Attention is an increasingly popular mechanism used in a wide range of neural
architectures. The mechanism itself has been realized in a variety of formats. However …

Optical character recognition (OCR) is one of the most popular techniques used for
converting printed documents into machine-readable ones. While OCR engines can do well …

The optical character recognition (OCR) quality of the historical part of the Finnish
newspaper and journal corpus is rather low for reliable search and scientific research on the …

Recently, Bert-based models have dominated the research of Chinese spelling correction
(CSC). These methods have two limitations:(1) they have poor performance on multi-typo …

There is little to no data available to build natural language processing models for most
endangered languages. However, textual data in these languages often exists in formats …

A great deal of historical corpora suffer from errors introduced by the OCR (optical character
recognition) methods used in the digitization process. Correcting these errors manually is a …

Optical character recognition (OCR) is crucial for a deeper access to historical collections.
OCR needs to account for orthographic variations, typefaces, or language evolution (ie, new …

Much of the existing linguistic data in many languages of the world is locked away in non-
digitized books and documents. Optical character recognition (OCR) can be used to produce …

Chinese spelling correction (CSC) is a difficult but gratifying work that not only helps
individuals read and understand the material in their daily lives but also serves as pre …

Historical corpora are known to contain errors introduced by OCR (optical character
recognition) methods used in the digitization process, often said to be degrading the …