PHPCLANCHILDES with regular expressions

6 matches in 5 utterances

6.18 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (144 utterances, 971 words searched).

  1. now we'll put this here [% FAT starts building bridge] . FAT · bilingual_eng_french_Watkins/a02wat01.cha, line 32 · Jeremy 2;06
  2. now so we've got to build this up to the same height as that do you see o… FAT · bilingual_eng_french_Watkins/a02wat01.cha, line 47 · Jeremy 2;06
  3. now what do you want now, do you want to put your garage on top ? FAT · bilingual_eng_french_Watkins/a02wat01.cha, line 70 · Jeremy 2;06
  4. now what do you want now, do you want to put your garage on top ? FAT · bilingual_eng_french_Watkins/a02wat01.cha, line 70 · Jeremy 2;06
  5. now what we want is, <we'll take those out> [>] . FAT · bilingual_eng_french_Watkins/a02wat01.cha, line 156 · Jeremy 2;06
  6. now hang on wait a moment you want to get some more +... FAT · bilingual_eng_french_Watkins/a02wat01.cha, line 208 · Jeremy 2;06
  1. CHIno .
    FATcome on don't be silly .
    FAT*FAT: now we'll put this here [% FAT starts building bridge] .
    FATand we'll put this here .
    FATand we'll put this here .
  2. FATcan you get your train under there or not ?
    CHIyes .
    FAT*FAT: now so we've got to build this up to the same height as that do you see okay ?
    CHIxx xx one xx this .
    FATwell it's not level is it, so we've got to build this side up haven't we ?
  3. FATthat's a fantastic bridge that don't you think ?
    FATlook .
    FAT*FAT: now what do you want now, do you want to put your garage on top ?
    CHIyes .
    CHIoh !
  4. FAToh look at that, that's rather clever, I'm rather proud of that .
    FATdon't you think that's good ?
    FAT*FAT: now what we want is, <we'll take those out> [>] .
    CHIan [//] and this .
    FATlook # look look Jeremy .
  5. CHII want some xx .
    FATthat's very clever .
    FAT*FAT: now hang on wait a moment you want to get some more +...
    FATanother couple of steps here .
    FATJeremy I've got an idea, I've got an idea .

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. Jeremy bilingual_eng_french_Watkins6.18
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
bilingual_eng_french_Watkins/a02wat01.chaJeremy 2;6.27971566.18

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. now6 · 100.0%