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arXiv Machine Learning By Xu He, Homayoon Beigi

Revisiting Accent Classification with DistilHuBERT: Speaker-Disjoint Evaluation and Cross-Corpus Generalization

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The paper evaluates the robustness of DistilHuBERT for accent classification using speaker‑disjoint splits and cross‑corpus tests with L2‑ARCTIC and other English accent datasets. It finds a large performance gap between in‑corpus and external evaluations, indicating that file‑level tests overestimate accuracy. The study shows that balanced external‑data training performs best, while pseudo‑labeling with confidence filtering is insufficient under domain mismatch.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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