PHPCLANCHILDES with regular expressions

7 matches in 7 utterances

3.27 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (523 utterances, 2,138 words searched).

  1. shall we put the gorilla back on ? MOT · eng_british_Manchester_II/warr03a.cha, line 107 · Warren 1;10
  2. it's a gorilla . MOT · eng_british_Manchester_II/warr03a.cha, line 536 · Warren 1;10
  3. gorilla's going to come and tickle you . MOT · eng_british_Manchester_II/warr03a.cha, line 542 · Warren 1;10
  4. gorilla . MOT · eng_british_Manchester_II/warr03a.cha, line 1557 · Warren 1;10
  5. and I think if we've got a gorilla and a cow we ought to have the zoo+keeper driving it . MOT · eng_british_Manchester_II/warr03a.cha, line 1561 · Warren 1;10
  6. oh the gorilla's waving . MOT · eng_british_Manchester_II/warr03a.cha, line 1568 · Warren 1;10
  7. where's the gorilla ? MOT · eng_british_Manchester_II/warr03a.cha, line 1578 · Warren 1;10
  1. MOTshall we make the tower taller ?
    CHIno more monkey .
    MOT*MOT: shall we put the gorilla back on ?
    CHIgorilla back on .
    MOTthere he is .
  2. MOTwhat's it called ?
    CHIoo^oo@o .
    MOT*MOT: it's a gorilla .
    CHIgorilla .
    MOToo^oo@o .
  3. CHIgorilla .
    MOToo^oo@o .
    MOT*MOT: gorilla's going to come and tickle you .
    MOTwhee .
    MOThe's scratching your nose .
  4. MOTone .
    MOTtwo .
    MOT*MOT: gorilla .
    MOTcow .
    MOTand I think if we've got a gorilla and a cow we ought to have the zoo+keeper driving it .
  5. MOTgorilla .
    MOTcow .
    MOT*MOT: and I think if we've got a gorilla and a cow we ought to have the zoo+keeper driving it .
    MOTbrumm@o .
    MOToh the gorilla's waving .
  6. MOTand I think if we've got a gorilla and a cow we ought to have the zoo+keeper driving it .
    MOTbrumm@o .
    MOT*MOT: oh the gorilla's waving .
    MOThe's saying hello Warren .
    CHIxxx .
  7. MOThe is , isn't he ?
    MOToh .
    MOT*MOT: where's the gorilla ?
    CHIhe's park .
    MOThe's on , isn't he ?

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. Warren eng_british_Manchester_II3.27
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_british_Manchester_II/warr03a.chaWarren 1;10.292,138773.27

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. gorilla7 · 100.0%