Enhancing Translation for Indigenous Languages: Experiments with Multilingual Models
Atnafu Lambebo Tonja, Hellina Hailu Nigatu, Olga Kolesnikova, Grigori Sidorov, Alexander Gelbukh, Jugal Kalita
Abstract
This paper describes CIC NLP’s submission to the AmericasNLP 2023 Shared Task on machine translation systems for indigenous languages of the Americas. We present the system descriptions for three methods. We used two multilingual models, namely M2M-100 and mBART50, and one bilingual (one-to-one) — Helsinki NLP Spanish-English translation model, and experimented with different transfer learning setups. We experimented with 11 languages from America and report the setups we used as well as the results we achieved. Overall, the mBART setup was able to improve upon the baseline for three out of the eleven languages.- Anthology ID:
- 2023.americasnlp-1.22
- Volume:
- Proceedings of the Workshop on Natural Language Processing for Indigenous Languages of the Americas (AmericasNLP)
- Month:
- July
- Year:
- 2023
- Address:
- Toronto, Canada
- Venue:
- AmericasNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 200–205
- Language:
- URL:
- https://aclanthology.org/2023.americasnlp-1.22
- DOI:
- Cite (ACL):
- Atnafu Lambebo Tonja, Hellina Hailu Nigatu, Olga Kolesnikova, Grigori Sidorov, Alexander Gelbukh, and Jugal Kalita. 2023. Enhancing Translation for Indigenous Languages: Experiments with Multilingual Models. In Proceedings of the Workshop on Natural Language Processing for Indigenous Languages of the Americas (AmericasNLP), pages 200–205, Toronto, Canada. Association for Computational Linguistics.
- Cite (Informal):
- Enhancing Translation for Indigenous Languages: Experiments with Multilingual Models (Tonja et al., AmericasNLP 2023)
- PDF:
- https://preview.aclanthology.org/paclic-22-ingestion/2023.americasnlp-1.22.pdf