PHPCLANCHILDES with regular expressions

7 matches in 7 utterances

2.84 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (517 utterances, 2,466 words searched).

  1. which picture are we going to do first ? MOT · eng_british_Manchester_II/nic06a.cha, line 425 · Nicole 2;02
  2. which picture are we going to do first ? MOT · eng_british_Manchester_II/nic06a.cha, line 428 · Nicole 2;02
  3. what's this picture doing ? MOT · eng_british_Manchester_II/nic06a.cha, line 751 · Nicole 2;02
  4. we'll have to show Rachel that nice picture you did , willn't we before she goes . MOT · eng_british_Manchester_II/nic06a.cha, line 795 · Nicole 2;02
  5. xxx draw a really good picture , didn't you ? MOT · eng_british_Manchester_II/nic06a.cha, line 804 · Nicole 2;02
  6. what's the weather doing in this picture ? MOT · eng_british_Manchester_II/nic06a.cha, line 1263 · Nicole 2;02
  7. and what's in that picture ? MOT · eng_british_Manchester_II/nic06a.cha, line 1386 · Nicole 2;02
  1. MOTlet's get them out .
    MOTright .
    MOT*MOT: which picture are we going to do first ?
    MOTwhich picture are we going to do first ?
    MOTare we going to do the rainy one ?
  2. MOTright .
    MOTwhich picture are we going to do first ?
    MOT*MOT: which picture are we going to do first ?
    MOTare we going to do the rainy one ?
    CHIyeah .
  3. MOTRachel can sit and write about you and you can sit and write about Rachel .
    MOTokay .
    MOT*MOT: what's this picture doing ?
    MOTNicole ?
    MOToh found that , have you ?
  4. CHIyeah .
    MOThmm ?
    MOT*MOT: we'll have to show Rachel that nice picture you did , willn't we before she goes .
    INVwhat was that ?
    MOTxxx draw a really good picture , didn't you ?
  5. MOTwe'll have to show Rachel that nice picture you did , willn't we before she goes .
    INVwhat was that ?
    MOT*MOT: xxx draw a really good picture , didn't you ?
    MOTof a house .
    MOTdidn't you ?
  6. CHIplay Daddy .
    CHIum hide .
    MOT*MOT: what's the weather doing in this picture ?
    MOTdo you know ?
    CHIrain .
  7. MOToh there it is .
    MOTand there .
    MOT*MOT: and what's in that picture ?
    MOTwhat's that ?
    CHIcoat .

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. Nicole eng_british_Manchester_II2.84
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_british_Manchester_II/nic06a.chaNicole 2;2.122,466772.84

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. picture7 · 100.0%