mlsanityData to 14 Oct 2026

A tailored Handwritten-Text-Recognition System for Medieval Latin

arXiv 2308.09368 ↗First posted 18 Aug 2023cs.CV cs.CL cs.CYcited by 4

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Abstract (arXiv)

The Bavarian Academy of Sciences and Humanities aims to digitize its Medieval Latin Dictionary. This dictionary entails record cards referring to lemmas in medieval Latin, a low-resource language. A crucial step of the digitization process is the Handwritten Text Recognition (HTR) of the handwritten lemmas found on these record cards. In our work, we introduce an end-to-end pipeline, tailored to the medieval Latin dictionary, for locating, extracting, and transcribing the lemmas. We employ two state-of-the-art (SOTA) image segmentation models to prepare the initial data set for the HTR task. Furthermore, we experiment with different transformer-based models and conduct a set of experiments to explore the capabilities of different combinations of vision encoders with a GPT-2 decoder. Additionally, we also apply extensive data augmentation resulting in a highly competitive model. The best-performing setup achieved a Character Error Rate (CER) of 0.015, which is even superior to the commercial Google Cloud Vision model, and shows more stable performance.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 15 of its 30 references that are in the map. First posted on arXiv 18 Aug 2023.

Builds on

15 of 30 references.

References · 15

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3 more
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Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 2; 2026: 2.

4 papers.

  1. 2025Digitizing Nepal's Written Heritage: A Comprehensive HTR Pipeline for Old Nepali Manuscriptscited by 2
  2. 2025ParsiPy: NLP Toolkit for Historical Persian Texts in Pythoncited by 1
  3. 2026Automated sign detection across the Electronic Babylonian Library: A large-scale dataset and end-to-end cuneiform OCR pipelinecited by 1
  4. 2026From Traditional Taggers to LLMs: A Comparative Study of POS Tagging for Medieval Romance Languagescited by 0