Brown/eve20.cha, line 4028 · Eve 2;03
  14. you drank an awful lot of eggnog, didn't you, that's wonderful . MOT · eng_USA_Brown/eve20.cha, line 4060 · Eve 2;03
  1. eng_USA_Brown/eve20.cha, line 101 · Eve, 2;3.
    MOTorange Fizzie ?
    CHIyeah .
    MOT*MOT: and you had an orange Fizzie ?
    CHIyeah .
    CHIyes(ter)day .
  2. eng_USA_Brown/eve20.cha, line 1096 · Eve, 2;3.
    MOThere's head .
    CHIxxx .
    MOT*MOT: and here's an eyebrow and here's another eyebrow and here's an eye .
    MOTand here's another eye .
    MOThow many eyes do you have ?
  3. eng_USA_Brown/eve20.cha, line 1208 · Eve, 2;3.
    MOTgrape Fizzie or orange Fizzie ?
    CHIgrape Fizzie .
    MOT*MOT: and let's put an ice cube in .
    CHIxxx .
    MOTthat's an ice cube .
  4. eng_USA_Brown/eve20.cha, line 1214 · Eve, 2;3.
    MOTand let's put an ice cube in .
    CHIxxx .
    MOT*MOT: that's an ice cube .
    CHIxxx .
    MOThow many ice cubes do we have ?
  5. eng_USA_Brown/eve20.cha, line 2787 · Eve, 2;3.
    MOTgo back soon .
    CHIno .
    MOT*MOT: xxx be like an exercise .
    MOTxxx .
    CHIhey, dat's an exercise .
  6. eng_USA_Brown/eve20.cha, line 2797 · Eve, 2;3.
    MOTxxx .
    CHIhey, dat's an exercise .
    MOT*MOT: is that an exercise ?
    MOTcan you do a Bx ?
    CHIno .
  7. eng_USA_Brown/eve20.cha, line 3061 · Eve, 2;3.
    CHIno .
    CHIwant to have an eggnog .
    MOT*MOT: an eggnog ?
    CHIyeah .
    MOTI think you better pee+pee first .
  8. eng_USA_Brown/eve20.cha, line 3188 · Eve, 2;3.
    GLOcan you see me now ?
    CHIxxx .
    FAT*FAT: now let's see, how can we make an eggnog .
    CHImove it .
    CHImove it .
  9. eng_USA_Brown/eve20.cha, line 3208 · Eve, 2;3.
    CHImove my high chair .
    MOThow's that ?
    MOT*MOT: now what do we need for an eggnog, Eve ?
    CHIa eggie .
    MOTan egg .
  10. eng_USA_Brown/eve20.cha, line 3216 · Eve, 2;3.
    MOTnow what do we need for an eggnog, Eve ?
    CHIa eggie .
    MOT*MOT: an egg .
    MOTwhat else ?
    CHIanother .
  11. eng_USA_Brown/eve20.cha, line 4022 · Eve, 2;3.
    CHIyes .
    CHIhmm .
    MOT*MOT: goodness+sakes, what an eggnog drinker .
    CHIgoodness+sakes .
    MOTgoodness+sakes, what an eggnog drinker .
  12. eng_USA_Brown/eve20.cha, line 4028 · Eve, 2;3.
    MOTgoodness+sakes, what an eggnog drinker .
    CHIgoodness+sakes .
    MOT*MOT: goodness+sakes, what an eggnog drinker .
    CHIgoodness+sakes a eggnog drinker .
    MOTyou've drunk all of your eggnog .
  13. eng_USA_Brown/eve20.cha, line 4060 · Eve, 2;3.
    GLOyes, I'm Gloria .
    CHIyes .
    MOT*MOT: you drank an awful lot of eggnog, didn't you, that's wonderful .
    CHIxxx ?
    CHIxxx .

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. Eve eng_USA_Brown4.52
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_USA_Brown/eve20.chaEve 2;3.3,09713144.52

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. an14 · 100.0%