Computer-Assisted Language Comparison

Computer-Assisted Language Comparison

Talk, held at the Annual Meeting of the Linguistic Society of Tianjin (2017-10-21, Tianjin, China).

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Johann-Mattis List

October 21, 2017
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  1. Computer-Assisted Language Comparison Johann-Mattis List Research Group “Computer-Assisted Language Comparison”

    Department of Linguistic and Cultural Evolution Max-Planck Institute for the Science of Human History Jena, Germany 2017-10-21 very long title P(A|B)=P(B|A)... 1 / 20
  2. Comparative Linguistics 2 / 20

  3. "All languages change, as long as they exist." (August Schleicher

    1863) walkman Indo-European Germanic Old English English p f f f ə a æ ɑː t d d ð eː eː e ə r r r r Germanic German English iPod Comparative Linguistics 2 / 20
  4. iPod Indo-European Germanic Old English English p f f f

    ə a æ ɑː t d d ð eː eː e ə r r r r Germanic German English walkman "All languages change, as long as they exist." (August Schleicher 1863) Comparative Linguistics 2 / 20
  5. walkman Indo-European Germanic Old English English p f f f

    ə a æ ɑː t d d ð eː eː e ə r r r r Germanic German English iPod "All languages change, as long as they exist." (August Schleicher 1863) Comparative Linguistics 2 / 20
  6. walkman Indo-European Germanic Old English English p f f f

    ə a æ ɑː t d d ð eː eː e ə r r r r Germanic German English iPod "All languages change, as long as they exist." (August Schleicher 1863) Comparative Linguistics 2 / 20
  7. iPod Indo-European Germanic Old English English p f f f

    ə a æ ɑː t d d ð eː eː e ə r r r r walkman L₁ L₁ L₁ L₁ L₁ "All languages change, as long as they exist." (August Schleicher 1863) Comparative Linguistics 2 / 20
  8. iPod Indo-European Germanic Old English English p f f f

    ə a æ ɑː t d d ð eː eː e ə r r r r walkman L₁ L₁ L₁ L₁ L₁ "All languages change, as long as they exist." (August Schleicher 1863) Comparative Linguistics 2 / 20
  9. iPod Indo-European Germanic Old English English p f f f

    ə a æ ɑː t d d ð eː eː e ə r r r r walkman L₁ L₁ L₁ L₁ L₁ "All languages change, as long as they exist." (August Schleicher 1863) Comparative Linguistics 2 / 20
  10. iPod Indo-European Germanic Old English English p f f f

    ə a æ ɑː t d d ð eː eː e ə r r r r walkman L₁ L₁ L₁ "All languages change, as long as they exist." (August Schleicher 1863) Comparative Linguistics 2 / 20
  11. iPod Indo-European Germanic Old English English p f f f

    ə a æ ɑː t d d ð eː eː e ə r r r r walkman L₂ L₁ L₃ "All languages change, as long as they exist." (August Schleicher 1863) Comparative Linguistics 2 / 20
  12. Comparative Linguistics Background Background 3 / 20

  13. Comparative Linguistics Background Background 3 / 20

  14. Comparative Linguistics Background Background 3 / 20

  15. Comparative Linguistics Background Background 3 / 20

  16. Comparative Linguistics Background Background 3 / 20

  17. Comparative Linguistics Comparative Method The Comparative Method COMPA- RATIVE METHOD

    4 / 20
  18. Comparative Linguistics Comparative Method The Comparative Method COMPA- RATIVE METHOD

    4 / 20
  19. Comparative Linguistics Comparative Method The Comparative Method COMPA- RATIVE METHOD

    4 / 20
  20. Comparative Linguistics Comparative Method The Comparative Method COMPA- RATIVE METHOD

    4 / 20
  21. Comparative Linguistics Comparative Method The Comparative Method COMPA- RATIVE METHOD

    4 / 20
  22. Comparative Linguistics Computational Linguistics Computational Historical Linguistics COMPUTA- TIONAL HISTORICAL

    LINGUISTICS 5 / 20
  23. Comparative Linguistics Computational Linguistics Computational Historical Linguistics COMPUTA- TIONAL HISTORICAL

    LINGUISTICS 5 / 20
  24. Comparative Linguistics Computational Linguistics Computational Historical Linguistics COMPUTA- TIONAL HISTORICAL

    LINGUISTICS 5 / 20
  25. Comparative Linguistics Computational Linguistics Computational Historical Linguistics COMPUTA- TIONAL HISTORICAL

    LINGUISTICS 5 / 20
  26. Comparative Linguistics Computational Linguistics Computational Historical Linguistics COMPUTA- TIONAL HISTORICAL

    LINGUISTICS 5 / 20
  27. Comparative Linguistics Computational Linguistics Classical vs. Computational Language Comparison LC

    CA COMPA- RATIVE METHOD lacks efficiency lacks consistency lacks efficiency lacks accuracy lacks flexibility high efficiency high consistency high flexibility high accuracy COMPUTA- TIONAL HISTORICAL LINGUISTICS 6 / 20
  28. Comparative Linguistics Computational Linguistics Classical vs. Computational Language Comparison LC

    CA COMPA- RATIVE METHOD lacks efficiency lacks consistency lacks efficiency lacks accuracy lacks flexibility high efficiency high consistency high flexibility high accuracy COMPUTA- TIONAL HISTORICAL LINGUISTICS 6 / 20
  29. Comparative Linguistics Computational Linguistics Classical vs. Computational Language Comparison LC

    CA lacks efficiency lacks consistency lacks efficiency lacks accuracy lacks flexibility high efficiency high consistency high flexibility high accuracy COMPA- RATIVE METHOD accuracy flexibility consistency efficiency COMPUTA- TIONAL HISTORICAL LINGUISTICS 6 / 20
  30. Comparative Linguistics CALC Computer-Assisted Language Comparison LC CA LC CA

    lacks efficiency lacks consistency lacks efficiency lacks accuracy lacks flexibility high efficiency high consistency high flexibility high accuracy COMPA- RATIVE METHOD accuracy flexibility consistency efficiency COMPUTA- TIONAL HISTORICAL LINGUISTICS 7 / 20
  31. Comparative Linguistics CALC Computer-Assisted Language Comparison LC CA 7 /

    20
  32. Examples 8 / 20

  33. Examples Cognate Detection Cognate Detection 9 / 20

  34. Examples Cognate Detection Cognate Detection 9 / 20

  35. Examples Cognate Detection Cognate Detection 9 / 20

  36. Examples Cognate Detection Cognate Detection 9 / 20

  37. Examples Cognate Detection Cognate Detection 10 / 20

  38. Examples Cognate Detection Cognate Detection 10 / 20

  39. Examples Cognate Detection Cognate Detection 10 / 20

  40. Examples Cognate Detection Cognate Detection 10 / 20

  41. Examples Cognate Detection Cognate Detection 10 / 20

  42. Examples Cognate Detection Cognate Detection 10 / 20

  43. Examples Cognate Detection Cognate Detection 10 / 20

  44. Examples Cognate Detection Cognate Detection 10 / 20

  45. Examples Cognate Detection DEMO: Software and Tools LingPy http://lingpy.org TSV

    EDICTOR http://tsv.lingpy.org 11 / 20
  46. Examples Cross-Linguistic Colexifications Cross-Linguistic Colexifications 12 / 20

  47. Examples Cross-Linguistic Colexifications Cross-Linguistic Colexifications Polysemy If a word has

    two or more meanings which are historically related. 12 / 20
  48. Examples Cross-Linguistic Colexifications Cross-Linguistic Colexifications Polysemy If a word has

    two or more meanings which are historically related. Homophony If two words which do not share a common etymological history have an identical pronunciation. 12 / 20
  49. Examples Cross-Linguistic Colexifications Cross-Linguistic Colexifications Polysemy If a word has

    two or more meanings which are historically related. Homophony If two words which do not share a common etymological history have an identical pronunciation. Colexification Coined by François (2008): If one word form denotes several meanings. 12 / 20
  50. Examples Cross-Linguistic Colexifications Database of Cross-Linguistic Colexifications CLICS (List et

    al. 2014, http://clics.lingpy.org) is an online database of synchronic lexical associations (“colexifica- tions”) in currently 221 language varieties of the world. Large databases offering lexical information on the world’s languages are already readily available for research in different online sources. However, the information on tendencies of meaning associations they enshrine is not easily extractable from these sources themselves. 13 / 20
  51. Examples Cross-Linguistic Colexifications Database of Cross-Linguistic Colexifications 684 678 871

    1043 6 30 129 196 1243 128 869 853 650 344 1103 150 185 627 232 709 1035 1206 177 97 311 496 606 137 207 444 840 1077 325 222 1063 1138 1204 1258 559 723 495 766 914 38 1101 652 865 891 872 633 291 980 700 144 410 430 1025 406 464 787 622 131 242 918 275 1159 99 1174 671 1038 786 705 641 760 1259 356 391 197 10 214 299 63 191 619 644 792 1205 897 67 1231 213 226 747 681 399 841 439 773 123 800 16 1067 1227 696 417 550 68 76 108 360 1244 339 500 81 867 79 1097 98 96 833 771 715 455 380 1268 1186 1046 39 252 1228 66 23 1112 133 676 336 739 1150 1071 986 485 112 372 1109 830 721 1053 1057 601 573 556 527 1248 614 488 908 499 1002 309 442 814 1193 569 458 258 563 653 682 774 70 1151 948 801 1082 243 47 71 83 153 1265 934 85 1215 1199 523 581 422 21 358 1261 111 354 219 759 15 890 261 1222 141 158 74 806 1031 845 770 850 903 1224 419 754 433 798 188 1256 613 528 208 539 323 981 132 1055 1001 790 804 844 1118 907 640 446 815 923 498 201 1184 578 566 427 532 452 151 750 598 1094 345 735 777 978 599 492 390 286 1107 742 1015 1202 1210 1257 1275 859 988 69 752 596 290 126 110 950 922 1047 741 253 347 385 620 966 221 431 3 224 1194 999 953 1029 852 301 389 318 530 1048 1032 175 701 544 1119 241 94 745 835 1270 62 107 159 20 767 512 331 248 549 1013 946 974 1022 1100 477 302 233 1168 1003 1211 570 307 40 945 1269 784 546 437 901 350 238 305 1191 482 1012 977 906 783 524 117 457 603 836 1181 880 229 124 216 1113 1074 72 586 647 447 2 113 1179 7 1006 665 397 502 610 1274 707 327 659 667 824 917 985 1089 346 1229 101 542 1042 727 782 733 967 462 592 468 1106 440 478 308 577 698 776 75 1155 51 145 517 359 938 1157 1160 1183 947 1102 1135 1252 343 608 537 103 634 251 383 506 25 829 396 686 679 574 516 42 250 379 809 602 660 780 765 697 856 899 594 1008 393 179 114 1140 11 100 1209 618 600 192 1277 896 1142 1278 762 421 713 182 521 861 672 297 1116 1190 1192 140 1212 46 493 1187 157 1225 212 403 519 616 173 413 912 1110 84 756 793 636 118 889 692 998 366 711 1045 61 240 1263 199 648 832 289 522 368 1091 931 982 949 400 119 388 811 53 59 1069 708 952 545 763 1238 184 825 377 1242 1233 262 635 269 1062 1061 1073 933 17 1247 352 64 384 50 632 736 1246 822 781 758 1 939 595 778 105 860 1049 1066 1072 995 503 370 919 1149 1127 1128 972 1126 245 921 973 675 587 1235 960 928 926 1143 548 1250 86 1021 32 1068 719 965 259 1070 863 638 303 324 873 249 892 976 1007 722 36 459 293 165 209 557 1245 788 862 651 900 31 483 236 935 1052 115 294 680 831 44 453 206 971 1273 170 753 256 1148 200 450 382 1240 561 615 317 572 725 870 438 139 1011 646 1117 392 45 276 264 704 1080 174 1050 808 1197 508 576 225 562 471 1217 333 1014 593 92 1034 611 1171 312 802 1253 29 902 244 582 466 668 878 341 432 1163 625 904 164 467 1195 1232 796 828 281 629 349 1166 411 369 387 1208 394 415 1000 58 1098 148 287 1223 818 263 220 838 876 313 260 65 1165 5 355 106 1172 490 718 171 1139 163 785 881 887 1169 319 585 553 894 306 314 1041 1009 799 674 848 1201 1004 689 1085 1218 1145 1170 228 911 279 73 104 690 1254 402 340 169 693 868 893 1018 78 1092 194 555 198 834 1249 997 932 237 1176 666 956 624 1262 541 520 795 866 702 4 734 1095 1180 728 964 1079 271 842 1241 1056 154 751 353 905 1136 504 909 910 1133 362 583 670 1124 381 1216 215 178 571 470 142 376 1154 172 296 533 364 963 152 797 1213 803 1051 738 426 1036 1153 637 823 915 428 1075 560 547 1137 35 882 89 511 1122 805 494 1130 1188 1086 1236 669 588 930 703 942 18 655 335 155 710 1156 1028 465 147 183 414 1221 273 166 1054 278 55 460 812 1090 810 180 768 143 156 404 367 1182 231 288 136 456 82 529 970 1016 729 395 187 604 408 330 1064 34 1267 847 726 543 677 642 940 645 958 683 695 864 1058 605 1084 451 443 699 1167 959 925 1198 227 886 628 1178 337 991 813 657 1185 1039 769 1081 484 712 1189 944 1207 322 33 685 424 80 270 937 1177 283 1237 816 130 161 189 77 300 1026 463 1104 326 589 60 983 474 1093 744 748 554 292 41 267 984 373 1214 957 1024 969 507 37 874 1030 630 579 962 535 706 688 122 497 1060 1083 1027 102 510 405 1134 658 617 936 929 363 1175 361 536 534 1219 181 386 884 418 558 8 479 979 551 505 316 298 26 315 761 202 1144 176 473 348 134 639 663 717 885 924 149 49 1078 1040 57 167 764 1173 673 280 1152 277 1272 1065 272 827 531 607 1123 257 996 436 9 826 234 1096 875 525 304 1108 475 1132 714 846 540 716 1005 1105 357 1162 694 920 743 28 994 1200 168 1266 420 515 568 755 895 218 916 730 807 210 375 854 1010 879 1125 268 1129 1114 1255 1158 1279 487 486 398 597 661 135 565 621 193 321 1230 513 654 265 612 737 855 211 1196 246 1264 584 338 749 1271 434 121 423 509 839 1147 656 230 239 489 14 469 22 1044 351 448 282 329 961 254 989 371 284 223 843 821 24 1023 643 819 285 514 746 757 791 138 186 849 93 951 127 877 1088 518 1164 1260 501 54 190 95 43 205 1276 116 146 662 217 461 883 204 1033 310 472 12 412 332 817 649 794 1037 943 927 481 968 425 109 195 857 1121 564 687 664 724 87 1120 88 449 429 255 987 992 1111 591 575 491 720 851 328 941 990 1019 993 1087 955 580 1226 975 1099 732 235 779 365 1234 441 609 247 334 91 1251 1131 913 691 52 274 1017 435 90 407 480 1239 13 623 0 266 626 295 954 1059 552 898 858 772 526 1115 48 1161 125 590 454 1020 1141 203 740 1146 342 820 1220 56 320 416 27 401 476 19 120 1203 445 789 775 888 567 378 1076 160 162 409 731 631 374 538 837 13 / 20
  52. Examples Cross-Linguistic Colexifications Database of Cross-Linguistic Colexifications We are currently

    substantially revising the amount of data in CLICS and hope to be able to release a much larger and also consistently enhanced version some time in the first half of next year. 13 / 20
  53. Examples Cross-Linguistic Colexifications Database of Cross-Linguistic Colexifications 13 / 20

  54. Examples Cross-Linguistic Colexifications Database of Cross-Linguistic Colexifications In addition to

    the original CLICS database, we are currently also testing algorithms which measure compoundhood across languages. 13 / 20
  55. Examples Cross-Linguistic Colexifications Database of Cross-Linguistic Colexifications WASP BEEHIVE WINE

    ALCOHOL (FERMENTED DRINK) BEER DRINK MEAD BEVERAGE HONEY BEESWAX SUGAR FRAGRANT STINKING BEE SWEET SMELL (STINK) FEEL SUGAR CANE SNIFF SMELL (PERCEIVE) 13 / 20
  56. Examples Rhyme Analysis Rhyme Analysis 14 / 20

  57. Examples Rhyme Analysis Rhyme Analysis rhyme analysis is crucial for

    Old Chinese phonology 14 / 20
  58. Examples Rhyme Analysis Rhyme Analysis rhyme analysis is crucial for

    Old Chinese phonology emerged when scholars of the Suí 隋 (581–618) and Táng 唐 (618–907) dynasties realized that old poems, especially those in the Book of Odes (Shījīng 詩經 ca. 1050–600 BCE) had many inconsistencies regarding the rhyming of words 14 / 20
  59. Examples Rhyme Analysis Rhyme Analysis rhyme analysis is crucial for

    Old Chinese phonology emerged when scholars of the Suí 隋 (581–618) and Táng 唐 (618–907) dynasties realized that old poems, especially those in the Book of Odes (Shījīng 詩經 ca. 1050–600 BCE) had many inconsistencies regarding the rhyming of words later scholars from the Míng 明 (1368–1644) and Qīng 清 dynasties (1644–1911) realized that the inconsistencies in the rhyme patterns reflect the effects of language change 14 / 20
  60. Examples Rhyme Analysis Rhyme Analysis 15 / 20

  61. Examples Rhyme Analysis Rhyme Analysis Poem Stanza Verse Sect. Text

    Rhyme Pattern MCH OCBS 4 1 1 1 南有樛木、 木 - muwk C.mˤok 4 1 1 2 葛藟纍之。 纍 A lwij [r]uj 4 1 2 1 樂只君子、 子 - tsiX tsəʔ 4 1 2 2 福履綏之。 綏 A swij s.nuj 4. 樛木 南有樛木、葛藟纍之。 樂只君子、福履綏之。 南有樛木、葛藟荒之。 樂只君子、福履將之。 南有樛木、葛藟縈之。 樂只君子、福履成之。 15 / 20
  62. Examples Rhyme Analysis Rhyme Analysis 1 1 1 1 1

    1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 2 1 1 1 1 1 1 1 1 1 3 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 2 1 2 1 1 1 1 1 1 1 1 4 2 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 2 1 1 3 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 2 2 1 1 2 1 1 1 1 2 1 1 2 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 3 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 2 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 2 1 1 1 1 2 1 1 1 2 1 1 2 3 1 1 1 1 1 2 1 1 2 1 3 1 1 1 1 1 1 1 1 1 1 2 1 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 2 1 2 1 1 1 1 1 3 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 1 1 5 1 2 1 1 1 2 1 1 1 1 1 1 4 1 3 1 1 1 1 3 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 2 2 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 2 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 2 1 2 3 1 3 2 1 1 1 1 1 4 1 2 1 1 2 1 2 3 1 1 2 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 3 1 1 1 1 1 1 3 2 1 1 1 1 2 1 1 1 2 1 1 1 1 1 1 1 1 1 2 1 2 1 1 3 1 1 1 1 4 1 3 3 9 7 2 1 1 1 2 1 1 1 2 1 1 1 1 1 1 2 1 2 1 1 2 2 1 1 1 4 1 2 1 2 3 1 1 1 2 4 1 1 1 1 1 1 1 1 1 1 1 1 1 3 2 1 1 1 1 1 1 3 1 1 2 1 1 1 2 5 4 2 2 1 1 52 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 2 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 1 1 1 2 2 1 1 1 1 嚴 談 濫 斬 惔 監 相 彊 傷 競 梗 牂 旁 翔 怲 頏 唐 上 往 痒 魴 姜 蒼 腸 詳 瞻 遑 掌 彭 庚 襄 桑 岡 張 忘 芒 螗 英 荒 良 簧 湯 傍 楊 堂 抗 瀼 牆 仰 狼 狂 漿 鏘 兄 陽 稂 伉 臧 爽 長 煌 糧 筐 雱 涼 防 盟 卿 蝱 粻 羹 囊 倉 粱 剛 揚 房 京 箱 商 梁 洋 昌 珩 泳 亡 瑲 貺 兵 樅 鏞 光 慶 嘗 香 亨 享 羊 方 喪 黃 斨 王 鶬 皇 將 常 衡 穰 饗 卬 杭 向 罔 望 讓 藏 觥 璋 鍚 綱 響 洸 鄉 羌 裳 央 鏜 章 祥霜 場 喤 床 康 蹌 行 明 疆 祊 尚 廱 1 1 1 1 2 1 2 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 2 1 1 3 1 2 2 1 1 1 1 1 1 1 1 2 1 1 4 1 1 2 2 2 1 1 1 2 1 1 1 1 4 2 2 1 2 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 4 1 1 1 1 1 3 1 1 1 1 1 1 1 5 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 3 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 3 1 3 4 14 3 2 3 1 1 1 2 8 1 1 1 3 1 1 1 1 1 1 1 1 1 2 1 1 3 1 1 1 3 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 2 1 2 1 1 2 1 1 1 1 1 1 3 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 2 2 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 4 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 2 3 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 3 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 2 1 1 2 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 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罶 燠 鴇 怓 首 逑 天 莘 鳩 問 丁 傾 蓫 屏 鵠 優 慆 酋 銶 繡 喬 嘵 翹 搖 翛 呶 譙 苕 瑤 驕 膋 毛 瀌 忉 巢 謠 桃 刀 號 旐 苗 郊 嗷 消 麃 高 遙 膏 朝 勞 鑣 曜 儦 旄 夭 猶 罩 樂 茅 夙 虐 告 綯 綽 耄 駮 秀 褎 藐 好 教 造 較 藥 苞 埽 寶 鷮 罦 牡 抽 孝 潦 軌 保 翿 陶 廟 孚 笑 皁 莠 杻 昭 栲 臭 櫟 茂 襮 到 鑿 芼 沃 朽 寮 傚 暴 盜 敖 蒿 囚 蕘 恌 悼 囂 基 淇 伾 絲 雨 獲 姬 媒 駓 丘 竿 龜 箕 期 梅 其 謀 儺 恥 之 采 有 哉 恃 逆 始 似 殆 躍 詩 尤 騏 翯 思 暑 敬 圉 瞽 苦 鼠 鱮 庭 戶 鼓 罟 否 敏 芑 涘 裏 使 理 梓 海 沼 倍 史 宰 事 負 炤 齒 耔 汜 時 鯉 久 薿 忌 止 耳 玖 耜 李 士 趾 畝 杞 秠 洧 里 友 祉 已 沚 喜 悔 子 位 字 祀 痗 寺 婦 意 戒 載 入 式 怠 右 饎 茲 紀 屺 舊 仕 母 俟 在 以 晦 能 燎 裒 叟 蹂 周 照 慘 騷 紹 觩 流 滔 殽 求 擣 休 酬 游 飽 漕 劉 滺 炮 卯 悠 遊 柔 浮 稻 救 髦 憂 舟 棗 讎 陸 謔 六 祝 妯 熇 蠋 鼛 售 蹻 裯 甥 正 鞠 名 育 昴 俶 茆 禱 手 阜 舅 戊 簋 洲 集 究 醜 老 報 軸 草 道 咎 鎬 冒 缶 考 狩 藻 櫜 壽 酒 覺 魗 宮 躬 臨甚 錦 弘 飾 極 祺 暱 螣 忒 直 特 力 賊 緎 食 嶷 則 葍 色 匐 備 翼 德 侑 輻 億 黑 域 稷 誨 妣 尾 潀 閟 秭 禮 履 偕 忡 驂 飲 蟲 螽 降 宗 中 砥 宋 匕 視 醴 涕 皆 仲 燬 旨 近 矢 邇 鱧 兕 藍 襜 巖 詹 東 功 棣 鍾 薈 弟 隮 火 穉 薺 西 指 濟 葦 爾 體 唯 水 死 崇 泥 豈 豐 務 姊 藟 禰 隼 濔 泲 几 戎 側 慝 彧 得 飭 織 北 弋 蜮 *-əj *-ək *-əʔ *-aʔ *-in *-aŋ 15 / 20
  63. Examples Rhyme Analysis Rhyme Analysis 2 1 1 1 3

    1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 2 1 3 1 1 1 1 1 1 2 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 2 1 2 1 2 1 1 1 1 1 1 1 1 1 2 1 1 1 1 2 1 1 1 3 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 2 1 1 1 2 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 2 1 1 1 1 1 5 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 1 1 2 1 1 1 1 1 1 3 1 1 4 1 1 1 1 1 1 1 1 1 1 3 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 嘆 安 閑 難 泉 彥 羨 粲 旦 援 鴈 岸 晏 爛 巘 乾 嘽 繁 漢 蕃 番 宣 歎 蘭 憲 單 軒 原 殘 那 翰 藩 渙 然 諫 板 遠 癉 亶 管 僊 墠 ⾔ 遷 園 連 漣 虔 焉 ⼭ ⼲ 垣 丸 諼 廛 咺 澗 貆 寬 熯 顏 痯 踐 媛 反 衍 愆 阪 罹 ⽪ 河 紽 磨 儀 佗 磋 池 差 婆 ⿇ 訛 娑 離 宜 錡 嘉 他 加 沙 多 儺 靡 左 嗟 犧 波 施 沱 駕 蛇 何 荷 陂 羆 過 歌 禍 詈 薖 馳 我 破 可 吪 它 為 椅 羅 ⽡ 議 A *-an *-aj *-ar *-an / *-ar 15 / 20
  64. Examples Rhyme Analysis Rhyme Analysis 1 1 1 1 1

    1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 2 1 1 2 1 1 1 2 1 1 1 2 2 1 2 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 3 1 1 1 1 1 1 1 3 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 2 1 1 1 2 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 4 3 1 2 1 1 1 2 1 1 1 1 1 1 1 3 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 5 1 1 1 1 3 1 1 1 1 2 2 1 1 1 1 1 1 1 1 羆 蛇 紽 ⽪ 癉 遠 諫 渙 阪 板 衍 墠 蘭 訛 池 ⿇ 薖 娑 痯 差 管 婆 嘽 番 歎 難 翰 單 嘆 憲 繁 泉 亶 岸 然 援 反 羨 踐 藩 原 宣 漢 那 蕃 巘 垣 爛 粲 鴈 彥 乾 晏 旦 歌 施 離 過 靡 椅 虔 廛 焉 殘 僊 諼 寬 咺 愆 熯 顏 媛 澗 我 儺 詈 左 禍 可 它 波 馳 河 破 議 加 羅 何 ⽡ 貆 安 漣 遷 ⼲ 園 閑 ⾔ 丸 連 軒 他 ⼭ 錡 吪 沱 磋 荷 佗 駕 儀 陂 嘉 宜 罹 嗟 犧 沙 多 為 磨 B 15 / 20
  65. Examples Rhyme Analysis Rhyme Analysis 3 1 1 1 1

    1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 安 焉 虔 園 遷 閑 廛 貆 ⾔ 漣 僊 ⼭ ⼲ 殘 軒 連 丸 C 3 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 安 焉 虔 園 遷 閑 廛 貆 ⾔ 漣 僊 ⼭ ⼲ 殘 軒 連 丸 D 15 / 20
  66. Examples Rhyme Analysis The Shījīng Browser In order to make

    it more convenient for the readers to investi- gate the data underlying this paper in full detail, an interactive web-based application was created. This freely available Shījīng Browser (http://digling.org/shijing/) lists all potential rhyme words in tabular form along with additional information including the pīnyīn transliteration, the Middle Chinese reading, the reconstruction by Baxter and Sagart (ibid.), the reading by Pān (2000), the GSR index (Karlgren 1957), and the number of poem, stanza, and section. 16 / 20
  67. Outlook 17 / 20

  68. Outlook “知可戰與不 可戰者勝!” (孫⼦, "兵法“) "Those who know when to

    fight and when not to fight will win!" (Sun Tzu, 6th century BC, "The art of war") 18 / 20
  69. Outlook In linguistics, as in science in general, we need

    to know what we are capable of and what we are not. If we keep on comparing languages manually, ignoring all the technical improvements of late, we will necessarily fail. On the other hand, if we blindly trust algorithms instead of experts expertise and intuition, we will also fail. We need integrated frameworks for historical language comparison in which the best of the two worlds is combined! 19 / 20
  70. 谢谢大家 20 / 20