Transformed Protoform Reconstruction
Abstract
Protoform reconstruction is the task of inferring what morphemes or words appeared like in the ancestral languages of a set of daughter languages. Meloni et al. (2021) achieved the state-of-the-art on Latin protoform reconstruction with an RNN-based encoder-decoder with attention model. We update their model with the state-of-the-art seq2seq model: the Transformer. Our model outperforms their model on a suite of different metrics on two different datasets: their Romance data of 8,000 cognates spanning 5 languages and a Chinese dataset (Hou 2004) of 800+ cognates spanning 39 varieties. We also probe our model for potential phylogenetic signal contained in the model. Our code is publicly available at https://github.com/cmu-llab/acl-2023.
Cite
@article{arxiv.2307.01896,
title = {Transformed Protoform Reconstruction},
author = {Young Min Kim and Kalvin Chang and Chenxuan Cui and David Mortensen},
journal= {arXiv preprint arXiv:2307.01896},
year = {2023}
}
Comments
Accepted at ACL 2023