PHPCLANCHILDES with regular expressions

9 matches in 9 utterances

6.39 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (397 utterances, 1,409 words searched).

  1. who's on it ? INV · eng_british_Manchester_II/joel08a.cha, line 415 · Joel 2;01
  2. who's on the front ? MOT · eng_british_Manchester_II/joel08a.cha, line 433 · Joel 2;01
  3. who's that ? MOT · eng_british_Manchester_II/joel08a.cha, line 439 · Joel 2;01
  4. who's that ? INV · eng_british_Manchester_II/joel08a.cha, line 472 · Joel 2;01
  5. who's that then ? INV · eng_british_Manchester_II/joel08a.cha, line 482 · Joel 2;01
  6. but who's this here ? INV · eng_british_Manchester_II/joel08a.cha, line 486 · Joel 2;01
  7. who's that ? MOT · eng_british_Manchester_II/joel08a.cha, line 750 · Joel 2;01
  8. who's that then ? MOT · eng_british_Manchester_II/joel08a.cha, line 1023 · Joel 2;01
  9. <who's> [<] that then ? MOT · eng_british_Manchester_II/joel08a.cha, line 1033 · Joel 2;01
  1. MOTxxx .
    MOTwho is it ?
    INV*INV: who's on it ?
    CHIxxx John .
    INVpardon ?
  2. MOTyeah .
    INVxxx .
    MOT*MOT: who's on the front ?
    MOTthat's not the front .
    MOThave a look at the front .
  3. MOTthat's not the front .
    MOThave a look at the front .
    MOT*MOT: who's that ?
    CHITilly 0and Tiny .
    MOTit's not Tilly Tiny xxx .
  4. INVat the top .
    INVyes .
    INV*INV: who's that ?
    CHITilly_Tiny .
    INVno .
  5. INVit's Rosie and Jim .
    INVI know they all look a little bit alike .
    INV*INV: who's that then ?
    INVthat's John .
    INVbut who's this here ?
  6. INVwho's that then ?
    INVthat's John .
    INV*INV: but who's this here ?
    INVyou like John , don't you ?
    MOThas he got a beard ?
  7. CHIxxx .
    MOTwhat's happened to baby ?
    MOT*MOT: who's that ?
    CHIthe seal .
    MOTseal .
  8. MOTsay hello .
    MOTwhat was that for ?
    MOT*MOT: who's that then ?
    MOTwho is it ?
    CHIno .
  9. MOTno .
    MOTright .
    MOT*MOT: <who's> [<] that then ?
    CHIno .
    MOTare you just in one of those moods today ?

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. Joel eng_british_Manchester_II6.39
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_british_Manchester_II/joel08a.chaJoel 2;1.101,409996.39

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. who's9 · 100.0%