OCR Error Post-Correction with LLMs in Historical Documents: No Free Lunches

Fuente: arXiv
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Main Authors: Kanerva, Jenna, Ledins, Cassandra, Käpyaho, Siiri, Ginter, Filip
Format: Preprint
Published: 2025
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author Kanerva, Jenna
Ledins, Cassandra
Käpyaho, Siiri
Ginter, Filip
author_facet Kanerva, Jenna
Ledins, Cassandra
Käpyaho, Siiri
Ginter, Filip
contents Optical Character Recognition (OCR) systems often introduce errors when transcribing historical documents, leaving room for post-correction to improve text quality. This study evaluates the use of open-weight LLMs for OCR error correction in historical English and Finnish datasets. We explore various strategies, including parameter optimization, quantization, segment length effects, and text continuation methods. Our results demonstrate that while modern LLMs show promise in reducing character error rates (CER) in English, a practically useful performance for Finnish was not reached. Our findings highlight the potential and limitations of LLMs in scaling OCR post-correction for large historical corpora.
format Preprint
id arxiv_https___arxiv_org_abs_2502_01205
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle OCR Error Post-Correction with LLMs in Historical Documents: No Free Lunches
Kanerva, Jenna
Ledins, Cassandra
Käpyaho, Siiri
Ginter, Filip
Computation and Language
Optical Character Recognition (OCR) systems often introduce errors when transcribing historical documents, leaving room for post-correction to improve text quality. This study evaluates the use of open-weight LLMs for OCR error correction in historical English and Finnish datasets. We explore various strategies, including parameter optimization, quantization, segment length effects, and text continuation methods. Our results demonstrate that while modern LLMs show promise in reducing character error rates (CER) in English, a practically useful performance for Finnish was not reached. Our findings highlight the potential and limitations of LLMs in scaling OCR post-correction for large historical corpora.
title OCR Error Post-Correction with LLMs in Historical Documents: No Free Lunches
topic Computation and Language
url https://arxiv.org/abs/2502.01205