4 papers
The Character Error Vector: Decomposable errors for page-level OCR evaluation
Jonathan Bourne, Mwiza Simbeye, Joseph Nockels
The Character Error Rate (CER) is a key metric for evaluating the quality of Optical Character Recognition (OCR). However, this metric assumes that text has been perfectly parsed,…
The COTe score: A decomposable framework for evaluating Document Layout Analysis models
Jonathan Bourne, Mwiza Simbeye, Ishtar Govia
Document Layout analysis (DLA), is the process by which a page is parsed into meaningful elements, often using machine learning models. Typically, the quality of a model is judged…
Reading the unreadable: Creating a dataset of 19th century English newspapers using image-to-text language models
Jonathan Bourne
Oscar Wilde said, "The difference between literature and journalism is that journalism is unreadable, and literature is not read." Unfortunately, The digitally archived journalism…
CLOCR-C: Context Leveraging OCR Correction with Pre-trained Language Models
Jonathan Bourne
The digitisation of historical print media archives is crucial for increasing accessibility to contemporary records. However, the process of Optical Character Recognition (OCR) use…