PHPCLANCHILDES with regular expressions

2 matches in 2 utterances

4.27 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (206 utterances, 468 words searched).

  1. dare ka naa ? %mov:"10000"_442532_444062 FAT · japanese_ishii/10000.cha, line 219 · Jun 1;00
  2. dare ka naa ? %mov:"10000"_444062_446690 FAT · japanese_ishii/10000.cha, line 220 · Jun 1;00
  1. japanese_ishii/10000.cha, line 219 · Jun, 1;0.01
    FATooi ! %mov:"10000"_440811_441635
    FATdare,, are (wa) . %mov:"10000"_441635_442532
    FAT*FAT: dare ka naa ? %mov:"10000"_442532_444062
    FATdare ka naa ? %mov:"10000"_444062_446690
    FATa, mata <yaba> [//] yabuttaa . %mov:"10000"_470772_475971
  2. japanese_ishii/10000.cha, line 220 · Jun, 1;0.01
    FATdare,, are (wa) . %mov:"10000"_441635_442532
    FATdare ka naa ? %mov:"10000"_442532_444062
    FAT*FAT: dare ka naa ? %mov:"10000"_444062_446690
    FATa, mata <yaba> [//] yabuttaa . %mov:"10000"_470772_475971
    FATmata bii@o shita [: yabutta] . %mov:"10000"_475971_477420

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_ishii4.27
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
japanese_ishii/10000.chaJun 1;0.01468224.27

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. naa2 · 100.0%