PHPCLANCHILDES with regular expressions

12 matches in 12 utterances

20.48 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (252 utterances, 586 words searched).

  1. dore ga jaajaa . %mov:"10405"_63888_65585 FAT · japanese_ishii/10405.cha, line 68 · Jun 1;04
  2. densha (wa) dore ? %mov:"10405"_207933_208698 FAT · japanese_ishii/10405.cha, line 187 · Jun 1;04
  3. densha (wa) dore,, densha (wa) . FAT · japanese_ishii/10405.cha, line 190 · Jun 1;04
  4. buu uu uu@o tte dore ? FAT · japanese_ishii/10405.cha, line 245 · Jun 1;04
  5. dore . %mov:"10405"_391075_391615 FAT · japanese_ishii/10405.cha, line 317 · Jun 1;04
  6. piyopiyopiyo@o (wa) dore ? %mov:"10405"_450848_452512 FAT · japanese_ishii/10405.cha, line 349 · Jun 1;04
  7. <kawaii> [>] no (wa) dore ? %mov:"10405"_452512_455630 FAT · japanese_ishii/10405.cha, line 351 · Jun 1;04
  8. dore ga wanwan ? %mov:"10405"_514657_515702 FAT · japanese_ishii/10405.cha, line 410 · Jun 1;04
  9. dore ga . %mov:"10405"_536335_536838 FAT · japanese_ishii/10405.cha, line 420 · Jun 1;04
  10. dore ga . %mov:"10405"_538391_539093 FAT · japanese_ishii/10405.cha, line 423 · Jun 1;04
  11. dore ga wanwan ? %mov:"10405"_539687_540536 FAT · japanese_ishii/10405.cha, line 425 · Jun 1;04
  12. dore ? %mov:"10405"_570264_570854 FAT · japanese_ishii/10405.cha, line 440 · Jun 1;04
  1. CHIdyaadya . %mov:"10405"_61939_62693
    FATjaajaa ? %mov:"10405"_62693_63888
    FAT*FAT: dore ga jaajaa . %mov:"10405"_63888_65585
    CHIbuua ? %mov:"10405"_65585_67001
    FATbuuabuua, kotchi muke ya [: da] . %mov:"10405"_67001_68479
  2. CHIdaada . %mov:"10405"_206512_207199
    FATdensha ? %mov:"10405"_207199_207933
    FAT*FAT: densha (wa) dore ? %mov:"10405"_207933_208698
    CHIaa ? %mov:"10405"_208698_213104
    FATdensha (wa) dore,, densha (wa) .
  3. FATdensha (wa) dore ? %mov:"10405"_207933_208698
    CHIaa ? %mov:"10405"_208698_213104
    FAT*FAT: densha (wa) dore,, densha (wa) .
    CHIae ? %mov:"10405"_214360_215022
    FATa ! %mov:"10405"_215022_215657
  4. CHIaata . %mov:"10405"_280742_281606
    CHIaa aata . %mov:"10405"_281606_283458
    FAT*FAT: buu uu uu@o tte dore ?
    CHIyeya . %mov:"10405"_288582_290972
    CHIawaabuu . %mov:"10405"_290972_293314
  5. FATbuua ya [: da] ne [<] . %mov:"10405"_385410_387511
    CHIee . %mov:"10405"_387511_391075
    FAT*FAT: dore . %mov:"10405"_391075_391615
    CHIee . %mov:"10405"_391615_393488
    CHIxxx . %mov:"10405"_393488_396305
  6. CHIwaawaa . %mov:"10405"_447125_448979
    CHIwaawaa . %mov:"10405"_448979_450848
    FAT*FAT: piyopiyopiyo@o (wa) dore ? %mov:"10405"_450848_452512
    FAT<kawaii> [>] no (wa) dore ? %mov:"10405"_452512_455630
    CHIee [<] . %mov:"10405"_452512_455630
  7. CHIwaawaa . %mov:"10405"_448979_450848
    FATpiyopiyopiyo@o (wa) dore ? %mov:"10405"_450848_452512
    FAT*FAT: <kawaii> [>] no (wa) dore ? %mov:"10405"_452512_455630
    CHIee [<] . %mov:"10405"_452512_455630
    FATkore ya [: da],, <piyopiyo@o> [>] . %mov:"10405"_455630_459416
  8. FATxxx yoisho . %mov:"10405"_509648_510758
    FATuun ? %mov:"10405"_510758_514657
    FAT*FAT: dore ga wanwan ? %mov:"10405"_514657_515702
    CHIdaada . %mov:"10405"_515702_522208
    FATe ? %mov:"10405"_522208_522967
  9. CHIaata . %mov:"10405"_532785_535727
    FATaa shita . %mov:"10405"_535727_536335
    FAT*FAT: dore ga . %mov:"10405"_536335_536838
    CHIxxx . %mov:"10405"_536838_537415
    CHIwaawa . %mov:"10405"_537286_538391
  10. CHIxxx . %mov:"10405"_536838_537415
    CHIwaawa . %mov:"10405"_537286_538391
    FAT*FAT: dore ga . %mov:"10405"_538391_539093
    CHIwaawa . %mov:"10405"_539093_539687
    FATdore ga wanwan ? %mov:"10405"_539687_540536
  11. FATdore ga . %mov:"10405"_538391_539093
    CHIwaawa . %mov:"10405"_539093_539687
    FAT*FAT: dore ga wanwan ? %mov:"10405"_539687_540536
    CHIapuu . %mov:"10405"_540536_546829
    CHIxxx . %mov:"10405"_546829_548387
  12. CHIwaawaa . %mov:"10405"_567001_567873
    CHItyatya . %mov:"10405"_567873_570264
    FAT*FAT: dore ? %mov:"10405"_570264_570854
    CHIxxx . %mov:"10405"_570854_572989
    CHIuu uubuugo ? %mov:"10405"_572989_574957

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_ishii20.48
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
japanese_ishii/10405.chaJun 1;4.05586121220.48

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. dore12 · 100.0%