Automating Sound Change Prediction for Phylogenetic Inference: A Tukanoan Case Study
Kalvin Chang, Nathaniel Robinson, Anna Cai, Ting Chen, Annie Zhang, David Mortensen
Abstract
We describe a set of new methods to partially automate linguistic phylogenetic inference given (1) cognate sets with their respective protoforms and sound laws, (2) a mapping from phones to their articulatory features and (3) a typological database of sound changes.We train a neural network on these sound change data to weight articulatory distances between phones and predict intermediate sound change steps between historical protoforms and their modern descendants, replacing a linguistic expert in part of a parsimony-based phylogenetic inference algorithm. In our best experiments on Tukanoan languages, this method produces trees with a Generalized Quartet Distance of 0.12 from a tree that used expert annotations, a significant improvement over other semi-automated baselines. We discuss potential benefits and drawbacks to our neural approach and parsimony-based tree prediction. We also experiment with a minimal generalization learner for automatic sound law induction, finding it less effective than sound laws from expert annotation. Our code is publicly available.- Anthology ID:
- 2023.lchange-1.14
- Volume:
- Proceedings of the 4th Workshop on Computational Approaches to Historical Language Change
- Month:
- December
- Year:
- 2023
- Address:
- Singapore
- Editors:
- Nina Tahmasebi, Syrielle Montariol, Haim Dubossarsky, Andrey Kutuzov, Simon Hengchen, David Alfter, Francesco Periti, Pierluigi Cassotti
- Venue:
- LChange
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 129–142
- Language:
- URL:
- https://aclanthology.org/2023.lchange-1.14
- DOI:
- 10.18653/v1/2023.lchange-1.14
- Cite (ACL):
- Kalvin Chang, Nathaniel Robinson, Anna Cai, Ting Chen, Annie Zhang, and David Mortensen. 2023. Automating Sound Change Prediction for Phylogenetic Inference: A Tukanoan Case Study. In Proceedings of the 4th Workshop on Computational Approaches to Historical Language Change, pages 129–142, Singapore. Association for Computational Linguistics.
- Cite (Informal):
- Automating Sound Change Prediction for Phylogenetic Inference: A Tukanoan Case Study (Chang et al., LChange 2023)
- PDF:
- https://preview.aclanthology.org/corrections-2024-05/2023.lchange-1.14.pdf