36.2899, Confs: Workshop at SLE 2026: Measuring Cross-linguistic Distances (Germany)

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LINGUIST List: Vol-36-2899. Mon Sep 29 2025. ISSN: 1069 - 4875.

Subject: 36.2899, Confs: Workshop at SLE 2026: Measuring Cross-linguistic Distances (Germany)

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Date: 28-Sep-2025
From: Ian Joo [joo at res.otaru-uc.ac.jp]
Subject: Workshop at SLE 2026: Measuring Cross-linguistic Distances


Workshop at SLE 2026: Measuring Cross-linguistic Distances

Date: 26-Aug-2026 - 29-Aug-2025
Location: Osnabrück, Germany
Contact: Ian Joo
Contact Email: joo at res.otaru-uc.ac.jp
Meeting URL: https://societaslinguistica.eu/sle2026/

Linguistic Field(s): Typology

Submission Deadline: 17-Nov-2025

Background:
To what degree a given variety of human language is similar to or
different from another variety has been a topic of great interest, not
only to linguists but also to the general public. With the advent of
big data and computational tools in language science, we can now
address this perennial question in ways that were not possible or
realistic before. In this proposed workshop, we will venture into the
many dimensions of cross-linguistic distance, the quantifiable degree
of dissimilarity between multiple lects ("language" or "dialect"),
including:
 - Geographical distance. Different varieties of the human language
are used by human groups residing in different geographical spaces. As
such, despite the intangible nature of language, most lects are
definable as belonging to a specific spatial range, at least within a
given time frame. It is thus possible to measure the geographical
distance between two lects, not only for its own sake but also to
compare it to other types of distances.
The most simplistic way of measuring a cross-linguistic geographical
distance is to define a given lect as a dot on a surface, i.e. in
two-dimensional coordinate values, and measure  the linear distance
between two dots. While convenient, this method has the obvious
limitations of (i) limiting the dynamic space of a given lect into a
unifocal location; and (ii) ignoring all the geographical barriers
between two spaces that make human transport more difficult and
non-linear, such as elevated lands, bodies of water, and political
borders. To overcome this simplicity, more sophisticated measures of
geographical distance are needed, taking into consideration not only
the physical distances between two ends but also the human capacity
and willingness to travel those distances.
 - Genealogical distance. By using the traditional historical
comparative method, the lects of a given language family can be
hierarchically classified in terms of when each lect has diverged from
which other lect. This hierarchy, often visualized as a tree, make it
possible the measure how genealogically close a given lect is to its
intrafamilial lect, analogous to measuring how distant a relative is
from a human individual.
Such genealogical distance can be quantified either as a count or
continuous variable, depending on whether the estimated time of
familial divergence is in relative or absolute scale. If the temporal
data of the divergences are only relatively ordered, i.e. if we only
know that lect A has split off from lect B before lect C has from lect
B but not when in history these two splits have happened, we can only
quantify the genealogical distances in terms of the number of
divergences, or "layers". If we do know when they happened, however,
with the aid of non-linguistic data from genetics, archaeology, and
written history, we are able to quantify the genealogical distance as
a continuous variable, weighing each divergence differently in terms
of how far back in time it has happened. Such temporal data, however,
are often unreliable, controversial, or unavailable.
 - Typological distance. Human groups using different lects can come
into contact and develop conduct-induced similarities in their lects.
Such convergence can occur in all linguistic domains, namely
phonology, syntax, and semantics.
  - Phonological distance. Lects can be compared in terms of which
forms they employ to represent concepts. As defined by Joo and Hsu
(accepted), a phonological distance can be intersequential, i.e.
between two phonological sequences, such as between English word man
/mæn/ and its German cognate Mann /man/ (Heeringa 2024, Do and Lai
2021, etc.). It can also be interstructural, i.e. between two
phonological structures, such as between the English phonemic
inventory and the German phonemic inventory (Avram 1964; Eden 2018;
Joo and Hsu accepted, e.g.).
  - Syntactic distance. The increasing number of cross-linguistic
databases encoding morphosyntactic parameters, such as the World Atlas
of Language Structures (WALS, Dryer and Haspelmath 2013) and Grambank
(Skirgård et al. 2023), allow us to quantify the degree of
cross-linguistic grammatical similarity. The parametrical values may
be categorical (e.g. the six possible values of "What is this lect's
basic order of subject, object, and verb?") or binary (e.g. the
logical values of "Is this lect verb-final?").
While the parametrical format is a convenient way to retrieve the
values from descriptive sources and encode them in a comparable
manner, it has some non-negligible limitations. First, the choice of
the parameters is inevitably biased by what aspects of grammar the
designer of the database deems important. The parameters may also bear
different weights, some being more typologically significant than
others, which is difficult to quantify and code into the database.
Moreover, the parameters are also almost always non-independent, such
as the Greenbergian universal of the correlation between word order
and adpositions, which must always be controlled for when using the
parametrical values for distance measurement. Innovative alternatives
are in need in order to overcome and complement such limitations.
  - Semantic distance. Semantic properties, due to their qualitative
and sociocultural nature, are arguably more difficult for quantitative
comparison than syntax and phonology. Recent advances in computational
semantics are helping us to overcome this difficulty. Natural Language
Processing techniques like Word2vec enable the quantification of the
semantic values of lexical items based on collocational data retrieved
from large corpora. Colexification databases, such as the Database of
Cross-Linguistic Colexifications (CLICS, Rzymski et al. 2020), also
allow us to measure the distance between two lects in terms of how
many colexification patterns they share. As computational semantics is
a rapidly growing field, many possibilities await us to measure
semantic distances in various innovative ways.
Call for Papers:
We call for papers that provide new methodologies in measuring any
form of cross-linguistic distances. The distance can be at any scale,
between genealogically distinct lects ("languages") or closely related
ones ("dialects"), and in any domain, such as phonology, syntax,
lexicon, genealogy, geography, chronology, or demographics.
Particularly welcome are studies that compare the distances of
different domains and/or those that compare the distances of the same
domain that employ different methodologies.
Please send your provisional abstract (max. 300 words, not including
the references) to the convener Ian Joo by 17 November 2026:
joo at res.otaru-uc.ac.jp
References:
Avram, Andrei (1964). “Sur la typologie phonologique quantitative [On
the quantiative phonological typology]”. In: Revue roumaine de
Linguistique IX, pp. 131–134.
Do, Youngah and Ryan Ka Yau Lai (2021). “Accounting for lexical tones
when modeling phonological distance”. In: Language 97.1, e39–e67.
Dryer, Matthew S. and Martin Haspelmath, eds. (2013). WALS Online
(v2020.4). Zenodo. url: doi.org/10.5281/zenodo.13950591.
Eden, S. Elizabeth (2018). “Measuring phonological distance between
languages”. PhD thesis. University College London.
Heeringa, Wilbert Jan (2004). “Measuring dialect pronunciation
differences using Levenshtein distance”. PhD thesis. University of
Groningen.
Joo, Ian and Yu-Yin Hsu (accepted). “Phonological distances between
Eurasian lects measured via Phonotacticon 1.0 reveal areal patterns”.
In: Linguistics.
Rzymski, Christoph et al. (2020). “The Database of Cross-Linguistic
Colexifications, reproducible analysis of cross-linguistic
polysemies”. In: Scientific Data 7.1. doi: 10.1038/s41597-019-0341-x.
Skirgård, Hedvig et al. (2023). “Grambank reveals the importance of
genealogical constraints on linguistic diversity and highlights the
impact of language loss”. In: Science Advances 9.16, eadg6175. doi:
10.1126/sciadv.adg6175.



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