  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.
