PHPCLANCHILDES with regular expressions

2 matches in 2 utterances

4.57 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (192 utterances, 438 words searched).

  1. moo nainai shoo ka . %mov:"00822"_534928_536187 FAT · japanese_ishii/00822.cha, line 194 · Jun 0;08
  2. tatchi shoo ka . %mov:"00822"_682133_684633 FAT · japanese_ishii/00822.cha, line 269 · Jun 0;08
  1. japanese_ishii/00822.cha, line 194 · Jun, 0;8.22
    FATun ? %mov:"00822"_519649_521157
    FATyoshi . %mov:"00822"_531660_534928
    FAT*FAT: moo nainai shoo ka . %mov:"00822"_534928_536187
    FATnainai shitokimashoo ka . %mov:"00822"_536187_538047
    FATnainaai . %mov:"00822"_538047_538961
  2. japanese_ishii/00822.cha, line 269 · Jun, 0;8.22
    FATe ! %mov:"00822"_673481_677069
    FATyoishoo, hai ! %mov:"00822"_677069_682133
    FAT*FAT: tatchi shoo ka . %mov:"00822"_682133_684633
    FAThai, tatchi wa ? %mov:"00822"_684633_685654
    FATtatchi wa ? %mov:"00822"_685654_687444

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. Jun japanese_ishii4.57
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
japanese_ishii/00822.chaJun 0;8.22438224.57

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. shoo2 · 100.0%