PHPCLANCHILDES with regular expressions

5 matches in 5 utterances

4.75 per 1,000 words of the child (CHI), in 1 of 1 transcripts (273 utterances, 1,052 words searched).

  1. she # goes like that on the telephone . CHI · eng_USA_Brown/sarah118.cha, line 57 · Sarah 4;07
  2. y(ou) can make a elephant on it # too . CHI · eng_USA_Brown/sarah118.cha, line 627 · Sarah 4;07
  3. I'm goin(g) make a clown on mine . CHI · eng_USA_Brown/sarah118.cha, line 629 · Sarah 4;07
  4. … [//] then you have a bottom (a)n(d) ya put all the # some of the [/] on the bottom huh ? CHI · eng_USA_Brown/sarah118.cha, line 787 · Sarah 4;07
  5. just put some <&sc> [/] <&sc> [//] taper+scot [: scotch+tape] on it . CHI · eng_USA_Brown/sarah118.cha, line 917 · Sarah 4;07
  1. eng_USA_Brown/sarah118.cha, line 57 · Sarah, 4;7.17
    CHIknow what my Mother does ?
    MELwhat does she do ?
    CHI*CHI: she # goes like that on the telephone .
    MELwhat for ?
    MOThere [//] here's one slipper .
  2. eng_USA_Brown/sarah118.cha, line 627 · Sarah, 4;7.17
    CHIbottom .
    CHImake all different kind of shape out of it .
    CHI*CHI: y(ou) can make a elephant on it # too .
    CHII'm goin(g) make a clown on mine .
    CHIlet's go get my crayons .
  3. eng_USA_Brown/sarah118.cha, line 629 · Sarah, 4;7.17
    CHImake all different kind of shape out of it .
    CHIy(ou) can make a elephant on it # too .
    CHI*CHI: I'm goin(g) make a clown on mine .
    CHIlet's go get my crayons .
    MOTyou want a cup of tea ?
  4. eng_USA_Brown/sarah118.cha, line 787 · Sarah, 4;7.17
    CHIand that bended over here .
    CHIcan you make a wastebasket ?
    CHI*CHI: all the lines # <then ya> [//] then you have a bottom (a)n(d) ya put all the # some of the [/] on the bottom huh ?
    CHI(a)n(d) wrap it around ?
    CHIcan ya do that ?
  5. eng_USA_Brown/sarah118.cha, line 917 · Sarah, 4;7.17
    MELhow do you do that ?
    CHIoh easy .
    CHI*CHI: just put some <&sc> [/] <&sc> [//] taper+scot [: scotch+tape] on it .
    CHIthen make a handle .
    CHIit's so easy to do .

Matches by age

One dot per transcript: matches per 1,000 words of the child (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_Brown4.75
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_USA_Brown/sarah118.chaSarah 4;7.171,052554.75

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. on5 · 100.0%