30.3429, Books: Information-theoretic causal inference of lexical flow: Dellert

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LINGUIST List: Vol-30-3429. Thu Sep 12 2019. ISSN: 1069 - 4875.

Subject: 30.3429, Books: Information-theoretic causal inference of lexical flow: Dellert

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Date: Thu, 12 Sep 2019 10:47:12
From: Sebastian Nordhoff [Sebastian.Nordhoff at langsci-press.org]
Subject: Information-theoretic causal inference of lexical flow: Dellert

 


Title: Information-theoretic causal inference of lexical flow 
Series Title: Language Variation  

Publication Year: 2019 
Publisher: Language Science Press
	   http://langsci-press.org
	

Book URL: http://langsci-press.org/catalog/book/233 


Author: Johannes Dellert

Electronic: ISBN:  9783961101436 Pages: 385 Price: Europe EURO 0 Comment: Open Access


Abstract:

This volume seeks to infer large phylogenetic networks from phonetically
encoded lexical data and contribute in this way to the historical study of
language varieties. The technical step that enables progress in this case is
the use of causal inference algorithms. Sample sets of words from language
varieties are preprocessed into automatically inferred cognate sets, and then
modeled as information-theoretic variables based on an intuitive measure of
cognate overlap. Causal inference is then applied to these variables in order
to determine the existence and direction of influence among the varieties. The
directed arcs in the resulting graph structures can be interpreted as
reflecting the existence and directionality of lexical flow, a unified model
which subsumes inheritance and borrowing as the two main ways of transmission
that shape the basic lexicon of languages. A flow-based separation criterion
and domain-specific directionality detection criteria are developed to make
existing causal inference algorithms more robust against imperfect cognacy
data, giving rise to two new algorithms. The Phylogenetic Lexical Flow
Inference (PLFI) algorithm requires lexical features of proto-languages to be
reconstructed in advance, but yields fully general phylogenetic networks,
whereas the more complex Contact Lexical Flow Inference (CLFI) algorithm
treats proto-languages as hidden common causes, and only returns hypotheses of
historical contact situations between attested languages. The algorithms are
evaluated both against a large lexical database of Northern Eurasia spanning
many language families, and against simulated data generated by a new model of
language contact that builds on the opening and closing of directional contact
channels as primary evolutionary events. The algorithms are found to infer the
existence of contacts very reliably, whereas the inference of directionality
remains difficult. This currently limits the new algorithms to a role as
exploratory tools for quickly detecting salient patterns in large lexical
datasets, but it should soon be possible for the framework to be enhanced e.g.
by confidence values for each directionality decision.
 



Linguistic Field(s): Computational Linguistics
                     Historical Linguistics


Written In: English  (eng)

See this book announcement on our website: 
http://linguistlist.org/pubs/books/get-book.cfm?BookID=138173




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