PHPCLANCHILDES with regular expressions

6 matches in 6 utterances

3.92 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (245 utterances, 1,532 words searched).

  1. I don't know how we would have finished building this house if you kept sleeping . MOT · bilingual_eng_Genesee/oli33b06m.cha, line 361 · Olivier 3;06
  2. no you'll never be able to blow hard enough to blow this house down . MOT · bilingual_eng_Genesee/oli33b06m.cha, line 417 · Olivier 3;06
  3. but this a super duper +... MOT · bilingual_eng_Genesee/oli33b06m.cha, line 656 · Olivier 3;06
  4. you go like this . MOT · bilingual_eng_Genesee/oli33b06m.cha, line 895 · Olivier 3;06
  5. xxx this to fly anyway . MOT · bilingual_eng_Genesee/oli33b06m.cha, line 974 · Olivier 3;06
  6. I need this piece here . MOT · bilingual_eng_Genesee/oli33b06m.cha, line 1035 · Olivier 3;06
  1. MOTyou're awake now !
    MOTit's a good thing .
    MOT*MOT: I don't know how we would have finished building this house if you kept sleeping .
    MOToh you're asleep again !
    CHI0.
  2. MOTthe big bad wolf blew as hard as he could but he couldn't blow it down because it was made of brick .
    CHI0.
    MOT*MOT: no you'll never be able to blow hard enough to blow this house down .
    CHI0.
    MOToh nope <that'll blow a> [/] that'll blow a straw house down or [/] or a wooden house but it won't blow down a brick house .
  3. MOTyeah you already did that .
    CHIyeah i know .
    MOT*MOT: but this a super duper +...
    CHIyy <ta maison juste> [//] ta maison s'en vole .
    MOTahh it can't it's a super duper .
  4. MOTnow we can build our airplane .
    MOTthere so we just look at the picture here and then we put it together see ?
    MOT*MOT: you go like this .
    CHIyyy .
    MOTno we have a visor .
  5. MOTwhere's the airplane ?
    CHIxxx .
    MOT*MOT: xxx this to fly anyway .
    MOTeh ?
    CHIMommy what she doing Johanne ?
  6. MOTyeah his hands are on .
    CHIyes .
    MOT*MOT: I need this piece here .
    CHIah !
    MOTdid you find something ?

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_Genesee3.92
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
bilingual_eng_Genesee/oli33b06m.chaOlivier 3;06.091,532663.92

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. this6 · 100.0%