PHPCLANCHILDES with regular expressions

2 matches in 2 utterances

5.12 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (202 utterances, 391 words searched).

  1. terebi miten no . %mov:"00920"_788178_788967 FAT · japanese_ishii/00920.cha, line 346 · Jun 0;09
  2. terebi miten no . %mov:"00920"_790141_791867 FAT · japanese_ishii/00920.cha, line 350 · Jun 0;09
  1. FATkoo shun [: suru] no . %mov:"00920"_781684_784907
    FATnani (o) miteru . %mov:"00920"_784907_788178
    FAT*FAT: terebi miten no . %mov:"00920"_788178_788967
    FATmieten [: mieteiru] no ka . %mov:"00920"_788967_790141
    FATterebi miten no . %mov:"00920"_790141_791867
  2. FATterebi miten no . %mov:"00920"_788178_788967
    FATmieten [: mieteiru] no ka . %mov:"00920"_788967_790141
    FAT*FAT: terebi miten no . %mov:"00920"_790141_791867
    FATxxx . %mov:"00920"_794806_796463
    FATitchini # itchini # itchini . %mov:"00920"_796463_800699

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_ishii5.12
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
japanese_ishii/00920.chaJun 0;9.20391225.12

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. terebi2 · 100.0%