PHPCLANCHILDES with regular expressions

8 matches in 8 utterances

5.42 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (424 utterances, 1,476 words searched).

  1. huh he's working . MOT · bilingual_eng_Genesee/oli13b11m.cha, line 54 · Olivier 1;11
  2. huh ? MOT · bilingual_eng_Genesee/oli13b11m.cha, line 329 · Olivier 1;11
  3. look at these worms, huh ? MOT · bilingual_eng_Genesee/oli13b11m.cha, line 389 · Olivier 1;11
  4. huh ? MOT · bilingual_eng_Genesee/oli13b11m.cha, line 465 · Olivier 1;11
  5. huh ? MOT · bilingual_eng_Genesee/oli13b11m.cha, line 549 · Olivier 1;11
  6. huh ? MOT · bilingual_eng_Genesee/oli13b11m.cha, line 681 · Olivier 1;11
  7. huh ? MOT · bilingual_eng_Genesee/oli13b11m.cha, line 1088 · Olivier 1;11
  8. huh ? MOT · bilingual_eng_Genesee/oli13b11m.cha, line 1103 · Olivier 1;11
  1. MOTis that a man ?
    MOTis that a man ?
    MOT*MOT: huh he's working .
    MOTis the man working ?
    MOTlook at that .
  2. MOTa wriggly worm !
    MOT0 aux you have something stuck in your shoe ?
    MOT*MOT: huh ?
    MOTis it stuck in your shoe ?
    MOTwhat is that ?
  3. MOTgood job !
    EXPthat's great !
    MOT*MOT: look at these worms, huh ?
    MOTyou've got worms in your shirt .
    MOTOlivier # why do you have worms in your shirt ?
  4. MOTthe men are working !
    MOTthey're putting # rocks <in the> [//] # # in their big buckets !
    MOT*MOT: huh ?
    MOT<look at the> [/] look at the big rocks .
    MOTxxx climbs up up up # # the ladder and then goes into the big big big container .
  5. CHIno !
    MOTwhere's the choochoo train ?
    MOT*MOT: huh ?
    MOTwhere's that ?
    MOTcan you find Mommy the choochoo train ?
  6. MOTtractor .
    MOTthat's a dumper !
    MOT*MOT: huh ?
    MOTit's called a dumper .
    MOTthis is the dumper # cause [: because] it dumps things on the floor !
  7. MOTthere's another horsy .
    MOTthere's two horsies .
    MOT*MOT: huh ?
    MOTthere's two horsies .
    MOT0.
  8. MOTone # two # three !
    CHIhow many ?
    MOT*MOT: huh ?
    MOTdo we have three horses ?
    MOTone horse # # two horses # # three horses !

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. Olivier bilingual_eng_Genesee5.42
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
bilingual_eng_Genesee/oli13b11m.chaOlivier 1;11.151,476885.42

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. huh8 · 100.0%