PHPCLANCHILDES with regular expressions

8 matches in 8 utterances

6.58 per 1,000 words of the child (CHI), in 1 of 1 transcripts (307 utterances, 1,215 words searched).

  1. alright . CHI · eng_USA_Brown/sarah113.cha, line 182
  2. alright . CHI · eng_USA_Brown/sarah113.cha, line 346
  3. alright . CHI · eng_USA_Brown/sarah113.cha, line 664
  4. alright . CHI · eng_USA_Brown/sarah113.cha, line 1011
  5. alright . CHI · eng_USA_Brown/sarah113.cha, line 1024
  6. alright . CHI · eng_USA_Brown/sarah113.cha, line 1249
  7. alright . CHI · eng_USA_Brown/sarah113.cha, line 1265
  8. first you draw the &tee [//] tree # alright ? CHI · eng_USA_Brown/sarah113.cha, line 1267
  1. eng_USA_Brown/sarah113.cha, line 182
    CHIwant me make # a cow (a)n(d) a horse in a barn ?
    MELyeah .
    CHI*CHI: alright .
    CHIlike dat .
    CHIhere's de barn .
  2. eng_USA_Brown/sarah113.cha, line 346
    CHIo:h # now want me make the barn ?
    MELright .
    CHI*CHI: alright .
    CHIit's like de a@l # huh ?
    MELuhhuh .
  3. eng_USA_Brown/sarah113.cha, line 664
    CHIwant me make those rip too ?
    MELuhhuh .
    CHI*CHI: alright .
    CHII gonna copy it .
    MELok .
  4. eng_USA_Brown/sarah113.cha, line 1011
    MELmmhm .
    MELcan you write it ?
    CHI*CHI: alright .
    CHIwant me to write car ?
    MELmmhm .
  5. eng_USA_Brown/sarah113.cha, line 1024
    CHIwant me to have it with some glass over it ?
    MELyeah .
    CHI*CHI: alright .
    CHIsee # dis is how you make some go now # like that .
    CHIwant me make it red ?
  6. eng_USA_Brown/sarah113.cha, line 1249
    CHIlet me make a tree now ?
    MELmmhm .
    CHI*CHI: alright .
    CHIthey fly up in there # huh ?
    CHInow # there .
  7. eng_USA_Brown/sarah113.cha, line 1265
    CHIlet me draw another one ?
    MELmmhm .
    CHI*CHI: alright .
    CHIfirst you draw the &tee [//] tree # alright ?
    MELok .
  8. eng_USA_Brown/sarah113.cha, line 1267
    MELmmhm .
    CHIalright .
    CHI*CHI: first you draw the &tee [//] tree # alright ?
    MELok .
    MELa different order this time # huh ?

Matches by child

Matches per 1,000 words, all transcripts of each child together, highest first.

  1. Sarah eng_USA_Brown6.58
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_USA_Brown/sarah113.chaSarah 1,215886.58

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. alright8 · 100.0%