Spelling Normalization of Historical Documents by Using a Machine Translation Approach

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Title: Spelling Normalization of Historical Documents by Using a Machine Translation Approach
Authors: Domingo, Miguel | Casacuberta, Francisco
Keywords: Machine Translation
Knowledge Area: Lenguajes y Sistemas Informáticos
Issue Date: 2018
Publisher: European Association for Machine Translation
Citation: Domingo, Miguel; Casacuberta, Francisco. “Spelling Normalization of Historical Documents by Using a Machine Translation Approach”. In: Pérez-Ortiz, Juan Antonio, et al. (Eds.). Proceedings of the 21st Annual Conference of the European Association for Machine Translation: 28-30 May 2018, Universitat d'Alacant, Alacant, Spain, pp. 129-137
Abstract: The lack of a spelling convention in historical documents makes their orthography to change depending on the author and the time period in which each document was written.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represents a problem for the preservation of the cultural heritage, which strives to create a digital text version of a historical document.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.
Sponsor: The research leading to these results has received funding from the Ministerio de Economía y Competitividad (MINECO) under project CoMUN-HaT (grant agreement TIN2015-70924-C2-1-R), and Generalitat Valenciana (grant agreement PROMETEO/2018/004).
URI: http://hdl.handle.net/10045/76035
ISBN: 978-84-09-01901-4
Language: eng
Type: info:eu-repo/semantics/conferenceObject
Rights: © 2018 The authors. This article is licensed under a Creative Commons 3.0 licence, no derivative works, attribution, CC-BY-ND.
Peer Review: si
Publisher version: http://eamt2018.dlsi.ua.es/proceedings-eamt2018.pdf
Appears in Collections:Congresos - EAMT2018 - Proceedings

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