Statistical Learning for OCR Text Correction
Table 2: Confusion matrix for error detection
['-1em [BOLD] Actual Correctness', '[EMPTY]', '[BOLD] Model Detection  [BOLD] Error', '[BOLD] Model Detection  [BOLD] Correct', '[BOLD] total']
The proposed model achieves 91.07% detection recall. There are considerable number of ture-positive errors, which are correct words but detected as errors. When using this type of errors for training or testing, we use the word itself as the intended word for each error.