PHPCLANCHILDES with regular expressions

9 matches in 9 utterances

3.38 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (775 utterances, 2,662 words searched).

  1. it's like a big cat, isn't it? MOT · downs-flusberg/martint.cha, line 487
  2. with his big long nose? MOT · downs-flusberg/martint.cha, line 496
  3. the big ones. MOT · downs-flusberg/martint.cha, line 596
  4. where's the big ones? MOT · downs-flusberg/martint.cha, line 597
  5. no, is that a big one? MOT · downs-flusberg/martint.cha, line 600
  6. where's a big one? MOT · downs-flusberg/martint.cha, line 603
  7. here, how about a big one? MOT · downs-flusberg/martint.cha, line 605
  8. let the big one stand up. MOT · downs-flusberg/martint.cha, line 607
  9. that's a big one. MOT · downs-flusberg/martint.cha, line 865
  1. CHIxxx.
    MOTno, panthers say roar, but I don't think you know that one.
    MOT*MOT: it's like a big cat, isn't it?
    CHIyeah.
    MOTok, what else we got that you know?
  2. CHIelephant.
    MOTelephant, huh?
    MOT*MOT: with his big long nose?
    CHIxxx.
    MOTwhat color is his ears?
  3. MOTok.
    MOTmake the other two stand up first.
    MOT*MOT: the big ones.
    MOTwhere's the big ones?
    CHIright here.
  4. MOTmake the other two stand up first.
    MOTthe big ones.
    MOT*MOT: where's the big ones?
    CHIright here.
    MOTno, is that a big one?
  5. MOTwhere's the big ones?
    CHIright here.
    MOT*MOT: no, is that a big one?
    CHIyeah.
    MOTno.
  6. CHIyeah.
    MOTno.
    MOT*MOT: where's a big one?
    CHIxxx.
    MOThere, how about a big one?
  7. MOTwhere's a big one?
    CHIxxx.
    MOT*MOT: here, how about a big one?
    CHI<oh> [/?].
    MOTlet the big one stand up.
  8. MOThere, how about a big one?
    CHI<oh> [/?].
    MOT*MOT: let the big one stand up.
    CHIxxx.
    MOT<oh> [/?], you're going to do it that way?
  9. MOTthat's good.
    MOTwhoa michael.
    MOT*MOT: that's a big one.
    CHIxxx.
    MOTI don't think that's gonna work.

Matches by child

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

  1. Martint downs-flusberg3.38
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
downs-flusberg/martint.chaMartint 2,662993.38

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. big9 · 100.0%