arXiv (All)
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Scrambled text: training Language Models to correct OCR errors using synthetic data
OCR errors are common in digitised historical archives significantly affecting their usability and value. Generative Language Models (LMs) have shown potential for correcting these errors using the context provided by the corrupted text and the broader socio-cultural context, a process called Contex
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