Representing and Computing Uncertainty in Phonological Reconstruction

Abstract

Despite the inherently fuzzy nature of recon- structions in historical linguistics, most schol- ars do not represent their uncertainty when proposing proto-forms. With the increasing success of recently proposed approaches to automating certain aspects of the traditional comparative method, the formal representation of proto-forms has also improved. This for- malization makes it possible to address both the representation and the computation of un- certainty. Building on recent advances in su- pervised phonological reconstruction, during which an algorithm learns how to reconstruct words in a given proto-language relying on previously annotated data, and inspired by im- proved methods for automated word prediction from cognate sets, we present a new framework that allows for the representation of uncertainty in linguistic reconstruction and also includes a workflow for the computation of fuzzy recon- structions from linguistic data.