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.
View on arXiv@article{farouq2025_2505.02518,
title={ Bemba Speech Translation: Exploring a Low-Resource African Language },
author={ Muhammad Hazim Al Farouq and Aman Kassahun Wassie and Yasmin Moslem },
journal={arXiv preprint arXiv:2505.02518},
year={ 2025 }
}