Artificial Intelligence in archival and historical scholarship workflow: HTS and ChatGPT

Salvatore Spina
7/5/2023
cs.DLcs.AIcs.CL

No confident code implementation found for this paper.

Abstract

This article examines the impact of Artificial Intelligence on the archival heritage digitization processes, specifically regarding the manuscripts' automatic transcription, their correction, and normalization. It highlights how digitality has compelled scholars to redefine Archive and History field and has facilitated the accessibility of analogue sources through digitization and integration into big data. The study focuses on two AI systems, namely Transkribus and ChatGPT, which enable efficient analysis and transcription of digitized sources. The article presents a test of ChatGPT, which was utilized to normalize the text of 366 letters stored in the Correspondence section of the Biscari Archive (Catania). Although the AI exhibited some limitations that resulted in inaccuracies, the corrected texts met expectations. Overall, the article concludes that digitization and AI can significantly enhance archival and historical research by allowing the analysis of vast amounts of data and the application of computational linguistic tools.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. Any repos shown below are weak matches — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

When Low CER is Not Enough: An Analysis of Hallucinations in Vision-Language OCR Systems on Historical Uruguayan Documents

84% match2026

Evaluating LLMs for Historical Document OCR: A Methodological Framework for Digital Humanities

83% match2025

ICDAR 2026 HIPE-OCRepair Competition on LLM-Assisted OCR Post-Correction for Historical Documents

82% match2026

Bengali Document Layout Analysis with Detectron2

81% match2023

Layout-Aware OCR for Black Digital Archives with Unsupervised Evaluation

80% match2025

Unlocking the Archives: Using Large Language Models to Transcribe Handwritten Historical Documents

80% match1 repo612024

Cite this paper

@article{spina2023artificial,
  title  = {Artificial Intelligence in archival and historical scholarship workflow: HTS and ChatGPT},
  author = {Salvatore Spina},
  year   = {2023},
  eprint = {2308.02044},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2308.02044v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2308.02044.svg)](https://codeofpaper.com/paper/2308.02044)

Discussion