Towards a token-by-token whole-spectrum approach to sound change using deep learning: A case study of Khmer coda palatalization

Sothornin Mam, Francesco Burroni, Sireemas Maspong


Anthology ID:
2024.paclic-1.120
Volume:
Proceedings of the 38th Pacific Asia Conference on Language, Information and Computation
Month:
December
Year:
2024
Address:
Tokyo, Japan
Editors:
Nathaniel Oco, Shirley N. Dita, Ariane Macalinga Borlongan, Jong-Bok Kim
Venue:
PACLIC
SIG:
Publisher:
Tokyo University of Foreign Studies
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Pages:
1243–1250
Language:
URL:
https://preview.aclanthology.org/fix-sig-urls/2024.paclic-1.120/
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Cite (ACL):
Sothornin Mam, Francesco Burroni, and Sireemas Maspong. 2024. Towards a token-by-token whole-spectrum approach to sound change using deep learning: A case study of Khmer coda palatalization. In Proceedings of the 38th Pacific Asia Conference on Language, Information and Computation, pages 1243–1250, Tokyo, Japan. Tokyo University of Foreign Studies.
Cite (Informal):
Towards a token-by-token whole-spectrum approach to sound change using deep learning: A case study of Khmer coda palatalization (Mam et al., PACLIC 2024)
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https://preview.aclanthology.org/fix-sig-urls/2024.paclic-1.120.pdf