PHPCLANCHILDES with regular expressions

5 matches in 5 utterances

2.35 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (390 utterances, 2,129 words searched).

  1. which character came over and gave jack a great big hug? MOT · autistic-flusberg/jack12.cha, line 408
  2. <jack> [/?] jack, which character came over and gave jack a great big hug and you were feeling all his fur? MOT · autistic-flusberg/jack12.cha, line 411
  3. <he did> [/?] dale gave jack a great big hug. MOT · autistic-flusberg/jack12.cha, line 767
  4. xxx a big chipmunk, was he ticklish? MOT · autistic-flusberg/jack12.cha, line 774
  5. and did goofy come over and give jack a great big hug? MOT · autistic-flusberg/jack12.cha, line 777
  1. MOTdid you see any of the characters?
    MOTjack, which character did you like?
    MOT*MOT: which character came over and gave jack a great big hug?
    CHIxxx did give us xxx.
    MOTjack, which character came +/.
  2. CHIxxx did give us xxx.
    MOTjack, which character came +/.
    MOT*MOT: <jack> [/?] jack, which character came over and gave jack a great big hug and you were feeling all his fur?
    MOTwho was that?
    MOTjoy-'isaux giving you a clue +/.
  3. MOTand who else?
    CHIxxx.
    MOT*MOT: <he did> [/?] dale gave jack a great big hug.
    CHIand he's ticklish.
    MOTand who's ticklish?
  4. MOTand who's ticklish?
    MOT<was> [/?] was dale <um> [/?] ticklish?
    MOT*MOT: xxx a big chipmunk, was he ticklish?
    CHIxxx.
    MOTand did goofy come over and give jack a great big hug?
  5. MOTxxx a big chipmunk, was he ticklish?
    CHIxxx.
    MOT*MOT: and did goofy come over and give jack a great big hug?
    CHIfunny shoes.
    MOT<oh> [/?], he had funny shoes on, didn't he?

Matches by child

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

  1. Jack autistic-flusberg2.35
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
autistic-flusberg/jack12.chaJack 2,129552.35

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. big5 · 100.0%