Gi2Pi Rule-based, index-preserving grapheme-to-phoneme transformations

Aidan Pine, Patrick William Littell, Eric Joanis, David Huggins-Daines, Christopher Cox, Fineen Davis, Eddie Antonio Santos, Shankhalika Srikanth, Delasie Torkornoo, Sabrina Yu


Abstract
This paper describes the motivation and implementation details for a rule-based, index-preserving grapheme-to-phoneme engine ‘Gi2Pi' implemented in pure Python and released under the open source MIT license. The engine and interface have been designed to prioritize the developer experience of potential contributors without requiring a high level of programming knowledge. ‘Gi2Pi' already provides mappings for 30 (mostly Indigenous) languages, and the package is accompanied by a web-based interactive development environment, a RESTful API, and extensive documentation to encourage the addition of more mappings in the future. We also present three downstream applications of ‘Gi2Pi' and show results of a preliminary evaluation.
Anthology ID:
2022.computel-1.7
Volume:
Proceedings of the Fifth Workshop on the Use of Computational Methods in the Study of Endangered Languages
Month:
May
Year:
2022
Address:
Dublin, Ireland
Venues:
ACL | ComputEL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
52–60
Language:
URL:
https://aclanthology.org/2022.computel-1.7
DOI:
10.18653/v1/2022.computel-1.7
Bibkey:
Cite (ACL):
Aidan Pine, Patrick William Littell, Eric Joanis, David Huggins-Daines, Christopher Cox, Fineen Davis, Eddie Antonio Santos, Shankhalika Srikanth, Delasie Torkornoo, and Sabrina Yu. 2022. Gi22Pi Rule-based, index-preserving grapheme-to-phoneme transformations Rule-based, index-preserving grapheme-to-phoneme transformations. In Proceedings of the Fifth Workshop on the Use of Computational Methods in the Study of Endangered Languages, pages 52–60, Dublin, Ireland. Association for Computational Linguistics.
Cite (Informal):
Gi22Pi Rule-based, index-preserving grapheme-to-phoneme transformations Rule-based, index-preserving grapheme-to-phoneme transformations (Pine et al., ComputEL 2022)
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PDF:
https://aclanthology.org/2022.computel-1.7.pdf