Abstract
We hypothesise and evaluate a language model-based approach for scoring the quality of OCR transcriptions in the British Library Newspapers (BLN) corpus parts 1 and 2, to identify the best quality OCR for use in further natural language processing tasks, with a wider view to link individual newspaper reports of crime in nineteenth-century London to the Digital Panopticon—a structured repository of criminal lives. We mitigate the absence of gold standard transcriptions of the BLN corpus by utilising a corpus of genre-adjacent texts that capture the common and legal parlance of nineteenth-century London—the Proceedings of the Old Bailey Online—with a view to rank the BLN transcriptions by their OCR quality.- Anthology ID:
- 2022.lrec-1.630
- Volume:
- Proceedings of the Thirteenth Language Resources and Evaluation Conference
- Month:
- June
- Year:
- 2022
- Address:
- Marseille, France
- Editors:
- Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Jan Odijk, Stelios Piperidis
- Venue:
- LREC
- SIG:
- Publisher:
- European Language Resources Association
- Note:
- Pages:
- 5859–5864
- Language:
- URL:
- https://aclanthology.org/2022.lrec-1.630
- DOI:
- Cite (ACL):
- Callum Booth, Robert Shoemaker, and Robert Gaizauskas. 2022. A Language Modelling Approach to Quality Assessment of OCR’ed Historical Text. In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pages 5859–5864, Marseille, France. European Language Resources Association.
- Cite (Informal):
- A Language Modelling Approach to Quality Assessment of OCR’ed Historical Text (Booth et al., LREC 2022)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/2022.lrec-1.630.pdf