Why does handwritten text recognition (HTR) using neural networks struggle with historical documents more than contemporary ones?

💡 Explanation

HTR systems struggle with historical texts because diachronic orthography introduces character combinations and spellings not found in modern training data; therefore, the system misinterprets these unfamiliar forms, rather than being due to purely visual factors like ink or contrast.

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