PHPCLANCHILDES with regular expressions

7 matches in 7 utterances

4.74 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. is the man working ? MOT · bilingual_eng_Genesee/oli13b11m.cha, line 56 · Olivier 1;11
  3. see the men they're working ? MOT · bilingual_eng_Genesee/oli13b11m.cha, line 454 · Olivier 1;11
  4. are the men working, honey ? MOT · bilingual_eng_Genesee/oli13b11m.cha, line 456 · Olivier 1;11
  5. the men are working ! MOT · bilingual_eng_Genesee/oli13b11m.cha, line 461 · Olivier 1;11
  6. are the men working ? MOT · bilingual_eng_Genesee/oli13b11m.cha, line 632 · Olivier 1;11
  7. yeah, the men are working . MOT · bilingual_eng_Genesee/oli13b11m.cha, line 637 · 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. MOTis that a man ?
    MOThuh he's working .
    MOT*MOT: is the man working ?
    MOTlook at that .
    MOTthat's a man's hat .
  3. MOTxxx .
    MOT0aux you wanna [: want to] do it like # the men are doing ?
    MOT*MOT: see the men they're working ?
    MOTare the men working, honey ?
    CHIyy xxx .
  4. MOT0aux you wanna [: want to] do it like # the men are doing ?
    MOTsee the men they're working ?
    MOT*MOT: are the men working, honey ?
    CHIyy xxx .
    MOTthe men are working !
  5. MOTare the men working, honey ?
    CHIyy xxx .
    MOT*MOT: the men are working !
    MOTthey're putting # rocks <in the> [//] # # in their big buckets !
    MOThuh ?
  6. CHImen ?
    MOTmen .
    MOT*MOT: are the men working ?
    CHImen men work working ?
    MOTyeah, the men are working .
  7. MOTare the men working ?
    CHImen men work working ?
    MOT*MOT: yeah, the men are working .
    MOTthey're # carrying the rocks .
    CHIuh # y [: il] fait dodo ?

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_Genesee4.74
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
bilingual_eng_Genesee/oli13b11m.chaOlivier 1;11.151,476774.74

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. working7 · 100.0%