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Acoustic domain shift in spoken language identification from systematic domain generalization evaluation to real-world application
Domain Generalization (DG) aims to develop models that remain robust to conditions unseen during training. While DG has been systematically studied in computer vision through controlled benchmarks and diverse distribution shifts, its evaluation in spoken language recognition remains less structured.
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