PHPCLANCHILDES with regular expressions

10 matches in 9 utterances

5.06 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (575 utterances, 1,977 words searched).

  1. Robber_Red runs very fast . MOT · eng_british_Manchester_II/ruth22a.cha, line 208 · Ruth 2;06
  2. Robber_Red runs very fast . MOT · eng_british_Manchester_II/ruth22a.cha, line 212 · Ruth 2;06
  3. is he very loud Harry_Hatman ? MOT · eng_british_Manchester_II/ruth22a.cha, line 323 · Ruth 2;06
  4. very quiet . MOT · eng_british_Manchester_II/ruth22a.cha, line 335 · Ruth 2;06
  5. that's very good . MOT · eng_british_Manchester_II/ruth22a.cha, line 373 · Ruth 2;06
  6. now you know this one very well . MOT · eng_british_Manchester_II/ruth22a.cha, line 1338 · Ruth 2;06
  7. you know that very very well . MOT · eng_british_Manchester_II/ruth22a.cha, line 1354 · Ruth 2;06
  8. you know that very very well . MOT · eng_british_Manchester_II/ruth22a.cha, line 1354 · Ruth 2;06
  9. well thank you very much . MOT · eng_british_Manchester_II/ruth22a.cha, line 1762 · Ruth 2;06
  10. that is very helpful . MOT · eng_british_Manchester_II/ruth22a.cha, line 1764 · Ruth 2;06
  1. MOTwhat does Robber_Red do ?
    MOTthat's right .
    MOT*MOT: Robber_Red runs very fast .
    INVoh right .
    MOTRobber_Red runs very fast .
  2. MOTRobber_Red runs very fast .
    INVoh right .
    MOT*MOT: Robber_Red runs very fast .
    MOTand what does +//.
    MOToh well let me put these socks on and then I'll ask you something else .
  3. CHI++ Hatman .
    MOTwhat does Harry_Hatman do ?
    MOT*MOT: is he very loud Harry_Hatman ?
    CHImmhm .
    MOTis he ?
  4. MOThe's not .
    MOTwhat is he ?
    MOT*MOT: very quiet .
    MOTdoes Harry_Hatman wear shoes ?
    CHIno .
  5. MOTyeah .
    MOThe des [: does] that .
    MOT*MOT: that's very good .
    MOTnow what does Wicked +...
    CHI++ Witch .
  6. MOTthat's Bouncy_Ben yeah .
    CHIthere .
    MOT*MOT: now you know this one very well .
    MOTwho's that ?
    CHINaughty_Nick .
  7. MOTRuth .
    MOTyou must look darling .
    MOT*MOT: you know that very very well .
    MOTthis is your favorite character .
    MOTwho's that ?
  8. CHImmhm .
    CHIme pick that up .
    MOT*MOT: well thank you very much .
    MOTthat is very helpful .
    MOTwhat're you doing now ?
  9. CHIme pick that up .
    MOTwell thank you very much .
    MOT*MOT: that is very helpful .
    MOTwhat're you doing now ?
    CHIbaby like tea , mmhm .

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. Ruth eng_british_Manchester_II5.06
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_british_Manchester_II/ruth22a.chaRuth 2;6.191,9779105.06

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. very10 · 100.0%