mlsanityData to 14 Oct 2026

Transformed Protoform Reconstruction

arXiv 2307.01896 ↗First posted 4 Jul 2023cs.CLcited by 2

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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

  1. 2017Attention Is All You Needcited by 60,361
  2. 2014On the Properties of Neural Machine Translation: Encoder-Decoder Approachescited by 1,304
  3. 2019Ab Antiquo: Neural Proto-language Reconstructioncited by 18
  4. 2018Are Automatic Methods for Cognate Detection Good Enough for Phylogenetic Reconstruction in Historical Linguistics?cited by 15
  5. 2022A New Framework for Fast Automated Phonological Reconstruction Using Trimmed Alignments and Sound Correspondence Patternscited by 10
  6. 2022Neural Unsupervised Reconstruction of Protolanguage Word Formscited by 5
  7. 2020In search of isoglosses: continuous and discrete language embeddings in Slavic historical phonologycited by 3

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2 papers.