PHPCLANCHILDES with regular expressions

7 matches in 7 utterances

3.52 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (591 utterances, 1,988 words searched).

  1. do you want to crayon in Noddy ? MOT · eng_british_Manchester_I/becky02a.cha, line 1344 · Becky 2;00
  2. there's Noddy . MOT · eng_british_Manchester_I/becky02a.cha, line 1672 · Becky 2;00
  3. and look at Noddy . MOT · eng_british_Manchester_I/becky02a.cha, line 1782 · Becky 2;00
  4. Noddy looks as though he's going to stand on his head . MOT · eng_british_Manchester_I/becky02a.cha, line 1784 · Becky 2;00
  5. Noddy's in bed . MOT · eng_british_Manchester_I/becky02a.cha, line 1864 · Becky 2;00
  6. night+night Noddy . MOT · eng_british_Manchester_I/becky02a.cha, line 1884 · Becky 2;00
  7. and Noddy can have some brown xxx . MOT · eng_british_Manchester_I/becky02a.cha, line 2035 · Becky 2;00
  1. CHIcrayons .
    CHIxxx .
    MOT*MOT: do you want to crayon in Noddy ?
    CHIyeah .
    CHIoh .
  2. MOTlet's see what else there is .
    MOToh there's a good one, look .
    MOT*MOT: there's Noddy .
    CHINoddy .
    CHIxxx .
  3. MOThe's standing on his arms .
    CHIxxx .
    MOT*MOT: and look at Noddy .
    MOTNoddy looks as though he's going to stand on his head .
    MOTdoesn't he ?
  4. CHIxxx .
    MOTand look at Noddy .
    MOT*MOT: Noddy looks as though he's going to stand on his head .
    MOTdoesn't he ?
    CHIyes .
  5. MOTyou've got a good memory, haven't you ?
    INVwww .
    MOT*MOT: Noddy's in bed .
    MOThe's got his eyes closed .
    MOTcan you close your eyes ?
  6. MOTwe say night+night .
    CHInight+night .
    MOT*MOT: night+night Noddy .
    CHInight+night Noddy .
    CHIteddy .
  7. MOTthere's no more beards there .
    MOTthere .
    MOT*MOT: and Noddy can have some brown xxx .
    MOTthere we go .
    CHIxxx .

Matches by age

One dot per transcript: matches per 1,000 words of everyone but 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. Becky eng_british_Manchester_I3.52
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_british_Manchester_I/becky02a.chaBecky 2;0.141,988773.52

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. noddy7 · 100.0%