PHPCLANCHILDES with regular expressions

8 matches in 8 utterances

2.87 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (649 utterances, 2,790 words searched).

  1. look how funny +/. MOT · downs-flusberg/jerryt.cha, line 489
  2. I like how you keep in the lines. MOT · downs-flusberg/jerryt.cha, line 556
  3. how come you're coloring my picture? MOT · downs-flusberg/jerryt.cha, line 629
  4. look at how many there are. MOT · downs-flusberg/jerryt.cha, line 638
  5. how many are we gonna have each? MOT · downs-flusberg/jerryt.cha, line 774
  6. how many of these are we gonna have each? MOT · downs-flusberg/jerryt.cha, line 777
  7. do you know how you know whether that's a six or a nine? MOT · downs-flusberg/jerryt.cha, line 834
  8. how did you know that I had a one? MOT · downs-flusberg/jerryt.cha, line 1035
  1. MOTthey got the wrong head with the wrong body.
    MOTlookit.
    MOT*MOT: look how funny +/.
    CHIsee that?
    CHIwrong body [$0a].
  2. MOTyou're faster than I <am> [/?].
    CHIyeah.
    MOT*MOT: I like how you keep in the lines.
    MOTthat's neat.
    MOTthat's really good.
  3. MOTyou don't need to be sorry.
    MOTthat's my picture.
    MOT*MOT: how come you're coloring my picture?
    MOTthanks.
    MOTare you finished?
  4. CHIthankyou.
    CHIyou gonna turn the page [$0ux]?
    MOT*MOT: look at how many there are.
    MOT<oh> [/?] I love this one.
    CHII love this one.
  5. CHImixed up.
    CHIwhat?
    MOT*MOT: how many are we gonna have each?
    CHIare you serious?
    MOTI'm serious.
  6. CHIare you serious?
    MOTI'm serious.
    MOT*MOT: how many of these are we gonna have each?
    MOTfive?
    MOTplease don't shoot that.
  7. MOTthat's a three?
    CHIyeah, a three.
    MOT*MOT: do you know how you know whether that's a six or a nine?
    MOTyou see the line?
    CHIyeah.
  8. MOTyes I do.
    CHIthankyou.
    MOT*MOT: how did you know that I had a one?
    MOTyou have one more turn.
    CHIok.

Matches by child

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

  1. Jerryt downs-flusberg2.87
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
downs-flusberg/jerryt.chaJerryt 2,790882.87

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. how8 · 100.0%