Transformed Protoform Reconstruction
Not on the map. Why?
Abstract (arXiv)
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.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 7 of its 36 references that are in the map. First posted on arXiv 4 Jul 2023.
Builds on
7 of 36 references.
References · 7
- 2017Attention Is All You Needcited by 60,361
- 2014On the Properties of Neural Machine Translation: Encoder-Decoder Approachescited by 1,304
- 2019Ab Antiquo: Neural Proto-language Reconstructioncited by 18
- 2018Are Automatic Methods for Cognate Detection Good Enough for Phylogenetic Reconstruction in Historical Linguistics?cited by 15
- 2022A New Framework for Fast Automated Phonological Reconstruction Using Trimmed Alignments and Sound Correspondence Patternscited by 10
- 2022Neural Unsupervised Reconstruction of Protolanguage Word Formscited by 5
- 2020In search of isoglosses: continuous and discrete language embeddings in Slavic historical phonologycited by 3
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2 papers.