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This paper introduces DonorRank, a learning-to-rank framework for selecting effective donor languages in low-resource cross-lingual speech recognition, evaluated on Indic and African language corpora. It demonstrates improved donor selection over genetic-similarity and high-resource heuristics, and provides insights into transfer patterns for multilingual ASR.
This paper investigates LLM-based generative error correction (GER) for low-resource West Frisian ASR, using a contamination-aware evaluation with a private dataset to show that GPT-5.1 reduces errors beyond oracle levels.