Most recently, Transformers–which are recurrent-free neural network architectures–
achieved tremendous performances on various Natural Language Processing (NLP) tasks …

Museums, archives, libraries and other cultural heritage institutes maintain large collections
of artefacts, which are valuable knowledge sources for both experts and interested lay …

Text alignment is one of the fundamental techniques text-related domains like natural
language processing, computational linguistics, and digital humanities. It compares two or …

According to a recent Deloitte study, the COVID-19 pandemic continues to place a huge
strain on the global health care sector. Covid-19 has also catalysed digital transformation …

The amount of images with embedded text shared on Online Social Networks (OSNs), such
as Twitter or Facebook has been growing in recent years. It is becoming important to …

Together with critical editions and translations, commentaries are one of the main genres of
publication in literary and textual scholarship, and have a century-long tradition. Yet, the …

We propose a novel approach to OCR post-correction that exploits repeated texts in large
corpora both as a source of noisy target outputs for unsupervised training and as a source of …

This paper aims to evaluate the accuracy of optical character recognition (OCR) systems on
real scanned books. The ground truth e-texts are obtained from the Project Gutenberg …

Text databases have grown tremendously in number, size, and volume over the last few
decades. Optical Character Recognition (OCR) software is used to scan the text and make …

In this paper we introduce a method that significantly reduces the character error rates for
OCR text obtained from OCRopus models trained on early printed books. The method uses …