PHPCLANCHILDES with regular expressions

10 matches in 10 utterances

4.88 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (534 utterances, 2,049 words searched).

  1. those are dolly's clothes . INV · eng_british_Manchester_II/nic05b.cha, line 53 · Nicole 2;02
  2. and dolly's hat . INV · eng_british_Manchester_II/nic05b.cha, line 57 · Nicole 2;02
  3. hasn't this dolly got a nice +/. MOT · eng_british_Manchester_II/nic05b.cha, line 613 · Nicole 2;02
  4. is she a nice dolly ? MOT · eng_british_Manchester_II/nic05b.cha, line 638 · Nicole 2;02
  5. look for dolly's trousers . MOT · eng_british_Manchester_II/nic05b.cha, line 658 · Nicole 2;02
  6. look for dolly's trousers . MOT · eng_british_Manchester_II/nic05b.cha, line 662 · Nicole 2;02
  7. oh dolly's dress is stuck to you . MOT · eng_british_Manchester_II/nic05b.cha, line 720 · Nicole 2;02
  8. shall we make a burger up for dolly ? MOT · eng_british_Manchester_II/nic05b.cha, line 920 · Nicole 2;02
  9. do you think dolly would like a burger ? MOT · eng_british_Manchester_II/nic05b.cha, line 922 · Nicole 2;02
  10. then you can feed it to dolly , can't you ? MOT · eng_british_Manchester_II/nic05b.cha, line 967 · Nicole 2;02
  1. CHIyeah .
    MOTwhoops .
    INV*INV: those are dolly's clothes .
    MOTyeah .
    INVand dolly's hat .
  2. INVthose are dolly's clothes .
    MOTyeah .
    INV*INV: and dolly's hat .
    MOTlook what I can see .
    CHIhelicopter .
  3. MOTmmhm .
    CHImmhm .
    MOT*MOT: hasn't this dolly got a nice +/.
    CHI++ hat .
    MOThat .
  4. MOTdoesn't she look smart ?
    MOThuh ?
    MOT*MOT: is she a nice dolly ?
    MOTyeah ?
    CHIbobble .
  5. INVjust behind you .
    MOTlet's look for her trousers, Nicole .
    MOT*MOT: look for dolly's trousers .
    MOTyou'll have to sit up properly .
    MOTlook for dolly's trousers .
  6. MOTlook for dolly's trousers .
    MOTyou'll have to sit up properly .
    MOT*MOT: look for dolly's trousers .
    CHIno way .
    CHIno way .
  7. CHIno , Mummy .
    CHIMummy .
    MOT*MOT: oh dolly's dress is stuck to you .
    CHIMummy .
    CHIMummy .
  8. MOTwe can't hear you with that piece of cheese stuck in your mouth .
    MOTshall we make a burger ?
    MOT*MOT: shall we make a burger up for dolly ?
    MOTdo you think dolly would like a burger ?
    MOTthere .
  9. MOTshall we make a burger ?
    MOTshall we make a burger up for dolly ?
    MOT*MOT: do you think dolly would like a burger ?
    MOTthere .
    MOTgot a bun .
  10. MOTxxx .
    MOTare you going to put the cheese on top of the meat for Mummy ?
    MOT*MOT: then you can feed it to dolly , can't you ?
    MOTmaybe Co_co would like some burger .
    MOTdo you think ?

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_II4.88
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_british_Manchester_II/nic05b.chaNicole 2;2.052,04910104.88

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. dolly10 · 100.0%