PHPCLANCHILDES with regular expressions

7 matches in 7 utterances

7.68 per 1,000 words of the child (CHI), in 1 of 1 transcripts (285 utterances, 912 words searched).

  1. I know how you do these now . CHI · eng_USA_Brown/sarah120.cha, line 14 · Sarah 4;08
  2. now how is it goin(g) out ? CHI · eng_USA_Brown/sarah120.cha, line 223 · Sarah 4;08
  3. how (a)bout l@l ? CHI · eng_USA_Brown/sarah120.cha, line 329 · Sarah 4;08
  4. dis is how will [?] it go . CHI · eng_USA_Brown/sarah120.cha, line 420 · Sarah 4;08
  5. how you can cut him out ? CHI · eng_USA_Brown/sarah120.cha, line 449 · Sarah 4;08
  6. I know how to cut . CHI · eng_USA_Brown/sarah120.cha, line 470 · Sarah 4;08
  7. I don't know how to cut . CHI · eng_USA_Brown/sarah120.cha, line 979 · Sarah 4;08
  1. CHI*CHI: I know how you do these now .
    CHIsee ya (sup)posed to go like that .
    MOTwell # turn around .
  2. CHI# am I goin(g) out the line ?
    MELno .
    CHI*CHI: now how is it goin(g) out ?
    CHIoh it's comin(g) off .
    MELbetter be careful or you're going in [!!] the line .
  3. CHIArthur # yeah .
    CHII cut one [!!] out .
    CHI*CHI: how (a)bout l@l ?
    CHInurse is for l@l # huh ?
    MELno # n@l is for nurse .
  4. GAIwhat ?
    CHImake someone hurt themself [*] .
    CHI*CHI: dis is how will [?] it go .
    MELoops .
    CHIwhat ?
  5. CHIz@l is for zebra .
    CHIit's hard to cut the snowman out .
    CHI*CHI: how you can cut him out ?
    MELwell # do you want me to cut a little piece out like this # and then you can cut from there ?
    CHIok .
  6. MOTthey don't push out .
    CHIno .
    CHI*CHI: I know how to cut .
    CHIsometimes snowman has a pipe in his mouth .
    MELmmhm .
  7. MOTyou didn't cut it very good # did ya ?
    CHIuhuh .
    CHI*CHI: I don't know how to cut .
    CHIxxx .
    MOTwhere are you gonna put it .

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_Brown7.68
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_USA_Brown/sarah120.chaSarah 4;8.07912777.68

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. how7 · 100.0%