Abstract
This paper describes our system submission to the International Conference on Spoken Language Translation (IWSLT 2025), low-resource languages track, namely for Bemba-to-English speech translation. We built cascaded speech translation systems based on Whisper and NLLB-200, and employed data augmentation techniques, such as back-translation. We investigate the effect of using synthetic data and discuss our experimental setup.
Cite
CITATION STYLE
Al Farouq, M. H., Wassie, A. K., & Moslem, Y. (2025). Bemba Speech Translation: Exploring a Low-Resource African Language. In IWSLT 2025 - 22nd International Conference on Spoken Language Translation, Proceedings of the Conference (pp. 354–359). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2025.iwslt-1.37
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.