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arxiv:2505.02518
Bemba Speech Translation: Exploring a Low-Resource African Language
Published on May 5
Abstract
A cascaded speech translation system for low-resource languages using Whisper and NLLB-200 employs data augmentation and synthetic data to improve performance.
AI-generated summary
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.
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