PHPCLANCHILDES with regular expressions

9 matches in 9 utterances

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

  1. piipoopiipoo@o doko ni aru no, sagashaite . %mov:"20017"_381108_386121 FAT · japanese_ishii/20017.cha, line 256 · Jun 2;00
  2. doko itta ka na, piipoopiipoo@o . %mov:"20017"_390638_393088 FAT · japanese_ishii/20017.cha, line 259 · Jun 2;00
  3. doko yatta ka na ? %mov:"20017"_404566_405828 FAT · japanese_ishii/20017.cha, line 265 · Jun 2;00
  4. doko ittaa ? %mov:"20017"_416470_418087 FAT · japanese_ishii/20017.cha, line 272 · Jun 2;00
  5. doko itta ? %mov:"20017"_530003_530614 FAT · japanese_ishii/20017.cha, line 349 · Jun 2;00
  6. <shinkansen> [<] byuwaan@o no omeme doko ? %mov:"20017"_560654_564215 FAT · japanese_ishii/20017.cha, line 361 · Jun 2;00
  7. mimi doko ni aru ? %mov:"20017"_580151_584163 FAT · japanese_ishii/20017.cha, line 371 · Jun 2;00
  8. Jun no okuchi wa doko ni aru ? %mov:"20017"_599523_601117 FAT · japanese_ishii/20017.cha, line 379 · Jun 2;00
  9. doko iku no . %mov:"20017"_773475_778218 FAT · japanese_ishii/20017.cha, line 485 · Jun 2;00
  1. japanese_ishii/20017.cha, line 256 · Jun, 2;0.17
    FATJun kore . %mov:"20017"_378611_379357
    FATuun ? %mov:"20017"_379357_381108
    FAT*FAT: piipoopiipoo@o doko ni aru no, sagashaite . %mov:"20017"_381108_386121
    FATJunkun nottan dore ? %mov:"20017"_386121_387637
    FATJunkun piipoopiipoo@o notta ? %mov:"20017"_387637_390638
  2. japanese_ishii/20017.cha, line 259 · Jun, 2;0.17
    FATJunkun nottan dore ? %mov:"20017"_386121_387637
    FATJunkun piipoopiipoo@o notta ? %mov:"20017"_387637_390638
    FAT*FAT: doko itta ka na, piipoopiipoo@o . %mov:"20017"_390638_393088
    FATkotchi yatta ka ne ? %mov:"20017"_393088_394205
    FATare ? %mov:"20017"_394205_395874
  3. japanese_ishii/20017.cha, line 265 · Jun, 2;0.17
    FATokashii naa . %mov:"20017"_398790_401108
    FATpiipoopiipoo@o atta nee ? %mov:"20017"_401108_404566
    FAT*FAT: doko yatta ka na ? %mov:"20017"_404566_405828
    CHInai yo . %mov:"20017"_405828_406849
    FATkore to shigau kyuukyuusha no hoo ? %mov:"20017"_406849_408558
  4. japanese_ishii/20017.cha, line 272 · Jun, 2;0.17
    CHIxxx . %mov:"20017"_414035_415574
    FATnai naa . %mov:"20017"_415574_416470
    FAT*FAT: doko ittaa ? %mov:"20017"_416470_418087
    CHIpiipoo nai . %mov:"20017"_418087_420043
    FATnai naa . %mov:"20017"_420043_421046
  5. japanese_ishii/20017.cha, line 349 · Jun, 2;0.17
    CHIchaacha . %mov:"20017"_527133_528808
    FATChaachan to issho ni notta . %mov:"20017"_528808_530003
    FAT*FAT: doko itta ? %mov:"20017"_530003_530614
    FAToishasan itta n. %mov:"20017"_530614_533059
    CHIn ? %mov:"20017"_533059_533719
  6. japanese_ishii/20017.cha, line 361 · Jun, 2;0.17
    FATa, meemee@o dore ? %mov:"20017"_546364_560654
    CHIun [>] ? %mov:"20017"_560654_564215
    FAT*FAT: <shinkansen> [<] byuwaan@o no omeme doko ? %mov:"20017"_560654_564215
    FATkore nani ? %mov:"20017"_564215_566307
    CHIkoe a ? %mov:"20017"_566307_567751
  7. japanese_ishii/20017.cha, line 371 · Jun, 2;0.17
    FATmeme, kore meme ka ? %mov:"20017"_576778_578124
    FATkore omeme ka ? %mov:"20017"_578124_580151
    FAT*FAT: mimi doko ni aru ? %mov:"20017"_580151_584163
    CHImimi . %mov:"20017"_584163_585805
    FATsore mimi ka . %mov:"20017"_585805_586773
  8. japanese_ishii/20017.cha, line 379 · Jun, 2;0.17
    FATokuchi wa ? %mov:"20017"_595030_596389
    FATokuchi # sore okuchi . %mov:"20017"_596389_599523
    FAT*FAT: Jun no okuchi wa doko ni aru ? %mov:"20017"_599523_601117
    FATatama wa ? %mov:"20017"_601117_604608
    FATshinkansen no atama wa ? %mov:"20017"_604608_607679
  9. japanese_ishii/20017.cha, line 485 · Jun, 2;0.17
    CHIkoo . %mov:"20017"_769666_770454
    FATdoo ? %mov:"20017"_770454_773475
    FAT*FAT: doko iku no . %mov:"20017"_773475_778218
    CHIatchii . %mov:"20017"_778218_779984
    FATaa, are mottekite . %mov:"20017"_779984_781435

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_ishii9.63
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
japanese_ishii/20017.chaJun 2;0.17935999.63

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. doko9 · 100.0%