PHPCLANCHILDES with regular expressions

11 matches in 11 utterances

11.76 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (383 utterances, 935 words searched).

  1. aa aa, dare ga yabutta n [: no] ? %mov:"20017"_51420_52885 FAT · japanese_ishii/20017.cha, line 47 · Jun 2;00
  2. dore ga . %mov:"20017"_77134_78083 FAT · japanese_ishii/20017.cha, line 66 · Jun 2;00
  3. jiijii [= writing] [<] dare ga kaitaa ? %mov:"20017"_223371_226228 FAT · japanese_ishii/20017.cha, line 163 · Jun 2;00
  4. Jun ga kaita n ? %mov:"20017"_226228_229304 FAT · japanese_ishii/20017.cha, line 164 · Jun 2;00
  5. zaa@o mizu ga deteru ne . %mov:"20017"_295568_297003 FAT · japanese_ishii/20017.cha, line 204 · Jun 2;00
  6. omizu ga deteru nee . %mov:"20017"_298157_299779 FAT · japanese_ishii/20017.cha, line 206 · Jun 2;00
  7. omizu ga deteru nee . %mov:"20017"_299779_305540 FAT · japanese_ishii/20017.cha, line 208 · Jun 2;00
  8. nani ga . %mov:"20017"_488578_489424 FAT · japanese_ishii/20017.cha, line 320 · Jun 2;00
  9. nani ga nai ? %mov:"20017"_490161_491356 FAT · japanese_ishii/20017.cha, line 322 · Jun 2;00
  10. dore ga kowai no ? %mov:"20017"_624177_625647 FAT · japanese_ishii/20017.cha, line 390 · Jun 2;00
  11. nani ga kowai ka . %mov:"20017"_659313_662760 FAT · japanese_ishii/20017.cha, line 408 · Jun 2;00
  1. FATbiyanbiyan@o . %mov:"20017"_49833_50503
    CHIa aa aa . %mov:"20017"_50503_51420
    FAT*FAT: aa aa, dare ga yabutta n [: no] ? %mov:"20017"_51420_52885
    CHIJun . %mov:"20017"_52885_53629
    FATJun ikan nee . %mov:"20017"_53629_55675
  2. FATun . %mov:"20017"_73425_75319
    CHIjaa . %mov:"20017"_75319_77134
    FAT*FAT: dore ga . %mov:"20017"_77134_78083
    CHIhora . %mov:"20017"_78083_78506
    FATa, zaa@o omizu no naka ya ne . %mov:"20017"_78506_80050
  3. FATe [<] ? %mov:"20017"_219231_223371
    CHIjiijii xxx [>] . %mov:"20017"_223371_226228
    FAT*FAT: jiijii [= writing] [<] dare ga kaitaa ? %mov:"20017"_223371_226228
    FATJun ga kaita n ? %mov:"20017"_226228_229304
    FATn ? %mov:"20017"_229304_231973
  4. CHIjiijii xxx [>] . %mov:"20017"_223371_226228
    FATjiijii [= writing] [<] dare ga kaitaa ? %mov:"20017"_223371_226228
    FAT*FAT: Jun ga kaita n ? %mov:"20017"_226228_229304
    FATn ? %mov:"20017"_229304_231973
    FATgohon ni kaita ra dame desu yo . %mov:"20017"_231973_234972
  5. FATun . %mov:"20017"_294096_294603
    CHIjaa hora . %mov:"20017"_294603_295568
    FAT*FAT: zaa@o mizu ga deteru ne . %mov:"20017"_295568_297003
    CHIn ? %mov:"20017"_297003_298157
    FATomizu ga deteru nee . %mov:"20017"_298157_299779
  6. FATzaa@o mizu ga deteru ne . %mov:"20017"_295568_297003
    CHIn ? %mov:"20017"_297003_298157
    FAT*FAT: omizu ga deteru nee . %mov:"20017"_298157_299779
    FATomizu ga deteru nee . %mov:"20017"_299779_305540
    CHIn aye [: are] . %mov:"20017"_305540_310166
  7. CHIn ? %mov:"20017"_297003_298157
    FATomizu ga deteru nee . %mov:"20017"_298157_299779
    FAT*FAT: omizu ga deteru nee . %mov:"20017"_299779_305540
    CHIn aye [: are] . %mov:"20017"_305540_310166
    CHIhoewa ? %mov:"20017"_310166_315023
  8. FATminna neechan ka ? %mov:"20017"_486809_487852
    CHIneu wa . %mov:"20017"_487852_488578
    FAT*FAT: nani ga . %mov:"20017"_488578_489424
    CHInai wa . %mov:"20017"_489424_490161
    FATnani ga nai ? %mov:"20017"_490161_491356
  9. FATnani ga . %mov:"20017"_488578_489424
    CHInai wa . %mov:"20017"_489424_490161
    FAT*FAT: nani ga nai ? %mov:"20017"_490161_491356
    CHIeesha . %mov:"20017"_491356_493095
    CHIeechan [>] . %mov:"20017"_493095_495701
  10. FATbyuwan@o ashi aru ka ? %mov:"20017"_614297_617654
    CHIkowai yoo . %mov:"20017"_617654_624177
    FAT*FAT: dore ga kowai no ? %mov:"20017"_624177_625647
    CHIxxx . %mov:"20017"_625647_626839
    FATdore . %mov:"20017"_626839_627402
  11. CHIkowa . %mov:"20017"_655927_658399
    FATkowakunai . %mov:"20017"_658399_659313
    FAT*FAT: nani ga kowai ka . %mov:"20017"_659313_662760
    CHIaye . %mov:"20017"_662760_663649
    FATare kowai ka . %mov:"20017"_663649_664521

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_ishii11.76
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
japanese_ishii/20017.chaJun 2;0.17935111111.76

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. ga11 · 100.0%