$30 off During Our Annual Pro Sale. View Details »

Non-Tree-Like Processes in Language Evolution

Non-Tree-Like Processes in Language Evolution

Talk, held at the EVOLUNET Summer School on Networks (Roscoff, 2016/07/04-08).

Johann-Mattis List

July 08, 2016
Tweet

More Decks by Johann-Mattis List

Other Decks in Science

Transcript

  1. Non-Tree-Like Processes in Language Evolution
    Johann-Mattis List
    DFG research fellow
    Centre des recherches linguistiques sur l’Asie Orientale
    Team Adaptation, Integration, Reticulation, Evolution
    EHESS and UPMC, Paris
    2016/07/08
    1 / 52

    View Slide

  2. Prolog
    2 / 52

    View Slide

  3. "All languages change, as long as they exist."
    (August Schleicher 1863)
    Prolog
    2 / 52

    View Slide

  4. walkman
    "All languages change, as long as they exist."
    (August Schleicher 1863)
    Prolog
    2 / 52

    View Slide

  5. iPod
    walkman
    "All languages change, as long as they exist."
    (August Schleicher 1863)
    Prolog
    2 / 52

    View Slide

  6. iPod
    Indo-European
    Germanic
    Old English
    English
    p
    f
    f
    f
    ə
    a
    æ
    ɑː
    t
    d
    d
    ð


    e
    ə
    r
    r
    r
    r
    walkman
    "All languages change, as long as they exist."
    (August Schleicher 1863)
    Prolog
    2 / 52

    View Slide

  7. iPod
    Indo-European
    Germanic
    Old English
    English
    p
    f
    f
    f
    ə
    a
    æ
    ɑː
    t
    d
    d
    ð


    e
    ə
    r
    r
    r
    r
    walkman
    L₁
    "All languages change, as long as they exist."
    (August Schleicher 1863)
    Prolog
    2 / 52

    View Slide

  8. iPod
    Indo-European
    Germanic
    Old English
    English
    p
    f
    f
    f
    ə
    a
    æ
    ɑː
    t
    d
    d
    ð


    e
    ə
    r
    r
    r
    r
    walkman
    L₁
    L₁
    L₁
    L₁ L₁
    "All languages change, as long as they exist."
    (August Schleicher 1863)
    Prolog
    2 / 52

    View Slide

  9. iPod
    Indo-European
    Germanic
    Old English
    English
    p
    f
    f
    f
    ə
    a
    æ
    ɑː
    t
    d
    d
    ð


    e
    ə
    r
    r
    r
    r
    walkman
    L₁
    L₁
    L₁
    L₁
    L₁
    "All languages change, as long as they exist."
    (August Schleicher 1863)
    Prolog
    2 / 52

    View Slide

  10. iPod
    Indo-European
    Germanic
    Old English
    English
    p
    f
    f
    f
    ə
    a
    æ
    ɑː
    t
    d
    d
    ð


    e
    ə
    r
    r
    r
    r
    walkman
    L₁
    L₁
    L₁
    "All languages change, as long as they exist."
    (August Schleicher 1863)
    Prolog
    2 / 52

    View Slide

  11. iPod
    Indo-European
    Germanic
    Old English
    English
    p
    f
    f
    f
    ə
    a
    æ
    ɑː
    t
    d
    d
    ð


    e
    ə
    r
    r
    r
    r
    walkman
    L₂
    L₁
    L₃
    "All languages change, as long as they exist."
    (August Schleicher 1863)
    Prolog
    2 / 52

    View Slide

  12. Prolog Background
    Background
    3 / 52

    View Slide

  13. Prolog Background
    Background
    3 / 52

    View Slide

  14. Prolog Background
    Background
    3 / 52

    View Slide

  15. Prolog Background
    Background
    3 / 52

    View Slide

  16. Prolog Background
    Background
    3 / 52

    View Slide

  17. Prolog Comparative Method
    The Comparative Method
    4 / 52

    View Slide

  18. Prolog Comparative Method
    The Comparative Method
    4 / 52

    View Slide

  19. Prolog Comparative Method
    The Comparative Method
    4 / 52

    View Slide

  20. Prolog Comparative Method
    The Comparative Method
    4 / 52

    View Slide

  21. Prolog Comparative Method
    The Comparative Method
    4 / 52

    View Slide

  22. Prolog Languages
    What is a Language?
    Norwegian, Swedish, and Danish are different languages
    .
    .
    Běijīng-Chinese, Shànghǎi-Chinese und Hakka-Chinese
    are dialects of the same language
    5 / 52

    View Slide

  23. Prolog Languages
    What is a Language?
    Běijīng Chinese 1 iou²¹ i⁵⁵ xuei³⁵ pei²¹fəŋ⁵⁵ kən⁵⁵ tʰai⁵¹iaŋ¹¹ t͡ʂəŋ⁵⁵ ʦai⁵³ naɚ⁵¹ t͡ʂəŋ⁵⁵luən⁵¹
    Hakka Chinese 1 iu³³ it⁵⁵ pai³³a¹¹ pet³³fuŋ³³ tʰuŋ¹¹ ɲit¹¹tʰeu¹¹ hɔk³³ e⁵³ au⁵⁵
    Shànghǎi Chinese 1 ɦi²² tʰɑ̃⁵⁵ ʦɿ²¹ poʔ³foŋ⁴⁴ taʔ⁵ tʰa³³ɦiã⁴⁴ ʦəŋ³³ hɔ⁴⁴ ləʔ¹lə²³ʦa⁵³
    Běijīng Chinese 2 ʂei³⁵ də⁵⁵ pən³⁵ liŋ²¹ ta⁵¹
    Hakka Chinese 2 man³³ ɲin¹¹ kʷɔ⁵⁵ vɔi⁵³
    Shànghǎi Chinese 2 sa³³ ɲiŋ⁵⁵ ɦəʔ²¹ pəŋ³³ zɿ⁴⁴ du¹³
    Norwegian 1 nuːɾɑʋinˑn̩ ɔ suːln̩ kɾɑŋlət ɔm
    Swedish 1 nuːɖanvɪndən ɔ suːlən tv̥ɪstadə ən gɔŋ ɔm
    Danish 1 noʌ̯ʌnvenˀn̩ ʌ soːl̩ˀn kʰʌm eŋg̊ɑŋ i sd̥ʁiðˀ ʌmˀ
    Norwegian 2 ʋem ɑ dem sɱ̩ ʋɑː ɖɳ̩ stæɾ̥kəstə
    Swedish 2 vɛm ɑv dɔm sɔm vɑ staɹkast
    Danish 2 vɛmˀ a b̥m̩ d̥ vɑ d̥n̩ sd̥æʌ̯g̊əsd̥ə
    6 / 52

    View Slide

  24. Prolog Languages
    What is a Language?
    From the perspective of the lexicon and the sound system,
    the Chinese dialects are at least as diverse as the Scandi-
    navian languages
    6 / 52

    View Slide

  25. Prolog Languages
    Language as a Diasystem
    Languages are complex aggregates of different linguistic
    systems which “coexist and mutually influence each other”
    (Coseriu 1973: 40, my translation).
    .
    .
    7 / 52

    View Slide

  26. Prolog Languages
    Language as a Diasystem
    Standard Language
    Diatopic Varieties
    Diastratic Varieties
    Diaphasic Varieties
    7 / 52

    View Slide

  27. Prolog Languages
    Language Variation: Dimensions
    LANGUAGE
    8 / 52

    View Slide

  28. Prolog Languages
    Language Variation: Dimensions
    LANGUAGE
    diatopic
    place
    8 / 52

    View Slide

  29. Prolog Languages
    Language Variation: Dimensions
    LANGUAGE
    diastratic diatopic
    social layer place
    8 / 52

    View Slide

  30. Prolog Languages
    Language Variation: Dimensions
    LANGUAGE
    diastratic diatopic
    diaphasic
    social layer place
    situation
    8 / 52

    View Slide

  31. Prolog Languages
    Language Variation: Dimensions
    LANGUAGE
    diastratic diatopic
    diaphasic
    diam
    esic
    social layer place
    situation
    m
    edium
    8 / 52

    View Slide

  32. Prolog Languages
    Language Variation: Dimensions
    LANGUAGE
    diachronic
    diastratic diatopic
    diaphasic
    diam
    esic
    time
    social layer place
    situation
    m
    edium
    8 / 52

    View Slide

  33. Prolog Languages
    Language Variation: Dimensions
    LANGUAGE
    diachronic
    diastratic diatopic
    diaphasic
    diam
    esic
    8 / 52

    View Slide

  34. Prolog Languages
    Language Variation: Complexity of Borrowing
    9 / 52

    View Slide

  35. Prolog Languages
    Language Variation: Complexity of Borrowing
    expected Mandarin [ma₅₅po₂₁lou]
    9 / 52

    View Slide

  36. Prolog Languages
    Language Variation: Complexity of Borrowing
    expected Mandarin [ma₅₅po₂₁lou]
    attested Mandarin [wan₅₁paw₂₁lu₅₁]
    9 / 52

    View Slide

  37. Prolog Languages
    Language Variation: Complexity of Borrowing
    expected Mandarin [ma₅₅po₂₁lou]
    attested Mandarin [wan₅₁paw₂₁lu₅₁]
    explanation Cantonese [maːn₂₂pow₃₅low₃₂]
    9 / 52

    View Slide

  38. Prolog Languages
    Language Variation: Complexity of Borrowing
    English Cantonese Mandarin
    maːlboʁo maːn22
    pow35
    low32
    wan51
    paw21
    lu51
    Proper Name
    “Road of 1000 Tre-
    asures”
    “Road of 1000 Tre-
    asures”
    万宝路
    10 / 52

    View Slide

  39. Prolog Language History
    Modeling Language History: Dendrophilia
    August Schleicher
    (1821-1868)
    11 / 52

    View Slide

  40. Prolog Language History
    Modeling Language History: Dendrophilia
    August Schleicher
    (1821-1868)
    “These assumptions, which follow
    logically from the results of our re-
    search, can be best illustrated by the
    image of a branching tree.” (Schle-
    icher 1853: 787)
    11 / 52

    View Slide

  41. Prolog Language History
    Modeling Language History: Dendrophilia
    Schleicher (1853)
    12 / 52

    View Slide

  42. Prolog Language History
    Modeling Language History: Dendrophobia
    Johannes Schmidt
    (1843-1901)
    13 / 52

    View Slide

  43. Prolog Language History
    Modeling Language History: Dendrophobia
    Johannes Schmidt
    (1843-1901)
    “You can turn it as you want, but as long
    as you stick to the idea that the his-
    torically attested languages have been
    developing by multiple furcations of an
    ancestral language, that is, as long as
    you assume that there is a Stammbaum
    [family tree] of the Indo-European lan-
    guages, you will never be able to explain
    all facts which have been assembled in
    a scientifically satisfying way.” (Schmidt
    1872: 17, my translation)
    13 / 52

    View Slide

  44. Prolog Language History
    Modeling Language History: Dendrophobia
    Johannes Schmidt
    (1843-1901)
    “I want to replace [the tree] by the im-
    age of a wave that spreads out from
    the center in concentric circles be-
    coming weaker and weaker the far-
    ther they get away from the center.”
    (Schmidt 1872: 27, my translation)
    14 / 52

    View Slide

  45. Prolog Language History
    Modeling Language History: Dendrophobia
    Schmidt (1875)
    15 / 52

    View Slide

  46. Prolog Language History
    Modeling Language History: Dendrophobia
    Meillet (1908)
    Hirt (1905)
    Bloomfield (1933)
    Bonfante (1931)
    15 / 52

    View Slide

  47. Prolog Language History
    Modeling Language History: Networks
    Trees are bad, because...
    16 / 52

    View Slide

  48. Prolog Language History
    Modeling Language History: Networks
    Trees are bad, because...
    they are difficult to
    reconstruct............
    16 / 52

    View Slide

  49. Prolog Language History
    Modeling Language History: Networks
    Trees are bad, because...
    they are difficult to
    reconstruct............
    languages do not always
    split............ .......... ............
    ............
    16 / 52

    View Slide

  50. Prolog Language History
    Modeling Language History: Networks
    Trees are bad, because...
    they are difficult to
    reconstruct............
    languages do not always
    split............ .......... ............
    ............
    they are boring, since they only
    model the vertical aspects of
    language history ............
    16 / 52

    View Slide

  51. Prolog Language History
    Modeling Language History: Networks
    Trees are bad, because...
    they are difficult to
    reconstruct............
    languages do not always
    split............ .......... ............
    ............
    they are boring, since they only
    model the vertical aspects of
    language history ............
    Waves are bad, because
    nobody knows how to
    reconstruct them
    16 / 52

    View Slide

  52. Prolog Language History
    Modeling Language History: Networks
    Trees are bad, because...
    they are difficult to
    reconstruct............
    languages do not always
    split............ .......... ............
    ............
    they are boring, since they only
    model the vertical aspects of
    language history ............
    Waves are bad, because
    nobody knows how to
    reconstruct them
    languages still diverge, even if
    not necessarily in split
    processes
    16 / 52

    View Slide

  53. Prolog Language History
    Modeling Language History: Networks
    Trees are bad, because...
    they are difficult to
    reconstruct............
    languages do not always
    split............ .......... ............
    ............
    they are boring, since they only
    model the vertical aspects of
    language history ............
    Waves are bad, because
    nobody knows how to
    reconstruct them
    languages still diverge, even if
    not necessarily in split
    processes
    they are boring, since they only
    model the horizontal aspects of
    language history
    16 / 52

    View Slide

  54. Prolog Language History
    Modeling Language History: Networks
    Hugo Schuchardt
    (1842-1927)
    17 / 52

    View Slide

  55. Prolog Language History
    Modeling Language History: Networks
    Hugo Schuchardt
    (1842-1927)
    “We connect the branches and twigs
    of the tree with countless horizon-
    tal lines and it ceases to be a tree.”
    (Schuchardt 1870 [1900]: 11)
    17 / 52

    View Slide

  56. Prolog Language History
    Phylogenetic Networks
    18 / 52

    View Slide

  57. Prolog Language History
    Phylogenetic Networks
    18 / 52

    View Slide

  58. Biological Approaches in Historical Linguistics
    Biological Approaches
    in
    Historical Linguistics
    19 / 52

    View Slide

  59. Biological Approaches in Historical Linguistics Keys to the Past
    Keys to the Past
    The Geological Evidences
    of
    The Antiquity of Man
    with Remarks on Theories of
    The Origin of Species by Variation
    By Sir Charles Lyell
    London
    John Murray, Albemarle Street
    1863
    20 / 52

    View Slide

  60. Biological Approaches in Historical Linguistics Keys to the Past
    Keys to the Past
    If we new not-
    hing of the existence
    of Latin, - if all
    historical documents
    previous to the fin-
    teenth century had
    been lost, - if tra-
    dition even was si-
    lent as to the former
    existance of a Ro-
    man empire, a me-
    re comparison of the
    Italian, Spanish,
    Portuguese, French,
    Wallachian, and
    Rhaetian dialects
    would enable us to
    say that at some
    time there must ha-
    ve been a language,
    from which these
    six modern dialects
    derive their origin
    in common.
    20 / 52

    View Slide

  61. Biological Approaches in Historical Linguistics Keys to the Past
    Keys to the Past: Uniformitarianism (C. Lyell)
    21 / 52

    View Slide

  62. Biological Approaches in Historical Linguistics Keys to the Past
    Keys to the Past: Uniformitarianism (C. Lyell)
    Uniformity of Change: Laws of change are uniform. They have
    applied in the past as they apply now and will apply in the future,
    no matter at which place.
    21 / 52

    View Slide

  63. Biological Approaches in Historical Linguistics Keys to the Past
    Keys to the Past: Uniformitarianism (C. Lyell)
    Uniformity of Change: Laws of change are uniform. They have
    applied in the past as they apply now and will apply in the future,
    no matter at which place.
    Graduality of Change: Change proceeds gradually, not abrupt.
    21 / 52

    View Slide

  64. Biological Approaches in Historical Linguistics Keys to the Past
    Keys to the Past: Uniformitarianism (C. Lyell)
    Uniformity of Change: Laws of change are uniform. They have
    applied in the past as they apply now and will apply in the future,
    no matter at which place.
    Graduality of Change: Change proceeds gradually, not abrupt.
    Abductive Reasoning: We can infer past events and processes
    by investigating patterns observed in the present, which becomes
    the “key to the interpretation of some mystery in the archives of
    remote ages” (Lyell 1830: 165)
    21 / 52

    View Slide

  65. Biological Approaches in Historical Linguistics Keys to the Past
    Keys to the Past: Uniformitarianism (A. Schleicher)
    Language Change
    is a gradual process (Schleicher 1848: 25).
    is a law-like process (Schleicher 1848: 25).
    is a natural process which occurs in all languages (Schleicher
    1848: 25).
    universal process which occurs in all times (Schleicher
    1863[1873]: 10f).
    allows us to infer past processes and extinct languages by
    investigating the languages of the present (see Schleicher 1848:
    25).
    22 / 52

    View Slide

  66. Biological Approaches in Historical Linguistics Keys to the Past
    Keys to the Past: Summary
    It was not the direct exchange of ideas that lead to the de-
    velopment of similar approaches in biology and linguistics,
    but the astonishing fact that scholars in both fields would
    at about the same time detect striking parallels between
    both disciplines, both regarding their theoretical founda-
    tions and the processes they were investigating.
    23 / 52

    View Slide

  67. Biological Approaches in Historical Linguistics Keys to the Past
    Keys to the Past: Summary
    It was not the direct exchange of ideas that lead to the de-
    velopment of similar approaches in biology and linguistics,
    but the astonishing fact that scholars in both fields would
    at about the same time detect striking parallels between
    both disciplines, both regarding their theoretical founda-
    tions and the processes they were investigating.
    And linguists were the first to draw trees!
    23 / 52

    View Slide

  68. Biological Approaches in Historical Linguistics Keys to the Past
    Keys to the Past: Summary
    1700 1800
    1750 1850
    List et al. (in preparation)
    Stiernhielm's
    Lingua Nova
    1671
    Gallet's
    Arbre
    ca. 1800
    Darwin's
    Origins
    1859
    De Buffon's
    Table
    1755
    Schleicher's
    Stammbaum
    1853
    Darwin's
    Tree Sketch
    1837
    Lamarck's
    Tableaux
    1809
    Čelakovský's
    Rodový Kmen
    1853
    Rühling's
    Tabula
    1774
    Hicke's
    Affinitas
    1689
    Schottels's
    Tabelle
    1663
    24 / 52

    View Slide

  69. 25 / 52

    View Slide

  70. 25 / 52

    View Slide

  71. 25 / 52

    View Slide

  72. 25 / 52

    View Slide

  73. Biological Approaches in Historical Linguistics The Quantitative Turn
    The Quantitative Turn
    “Indo-European and computational cladistics” (Ringe, Warnow and Taylor
    2002)
    “Language-tree divergence times support the Anatolian theory of
    Indo-European origin” (Gray und Atkinson 2003)
    “Language classification by numbers” (McMahon und McMahon 2005)
    “Curious Parallels and Curious Connections: Phylogenetic Thinking in
    Biology and Historical Linguistics” (Atkinson und Gray 2005)
    “Automated classification of the world’s languages” (Brown et al. 2008)
    “Indo-European languages tree by Levenshtein distance” (Serva and
    Petroni 2008)
    “Networks uncover hidden lexical borrowing in Indo-European language
    evolution” (Nelson-Sathi et al. 2011)
    26 / 52

    View Slide

  74. Biological Approaches in Historical Linguistics The Quantitative Turn
    The Quantitative Turn
    “Indo-European and computational cladistics” (Ringe, Warnow and Taylor
    2002)
    “Language-tree divergence times support the Anatolian theory of
    Indo-European origin” (Gray und Atkinson 2003)
    “Language classification by numbers” (McMahon und McMahon 2005)
    “Curious Parallels and Curious Connections: Phylogenetic Thinking in
    Biology and Historical Linguistics” (Atkinson und Gray 2005)
    “Automated classification of the world’s languages” (Brown et al. 2008)
    “Indo-European languages tree by Levenshtein distance” (Serva and
    Petroni 2008)
    “Networks uncover hidden lexical borrowing in Indo-European language
    evolution” (Nelson-Sathi et al. 2011)
    26 / 52

    View Slide

  75. Biological Approaches in Historical Linguistics The Quantitative Turn
    The Quantitative Turn: Words as Genes
    Basic Concept German ID English ID Italian ID French ID
    HAND Hand 1 hand 1 mano 2 main 2
    BLOOD Blut 3 blood 3 sangue 4 sang 4
    HEAD Kopf 5 head 6 testa 7 tête 7
    TOOTH Zahn 8 tooth 8 dente 8 dent 8
    TO SLEEP schlafen 9 sleep 9 dormir 10 dormir 10
    TO SAY sagen 11 say 11 dire 12 dire 12
    ... ... ... ... ... ... ... ... ...
    27 / 52

    View Slide

  76. Biological Approaches in Historical Linguistics The Quantitative Turn
    The Quantitative Turn: Words as Genes
    Basic Concept German ID English ID Italian ID French ID
    HAND Hand 1 hand 1 mano 2 main 2
    BLOOD Blut 3 blood 3 sangue 4 sang 4
    HEAD Kopf 5 head 6 testa 7 tête 7
    TOOTH Zahn 8 tooth 8 dente 8 dent 8
    TO SLEEP schlafen 9 sleep 9 dormir 10 dormir 10
    TO SAY sagen 11 say 11 dire 12 dire 12
    ... ... ... ... ... ... ... ... ...
    27 / 52

    View Slide

  77. Biological Approaches in Historical Linguistics The Quantitative Turn
    The Quantitative Turn: Words as Genes
    ID Proto-Form Basic Concept German English Italian French
    1 PGM *xanda- HAND 1 1 0 0
    2 LAT mānus HAND 0 0 1 1
    3 PGM *blođa- BLOOD 1 1 0 0
    4 LAT sanguis BLOOD 0 0 1 1
    5 PGM *kuppa- HEAD 1 0 0 0
    6 PGM *xawbda- HEAD 0 1 0 0
    7 LAT tēsta HEAD 0 0 1 1
    8 PIE *h3
    dont- TOOTH 1 1 1 1
    9 PGM *slēpan- TO SLEEP 1 1 0 0
    10 LAT dormīre TO SLEEP 0 0 1 1
    11 PGM *sagjan- TO SAY 1 1 0 0
    12 LAT dīcere TO SAY 0 0 1 1
    ... ... ... ... ... ... ...
    27 / 52

    View Slide

  78. Biological Approaches in Historical Linguistics The Quantitative Turn
    The Quantitative Turn: Words as Genes
    English
    111
    German
    101
    French
    000
    Italian
    001
    101 001
    001
    + B
    − C
    +
    A
    Char. English German French Italian
    A 1 1 0 0
    B 1 0 0 0
    C 1 1 0 1
    27 / 52

    View Slide

  79. Biological Approaches in Historical Linguistics The Quantitative Turn
    The Quantitative Turn: Sounds as Nuclein Bases
    Concept
    German
    English
    Italian
    French
    “HAND” G E I F
    Hand 0 1 2 3
    hand 1 0 2 3
    mano 2 2 0 2
    main 3 3 2 0
    “BLOOD” G E I F
    Blut 0 4 5 4
    blood 4 0 6 5
    sangue 5 6 0 2
    sang 4 5 2 0
    Edit Distances between Orthographic Entries
    28 / 52

    View Slide

  80. Biological Approaches in Historical Linguistics The Quantitative Turn
    The Quantitative Turn: Sounds as Nuclein Bases
    German English Italian French
    German 0 30 60 55
    English 30 0 60 50
    Italian 60 60 0 20
    French 55 50 20 0
    28 / 52

    View Slide

  81. Biological Approaches in Historical Linguistics Analogies and Parallels
    Analogies and Parallels
    Parallels between Species and Languages (Pagel 2009)
    aspect species languages
    unit of replication gene word
    replication asexual und sexual
    reproduction
    learning
    speciation cladogenesis language split
    forces of change natural selection and
    genetic drift
    social selection and
    trends
    differentiation tree-like tree-like
    29 / 52

    View Slide

  82. Biological Approaches in Historical Linguistics Analogies and Parallels
    Analogies and Parallels
    30 / 52

    View Slide

  83. Biological Approaches in Historical Linguistics Analogies and Parallels
    Analogies and Parallels
    30 / 52

    View Slide

  84. Biological Approaches in Historical Linguistics Analogies and Parallels
    Analogies and Parallels
    Differences between Species and Languages (Geisler & List 2013)
    Aspect Species Languages
    domain Popper’s World I Popper’s World III
    relation between
    form and function
    mechanical arbitrary
    origin monogenesis unclear
    sequence similarity universal (indepen-
    dent of species)
    language-specific
    differentiation tree-like network-like
    31 / 52

    View Slide

  85. Non-Tree-Like Processes in Language Evolution
    Non-Tree-Like Processes
    in Language Evolution
    32 / 52

    View Slide

  86. Non-Tree-Like Processes in Language Evolution
    Non-Tree-Like Processes
    in Language Evolution
    33 / 52

    View Slide

  87. Non-Tree-Like Processes in Language Evolution Background
    Background
    Organizational Complexity in Biological Evolution (E. Bapteste)
    multi-agent
    multi-lineages
    multi-levels
    nested
    interconnected
    34 / 52

    View Slide

  88. Non-Tree-Like Processes in Language Evolution Background
    Background
    Organizational Complexity in Language Evolution
    multi-agent → yes! e.g., dimensions of variation
    multi-lineages → yes! e.g., “chaque mot a son histoire”
    multi-levels → yes! e.g., levels of grammar
    nested → yes! e.g., syntax, morphology
    interconnected → yes! e.g., lexicon and phonology
    34 / 52

    View Slide

  89. Non-Tree-Like Processes in Language Evolution Background
    Background
    1 sound change (no parallel with biology)
    2 semantic change (no parallel with biology)
    3 word formation (protein assembly)
    35 / 52

    View Slide

  90. Non-Tree-Like Processes in Language Evolution Sound Change
    Sound Change: Background
    Meaning Latin Italian
    ‘FEATHER’ pluːma pjuma
    ‘FLAT’ plaːnus pjano
    ‘SQUARE’ plateːa pjaʦːa
    36 / 52

    View Slide

  91. Non-Tree-Like Processes in Language Evolution Sound Change
    Sound Change: Background
    Meaning Latin Italian
    ‘FEATHER’ pluːma pjuma
    ‘FLAT’ plaːnus pjano
    ‘SQUARE’ plateːa pjaʦːa
    l > j
    36 / 52

    View Slide

  92. Non-Tree-Like Processes in Language Evolution Sound Change
    Sound Change: Background
    Meaning Latin Italian
    ‘FEATHER’ pluːma pjuma
    ‘FLAT’ plaːnus pjano
    ‘SQUARE’ plateːa pjaʦːa
    Meaning Latin Italian
    ‘TONGUE’ liŋgua liŋgwa
    ‘MOON’ lu:na luna
    ‘SLOW’ lentus lento
    l > j
    36 / 52

    View Slide

  93. Non-Tree-Like Processes in Language Evolution Sound Change
    Sound Change: Background
    Meaning Latin Italian
    ‘FEATHER’ pluːma pjuma
    ‘FLAT’ plaːnus pjano
    ‘SQUARE’ plateːa pjaʦːa
    Meaning Latin Italian
    ‘TONGUE’ liŋgua liŋgwa
    ‘MOON’ lu:na luna
    ‘SLOW’ lentus lento
    l > j l > l
    36 / 52

    View Slide

  94. Non-Tree-Like Processes in Language Evolution Sound Change
    Sound Change: Background
    Meaning Latin Italian
    ‘FEATHER’ pluːma pjuma
    ‘FLAT’ plaːnus pjano
    ‘SQUARE’ plateːa pjaʦːa
    Meaning Latin Italian
    ‘TONGUE’ liŋgua liŋgwa
    ‘MOON’ lu:na luna
    ‘SLOW’ lentus lento
    l > j l > l
    l > j / p _
    36 / 52

    View Slide

  95. Non-Tree-Like Processes in Language Evolution Sound Change
    Sound Change: Background
    Meaning Latin Italian
    ‘FEATHER’ pluːma pjuma
    ‘FLAT’ plaːnus pjano
    ‘SQUARE’ plateːa pjaʦːa
    Meaning Latin Italian
    ‘TONGUE’ liŋgua liŋgwa
    ‘MOON’ lu:na luna
    ‘SLOW’ lentus lento
    l > j l > l
    l > j / p _
    Not sounds change, sound systems change (Bloomfield 1933)!
    36 / 52

    View Slide

  96. Non-Tree-Like Processes in Language Evolution Sound Change
    Sound Change: Background
    Meaning Latin Italian
    ‘FEATHER’ pluːma pjuma
    ‘FLAT’ plaːnus pjano
    ‘SQUARE’ plateːa pjaʦːa
    Meaning Latin Italian
    ‘TONGUE’ liŋgua liŋgwa
    ‘MOON’ lu:na luna
    ‘SLOW’ lentus lento
    l > j l > l
    l > j / p _
    Not sounds change, sound systems change (Bloomfield 1933)!
    Sound change depends on the context in which the sounds occur!
    36 / 52

    View Slide

  97. Non-Tree-Like Processes in Language Evolution Sound Change
    Sound Change: Background
    Meaning Latin Italian
    ‘FEATHER’ pluːma pjuma
    ‘FLAT’ plaːnus pjano
    ‘SQUARE’ plateːa pjaʦːa
    Meaning Latin Italian
    ‘TONGUE’ liŋgua liŋgwa
    ‘MOON’ lu:na luna
    ‘SLOW’ lentus lento
    l > j l > l
    l > j / p _
    Not sounds change, sound systems change (Bloomfield 1933)!
    Sound change depends on the context in which the sounds occur!
    Sound change largely follows irreversible patterns!
    36 / 52

    View Slide

  98. Non-Tree-Like Processes in Language Evolution Sound Change
    Sound Change: Background
    Cognate List Alignment Correspondence List
    German dünn d ʏ n GER ENG Frequ.
    d θ 3 x
    d d 1 x
    n n 1 x
    m m 1 x
    ŋ ŋ 1 x
    English thin θ ɪ n
    German Ding d ɪ ŋ
    English thing θ ɪ ŋ
    German dumm d ʊ m
    English dumb d ʌ m
    German Dorn d ɔɐ n
    English thorn d ɔː n
    37 / 52

    View Slide

  99. Non-Tree-Like Processes in Language Evolution Sound Change
    Sound Change: Background
    Cognate List Alignment Correspondence List
    German dünn d ʏ n GER ENG Frequ.
    d θ 3 x
    d d 1 x
    n n 1 x
    m m 1 x
    ŋ ŋ 1 x
    English thin θ ɪ n
    German Ding d ɪ ŋ
    English thing θ ɪ ŋ
    German dumm d ʊ m
    English dumb d ʌ m
    German Dorn d ɔɐ n
    English thorn d ɔː n
    37 / 52

    View Slide

  100. Non-Tree-Like Processes in Language Evolution Sound Change
    Sound Change: Background
    Cognate List Alignment Correspondence List
    German dünn d ʏ n GER ENG Frequ.
    d θ 2 x
    d d 1 x
    n n 1 x
    m m 1 x
    ŋ ŋ 1 x
    English thin θ ɪ n
    German Ding d ɪ ŋ
    English thing θ ɪ ŋ
    German dumm d ʊ m
    English dumb d ʌ m
    German Dorn d ɔɐ n
    English thorn d ɔː n
    37 / 52

    View Slide

  101. Non-Tree-Like Processes in Language Evolution Sound Change
    Sound Change: Background
    Cognate List Alignment Correspondence List
    German dünn d ʏ n GER ENG Frequ.
    d θ 2 x
    d d 1 x
    n n 1 x
    m m 1 x
    ŋ ŋ 1 x
    English thin θ ɪ n
    German Ding d ɪ ŋ
    English thing θ ɪ ŋ
    German dumm d ʊ m
    English dumb d ʌ m
    German Dorn d ɔɐ n
    English thorn θ ɔː n
    37 / 52

    View Slide

  102. Non-Tree-Like Processes in Language Evolution Sound Change
    Sound Change: Background
    Cognate List Alignment Correspondence List
    German dünn d ʏ n GER ENG Frequ.
    d θ 3 x
    d d 1 x ?
    n n 2 x
    m m 1 x
    ŋ ŋ 1 x
    English thin θ ɪ n
    German Ding d ɪ ŋ
    English thing θ ɪ ŋ
    German dumm d ʊ m
    English dumb d ʌ m
    German Dorn d ɔɐ n
    English thorn θ ɔː n
    37 / 52

    View Slide

  103. Non-Tree-Like Processes in Language Evolution Sound Change
    Sound Change: Background
    Cognate List Alignment Correspondence List
    German dünn d ʏ n GER ENG Frequ.
    d θ 3 x
    d d 1 x
    n n 2 x
    m m 1 x
    ŋ ŋ 1 x
    English thin θ ɪ n
    German Ding d ɪ ŋ
    English thing θ ɪ ŋ
    German dumm d ʊ m
    English dumb d ʌ m
    German Dorn d ɔɐ n
    English thorn θ ɔː n
    37 / 52

    View Slide

  104. Non-Tree-Like Processes in Language Evolution Sound Change
    Sound Change: Background
    Cognate List Alignment Correspondence List
    German dünn d ʏ n GER ENG Frequ.
    d θ 3 x
    n n 2 x
    ŋ ŋ 1 x
    English thin θ ɪ n
    German Ding d ɪ ŋ
    English thing θ ɪ ŋ
    German Dorn d ɔɐ n
    English thorn θ ɔː n
    German dumm d ʊ m
    English dumb d ʌ m
    37 / 52

    View Slide

  105. Non-Tree-Like Processes in Language Evolution Sound Change
    Sound Change: Characteristics
    38 / 52

    View Slide

  106. Non-Tree-Like Processes in Language Evolution Sound Change
    Sound Change: Characteristics
    • universal • language-specific
    38 / 52

    View Slide

  107. Non-Tree-Like Processes in Language Evolution Sound Change
    Sound Change: Characteristics
    • universal • language-specific
    • limited • widely varying
    38 / 52

    View Slide

  108. Non-Tree-Like Processes in Language Evolution Sound Change
    Sound Change: Characteristics
    • universal • language-specific
    • limited • widely varying
    • constant • mutable
    38 / 52

    View Slide

  109. Non-Tree-Like Processes in Language Evolution Sound Change
    Sound Change: Investigation
    A little experiment...
    data from 8 Bai dialects (Sino-Tibetan language
    spoken in China, Allen 2007)
    cognate (homologous) parts in all words were aligned
    from the sounds, a network was reconstructed,
    showing the frequency in which homologous sounds
    occur in the same column of an alignment
    the network was further clustered using Markov
    clustering (Dongen 2002) for community structure
    39 / 52

    View Slide

  110. Non-Tree-Like Processes in Language Evolution Sound Change
    Sound Change: Investigation
    Luobenzhuo.tɕʰ.T
    Yunlong.tɕʰ.T
    Luobenzhuo.tʂʰ.T
    Eryuan.tɕʰ.T
    Qiliqiao.tʃʰ.T
    Luobenzhuo.ʈʰ.T
    Yunlong.tsʰ.T
    Xiangyun.tsʰ.T
    Jianchuan.k.K
    Heqi.k.K
    Xiangyun.k.K
    Xiangyun.z.S
    Yunlong.k.K
    Xiangyun.kʲ.K
    Qiliqiao.k.K
    Jianchuan.kʰ.K
    Eryuan.kʰ.K
    Lanping.kʰ.K
    Heqi.kʰ.K
    Luobenzhuo.kʰ.K
    Jianchuan.tɕ.T
    Eryuan.kʲ.K
    Luobenzhuo.z.S
    Xiangyun.kʰ.K
    Qiliqiao.kʰ.K
    Yunlong.kʰ.K
    Luobenzhuo.c.K
    Eryuan.kʰʲ.K
    Heqi.tɕ.T
    Qiliqiao.tʃ.T
    Luobenzhuo.dʐ.T
    Eryuan.tɕ.T
    Lanping.tɕ.T
    Luobenzhuo.tʂ.T
    Jianchuan.ts.T
    Eryuan.tʂ.T
    Yunlong.dz.T
    Eryuan.ts.T
    Qiliqiao.tɕ.T
    Yunlong.tɕ.T
    Lanping.ts.T
    Qiliqiao.tɕʰ.T
    Luobenzhuo.tsʰ.T
    Yunlong.dʑ.T
    Heqi.tsʰ.T
    Lanping.tɕʰ.T
    Xiangyun.tɕʰ.T
    Eryuan.tsʰ.T
    Xiangyun.tɕ.T
    Jianchuan.tɕʰ.T
    Heqi.ts.T
    Heqi.tɕʰ.T
    Jianchuan.tsʰ.T
    Xiangyun.ts.T
    Yunlong.ts.T
    Eryuan.z.S
    Luobenzhuo.ʑ.S
    Heqi.j.J
    Qiliqiao.ɲ.N
    Xiangyun.w.W
    Yunlong.ɕ.S
    Qiliqiao.n.N
    Lanping.n.N
    Qiliqiao.j.J
    Yunlong.j.J
    Eryuan.j.J
    Jianchuan.n.N
    Lanping.ʐ.S
    Heqi.z.S
    Luobenzhuo.s.S
    Lanping.ɕ.S
    Yunlong.s.S
    Luobenzhuo.ʐ.S
    Heqi.ɕ.S
    Qiliqiao.ʃ.S
    Xiangyun.s.S
    Eryuan.s.S
    Qiliqiao.s.S
    Heqi.sʰ.S
    Jianchuan.s.S
    Lanping.s.S
    Luobenzhuo.ɕ.S
    Luobenzhuo.k.K
    Lanping.k.K
    Yunlong.ɡ.K
    Luobenzhuo.ʂ.S
    Qiliqiao.z.S
    Luobenzhuo.ɡ.K Eryuan.k.K
    Eryuan.ʂ.S
    Xiangyun.ɕ.S
    Jianchuan.ɕ.S
    Eryuan.ɕ.S
    Eryuan.ʐ.S
    Yunlong.ʃ.S
    Heqi.s.S
    Yunlong.z.S
    Qiliqiao.ɕ.S
    Heqi.ɕʰ.S
    Luobenzhuo.w.W
    Jianchuan.v.W
    Eryuan.w.W
    Xiangyun.j.J
    Lanping.w.W
    Xiangyun.ŋ.N
    Eryuan.v.W
    Yunlong.v.W
    Heqi.v.W
    Luobenzhuo.v.W
    Lanping.v.W
    Luobenzhuo.ŋ.N
    Qiliqiao.v.W
    Yunlong.ɥ.J
    Qiliqiao.w.W
    Eryuan.ɲ.N
    Heqi.ɲ.N
    Xiangyun.n.N
    Luobenzhuo.ɲ.N
    Yunlong.w.W
    Jianchuan.j.J
    Jianchuan.w.W
    Luobenzhuo.j.J
    Heqi.w.W
    Lanping.j.J
    Luobenzhuo.m.M
    Eryuan.ŋ.N
    Yunlong.n.N
    Luobenzhuo.n.N
    Qiliqiao.ɣ.K
    Heqi.n.N
    Yunlong.ɲ.N
    Luobenzhuo.ʔ.H
    Qiliqiao.m.M
    Yunlong.ɣ.K
    Luobenzhuo.ɣ.K
    Yunlong.ʔ.H
    Lanping.ɣ.K
    Luobenzhuo.ɴ.N
    Lanping.ŋ.N
    Heqi.ŋ.N
    Heqi.ɣ.K
    Yunlong.ʁ.R
    Jianchuan.ɣ.K
    Yunlong.ŋ.N
    Qiliqiao.ŋ.N
    Jianchuan.ŋ.N
    Xiangyun.ɣ.K
    Lanping.m.M
    Yunlong.f.P
    Jianchuan.m.M
    Eryuan.n.N
    Xiangyun.f.P
    Xiangyun.m.M
    Eryuan.m.M
    Heqi.m.M
    Heqi.ɔ̃.V Xiangyun.ɔ̃.V
    Lanping.o.V
    Luobenzhuo.ʊ.V Heqi.o.V
    Jianchuan.o.V
    Jianchuan.õ.V
    Lanping.ɔ̃.V
    Xiangyun.ỹ.V
    Yunlong.ɔ.V Heqi.ũ.V
    Lanping.õ.V
    Heqi.ɔ.V Luobenzhuo.ɤ̃.V
    Luobenzhuo.ɤ.V
    Xiangyun.ɤ̃.V
    Jianchuan.ũ.V
    Jianchuan.u.V
    Eryuan.o.V
    Yunlong.ɤ.V
    Lanping.ɔ.V
    Heqi.u.V
    Xiangyun.ũ.V
    Luobenzhuo.a.V
    Lanping.u.V
    Eryuan.ɔ.V
    Yunlong.a.V
    Yunlong.ɯ.V
    Qiliqiao.ɔ.V
    Luobenzhuo.õ.V
    Eryuan.u.V
    Qiliqiao.u.V
    Xiangyun.ɛ̃.V
    Yunlong.ɿ.V
    Xiangyun.a.V
    Luobenzhuo.ɔ.V
    Xiangyun.o.V
    Heqi.ã.V
    Yunlong.u.V
    Qiliqiao.ɯ.V
    Lanping.ã.V
    Lanping.ɯ
    ̃ .V
    Xiangyun.ã.V
    Heqi.õ.V
    Xiangyun.u.V
    Lanping.ɤ.V
    Luobenzhuo.ʊ̃.V
    Eryuan.ɤ.V
    Yunlong.o.V
    Jianchuan.ɤ̃.V
    Qiliqiao.ɤ.V
    Eryuan.²¹.1
    Heqi.⁵⁵.1
    Qiliqiao.²¹.1
    Eryuan.⁴⁴.1
    Eryuan.⁵⁵.1
    Luobenzhuo.³⁵.1
    Heqi.²¹.1
    Jianchuan.²¹.1
    Xiangyun.⁵⁵.1
    Eryuan.l.R
    Xiangyun.l.R
    Jianchuan.l.R
    Xiangyun.x.K
    Yunlong.l.R
    Qiliqiao.l.R
    Luobenzhuo.f.P
    Lanping.l.R
    Jianchuan.³³.1
    Lanping.⁵⁵.1
    Heqi.⁴⁴.1
    Qiliqiao.⁴⁴.1
    Qiliqiao.³³.1
    Eryuan.³³.1
    Xiangyun.³³.1
    Luobenzhuo.χ.K
    Eryuan.x.K
    Eryuan.ɣ.K
    Qiliqiao.x.K
    Heqi.x.K
    Heqi.xʰ.K
    Lanping.x.K
    Jianchuan.x.K
    Luobenzhuo.⁴⁴.1
    Yunlong.³¹.1
    Qiliqiao.³⁵.1
    Luobenzhuo.²¹.1
    Jianchuan.³¹.1
    Lanping.²¹.1 Heqi.³³.1
    Jianchuan.³⁵.1
    Jianchuan.⁴⁴.1
    Yunlong.⁴⁴.1
    Lanping.³¹.1
    Heqi.⁴².1
    Eryuan.⁴².1
    Eryuan.³¹.1
    Lanping.³³.1
    Xiangyun.²¹.1
    Xiangyun.³¹.1
    Lanping.⁴².1
    Xiangyun.⁴⁴.1
    Yunlong.²¹.1
    Jianchuan.⁵⁵.1
    Luobenzhuo.³¹.1 Xiangyun.³⁵.1
    Luobenzhuo.³³.1
    Yunlong.³³.1
    Lanping.⁴⁴.1
    Luobenzhuo.⁵⁵.1
    Yunlong.⁵⁵.1
    Luobenzhuo.⁴².1
    Jianchuan.⁴².1
    Yunlong.⁴².1
    Xiangyun.⁴².1
    Qiliqiao.³¹.1
    Qiliqiao.⁴².1
    Heqi.³¹.1
    Heqi.l.R
    Luobenzhuo.x.K
    Qiliqiao.f.P
    Luobenzhuo.l.R
    Yunlong.x.K
    Yunlong.³⁵.1
    Qiliqiao.⁵⁵.1
    Heqi.³⁵.1
    Eryuan.³⁵.1
    Lanping.³⁵.1
    Luobenzhuo.i.V
    Jianchuan.i.V
    Yunlong.i.V
    Luobenzhuo.ɛ̃.V
    Lanping.i.V
    Heqi.ɤ̃.V
    Jianchuan.ã.V
    Jianchuan.ɛ.V
    Heqi.ɿ.V
    Lanping.ɛ.V
    Luobenzhuo.ã.V
    Heqi.ɑ.V
    Jianchuan.ɿ.V
    Jianchuan.ɯ.V
    Jianchuan.a.V
    Heqi.a.V
    Luobenzhuo.ʅ.V Heqi.ɛ.V
    Luobenzhuo.ĩ.V
    Luobenzhuo.ɯ
    ̃ .V
    Lanping.æ.V
    Xiangyun.ẽ.V
    Qiliqiao.ɛ̃.V
    Heqi.ɛ̃.V
    Qiliqiao.ɛ.V
    Luobenzhuo.e.V
    Xiangyun.ɤ.V
    Luobenzhuo.ɯ.V
    Xiangyun.ɔ.V
    Xiangyun.ɯ.V
    Lanping.ɯ.V
    Eryuan.ɯ.V
    Eryuan.ɿ.V
    Qiliqiao.ɿ.V
    Qiliqiao.a.V
    Xiangyun.ɿ.V
    Lanping.ɿ.V
    Eryuan.a.V
    Luobenzhuo.æ
    ̃ .V
    Lanping.ɛ̃.V
    Heqi.ɯ
    ̃ .V
    Luobenzhuo.æ.V
    Xiangyun.e.V
    Qiliqiao.e.V
    Lanping.ẽ.V
    Eryuan.i.V
    Eryuan.ɛ.V
    Yunlong.e.V
    Jianchuan.ɯ
    ̃ .V
    Yunlong.ɛ.V
    Jianchuan.ẽ.V
    Heqi.e.V
    Luobenzhuo.ɿ.V
    Jianchuan.ɛ̃.V
    Heqi.ɤ.V
    Xiangyun.ɛ.V
    Xiangyun.i.V
    Luobenzhuo.o.V
    Heqi.ɯ.V
    Luobenzhuo.ɔ̃.V
    Luobenzhuo.ɛ.V
    Lanping.a.V
    Qiliqiao.i.V
    Eryuan.pʰ.P
    Lanping.pʰ.P
    Qiliqiao.tʰ.T
    Xiangyun.pʰ.P
    Yunlong.pʰ.P
    Qiliqiao.pʰ.P
    Lanping.t.T
    Eryuan.tʂʰ.T
    Jianchuan.t.T
    Xiangyun.t.T
    Heqi.t.T
    Heqi.p.P
    Qiliqiao.t.T
    Eryuan.t.T
    Luobenzhuo.ts.T
    Luobenzhuo.dʑ.T
    Luobenzhuo.p.P
    Lanping.f.P
    Jianchuan.f.P
    Yunlong.m.M
    Yunlong.t.T
    Yunlong.p.P
    Eryuan.f.P
    Heqi.f.P
    Luobenzhuo.q.K
    Lanping.tsʰ.T
    Luobenzhuo.qʰ.K
    Luobenzhuo.d.T
    Luobenzhuo.ɖ.T
    Qiliqiao.ts.T
    Yunlong.d.T
    Xiangyun.tʰ.T
    Yunlong.tʰ.T
    Lanping.tʰ.T
    Jianchuan.pʰ.P
    Eryuan.tʰ.T
    Jianchuan.tʰ.T
    Heqi.pʰ.P
    Luobenzhuo.b.P
    Jianchuan.p.P
    Qiliqiao.p.P
    Eryuan.p.P
    Luobenzhuo.tʃ.T
    Luobenzhuo.pʰ.P
    Lanping.p.P
    Xiangyun.p.P
    Yunlong.b.P
    Heqi.tʰ.T
    Luobenzhuo.tʃʰ.T
    Luobenzhuo.tʰ.T
    Luobenzhuo.t.T
    Luobenzhuo.ʈ.T
    Luobenzhuo.tɕ.T
    Qiliqiao.tsʰ.T
    Luobenzhuo.cʰ.K
    Luobenzhuo.ỹ.V
    Luobenzhuo.ẽ.V
    Jianchuan.ĩ.V
    Heqi.∼.N
    Lanping.∼.N
    Lanping.ỹ.V
    Heqi.y.V
    Lanping.y.V
    Heqi.ỹ.V
    Jianchuan.ỹ.V
    Jianchuan.y.V
    Xiangyun.y.V
    Luobenzhuo.y.V
    Xiangyun.∼.N
    Jianchuan.ɤ.V
    Xiangyun.ɯ
    ̃ .V
    Luobenzhuo.∼.N
    Luobenzhuo.u.V
    Qiliqiao.o.V
    Heqi.i.V
    Lanping.ũ.V
    Heqi.ẽ.V
    Heqi.ĩ.V
    Lanping.ĩ.V
    Jianchuan.e.V
    Eryuan.e.V
    Lanping.e.V
    Qiliqiao.∼.N
    Xiangyun.ĩ.V
    Luobenzhuo.ɴ̩.N
    tones
    vowels
    consonants
    Jianchuan.∼.N
    Qiliqiao.y.V
    Luobenzhuo.ũ.V
    Eryuan.y.V
    Yunlong.y.V
    40 / 52

    View Slide

  111. Non-Tree-Like Processes in Language Evolution Sound Change
    Sound Change: Investigation
    v
    v
    w
    v
    v
    v
    ɥ
    v
    w
    w
    w
    w
    v
    w w
    e
    e
    e

    e

    ɛ
    ɛ̃

    æ
    ̃
    æ
    e


    e
    e
    ts
    ts
    ts

    ts

    ɖ
    ʈ
    ts
    ts
    c

    ts

    z

    ts

    dz
    ɔ
    ɔ
    o
    ɔ o
    ɔ
    o
    õ
    ɔ̃
    ɔ
    ɔ
    ɔ̃
    o
    ³⁵
    ⁵⁵
    ⁵⁵
    ⁵⁵
    ⁵⁵
    ³⁵
    ⁵⁵
    õ
    o
    ɔ
    ɤ̃
    o
    õ
    ³⁵
    ⁵⁵
    ⁵⁵
    ³⁵
    ³⁵
    ³⁵
    ³⁵
    ³⁵
    t
    t
    t
    d
    t
    t
    t
    d t
    t
    ĩ ɛ
    ɛ̃
    i
    i
    ɛ̃
    i
    ɛ
    ɛ
    ɛ
    ɛ̃
    ɿ
    ɿ
    ɿ
    ɿ
    ɿ
    ɿ
    ʅ
    ɿ
    ɿ
    ɤ
    ʊ
    ɤ
    ɤ
    ɤ̃
    ɤ
    ɤ
    ɤ
    ⁵⁵
    ʁ
    ɣ
    ɣ
    ɣ
    ɣ
    ɣ
    ʔ
    ɣ
    ɣ
    æ
    ɛ
    ɛ
    ɛ
    ɛ̃
    w
    ɛ̃
    ã
    ʊ̃
    ɤ̃
    ɔ̃
    õ
    ɤ
    ɤ̃
    o
    ɯ
    ɯ
    ɯ
    ̃
    ɯ
    ɯ
    ̃
    ɯ
    ̃
    ɯ
    ɯ
    ̃ ɯ
    u
    o
    u
    ũ
    ũ
    i
    i
    ĩ
    i
    a
    a
    e
    a
    a
    ã
    ã

    ĩ
    ĩ
    ĩ
    i
    i

    tʃʰ
    tsʰ
    ʈʰ
    tʂʰ
    tsʰ
    tsʰ tsʰ
    ɯ

    ɯ
    ɯ
    ̃
    ɑ
    ɯ
    u
    u
    ɤ
    u
    u
    u
    u
    ũ
    tsʰ
    tʂʰ
    tsʰ
    tʃʰ
    tsʰ
    tsʰ
    a
    a
    ã
    ã
    a
    ɔ̃
    ŋ
    ŋ
    ŋ
    ŋ
    ŋ
    ŋ
    ŋ
    ɴ
    f
    f
    f
    f
    f
    f
    f
    f
    ²¹
    ²¹
    ²¹
    ²¹
    ²¹
    ²¹
    ³¹
    ²¹
    ɕ
    ɕ
    ɕ
    ɕ
    ɕ
    ɕ
    ɕ
    ɕʰ
    ³³
    ³³
    ³³
    ³³
    ³³
    ³³
    ³³
    tɕʰ
    tɕʰ
    tɕʰ
    tɕʰ
    tɕʰ
    tɕʰ
    tɕʰ
    tɕʰ







    ⁴⁴
    ⁴⁴
    ⁴⁴
    ⁴⁴
    ⁴⁴
    ⁴⁴
    ⁴⁴
    ⁴⁴
    n
    n
    ɲ
    n
    n
    ɲ
    j
    n
    n
    ʔ
    ɲ
    n
    n
    ɲ
    ɲ ʂ
    z
    s
    s
    s
    s
    ɕ
    s
    ʃ
    s
    ʂ
    s
    ʃ

    s
    j
    ʑ
    j
    ɣ
    j
    j
    j
    j
    j
    z
    z
    z
    ʐ
    ʐ
    z
    ʐ

    k
    k
    k
    k
    q
    k
    k

    k
    x
    x
    kʰ x


    y

    y
    y
    ³³
    p
    y
    ²¹
    y
    ũ



    y
    y
    y




    b kʰʲ


    p
    p
    p
    ũ
    p
    p
    p
    p

    b

    χ

    a
    x
    x
    x
    x
    x
    ɡ
    ŋ
    ɡ
    k
    m
    m
    m
    m
    m
    m
    m
    m
    ɴ̩
    ³¹
    ³¹
    ³¹

    ³¹
    ³¹
    ³¹
    ³¹




















    l
    l
    l
    l
    l
    ⁴²
    ⁴²
    ⁴²
    l
    ⁴²
    l
    ⁴²
    ⁴²
    ⁴²
    ⁴²
    l
    40 / 52

    View Slide

  112. Non-Tree-Like Processes in Language Evolution Sound Change
    Sound Change: Investigation
    v
    v
    w
    v
    v
    v
    ɥ
    v
    w
    w
    w
    w
    v
    w w
    e
    e
    e

    e

    ɛ
    ɛ̃

    æ
    ̃
    æ
    e


    e
    e
    ts
    ts
    ts

    ts

    ɖ
    ʈ
    ts
    ts
    c

    ts

    z

    ts

    dz
    ɔ
    ɔ
    o
    ɔ o
    ɔ
    o
    õ
    ɔ̃
    ɔ
    ɔ
    ɔ̃
    o
    ³⁵
    ⁵⁵
    ⁵⁵
    ⁵⁵
    ⁵⁵
    ³⁵
    ⁵⁵
    õ
    o
    ɔ
    ɤ̃
    o
    õ
    ³⁵
    ⁵⁵
    ⁵⁵
    ³⁵
    ³⁵
    ³⁵
    ³⁵
    ³⁵
    t
    t
    t
    d
    t
    t
    t
    d t
    t
    ĩ ɛ
    ɛ̃
    i
    i
    ɛ̃
    i
    ɛ
    ɛ
    ɛ
    ɛ̃
    ɿ
    ɿ
    ɿ
    ɿ
    ɿ
    ɿ
    ʅ
    ɿ
    ɿ
    ɤ
    ʊ
    ɤ
    ɤ
    ɤ̃
    ɤ
    ɤ
    ɤ
    ⁵⁵
    ʁ
    ɣ
    ɣ
    ɣ
    ɣ
    ɣ
    ʔ
    ɣ
    ɣ
    æ
    ɛ
    ɛ
    ɛ
    ɛ̃
    w
    ɛ̃
    ã
    ʊ̃
    ɤ̃
    ɔ̃
    õ
    ɤ
    ɤ̃
    o
    ɯ
    ɯ
    ɯ
    ̃
    ɯ
    ɯ
    ̃
    ɯ
    ̃
    ɯ
    ɯ
    ̃ ɯ
    u
    o
    u
    ũ
    ũ
    i
    i
    ĩ
    i
    a
    a
    e
    a
    a
    ã
    ã

    ĩ
    ĩ
    ĩ
    i
    i

    tʃʰ
    tsʰ
    ʈʰ
    tʂʰ
    tsʰ
    tsʰ tsʰ
    ɯ

    ɯ
    ɯ
    ̃
    ɑ
    ɯ
    u
    u
    ɤ
    u
    u
    u
    u
    ũ
    tsʰ
    tʂʰ
    tsʰ
    tʃʰ
    tsʰ
    tsʰ
    a
    a
    ã
    ã
    a
    ɔ̃
    ŋ
    ŋ
    ŋ
    ŋ
    ŋ
    ŋ
    ŋ
    ɴ
    f
    f
    f
    f
    f
    f
    f
    f
    ²¹
    ²¹
    ²¹
    ²¹
    ²¹
    ²¹
    ³¹
    ²¹
    ɕ
    ɕ
    ɕ
    ɕ
    ɕ
    ɕ
    ɕ
    ɕʰ
    ³³
    ³³
    ³³
    ³³
    ³³
    ³³
    ³³
    tɕʰ
    tɕʰ
    tɕʰ
    tɕʰ
    tɕʰ
    tɕʰ
    tɕʰ
    tɕʰ







    ⁴⁴
    ⁴⁴
    ⁴⁴
    ⁴⁴
    ⁴⁴
    ⁴⁴
    ⁴⁴
    ⁴⁴
    n
    n
    ɲ
    n
    n
    ɲ
    j
    n
    n
    ʔ
    ɲ
    n
    n
    ɲ
    ɲ ʂ
    z
    s
    s
    s
    s
    ɕ
    s
    ʃ
    s
    ʂ
    s
    ʃ

    s
    j
    ʑ
    j
    ɣ
    j
    j
    j
    j
    j
    z
    z
    z
    ʐ
    ʐ
    z
    ʐ

    k
    k
    k
    k
    q
    k
    k

    k
    x
    x
    kʰ x


    y

    y
    y
    ³³
    p
    y
    ²¹
    y
    ũ



    y
    y
    y




    b kʰʲ


    p
    p
    p
    ũ
    p
    p
    p
    p

    b

    χ

    a
    x
    x
    x
    x
    x
    ɡ
    ŋ
    ɡ
    k
    m
    m
    m
    m
    m
    m
    m
    m
    ɴ̩
    ³¹
    ³¹
    ³¹

    ³¹
    ³¹
    ³¹
    ³¹




















    l
    l
    l
    l
    l
    ⁴²
    ⁴²
    ⁴²
    l
    ⁴²
    l
    ⁴²
    ⁴²
    ⁴²
    ⁴²
    l
    40 / 52

    View Slide

  113. Non-Tree-Like Processes in Language Evolution Sound Change
    Sound Change: Investigation
    n
    n
    n
    n
    n
    j
    j
    j
    j
    j
    ʑ
    j
    ɣ
    j
    j
    ɲ
    n
    n
    n
    ɲ
    ɲ
    ɲ
    ɲ
    ʔ
    40 / 52

    View Slide

  114. Non-Tree-Like Processes in Language Evolution Sound Change
    Sound Change: Investigation
    ²¹
    ²¹
    ²¹
    ²¹
    ²¹
    ²¹
    ²¹
    ³¹
    ²¹
    ³⁵
    ⁵⁵
    ⁵⁵
    ³⁵
    ⁵⁵
    ⁵⁵
    ⁵⁵
    ⁵⁵
    ⁴⁴
    ⁴⁴
    ⁴⁴
    ⁴⁴
    ⁴⁴
    ⁴⁴
    ⁴⁴
    ⁴⁴
    ³³
    ³³
    ³³
    ³³
    ³³
    ³³
    ³³
    ³³
    ³¹
    ³¹
    ³¹
    ³¹
    ³¹
    ³¹
    ³¹
    ⁴²
    ⁴²
    ⁴²
    ⁴²
    ⁴²
    ⁴²
    ⁴²
    ⁴²
    ⁵⁵
    ³⁵
    ³⁵ ³⁵
    ³⁵
    ⁵⁵
    ³⁵
    ³⁵
    40 / 52

    View Slide

  115. Non-Tree-Like Processes in Language Evolution Sound Change
    Sound Change: Investigation
    ²¹
    ²¹
    ²¹
    ²¹
    ²¹
    ²¹
    ²¹
    ³¹
    ²¹
    ³⁵
    ⁵⁵
    ⁵⁵
    ³⁵
    ⁵⁵
    ⁵⁵
    ⁵⁵
    ⁵⁵
    ⁴⁴
    ⁴⁴
    ⁴⁴
    ⁴⁴
    ⁴⁴
    ⁴⁴
    ⁴⁴
    ⁴⁴
    ³³
    ³³
    ³³
    ³³
    ³³
    ³³
    ³³
    ³³
    ³¹
    ³¹
    ³¹
    ³¹
    ³¹
    ³¹
    ³¹
    ⁴²
    ⁴²
    ⁴²
    ⁴²
    ⁴²
    ⁴²
    ⁴²
    ⁴²
    ⁵⁵
    ³⁵
    ³⁵ ³⁵
    ³⁵
    ⁵⁵
    ³⁵
    ³⁵
    44
    35/55
    31
    42
    33
    21
    40 / 52

    View Slide

  116. Non-Tree-Like Processes in Language Evolution Sound Change
    Sound Change: Chances/Challenges
    so far, we only explore, we do not yet analyse the patterns
    as a next step, we need to start thinking about ways to infer
    potential directions of changes
    we also need to find more rigorous ways to handle the context of
    change patterns, as context is one of the major factors conditioning
    sound change
    we only use monopartite networks in this exploration, and do not
    really illustrate which sound occurs in which language
    for a deep analysis, we will need to include the languages in which
    the sounds occur into our analysis need to include the information
    41 / 52

    View Slide

  117. Non-Tree-Like Processes in Language Evolution Semantic Change
    Semantic Change: Background
    hand
    arm
    foot
    day
    m
    eat
    animal
    day
    sand
    moon
    leg
    T₁
    42 / 52

    View Slide

  118. Non-Tree-Like Processes in Language Evolution Semantic Change
    Semantic Change: Background
    hand
    arm
    foot
    day
    m
    eat
    animal
    day
    sand
    moon
    leg
    T₁
    hand
    arm
    foot
    day
    m
    eat
    animal
    day
    sand
    moon
    leg
    T₂
    42 / 52

    View Slide

  119. Non-Tree-Like Processes in Language Evolution Semantic Change
    Semantic Change: Background
    hand
    arm
    foot
    day
    m
    eat
    animal
    day
    sand
    moon
    leg
    T₂
    ?
    ?
    ?
    42 / 52

    View Slide

  120. Non-Tree-Like Processes in Language Evolution Semantic Change
    Semantic Change: Background
    hand
    arm
    foot
    day
    m
    eat
    animal
    day
    sand
    moon
    leg
    T₂
    hand
    arm
    foot
    day
    m
    eat
    animal
    sun
    sand
    moon
    leg
    42 / 52

    View Slide

  121. Non-Tree-Like Processes in Language Evolution Semantic Change
    Semantic Change: Characteristics
    Semantic change plays a crucial role in language change.
    Although most linguists assume that it proceeds according
    to certain general patterns, we currently lack the empirical
    basis to pursue the question in depth. Normally, semantic
    change proceeds by cumulation and reduction.
    43 / 52

    View Slide

  122. Non-Tree-Like Processes in Language Evolution Semantic Change
    Semantic Change: Characteristics
    German “head”
    Kopf .
    k ɔ p͡f
    Pre-German “head”
    *kop –
    k ɔ p “vessel”
    Proto-
    Germanic
    *kuppa-
    k u pː a “vessel”
    POLYSEMY
    PHASE
    FORM MEANING
    MONOSEMY
    PHASE
    MONOSEMY
    PHASE
    CUMULATION
    REDUCTION
    43 / 52

    View Slide

  123. Non-Tree-Like Processes in Language Evolution Semantic Change
    Semantic Change: Characteristics
    “cup”
    CONTEST
    TROPHY
    [kʌp] CUP
    English polysemy structure for cup
    43 / 52

    View Slide

  124. Non-Tree-Like Processes in Language Evolution Semantic Change
    Semantic Change: Characteristics
    “head, cup”
    CUP
    HEAD
    [kɔp] TOP
    Dutch polysemy structure for kop
    43 / 52

    View Slide

  125. Non-Tree-Like Processes in Language Evolution Semantic Change
    Semantic Change: Characteristics
    “head”
    HEAD
    TOP
    [kɔp͡f] CHIEF
    German polysemy structure for Kopf
    43 / 52

    View Slide

  126. Non-Tree-Like Processes in Language Evolution Semantic Change
    Semantic Change: Investigation
    Key Concept Russian German ...
    1.1 world mir, svet Welt ...
    1.21 earth, land zemlja Erde, Land ...
    1.212 ground, soil počva Erde, Boden ...
    1.420 tree derevo Baum ...
    1.430 wood derevo Wald ...
    ... ... ... ... ...
    44 / 52

    View Slide

  127. Non-Tree-Like Processes in Language Evolution Semantic Change
    Semantic Change: Investigation
    CLICS: Crosslinguistic Colexifications
    - 221 Languages
    - 64 language families
    - 1280 concepts
    - 301,498 words
    - 45,667 polysemies (colexifications)
    - 16,239 different links between concepts
    - http://clics.lingpy.org
    44 / 52

    View Slide

  128. Non-Tree-Like Processes in Language Evolution Semantic Change
    Semantic Change: Investigation
    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
    44 / 52

    View Slide

  129. Non-Tree-Like Processes in Language Evolution Semantic Change
    Semantic Change: Investigation
    Concept "money" is part of a cluster with the central concept "fishscale" with a total of 10 nodes. Hover over
    forms for each link. Click on the forms to check their sources. Click HERE to export the current network.
    ty: Line weights: Coloring: Family
    silver
    leather
    fishscale
    bark
    coin
    fur
    snail
    skin, hide
    money
    shell
    49 links for "silver" and "money":
    Language Family Form
    1. Ignaciano Arawakan ne
    2. Aymara, Central Aymaran ḳulʸḳi
    3. Tsafiki Barbacoan kaˈla
    4. Seselwa Creole French Creole larzan
    5. Miao, White Hmong-Mien nyiaj
    6. Breton Indo-European arhant
    7. French Indo-European argent
    8. Gaelic, Irish Indo-European airgead
    9. Welsh Indo-European arian
    10. Cofán Isolate koriΦĩʔdi
    44 / 52

    View Slide

  130. Non-Tree-Like Processes in Language Evolution Semantic Change
    Semantic Change: Investigation
    Concept "wheel" is part of a cluster with the central concept "leg" with a total of 11 nodes. Hover over the e
    each link. Click on the forms to check their sources. Click HERE to export the current network.
    ity: Line weights: Coloring: Geolocation
    sphere, ball
    round
    footprint
    foot
    calf of leg
    circle
    thigh
    wheel
    leg
    hip
    buttocks
    6 links for "foot" and "wheel":
    Language Family Form
    1. Cofán Isolate c̷ɨʔtʰe
    2. Puinave Isolate sim
    3. Yaminahua Panoan taɨ
    4. Wayampi Tupi pɨ
    5. Pumé Unclassified taɔ
    6. Ninam Yanomam mãhuk
    44 / 52

    View Slide

  131. Non-Tree-Like Processes in Language Evolution Semantic Change
    Semantic Change: Chances/Challenges
    so far, we use monopartite networks for our modeling and rather
    simple community-detection algorithms,
    as a result, we loose signal, since words do not change their
    meaning in isolation, but we know that semantic change is often
    interconnected: the change of the meaning in one word goes along
    with changes in other words
    bipartite networks seem to be a straightforward way to model our
    networks to account for interdependencies
    we only compare the meanings of words in isolation, but we know
    that the meaning of a word can be compositional, involving
    complex structures of denotation (compare “apple tree”,
    “grandfather”, etc.)
    by investigating partial colexifications (partial polysemy) we may
    gain new insights into the roads of perception and denotation
    45 / 52

    View Slide

  132. Non-Tree-Like Processes in Language Evolution Word Formation
    Word Formation: Background
    46 / 52

    View Slide

  133. Non-Tree-Like Processes in Language Evolution Word Formation
    Word Formation: Background
    One beer please! A beer for me!
    Beer? Please?
    You have beer?
    I'm thirsty, but I do
    not drink water, can
    you help me?
    I want the same as
    everybody else
    here.
    46 / 52

    View Slide

  134. Non-Tree-Like Processes in Language Evolution Word Formation
    Word Formation: Background
    46 / 52

    View Slide

  135. Non-Tree-Like Processes in Language Evolution Word Formation
    Word Formation: Background
    46 / 52

    View Slide

  136. Non-Tree-Like Processes in Language Evolution Word Formation
    Word Formation: Background
    Tokens Units Relations Levels
    sounds phonemes phonotactics phonemics
    words morphemes morpho-tactics morphemics
    sentences constructions grammatical syntax
    47 / 52

    View Slide

  137. Non-Tree-Like Processes in Language Evolution Word Formation
    Word Formation: Background
    English steam train
    German Dampfzug (steam + train)
    Chinese huǒ chē (fire + vehicle)
    Russian parovoz (steam + driver)
    French locomotive à vapeur (locomotive + with +
    steam)
    47 / 52

    View Slide

  138. Non-Tree-Like Processes in Language Evolution Word Formation
    Word Formation: Background
    We can think of many different ways of how to express a
    certain meaning, but although the potential is virtually un-
    limited, the roads of denotation, that is, the mechanisms by
    which words are formed from morphemes, follow certain re-
    curring patterns across all languages. Comparing these pat-
    terns can give us important insights into human cognition.
    47 / 52

    View Slide

  139. Non-Tree-Like Processes in Language Evolution Word Formation
    Word Formation: Background
    On the other hand, the fact that words are often formed from
    smaller parts, be it by compounding existing words, or us-
    ing specific morphemes to derive new words, makes it very
    difficult to identify homologous words automatically!
    What are the mechanisms by which the roads of
    denotation are created across the worlds languages?
    How can we distinguish direct homologues
    (orthologues) from indirect ones (partial homologues,
    etc.) in phylogenetic models or homologue detection?
    47 / 52

    View Slide

  140. Non-Tree-Like Processes in Language Evolution Word Formation
    Word Formation: Background
    'soh₂-wl̩- sh₂uˈen-
    SUN
    Indo-European
    48 / 52

    View Slide

  141. Non-Tree-Like Processes in Language Evolution Word Formation
    Word Formation: Background
    'soh₂-wl̩- sh₂uˈen-
    SUN
    Indo-European
    soːwel- sunːoː-
    SUN
    Germanic
    48 / 52

    View Slide

  142. Non-Tree-Like Processes in Language Evolution Word Formation
    Word Formation: Background
    'soh₂-wl̩- sh₂uˈen-
    SUN
    Indo-European
    soːwel- sunːoː-
    SUN
    Germanic
    zɔnə
    SUN
    German
    suːl
    SUN
    Swedish
    48 / 52

    View Slide

  143. Non-Tree-Like Processes in Language Evolution Word Formation
    Word Formation: Background
    'soh₂-wl̩- sh₂uˈen-
    SUN
    Indo-European
    soːwel- sunːoː-
    SUN
    Germanic
    soːl-
    SUN
    Romance
    zɔnə
    SUN
    German
    suːl
    SUN
    Swedish
    48 / 52

    View Slide

  144. Non-Tree-Like Processes in Language Evolution Word Formation
    Word Formation: Background
    'soh₂-wl̩- sh₂uˈen-
    SUN
    Indo-European
    soːwel- sunːoː-
    SUN
    Germanic
    soːl-
    SUN
    soːlikul-
    SMALL SUN
    Romance
    zɔnə
    SUN
    German
    suːl
    SUN
    Swedish
    48 / 52

    View Slide

  145. Non-Tree-Like Processes in Language Evolution Word Formation
    Word Formation: Background
    'soh₂-wl̩- sh₂uˈen-
    SUN
    Indo-European
    soːwel- sunːoː-
    SUN
    Germanic
    soːl-
    SUN
    soːlikul-
    SMALL SUN
    Romance
    solej
    SUN
    French
    sol
    SUN
    Spanish
    zɔnə
    SUN
    German
    suːl
    SUN
    Swedish
    48 / 52

    View Slide

  146. Non-Tree-Like Processes in Language Evolution Word Formation
    Word Formation: Background
    'soh₂-wl◌̩
    - sh₂uˈen-
    SUN
    Indo-European
    soːwel- sunːoː-
    SUN
    Germanic
    soːl-
    SUN
    soːlikul-
    SMALL SUN
    Romance
    solej
    SUN
    French
    sol
    SUN
    Spanish
    zɔnə
    SUN
    German
    suːl
    SUN
    Swedish
    SEM
    ANTIC
    SHIFT
    M
    O
    RPH
    O
    LO
    G
    ICAL
    CH
    AN
    G
    E
    M
    O
    R
    PH
    O
    LO
    G
    ICA
    L
    CH
    A
    N
    G
    E
    MORPHOLOGICAL
    CHANGE
    MORPHOLOGICAL
    CHANGE
    48 / 52

    View Slide

  147. Non-Tree-Like Processes in Language Evolution Word Formation
    Word Formation: Background
    Italian
    dare
    French
    donner
    Indo-European
    *deh₃-
    *deh₃-no-
    Latin
    dare
    dōnum
    dōnāre
    Italian
    sole
    French
    soleil
    Swedish
    sol
    German
    Sonne
    Germanic
    *sōwel-
    *sunnō-
    Latin
    sol
    soliculus
    Indo-European
    *sóh₂-wl̩ -
    *sh₂én-
    A B
    48 / 52

    View Slide

  148. Non-Tree-Like Processes in Language Evolution Word Formation
    Word Formation: Investigation
    Automatic Detection of Partial Cognates: The Problem
    languages in which words are frequently created by
    compounding the identification of homologous words is
    extremely difficult
    current phylogenetic models cannot handle partial
    homology, and as a result, very important signal is lost
    current methods for automatic homologue detection in
    linguistics also cannot handle partial homologues and
    show a very low accuracy in languages where
    compounding is frequent (especially in the languages
    of South-East Asia)
    49 / 52

    View Slide

  149. Non-Tree-Like Processes in Language Evolution Word Formation
    Word Formation: Investigation
    German m oː n t -
    English m uː n - -
    Danish m ɔː n - ə
    Swedish m oː n - e
    49 / 52

    View Slide

  150. Non-Tree-Like Processes in Language Evolution Word Formation
    Word Formation: Investigation
    German m oː n t -
    English m uː n - -
    Danish m ɔː n - ə
    Swedish m oː n - e
    Fúzhōu ŋ u o ʔ ⁵ - - - - - - - - - -
    Měixiàn ŋ i a t ⁵ - - - - - k u o ŋ ⁴⁴
    Guǎngzhōu j - y t ² l - œ ŋ ²² - - - - -
    Běijīng - y ɛ - ⁵¹ l i ɑ ŋ - - - - - -
    49 / 52

    View Slide

  151. Non-Tree-Like Processes in Language Evolution Word Formation
    Word Formation: Investigation
    German m oː n t -
    English m uː n - -
    Danish m ɔː n - ə
    Swedish m oː n - e
    Fúzhōu ŋ u o ʔ ⁵ - - - - - - - - - -
    Měixiàn ŋ i a t ⁵ - - - - - k u o ŋ ⁴⁴
    Guǎngzhōu j - y t ² l - œ ŋ ²² - - - - -
    Běijīng - y ɛ - ⁵¹ l i ɑ ŋ - - - - - -
    "MOON"
    "MOON"
    "SHINE" "LIGHT"
    49 / 52

    View Slide

  152. Non-Tree-Like Processes in Language Evolution Word Formation
    Word Formation: Investigation
    Automatic Detection of Partial Cognates: The Solution
    use sequence similarity networks to determine the
    similarity between the parts of the words in the data
    apply filters to reduce the edges in the similarity
    networks
    use a community detection algorithm to further
    partition the data into clusters
    49 / 52

    View Slide

  153. Non-Tree-Like Processes in Language Evolution Word Formation
    Word Formation: Investigation
    Fúzhōu ŋuoʔ⁵
    Měixiàn
    ŋiat⁵ 0.44
    kuoŋ⁴⁴ 0.78 0.78
    Wēnzhōu
    y²¹
    ȵ 0.30 0.35 0.67
    ku ³
    ɔ ⁵ 0.80 0.85 0.27 0.67
    vai¹³ 0.85 0.85 0.82 0.73 0.73
    Běijīng y ¹
    ɛ⁵ 0.77 0.84 0.73 0.56 0.56 0.66
    li ŋ¹
    ɑ 0.78 0.78 0.44 0.67 0.82 0.82 0.80
    ŋiat⁵
    kuoŋ⁴⁴
    ŋuoʔ⁵
    ȵy²¹
    yɛ⁵¹
    kuɔ³⁵
    liɑŋ¹
    vai¹³
    ŋiat⁵
    vai¹³
    kuoŋ⁴⁴
    ŋuoʔ⁵
    liɑŋ¹
    yɛ⁵¹
    ȵy²¹
    kuɔ³⁵
    ȵy²¹
    kuɔ³⁵
    ŋiat⁵
    yɛ⁵¹
    liɑŋ¹
    ŋuoʔ⁵
    kuoŋ⁴⁴
    vai¹³
    B C
    D
    A
    49 / 52

    View Slide

  154. Non-Tree-Like Processes in Language Evolution Word Formation
    Word Formation: Investigation
    Fúzhōu ŋuoʔ⁵
    Měixiàn
    ŋiat⁵ 0.44
    kuoŋ⁴⁴ 0.78 0.78
    Wēnzhōu
    y²¹
    ȵ 0.30 0.35 0.67
    ku ³
    ɔ ⁵ 0.80 0.85 0.27 0.67
    vai¹³ 0.85 0.85 0.82 0.73 0.73
    Běijīng y ¹
    ɛ⁵ 0.77 0.84 0.73 0.56 0.56 0.66
    li ŋ¹
    ɑ 0.78 0.78 0.44 0.67 0.82 0.82 0.80
    ŋiat⁵
    kuoŋ⁴⁴
    ŋuoʔ⁵
    ȵy²¹
    yɛ⁵¹
    kuɔ³⁵
    liɑŋ¹
    vai¹³
    ŋiat⁵
    vai¹³
    kuoŋ⁴⁴
    ŋuoʔ⁵
    liɑŋ¹
    yɛ⁵¹
    ȵy²¹
    kuɔ³⁵
    ȵy²¹
    kuɔ³⁵
    ŋiat⁵
    yɛ⁵¹
    liɑŋ¹
    ŋuoʔ⁵
    kuoŋ⁴⁴
    vai¹³
    B C
    D
    A
    49 / 52

    View Slide

  155. Non-Tree-Like Processes in Language Evolution Word Formation
    Word Formation: Investigation
    Fúzhōu ŋuoʔ⁵
    Měixiàn
    ŋiat⁵ 0.44
    kuoŋ⁴⁴ 0.78 0.78
    Wēnzhōu
    y²¹
    ȵ 0.30 0.35 0.67
    ku ³
    ɔ ⁵ 0.80 0.85 0.27 0.67
    vai¹³ 0.85 0.85 0.82 0.73 0.73
    Běijīng y ¹
    ɛ⁵ 0.77 0.84 0.73 0.56 0.56 0.66
    li ŋ¹
    ɑ 0.78 0.78 0.44 0.67 0.82 0.82 0.80
    ŋiat⁵
    kuoŋ⁴⁴
    ŋuoʔ⁵
    ȵy²¹
    yɛ⁵¹
    kuɔ³⁵
    liɑŋ¹
    vai¹³
    ŋiat⁵
    vai¹³
    kuoŋ⁴⁴
    ŋuoʔ⁵
    liɑŋ¹
    yɛ⁵¹
    ȵy²¹
    kuɔ³⁵
    ȵy²¹
    kuɔ³⁵
    ŋiat⁵
    yɛ⁵¹
    liɑŋ¹
    ŋuoʔ⁵
    kuoŋ⁴⁴
    vai¹³
    B C
    D
    A
    49 / 52

    View Slide

  156. Non-Tree-Like Processes in Language Evolution Word Formation
    Word Formation: Investigation
    Fúzhōu ŋuoʔ⁵
    Měixiàn
    ŋiat⁵ 0.44
    kuoŋ⁴⁴ 0.78 0.78
    Wēnzhōu
    y²¹
    ȵ 0.30 0.35 0.67
    ku ³
    ɔ ⁵ 0.80 0.85 0.27 0.67
    vai¹³ 0.85 0.85 0.82 0.73 0.73
    Běijīng y ¹
    ɛ⁵ 0.77 0.84 0.73 0.56 0.56 0.66
    li ŋ¹
    ɑ 0.78 0.78 0.44 0.67 0.82 0.82 0.80
    ŋiat⁵
    kuoŋ⁴⁴
    ŋuoʔ⁵
    ȵy²¹
    yɛ⁵¹
    kuɔ³⁵
    liɑŋ¹
    vai¹³
    ŋiat⁵
    vai¹³
    kuoŋ⁴⁴
    ŋuoʔ⁵
    liɑŋ¹
    yɛ⁵¹
    ȵy²¹
    kuɔ³⁵
    ȵy²¹
    kuɔ³⁵
    ŋiat⁵
    yɛ⁵¹
    liɑŋ¹
    ŋuoʔ⁵
    kuoŋ⁴⁴
    vai¹³
    B C
    D
    A
    49 / 52

    View Slide

  157. Non-Tree-Like Processes in Language Evolution Word Formation
    Word Formation: Investigation
    Fúzhōu ŋuoʔ⁵
    Měixiàn
    ŋiat⁵ 0.44
    kuoŋ⁴⁴ 0.78 0.78
    Wēnzhōu
    y²¹
    ȵ 0.30 0.35 0.67
    ku ³
    ɔ ⁵ 0.80 0.85 0.27 0.67
    vai¹³ 0.85 0.85 0.82 0.73 0.73
    Běijīng y ¹
    ɛ⁵ 0.77 0.84 0.73 0.56 0.56 0.66
    li ŋ¹
    ɑ 0.78 0.78 0.44 0.67 0.82 0.82 0.80
    ŋiat⁵
    kuoŋ⁴⁴
    ŋuoʔ⁵
    ȵy²¹
    yɛ⁵¹
    kuɔ³⁵
    liɑŋ¹
    vai¹³
    ŋiat⁵
    vai¹³
    kuoŋ⁴⁴
    ŋuoʔ⁵
    liɑŋ¹
    yɛ⁵¹
    ȵy²¹
    kuɔ³⁵
    ȵy²¹
    kuɔ³⁵
    ŋiat⁵
    yɛ⁵¹
    liɑŋ¹
    ŋuoʔ⁵
    kuoŋ⁴⁴
    vai¹³
    B C
    D
    A
    49 / 52

    View Slide

  158. Non-Tree-Like Processes in Language Evolution Word Formation
    Word Formation: Investigation
    Automatic Detection of Partial Cognates: The Solution
    with help of sequence similarity networks, we (List,
    Lopez, and Bapteste 2016) have created the first
    algorithm to detect partial cognates (homologues) in
    linguistic data
    our method outperforms traditional methods largely,
    reaching a plus of more than 5% in accuracy on our
    test sets
    the algorithms is also very fast and can be easily
    applied to considerably large datasets
    49 / 52

    View Slide

  159. Non-Tree-Like Processes in Language Evolution Word Formation
    Word Formation: Chances/Challenges
    with our new algorithm for partial cognate detection with help of
    sequence similarity networks, we have opened the door for the fast
    creation of large datasets for language families in historical
    linguistics which could so far not be sufficiently analysed with
    phylogenetic methods
    unfortunately, however, we lack the phylogenetic models to
    sufficiently further analyse the data (in List 2016, it is shown, that
    we need multi-state models in order to handle partial homology
    sufficiently)
    our knowledge about the underlying processes from an
    evolutionary perspective is also not very profound, and we need to
    try to find new ways to study the roads of denotation across the
    languages in the world
    50 / 52

    View Slide

  160. Outlook
    Outlook
    Outlook
    51 / 52

    View Slide

  161. Language evolution is characterized by a large number of
    non-tree-like processes which have triggered the diversity
    of the linguistic diversity we observe today. By reducing the
    investigation of language evolution to the search for phylo-
    genetic trees, we deprive ourselves of an abundance of data
    which can offer new explanations for the development of in-
    dividual language families, universal characteristics of lan-
    guage change, and even universal characteristics of human
    cognition.
    Whether evolutionary processes in biology and linguistics
    are indeed similar is difficult to tell. However, when carefully
    comparing the commonalities, we may find ways to success-
    fully transfer and adapt methods across disciplines, but also
    to gain new insights into overarching processes of evolution.
    52 / 52

    View Slide

  162. 52 / 52

    View Slide

  163. Thanks for your attention!
    52 / 52

    View Slide