Computational phylogenetics reveal histories of sign languages

Author:

Abner Natasha1ORCID,Clarté Grégoire234ORCID,Geraci Carlo5ORCID,Ryder Robin J.4ORCID,Mertz Justine56,Salgat Anah17ORCID,Yu Shi58ORCID

Affiliation:

1. Department of Linguistics, University of Michigan, Ann Arbor, MI, USA.

2. Finnish Center for Artificial Intelligence, Helsinki, Finland.

3. Department of Computer Science, University of Helsinki, Helsinki, Finland.

4. Centre de Recherche en Mathématiques de la Décision (CEREMADE), CNRS, UMR 7534, Université Paris-Dauphine, PSL University, Paris, France.

5. Département d’Études Cognitives, Institut Jean-Nicod (ENS-EHESS-CNRS), PSL University, Paris, France.

6. Laboratoire de Linguistique Formelle, CNRS, UMR 7110, Université Paris Cité, Paris, France.

7. School of Medicine, Wayne State University, Detroit, MI, USA.

8. Laboratoire de Phonétique et Phonologie, UMR 7018, CNRS, Université Sorbonne Nouvelle Paris 3, Paris, France.

Abstract

Sign languages are naturally occurring languages. As such, their emergence and spread reflect the histories of their communities. However, limitations in historical recordkeeping and linguistic documentation have hindered the diachronic analysis of sign languages. In this work, we used computational phylogenetic methods to study family structure among 19 sign languages from deaf communities worldwide. We used phonologically coded lexical data from contemporary languages to infer relatedness and suggest that these methods can help study regular form changes in sign languages. The inferred trees are consistent in key respects with known historical information but challenge certain assumed groupings and surpass analyses made available by traditional methods. Moreover, the phylogenetic inferences are not reducible to geographic distribution but do affirm the importance of geopolitical forces in the histories of human languages.

Publisher

American Association for the Advancement of Science (AAAS)

Subject

Multidisciplinary

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