Deciphering Undersegmented Ancient Scripts Using Phonetic Prior
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tacl_a_00354.pdf
Description
Published version
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745.64 KB
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Adobe PDF
Checksum (MD5)
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Author(s)
Luo, Jiaming
Hartmann, Frederik
Santus, Enrico
Barzilay, Regina
Cao, Yuan
Date Issued
2021
Journal
Transactions of the Association for Computational Linguistics
Publisher
MIT Press - Journals
Citation
Luo, Jiaming, Hartmann, Frederik, Santus, Enrico, Barzilay, Regina and Cao, Yuan. 2021. "Deciphering Undersegmented Ancient Scripts Using Phonetic Prior." Transactions of the Association for Computational Linguistics, 9.
Version
Final published version
Abstract
Most undeciphered lost languages exhibit two characteristics that pose significant decipherment challenges: (1) the scripts are not fully segmented into words; (2) the closest known language is not determined. We propose a decipherment model that handles both of these challenges by building on rich linguistic constraints reflecting consistent patterns in historical sound change. We capture the natural phonological geometry by learning character embeddings based on the International Phonetic Alphabet (IPA). The resulting generative framework jointly models word segmentation and cognate alignment, informed by phonological constraints. We evaluate the model on both deciphered languages (Gothic, Ugaritic) and an undeciphered one (Iberian). The experiments show that incorporating phonetic geometry leads to clear and consistent gains. Additionally, we propose a measure for language closeness which correctly identifies related languages for Gothic and Ugaritic. For Iberian, the method does not show strong evidence supporting Basque as a related language, concurring with the favored position by the current scholarship. 1
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Terms of Use
Creative Commons Attribution 4.0 International license
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1162/TACL_A_00354
