Concept

Human-Level Performance as a Proxy for Optimal Error Rate

In cat recognition, because a human can recognize whether a picture contains a cat almost all the time, the ideal error rate achievable by an optimal classifier is nearly 0%. In a speech-recognition task where 14% of audio clips are too noisy or unintelligible for even a human to recognize, even the most optimal speech recognition system might have error around 14%.

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Updated 2026-05-26

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