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. a, sore chiisai no . %mov:"20017"_94241_95525 FAT · japanese_ishii/20017.cha, line 74 · Jun 2;00
  2. sore nan daro . %mov:"20017"_217844_219231 FAT · japanese_ishii/20017.cha, line 159 · Jun 2;00
  3. a, sore buun@o . %mov:"20017"_263594_265033 FAT · japanese_ishii/20017.cha, line 178 · Jun 2;00
  4. Jun sore . %mov:"20017"_367231_367931 FAT · japanese_ishii/20017.cha, line 245 · Jun 2;00
  5. sore mo Jun . %mov:"20017"_371164_372303 FAT · japanese_ishii/20017.cha, line 248 · Jun 2;00
  6. kankankan@o yaro,, sore ? %mov:"20017"_457953_460070 FAT · japanese_ishii/20017.cha, line 301 · Jun 2;00
  7. a, sore okuchi . %mov:"20017"_573013_576778 FAT · japanese_ishii/20017.cha, line 368 · Jun 2;00
  8. sore mimi ka . %mov:"20017"_585805_586773 FAT · japanese_ishii/20017.cha, line 373 · Jun 2;00
  9. sore ohana ? %mov:"20017"_591232_595030 FAT · japanese_ishii/20017.cha, line 376 · Jun 2;00
  10. okuchi # sore okuchi . %mov:"20017"_596389_599523 FAT · japanese_ishii/20017.cha, line 378 · Jun 2;00
  11. aa, sore buu@o yuu no . %mov:"20017"_745301_746977 FAT · japanese_ishii/20017.cha, line 467 · Jun 2;00
  1. FATchiisai jitensha dore ? %mov:"20017"_87024_92072
    CHIchiisha . %mov:"20017"_92072_94241
    FAT*FAT: a, sore chiisai no . %mov:"20017"_94241_95525
    FATookii jitensha wa ? %mov:"20017"_95525_97012
    CHIn ? %mov:"20017"_97012_99521
  2. FAThai [<] . %mov:"20017"_215877_217193
    CHIkoe wa ? %mov:"20017"_217193_217844
    FAT*FAT: sore nan daro . %mov:"20017"_217844_219231
    CHIjiijiita <hoa> [>] . %mov:"20017"_219231_223371
    FATe [<] ? %mov:"20017"_219231_223371
  3. FATnan te kaitaaru no ? %mov:"20017"_257522_258775
    CHIbuun e . %mov:"20017"_258775_263594
    FAT*FAT: a, sore buun@o . %mov:"20017"_263594_265033
    FATjuusaa ya ne . %mov:"20017"_265033_266326
    CHIn [>] ? %mov:"20017"_266326_266919
  4. FATPapa kore ? %mov:"20017"_364166_365378
    CHIaduun . %mov:"20017"_365378_367231
    FAT*FAT: Jun sore . %mov:"20017"_367231_367931
    FATuun ? %mov:"20017"_367931_370025
    CHIae Jun . %mov:"20017"_370025_371164
  5. FATuun ? %mov:"20017"_367931_370025
    CHIae Jun . %mov:"20017"_370025_371164
    FAT*FAT: sore mo Jun . %mov:"20017"_371164_372303
    CHIae Jun . %mov:"20017"_372303_373856
    FATuun . %mov:"20017"_373856_374801
  6. FATpia sense yoo tte ka ? %mov:"20017"_452835_456546
    CHIoe a ? %mov:"20017"_456546_457953
    FAT*FAT: kankankan@o yaro,, sore ? %mov:"20017"_457953_460070
    CHImaiyoo [>] . %mov:"20017"_460070_463254
    FAT<abunai yoo> [<] un . %mov:"20017"_460070_463254
  7. FATohana # kore ka ? %mov:"20017"_569343_570855
    FATokuchi wa ? %mov:"20017"_570855_573013
    FAT*FAT: a, sore okuchi . %mov:"20017"_573013_576778
    FATmeme, kore meme ka ? %mov:"20017"_576778_578124
    FATkore omeme ka ? %mov:"20017"_578124_580151
  8. FATmimi doko ni aru ? %mov:"20017"_580151_584163
    CHImimi . %mov:"20017"_584163_585805
    FAT*FAT: sore mimi ka . %mov:"20017"_585805_586773
    FATohana wa ? %mov:"20017"_586773_590200
    FATohana wa ? %mov:"20017"_590200_591232
  9. FATohana wa ? %mov:"20017"_586773_590200
    FATohana wa ? %mov:"20017"_590200_591232
    FAT*FAT: sore ohana ? %mov:"20017"_591232_595030
    FATokuchi wa ? %mov:"20017"_595030_596389
    FATokuchi # sore okuchi . %mov:"20017"_596389_599523
  10. FATsore ohana ? %mov:"20017"_591232_595030
    FATokuchi wa ? %mov:"20017"_595030_596389
    FAT*FAT: okuchi # sore okuchi . %mov:"20017"_596389_599523
    FATJun no okuchi wa doko ni aru ? %mov:"20017"_599523_601117
    FATatama wa ? %mov:"20017"_601117_604608
  11. FATaa ! %mov:"20017"_741766_743164
    CHIbuu . %mov:"20017"_743164_745301
    FAT*FAT: aa, sore buu@o yuu no . %mov:"20017"_745301_746977
    CHIjaa ya . %mov:"20017"_746977_747872
    FATsoo ya soo ya . %mov:"20017"_747872_748554

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. sore11 · 100.0%