PHPCLANCHILDES with regular expressions

7 matches in 7 utterances

7.38 per 1,000 words of the child (CHI), in 1 of 1 transcripts (231 utterances, 949 words searched).

  1. um # I don't know . CHI · eng_USA_Brown/sarah131.cha, line 324 · Sarah 4;11
  2. I don't know how to write that . CHI · eng_USA_Brown/sarah131.cha, line 395 · Sarah 4;11
  3. (be)cause this one don't have um # a plus # see ? CHI · eng_USA_Brown/sarah131.cha, line 475 · Sarah 4;11
  4. this one don't either # so it's that one # right ? CHI · eng_USA_Brown/sarah131.cha, line 478 · Sarah 4;11
  5. no # I don't . CHI · eng_USA_Brown/sarah131.cha, line 522 · Sarah 4;11
  6. um # I don't know . CHI · eng_USA_Brown/sarah131.cha, line 583 · Sarah 4;11
  7. no # ya don't . CHI · eng_USA_Brown/sarah131.cha, line 913 · Sarah 4;11
  1. GAIyes .
    GAIwhat will you do with it ?
    CHI*CHI: um # I don't know .
    CHII have to do somethin(g) .
    MELyour scar went # your vaccination went away ?
  2. CHII made a two before .
    CHIum # four .
    CHI*CHI: I don't know how to write that .
    CHImake a line # then make a cross # then go like that ?
    MELmmhm .
  3. MELthen that's the one you're doing .
    CHIoh .
    CHI*CHI: (be)cause this one don't have um # a plus # see ?
    CHIthis one don't either # so it's that one # right ?
    MELI think so # yeah .
  4. CHIoh .
    CHI(be)cause this one don't have um # a plus # see ?
    CHI*CHI: this one don't either # so it's that one # right ?
    MELI think so # yeah .
    CHI(be)cause I was first starting on that one # then I was goin(g) on that one # then I was goin(g) on that one .
  5. CHImmhm # well # two # yeah .
    CHImmhm # I have to erase that off .
    CHI*CHI: no # I don't .
    MOTyou've been to the beach ?
    MOTyou feel it # too .
  6. CHImm # good .
    GAIwhat does it look like # Sarah ?
    CHI*CHI: um # I don't know .
    CHII forget .
    CHItomorrow I'm goin(g) the beach .
  7. CHIwhich side ya (sup)posed to go on ?
    MOTthis one .
    CHI*CHI: no # ya don't .
    CHIoh # yes ya do .
    CHIlike this ?

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_Brown7.38
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_USA_Brown/sarah131.chaSarah 4;11.13949777.38

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. don't7 · 100.0%