PHPCLANCHILDES with regular expressions

10 matches in 10 utterances

8.89 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (287 utterances, 1,125 words searched).

  1. are you ready ? MOT · eng_british_Manchester_II/liz27a.cha, line 66 · Liz 2;08
  2. are you ready ? MOT · eng_british_Manchester_II/liz27a.cha, line 74 · Liz 2;08
  3. are you pulling funny faces for Anna ? MOT · eng_british_Manchester_II/liz27a.cha, line 140 · Liz 2;08
  4. are you a cheeky monkey ? MOT · eng_british_Manchester_II/liz27a.cha, line 160 · Liz 2;08
  5. are we using all the colors or just one ? MOT · eng_british_Manchester_II/liz27a.cha, line 249 · Liz 2;08
  6. we're going on top now , are we ? MOT · eng_british_Manchester_II/liz27a.cha, line 282 · Liz 2;08
  7. which ones are having something on top ? MOT · eng_british_Manchester_II/liz27a.cha, line 285 · Liz 2;08
  8. you're going to wobble off , are you ? MOT · eng_british_Manchester_II/liz27a.cha, line 501 · Liz 2;08
  9. are you gonna [: going to] put the eyes on mine for me ? MOT · eng_british_Manchester_II/liz27a.cha, line 737 · Liz 2;08
  10. I'm afraid these felt tips are a bit of a dead loss , aren't they when it comes to lids . MOT · eng_british_Manchester_II/liz27a.cha, line 897 · Liz 2;08
  1. MOToh: nearly .
    MOTstuck to the book .
    MOT*MOT: are you ready ?
    MOTready ?
    MOToh: .
  2. MOToh: .
    CHIit's stuck by my potty .
    MOT*MOT: are you ready ?
    CHIyeah .
    CHIthat nearly bump [*] my elbow .
  3. MOTwhat ?
    MOTwhat ?
    MOT*MOT: are you pulling funny faces for Anna ?
    INVwhat a funny face .
    INVyou do look silly .
  4. INVit certainly is .
    MOTwww .
    MOT*MOT: are you a cheeky monkey ?
    CHIcan I sit on this table ?
    MOTum I think so but just be careful .
  5. MOTa shape .
    MOToh: .
    MOT*MOT: are we using all the colors or just one ?
    CHIjust two .
    MOTokay .
  6. CHIone on that one .
    MOToh right .
    MOT*MOT: we're going on top now , are we ?
    MOTwhich ones are having something on top ?
    MOTthese ones ?
  7. MOToh right .
    MOTwe're going on top now , are we ?
    MOT*MOT: which ones are having something on top ?
    MOTthese ones ?
    MOToh: .
  8. CHII going to xxx .
    CHII 0am [*] going to wibble@wp .
    MOT*MOT: you're going to wobble off , are you ?
    MOTwe'll have to get you some more paper soon .
    MOTit's getting full , isn't it ?
  9. MOTyou're giving yours some eyes , aren't you ?
    MOToh that's nice .
    MOT*MOT: are you gonna [: going to] put the eyes on mine for me ?
    MOToh that one's got big eyes , hasn't it ?
    MOToh: .
  10. MOTthere it is .
    CHIyeah .
    MOT*MOT: I'm afraid these felt tips are a bit of a dead loss , aren't they when it comes to lids .
    CHIlook .
    MOTwhat's that ?

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. Liz eng_british_Manchester_II8.89
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_british_Manchester_II/liz27a.chaLiz 2;8.141,12510108.89

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. are10 · 100.0%