WildASR: A Multilingual Diagnostic Benchmark for ASR Robustness.

Multilingual (English, Chinese, Japanese, Korean) diagnostic benchmark evaluating ASR robustness across three out-of-distribution dimensions: environmental degradation (reverberation, noise, clipping), demographic shift (accents, children, older speakers), and linguistic diversity (code-switching, short utterances, incomplete speech). Uses WER for English and CER for CJK languages.

Best published scores.

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Primary

wer · lower is better

Neighbouring benchmarks.

Other Speech Recognition datasets on Codesota.

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• 01A public checkpoint or API endpoint
• 02A reproduction script with frozen commit + seed
• 03Declared evaluation environment (Python, deps)
• 04One row per metric declared by this dataset
• 05A contact so we can follow up on discrepancies