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license: apache-2.0 |
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language: |
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- en |
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- fr |
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- de |
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**OCRerrcr** is a small language model specialized for the detection of OCR error. |
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OCRerrcr was trained by Eliot Jones for PleIAs on a sample of 1000 documents with labelled OCR errors from open data documents (Finance Commons) and cultural heritage sources (Common Corpus). |
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To date, OCRerrcr provide the most accurate agnostic OCR error rate estimate. PleIAs has also develop an alternative pipeline for this tasks, [OCRoscope](https://github.com/Pleias/OCRoscope), that scale significantly better but also significantly less accurate, especially for document with fewer mistakes. |
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The name OCRerrcr (instead of OCRerror) is a playful allusion to a common OCR misreading. |
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## Example |
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The following is a low-error example sentence taken from Common Corpus: |
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> They did not approach cer, but turned away and passed irom her presence, filled with sorrow and moved with sympathy, |
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> which her intense emotions seemed to communicate to even these thoughtless young men of the tho plains. |
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And the OCRerrcr detection (with formatting for clarity): |
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> They did not approach \<er\>cer,\</er\> but turned away and passed \<er\>irom\<\/er\> her presence, filled with sorrow and moved with sympathy, |
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> which her intense emotions seemed to communicate to even these thoughtless young men of the \<er\>tho\<\/er\> plains. |
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