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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
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Prolog
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"All languages change, as long as they exist."
(August Schleicher 1863)
Prolog
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walkman
"All languages change, as long as they exist."
(August Schleicher 1863)
Prolog
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iPod
walkman
"All languages change, as long as they exist."
(August Schleicher 1863)
Prolog
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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
"All languages change, as long as they exist."
(August Schleicher 1863)
Prolog
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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
"All languages change, as long as they exist."
(August Schleicher 1863)
Prolog
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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)
Prolog
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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)
Prolog
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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)
Prolog
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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)
Prolog
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Prolog Background
Background
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Prolog Background
Background
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Prolog Background
Background
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Prolog Background
Background
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Prolog Background
Background
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Prolog Comparative Method
The Comparative Method
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Prolog Comparative Method
The Comparative Method
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Prolog Comparative Method
The Comparative Method
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Prolog Comparative Method
The Comparative Method
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Prolog Comparative Method
The Comparative Method
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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
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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
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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
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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).
.
.
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Prolog Languages
Language as a Diasystem
Standard Language
Diatopic Varieties
Diastratic Varieties
Diaphasic Varieties
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Prolog Languages
Language Variation: Dimensions
LANGUAGE
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Prolog Languages
Language Variation: Dimensions
LANGUAGE
diatopic
place
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Prolog Languages
Language Variation: Dimensions
LANGUAGE
diastratic diatopic
social layer place
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Prolog Languages
Language Variation: Dimensions
LANGUAGE
diastratic diatopic
diaphasic
social layer place
situation
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Prolog Languages
Language Variation: Dimensions
LANGUAGE
diastratic diatopic
diaphasic
diam
esic
social layer place
situation
m
edium
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Prolog Languages
Language Variation: Dimensions
LANGUAGE
diachronic
diastratic diatopic
diaphasic
diam
esic
time
social layer place
situation
m
edium
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Prolog Languages
Language Variation: Dimensions
LANGUAGE
diachronic
diastratic diatopic
diaphasic
diam
esic
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Prolog Languages
Language Variation: Complexity of Borrowing
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Prolog Languages
Language Variation: Complexity of Borrowing
expected Mandarin [ma₅₅po₂₁lou]
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Prolog Languages
Language Variation: Complexity of Borrowing
expected Mandarin [ma₅₅po₂₁lou]
attested Mandarin [wan₅₁paw₂₁lu₅₁]
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Prolog Languages
Language Variation: Complexity of Borrowing
expected Mandarin [ma₅₅po₂₁lou]
attested Mandarin [wan₅₁paw₂₁lu₅₁]
explanation Cantonese [maːn₂₂pow₃₅low₃₂]
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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
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Prolog Language History
Modeling Language History: Dendrophilia
August Schleicher
(1821-1868)
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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)
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Prolog Language History
Modeling Language History: Dendrophilia
Schleicher (1853)
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Prolog Language History
Modeling Language History: Dendrophobia
Johannes Schmidt
(1843-1901)
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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)
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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)
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Prolog Language History
Modeling Language History: Dendrophobia
Schmidt (1875)
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Prolog Language History
Modeling Language History: Dendrophobia
Meillet (1908)
Hirt (1905)
Bloomfield (1933)
Bonfante (1931)
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Prolog Language History
Modeling Language History: Networks
Trees are bad, because...
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Prolog Language History
Modeling Language History: Networks
Trees are bad, because...
they are difficult to
reconstruct............
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Prolog Language History
Modeling Language History: Networks
Trees are bad, because...
they are difficult to
reconstruct............
languages do not always
split............ .......... ............
............
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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 ............
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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
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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
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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
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Prolog Language History
Modeling Language History: Networks
Hugo Schuchardt
(1842-1927)
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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)
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Prolog Language History
Phylogenetic Networks
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Prolog Language History
Phylogenetic Networks
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Biological Approaches in Historical Linguistics
Biological Approaches
in
Historical Linguistics
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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
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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.
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Biological Approaches in Historical Linguistics Keys to the Past
Keys to the Past: Uniformitarianism (C. Lyell)
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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.
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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.
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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)
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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).
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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.
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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!
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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
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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)
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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)
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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
... ... ... ... ... ... ... ... ...
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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
... ... ... ... ... ... ... ... ...
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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
... ... ... ... ... ... ...
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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
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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
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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
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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
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Biological Approaches in Historical Linguistics Analogies and Parallels
Analogies and Parallels
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Biological Approaches in Historical Linguistics Analogies and Parallels
Analogies and Parallels
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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
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Non-Tree-Like Processes in Language Evolution
Non-Tree-Like Processes
in Language Evolution
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Non-Tree-Like Processes in Language Evolution
Non-Tree-Like Processes
in Language Evolution
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Non-Tree-Like Processes in Language Evolution Background
Background
Organizational Complexity in Biological Evolution (E. Bapteste)
multi-agent
multi-lineages
multi-levels
nested
interconnected
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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
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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)
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Non-Tree-Like Processes in Language Evolution Sound Change
Sound Change: Background
Meaning Latin Italian
‘FEATHER’ pluːma pjuma
‘FLAT’ plaːnus pjano
‘SQUARE’ plateːa pjaʦːa
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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
Slide 92
Slide 92 text
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
Slide 93
Slide 93 text
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
Slide 94
Slide 94 text
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
Slide 95
Slide 95 text
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
Slide 96
Slide 96 text
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
Slide 97
Slide 97 text
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
Slide 98
Slide 98 text
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
Slide 99
Slide 99 text
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
Slide 100
Slide 100 text
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
Slide 101
Slide 101 text
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
Slide 102
Slide 102 text
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
Slide 103
Slide 103 text
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
Slide 104
Slide 104 text
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
Slide 105
Slide 105 text
Non-Tree-Like Processes in Language Evolution Sound Change
Sound Change: Characteristics
38 / 52
Slide 106
Slide 106 text
Non-Tree-Like Processes in Language Evolution Sound Change
Sound Change: Characteristics
• universal • language-specific
38 / 52
Slide 107
Slide 107 text
Non-Tree-Like Processes in Language Evolution Sound Change
Sound Change: Characteristics
• universal • language-specific
• limited • widely varying
38 / 52
Slide 108
Slide 108 text
Non-Tree-Like Processes in Language Evolution Sound Change
Sound Change: Characteristics
• universal • language-specific
• limited • widely varying
• constant • mutable
38 / 52
Slide 109
Slide 109 text
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
Slide 110
Slide 110 text
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
Slide 111
Slide 111 text
Non-Tree-Like Processes in Language Evolution Sound Change
Sound Change: Investigation
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Slide 112 text
Non-Tree-Like Processes in Language Evolution Sound Change
Sound Change: Investigation
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40 / 52
Slide 113
Slide 113 text
Non-Tree-Like Processes in Language Evolution Sound Change
Sound Change: Investigation
n
n
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40 / 52
Slide 114
Slide 114 text
Non-Tree-Like Processes in Language Evolution Sound Change
Sound Change: Investigation
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40 / 52
Slide 115
Slide 115 text
Non-Tree-Like Processes in Language Evolution Sound Change
Sound Change: Investigation
²¹
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35/55
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40 / 52
Slide 116
Slide 116 text
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
Slide 117
Slide 117 text
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
Slide 118
Slide 118 text
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
Slide 119
Slide 119 text
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
Slide 120
Slide 120 text
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
Slide 121
Slide 121 text
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
Slide 122
Slide 122 text
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
Slide 123
Slide 123 text
Non-Tree-Like Processes in Language Evolution Semantic Change
Semantic Change: Characteristics
“cup”
CONTEST
TROPHY
[kʌp] CUP
English polysemy structure for cup
43 / 52
Slide 124
Slide 124 text
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
Slide 125
Slide 125 text
Non-Tree-Like Processes in Language Evolution Semantic Change
Semantic Change: Characteristics
“head”
HEAD
TOP
[kɔp͡f] CHIEF
German polysemy structure for Kopf
43 / 52
Slide 126
Slide 126 text
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
Slide 127
Slide 127 text
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
Slide 128
Slide 128 text
Non-Tree-Like Processes in Language Evolution Semantic Change
Semantic Change: Investigation
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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
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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
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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
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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
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Non-Tree-Like Processes in Language Evolution Word Formation
Word Formation: Background
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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.
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Non-Tree-Like Processes in Language Evolution Word Formation
Word Formation: Background
46 / 52
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Non-Tree-Like Processes in Language Evolution Word Formation
Word Formation: Background
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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
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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)
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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.
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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?
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Non-Tree-Like Processes in Language Evolution Word Formation
Word Formation: Background
'soh₂-wl̩- sh₂uˈen-
SUN
Indo-European
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Non-Tree-Like Processes in Language Evolution Word Formation
Word Formation: Background
'soh₂-wl̩- sh₂uˈen-
SUN
Indo-European
soːwel- sunːoː-
SUN
Germanic
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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
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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
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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
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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
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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
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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
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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)
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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
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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 - - - - - -
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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"
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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
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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
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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
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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
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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
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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
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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
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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
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Outlook
Outlook
Outlook
51 / 52
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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.
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Slide 163 text
Thanks for your attention!
52 / 52