KenLM

Cross-lingual transfer from Sinhala improves low-resource Dhivehi ASR

A new arXiv paper investigates cross-lingual transfer learning from Sinhala to improve automatic speech recognition for Dhivehi, a severely low-resource language of the Maldives. Across 17 experiments spanning five transfer paradigms, the best system—continual pre-training on Sinhala followed by Dhivehi fine-tuning with KenLM—achieves 12.89% WER, outperforming the Dhivehi-only baseline by 13.50% WER. A Turkish control experiment confirms that linguistic relatedness, not just additional data, drives the improvement.