Ensemble Method for OCR Error Handling in Early-Modern Japanese Texts
Year: 2026
Type: preprint
Abstract: Recently, the digitization of books has been actively promoted to improve accessibility. However, early modern Japanese books published from the Meiji to early Showa era (1868--1935) exhibit numerous characteristics that differ from contemporary publications. Current research continues to advance specialized character--recognition systems for these books. Nevertheless, recognition errors remain prevalent. In this study, we introduce a method for textual error detection and correction in Optical Character Recognition (OCR)--processed early--modern Japanese texts. The proposed approach employs an ensemble framework that integrates a Bidirectional Gated Recurrent Unit (Bi--GRU) model and a dictionary for error detection, alongside BERT for error correction. Evaluation experiments demonstrate that our method achieves an F--measure of \((74.9%)\), outperforms baseline methods, and effectively identifies erroneous characters with high accuracy while minimizing false detections.
Source: Research Square
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7225873152