TL;DR
This paper reviews recent advances in computational historical linguistics, highlighting methods like genetic relatedness assessment, cognate detection, and phylogenetic inference, demonstrated through reconstructing Proto-Romance words from modern languages.
Contribution
It introduces key research topics in computational historical linguistics and demonstrates their application in reconstructing ancestral language data.
Findings
Successful automatic reconstruction of Proto-Romance word list
Enhanced methods for genetic relatedness and cognate detection
Phylogenetic inference applied to Romance languages
Abstract
Computational approaches to historical linguistics have been proposed since half a century. Within the last decade, this line of research has received a major boost, owing both to the transfer of ideas and software from computational biology and to the release of several large electronic data resources suitable for systematic comparative work. In this article, some of the central research topic of this new wave of computational historical linguistics are introduced and discussed. These are automatic assessment of genetic relatedness, automatic cognate detection, phylogenetic inference and ancestral state reconstruction. They will be demonstrated by means of a case study of automatically reconstructing a Proto-Romance word list from lexical data of 50 modern Romance languages and dialects.
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