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DonorRank reveals that the right selection of donor languages can drastically enhance zero-shot ASR performance in low-resource contexts, challenging existing heuristics.
Character-noised continued pre-training boosts zero-shot dialect robustness while preserving standard performance, revealing distinct adaptation mechanisms in language models.
