Bibliographie complète
LLM-Assisted Rule Based Machine Translation for Low/No-Resource Languages
Type de ressource
Conference Paper
Auteurs/contributeurs
- Coleman, Jared (Author)
- Krishnamachari, Bhaskar (Author)
- Rosales, Ruben (Author)
- Iskarous, Khalil (Author)
- Mager, Manuel (Editor)
- Ebrahimi, Abteen (Editor)
- Rijhwani, Shruti (Editor)
- Oncevay, Arturo (Editor)
- Chiruzzo, Luis (Editor)
- Pugh, Robert (Editor)
- von der Wense, Katharina (Editor)
Title
LLM-Assisted Rule Based Machine Translation for Low/No-Resource Languages
Abstract
We propose a new paradigm for machine translation that is particularly useful for no-resource languages (those without any publicly available bilingual or monolingual corpora): LLM-RBMT (LLM-Assisted Rule Based Machine Translation). Using the LLM-RBMT paradigm, we design the first language education/revitalization-oriented machine translator for Owens Valley Paiute (OVP), a critically endangered Indigenous American language for which there is virtually no publicly available data. We present a detailed evaluation of the translator's components: a rule-based sentence builder, an OVP to English translator, and an English to OVP translator. We also discuss the potential of the paradigm, its limitations, and the many avenues for future research that it opens up.
Date
2024-06
Proceedings Title
Proceedings of the 4th Workshop on Natural Language Processing for Indigenous Languages of the Americas (AmericasNLP 2024)
Place
Mexico City, Mexico
Publisher
Association for Computational Linguistics
Pages
67–87
Accessed
01/08/2024 08:31
Library Catalog
ACLWeb
Référence
Coleman, J., Krishnamachari, B., Rosales, R., & Iskarous, K. (2024). LLM-Assisted Rule Based Machine Translation for Low/No-Resource Languages. In M. Mager, A. Ebrahimi, S. Rijhwani, A. Oncevay, L. Chiruzzo, R. Pugh, & K. von der Wense (Eds.), Proceedings of the 4th Workshop on Natural Language Processing for Indigenous Languages of the Americas (AmericasNLP 2024) (pp. 67–87). Association for Computational Linguistics. https://doi.org/10.18653/v1/2024.americasnlp-1.9
Tâche
Lien vers cette notice