PHPCLANCHILDES with regular expressions

16 matches in 14 utterances

8.36 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (386 utterances, 1,915 words searched).

  1. not that she looks like either of your Grandmothers , does she ? MOT · eng_british_Manchester_II/warr16a.cha, line 276 · Warren 2;03
  2. not that she looks like either of your Grandmothers , does she ? MOT · eng_british_Manchester_II/warr16a.cha, line 276 · Warren 2;03
  3. there she is there , look . MOT · eng_british_Manchester_II/warr16a.cha, line 360 · Warren 2;03
  4. is she a nice Granny ? MOT · eng_british_Manchester_II/warr16a.cha, line 364 · Warren 2;03
  5. so she is . MOT · eng_british_Manchester_II/warr16a.cha, line 456 · Warren 2;03
  6. she is on the plane . MOT · eng_british_Manchester_II/warr16a.cha, line 458 · Warren 2;03
  7. she's fainted . MOT · eng_british_Manchester_II/warr16a.cha, line 462 · Warren 2;03
  8. is she just going to sit on the floor with her feet in the air ? MOT · eng_british_Manchester_II/warr16a.cha, line 820 · Warren 2;03
  9. what's she called ? MOT · eng_british_Manchester_II/warr16a.cha, line 835 · Warren 2;03
  10. what's she called ? MOT · eng_british_Manchester_II/warr16a.cha, line 842 · Warren 2;03
  11. you don't know what she's called ? MOT · eng_british_Manchester_II/warr16a.cha, line 928 · Warren 2;03
  12. where's she going ? MOT · eng_british_Manchester_II/warr16a.cha, line 1021 · Warren 2;03
  13. is she ? MOT · eng_british_Manchester_II/warr16a.cha, line 1025 · Warren 2;03
  14. is she driving to the airport so she can get onto the plane ? MOT · eng_british_Manchester_II/warr16a.cha, line 1027 · Warren 2;03
  15. is she driving to the airport so she can get onto the plane ? MOT · eng_british_Manchester_II/warr16a.cha, line 1027 · Warren 2;03
  16. where's she taking the soft stuff ? MOT · eng_british_Manchester_II/warr16a.cha, line 1046 · Warren 2;03
  1. MOTshall Mummy add this to here ?
    MOTand Mummy'll squash it all together and then we can make Granny .
    MOT*MOT: not that she looks like either of your Grandmothers , does she ?
    MOTright .
    MOTlet's get this squashed .
  2. MOTwhoops .
    MOTher head's stuck , isn't it ?
    MOT*MOT: there she is there , look .
    MOTthere's Granny .
    MOTis she a nice Granny ?
  3. MOTthere she is there , look .
    MOTthere's Granny .
    MOT*MOT: is she a nice Granny ?
    CHIyes .
    MOTwhere are you going to put Granny ?
  4. MOTis Granny on the plane going to Malta ?
    CHIyes .
    MOT*MOT: so she is .
    MOTshe is on the plane .
    MOTwhoo .
  5. CHIyes .
    MOTso she is .
    MOT*MOT: she is on the plane .
    MOTwhoo .
    MOTshe's fainted .
  6. MOTshe is on the plane .
    MOTwhoo .
    MOT*MOT: she's fainted .
    MOTwake up , Granny .
    MOTgoing to cut out the kangaroo ?
  7. CHIthis don't [*] fit in there .
    CHIGranny on the +...
    MOT*MOT: is she just going to sit on the floor with her feet in the air ?
    CHIyes .
    CHIthat's Granny .
  8. CHIno .
    CHIthat's a lady .
    MOT*MOT: what's she called ?
    MOTwhat's the lady called ?
    CHI<this 0is [*] called> [/] this 0is [*] called Daddy .
  9. MOTwhat's the lady called ?
    CHI<this 0is [*] called> [/] this 0is [*] called Daddy .
    MOT*MOT: what's she called ?
    CHIthis 0is [*] called Mummy .
    MOTno .
  10. MOTwell +/.
    CHIdon't know .
    MOT*MOT: you don't know what she's called ?
    CHIno .
    MOToh .
  11. CHIhe's parked .
    CHIlady want to go .
    MOT*MOT: where's she going ?
    CHIMalta .
    MOTis she ?
  12. MOTwhere's she going ?
    CHIMalta .
    MOT*MOT: is she ?
    MOTis she driving to the airport so she can get onto the plane ?
    CHIno .
  13. CHIMalta .
    MOTis she ?
    MOT*MOT: is she driving to the airport so she can get onto the plane ?
    CHIno .
    CHIshe stay on the plane .
  14. CHIit's a xxx .
    CHIxxx .
    MOT*MOT: where's she taking the soft stuff ?
    CHIMalta .
    MOTto Malta ?

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_II8.36
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_british_Manchester_II/warr16a.chaWarren 2;3.081,91514168.36

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. she16 · 100.0%