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Spelling normalization of historical documents by using a machine translation approach

  • Autores: Miguel Domingo, Francisco Casacuberta Nolla Árbol académico
  • Localización: Proceedings of the 21st Annual Conference of the European Association for Machine Translation: 28-30 May 2018, Universitat d'Alacant, Alacant, Spain / coord. por Juan Antonio Pérez Ortiz Árbol académico, Felipe Sánchez Martínez Árbol académico, Miquel Esplà Gomis, Maja Popovic, Celia Rico Pérez Árbol académico, André Martins, Joachim Van den Bogaert, Mikel L. Forcada Zubizarreta Árbol académico, 2018, ISBN 978-84-09-01901-4, págs. 129-137
  • Idioma: inglés
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  • Resumen
    • The lack of a spelling convention in historical documents makes their orthography to change depending on the author and the time period in which each document was written. This represents a problem for the preservation of the cultural heritage, which strives to create a digital text version of a historical document. With the aim of solving this problem, we propose three approaches—based on statistical, neural and character-based machine translation— to adapt the document’s spelling to modern standards. We tested these approaches in different scenarios, obtaining very encouraging results.


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