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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

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Comparative Linguistics 2 / 20

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"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

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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

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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

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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

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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

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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

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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

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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

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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

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Comparative Linguistics Background Background 3 / 20

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Comparative Linguistics Background Background 3 / 20

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Comparative Linguistics Background Background 3 / 20

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Comparative Linguistics Background Background 3 / 20

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Comparative Linguistics Background Background 3 / 20

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

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

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

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

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

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

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

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

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

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

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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

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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

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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

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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

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Comparative Linguistics CALC Computer-Assisted Language Comparison LC CA 7 / 20

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Examples 8 / 20

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Examples Cognate Detection Cognate Detection 9 / 20

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Examples Cognate Detection Cognate Detection 9 / 20

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Examples Cognate Detection Cognate Detection 9 / 20

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Examples Cognate Detection Cognate Detection 9 / 20

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Examples Cognate Detection Cognate Detection 10 / 20

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Examples Cognate Detection Cognate Detection 10 / 20

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Examples Cognate Detection Cognate Detection 10 / 20

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Examples Cognate Detection Cognate Detection 10 / 20

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Examples Cognate Detection Cognate Detection 10 / 20

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Examples Cognate Detection Cognate Detection 10 / 20

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Examples Cognate Detection Cognate Detection 10 / 20

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Examples Cognate Detection Cognate Detection 10 / 20

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Examples Cognate Detection DEMO: Software and Tools LingPy http://lingpy.org TSV EDICTOR http://tsv.lingpy.org 11 / 20

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Examples Cross-Linguistic Colexifications Cross-Linguistic Colexifications 12 / 20

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

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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

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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

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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

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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 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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

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Examples Cross-Linguistic Colexifications Database of Cross-Linguistic Colexifications 13 / 20

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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

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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

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Examples Rhyme Analysis Rhyme Analysis 14 / 20

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

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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

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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

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Examples Rhyme Analysis Rhyme Analysis 15 / 20

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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

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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 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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

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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

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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

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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

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Outlook 17 / 20

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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

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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

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谢谢大家 20 / 20