Deciphering Undersegmented Ancient Scripts Using Phonetic Prior

Jiaming Luo, Frederik Hartmann, Enrico Santus, Regina Barzilay, Yuan Cao

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
Anthology ID:
2021.tacl-1.5
Volume:
Transactions of the Association for Computational Linguistics, Volume 9
Month:
Year:
2021
Address:
Cambridge, MA
Editors:
Brian Roark, Ani Nenkova
Venue:
TACL
SIG:
Publisher:
MIT Press
Note:
Pages:
69–81
Language:
URL:
https://aclanthology.org/2021.tacl-1.5
DOI:
10.1162/tacl_a_00354
Bibkey:
Cite (ACL):
Jiaming Luo, Frederik Hartmann, Enrico Santus, Regina Barzilay, and Yuan Cao. 2021. Deciphering Undersegmented Ancient Scripts Using Phonetic Prior. Transactions of the Association for Computational Linguistics, 9:69–81.
Cite (Informal):
Deciphering Undersegmented Ancient Scripts Using Phonetic Prior (Luo et al., TACL 2021)
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PDF:
https://preview.aclanthology.org/nschneid-patch-5/2021.tacl-1.5.pdf
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