Unverified50% confidenceBenchmarkExact time
Academia typically measures OCR quality using Character Error Rate (CER) and Word Error Rate (WER), and these metrics have already approached human-level performance on standard printed-text datasets.
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50%
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Long-term
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10/8/2026
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UnverifiedWord error rate measures the proportion of edit distance between a model's output and the ground-truth transcription, and is the most core accuracy metric.71% similarVerifiedThe formula for Word Error Rate (WER) is (substitutions + deletions + insertions) / total number of words in the reference text, and a lower WER indicates higher transcription quality.70% similarUnverified词错误率WER计算公式为(替换错误数+删除错误数+插入错误数)/参考文本总词数×100%，业界通常将WER<5%视为接近人类水平69% similarUnverified研究者通常使用期望校准误差（ECE）来量化模型的校准程度65% similarUnverifiedThe inconsistency score in the study is calculated as follows: compute pairwise similarities between baseline IPA transcriptions, compute pairwise similarities between corresponding phonetic codes, and take the absolute difference between the two, using normalized edit distance as the similarity measure.64% similar
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