'I'm here to fight for ground truth': HTR-United, a solution towards a common for HTR training data
| Autor: | Chagué, Alix, Clérice, Thibault |
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| Přispěvatelé: | Scholger, Walter, Vogeler, Georg, Tasovac, Toma, Baillot, Anne, Raunig, Elisabeth, Scholger, Martina, Steiner, Elisabeth, Centre for Information Modelling, Helling, Patrick, École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL), Université de Montréal (UdeM), Automatic Language Modelling and ANAlysis & Computational Humanities (ALMAnaCH), Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Centre Jean Mabillon (CJM), École nationale des chartes (ENC), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Alliance of Digital Humanities Organizations, University of Graz |
| Jazyk: | angličtina |
| Rok vydání: | 2023 |
| Předmět: |
Paper
and methods History Handwritten Text Recognition datasets commons optical character recognition and handwriting recognition Training datasets Computer science HTR-United [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI] [SHS]Humanities and Social Sciences data publishing projects metadata standards Short Presentation Literary studies systems HTR Philology artificial intelligence and machine learning ground truth FAIR Data principles |
| Zdroj: | Digital Humanities 2023: Collaboration as Opportunity Digital Humanities 2023: Collaboration as Opportunity, Alliance of Digital Humanities Organizations; University of Graz, Jul 2023, Graz, Austria |
| DOI: | 10.5281/zenodo.8107760 |
| Popis: | The improvement of the automatic transcription of manuscripts relies on an easier access to training data of good quality (ground truth). HTR-United offers a solution to find and document such datasets, potentially creating a common. We present the set-up of this ecosystem and its main outcomes. |
| Databáze: | OpenAIRE |
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