Lost in Transcription of Graphic Signs in Ciphers

Authors

  • Giacomo Magnifico
  • Beáta Megyesi
  • Mohamed Ali Souibgui
  • Jialuo Chen
  • Alicia Fornés

DOI:

https://doi.org/10.3384/ecp188403

Keywords:

transcription of ciphers, hand-written text recognition of symbols, graphic signs

Abstract

Hand-written Text Recognition techniques with the aim to automatically identify and transcribe hand-written text have been applied to historical sources including ciphers. In this paper, we compare the performance of two machine learning architectures, an unsupervised method based on clustering and a deep learning method with few-shot learning. Both models are tested on seen and unseen data from historical ciphers with different symbol sets consisting of various types of graphic signs. We compare the models and highlight their differences in performance, with their advantages and shortcomings.

Downloads

Published

2022-06-09