PHPCLANCHILDES with regular expressions

8 matches in 8 utterances

4.51 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (535 utterances, 1,772 words searched).

  1. let's um play with some other toys . MOT · eng_british_Manchester_II/joel32b.cha, line 192 · Joel 2;09
  2. got some what ? MOT · eng_british_Manchester_II/joel32b.cha, line 212 · Joel 2;09
  3. some shapes ? MOT · eng_british_Manchester_II/joel32b.cha, line 216 · Joel 2;09
  4. do we know some dogs ? MOT · eng_british_Manchester_II/joel32b.cha, line 254 · Joel 2;09
  5. we know some +//. MOT · eng_british_Manchester_II/joel32b.cha, line 279 · Joel 2;09
  6. can you sing some Pavarotti for us ? MOT · eng_british_Manchester_II/joel32b.cha, line 1691 · Joel 2;09
  7. you need some new ones anyway , don't you ? MOT · eng_british_Manchester_II/joel32b.cha, line 1847 · Joel 2;09
  8. get you some new ones . MOT · eng_british_Manchester_II/joel32b.cha, line 1875 · Joel 2;09
  1. INVxxx .
    MOTright .
    MOT*MOT: let's um play with some other toys .
    MOTxxx .
    MOTyou might swallow a cow .
  2. MOTwhat've you got ?
    CHIgot some shapes .
    MOT*MOT: got some what ?
    CHII 0have [*] got some shapes .
    MOTsome shapes ?
  3. MOTgot some what ?
    CHII 0have [*] got some shapes .
    MOT*MOT: some shapes ?
    MOTthey're animals .
    MOToh .
  4. MOTthey're nice , aren't they ?
    MOT<we don't know> [/] we don't know any cows , do we ?
    MOT*MOT: do we know some dogs ?
    INVoh .
    INVcows are always called Buttercup .
  5. MOTcan't understand a word you're saying .
    MOToh .
    MOT*MOT: we know some +//.
    MOTwe know a rabbit , don't we ?
    CHIta .
  6. MOTyou look like Elton_John .
    MOTxxx Pavarotti .
    MOT*MOT: can you sing some Pavarotti for us ?
    INVlook .
    INVlook .
  7. MOTyou don't normally want to wear them .
    CHIyeah .
    MOT*MOT: you need some new ones anyway , don't you ?
    CHIxxx .
    MOTdo you want me to put them on you ?
  8. MOTlook .
    MOTtoes right up there .
    MOT*MOT: get you some new ones .
    MOTwhat size were these ?
    MOTpass .

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_II4.51
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_british_Manchester_II/joel32b.chaJoel 2;9.201,772884.51

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. some8 · 100.0%