PHPCLANCHILDES with regular expressions

11 matches in 11 utterances

7.28 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (641 utterances, 1,510 words searched).

  1. moo nai ? %mov:"20220"_52854_53447 FAT · japanese_ishii/20220.cha, line 57 · Jun 2;02
  2. moo nai yan . %mov:"20220"_61565_62357 FAT · japanese_ishii/20220.cha, line 67 · Jun 2;02
  3. moo nai ? %mov:"20220"_239760_240970 FAT · japanese_ishii/20220.cha, line 188 · Jun 2;02
  4. moo nai nee [<] . %mov:"20220"_240970_243708 FAT · japanese_ishii/20220.cha, line 190 · Jun 2;02
  5. a, hikooki nai nee . %mov:"20220"_1032214_1033549 FAT · japanese_ishii/20220.cha, line 732 · Jun 2;02
  6. nai ? %mov:"20220"_1040419_1040883 FAT · japanese_ishii/20220.cha, line 738 · Jun 2;02
  7. memechi nai ? %mov:"20220"_1084689_1085511 FAT · japanese_ishii/20220.cha, line 758 · Jun 2;02
  8. nai naa . %mov:"20220"_1283526_1285122 FAT · japanese_ishii/20220.cha, line 875 · Jun 2;02
  9. hikooki wa nai yo . %mov:"20220"_1407719_1408897 FAT · japanese_ishii/20220.cha, line 964 · Jun 2;02
  10. nai ka ? %mov:"20220"_1789650_1790965 FAT · japanese_ishii/20220.cha, line 1196 · Jun 2;02
  11. aisukuriimu nai naa . %mov:"20220"_1792128_1793470 FAT · japanese_ishii/20220.cha, line 1198 · Jun 2;02
  1. CHIna ? %mov:"20220"_51596_52056
    FATmada aru ? %mov:"20220"_52056_52854
    FAT*FAT: moo nai ? %mov:"20220"_52854_53447
    CHImada aru xxx [>] . %mov:"20220"_53447_56517
    FATdoko ni aru [<] ? %mov:"20220"_53447_56517
  2. FATe ? %mov:"20220"_60035_60573
    CHIxxx . %mov:"20220"_60573_61565
    FAT*FAT: moo nai yan . %mov:"20220"_61565_62357
    FATkore ka ? %mov:"20220"_62357_63582
    CHIkoe un . %mov:"20220"_63582_63582
  3. CHIputchii wa ? %mov:"20220"_235462_237754
    CHIa [: aru] ka naa . %mov:"20220"_237754_239760
    FAT*FAT: moo nai ? %mov:"20220"_239760_240970
    CHImoo nai naa [>] . %mov:"20220"_240970_243708
    FATmoo nai nee [<] . %mov:"20220"_240970_243708
  4. FATmoo nai ? %mov:"20220"_239760_240970
    CHImoo nai naa [>] . %mov:"20220"_240970_243708
    FAT*FAT: moo nai nee [<] . %mov:"20220"_240970_243708
    CHInaa ? %mov:"20220"_243708_245405
    FATuun . %mov:"20220"_245405_245980
  5. FAThikooki wa ? %mov:"20220"_1027453_1028833
    CHIhokooki # nai yo . %mov:"20220"_1028833_1032214
    FAT*FAT: a, hikooki nai nee . %mov:"20220"_1032214_1033549
    FAThikooki noru ? %mov:"20220"_1033549_1035182
    CHInai yo . %mov:"20220"_1035182_1037491
  6. CHInai yo . %mov:"20220"_1037945_1039192
    CHInai yo . %mov:"20220"_1039192_1040419
    FAT*FAT: nai ? %mov:"20220"_1040419_1040883
    CHIkoko ayu yo,, horee . %mov:"20220"_1040883_1043408
    FATnani ga iru no,, sore ? %mov:"20220"_1043408_1044531
  7. FATe ? %mov:"20220"_1082840_1083372
    CHImemechi [= bug] . %mov:"20220"_1083372_1083372
    FAT*FAT: memechi nai ? %mov:"20220"_1084689_1085511
    FATfuun . %mov:"20220"_1085511_1087619
    FATkotchi nani ga an no ? %mov:"20220"_1087619_1090785
  8. FATxxx . %mov:"20220"_1281292_1282622
    CHInaai . %mov:"20220"_1282622_1283526
    FAT*FAT: nai naa . %mov:"20220"_1283526_1285122
    CHIaa . %mov:"20220"_1285122_1286304
    CHIaa aa . %mov:"20220"_1286304_1288040
  9. FATun . %mov:"20220"_1405102_1405996
    CHIkooki [: hikooki] wa nai ka ? %mov:"20220"_1405996_1405996
    FAT*FAT: hikooki wa nai yo . %mov:"20220"_1407719_1408897
    CHIaa ? %mov:"20220"_1408897_1412008
    CHInanii ? %mov:"20220"_1412008_1413565
  10. CHIare ? %mov:"20220"_1786004_1786630
    CHIare ? %mov:"20220"_1786630_1789650
    FAT*FAT: nai ka ? %mov:"20220"_1789650_1790965
    CHIbai naa . %mov:"20220"_1790965_1792128
    FATaisukuriimu nai naa . %mov:"20220"_1792128_1793470
  11. FATnai ka ? %mov:"20220"_1789650_1790965
    CHIbai naa . %mov:"20220"_1790965_1792128
    FAT*FAT: aisukuriimu nai naa . %mov:"20220"_1792128_1793470
    CHIoshi [: okashii] naa . %mov:"20220"_1793470_1795278
    CHIooshoomen naa ? %mov:"20220"_1795278_1797415

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_ishii7.28
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
japanese_ishii/20220.chaJun 2;2.201,51011117.28

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. nai11 · 100.0%