PHPCLANCHILDES with regular expressions

6 matches in 6 utterances

3.28 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (595 utterances, 1,830 words searched).

  1. and some teeth . MOT · eng_british_Manchester_I/becky18a.cha, line 1873 · Becky 2;06
  2. shall we have some teeth ? MOT · eng_british_Manchester_I/becky18a.cha, line 1875 · Becky 2;06
  3. have you got any teeth ? MOT · eng_british_Manchester_I/becky18a.cha, line 1877 · Becky 2;06
  4. got some teeth . MOT · eng_british_Manchester_I/becky18a.cha, line 1881 · Becky 2;06
  5. I've got some teeth . INV · eng_british_Manchester_I/becky18a.cha, line 1885 · Becky 2;06
  6. teeth . MOT · eng_british_Manchester_I/becky18a.cha, line 1893 · Becky 2;06
  1. eng_british_Manchester_I/becky18a.cha, line 1873 · Becky, 2;6.05
    MOTlike that .
    CHIyes .
    MOT*MOT: and some teeth .
    MOTshall we have some teeth ?
    MOThave you got any teeth ?
  2. eng_british_Manchester_I/becky18a.cha, line 1875 · Becky, 2;6.05
    CHIyes .
    MOTand some teeth .
    MOT*MOT: shall we have some teeth ?
    MOThave you got any teeth ?
    MOToh yes .
  3. eng_british_Manchester_I/becky18a.cha, line 1877 · Becky, 2;6.05
    MOTand some teeth .
    MOTshall we have some teeth ?
    MOT*MOT: have you got any teeth ?
    MOToh yes .
    MOTgot some teeth .
  4. eng_british_Manchester_I/becky18a.cha, line 1881 · Becky, 2;6.05
    MOThave you got any teeth ?
    MOToh yes .
    MOT*MOT: got some teeth .
    CHIand Caroline 0has [*] get some teeth .
    INVI've got some teeth .
  5. eng_british_Manchester_I/becky18a.cha, line 1885 · Becky, 2;6.05
    MOTgot some teeth .
    CHIand Caroline 0has [*] get some teeth .
    INV*INV: I've got some teeth .
    INVyes .
    CHIno .
  6. eng_british_Manchester_I/becky18a.cha, line 1893 · Becky, 2;6.05
    CHIno .
    CHIwhere's some +...
    MOT*MOT: teeth .
    MOTnow .
    MOTyou need some eyes , don't you ?

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. Becky eng_british_Manchester_I3.28
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_british_Manchester_I/becky18a.chaBecky 2;6.051,830663.28

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. teeth6 · 100.0%