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A Multilingual Evaluation of Three Spelling Normalization Methods for Historical Text.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Languages, Department of Linguistics and Philology. (Computational Linguistics)
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Languages, Department of Linguistics and Philology. (Computational linguistics)ORCID iD: 0000-0002-4838-6518
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Languages, Department of Linguistics and Philology. (Computational linguistics)
2014 (English)In: Workshop on Language Technology for Cultural Heritage, Social Sciences and Humanities, LaTeCH 2014, 2014Conference paper, Published paper (Refereed)
Abstract [en]

We present a multilingual evaluation of approaches for spelling normalisation of historical text based on data from five languages: English, German, Hungarian, Icelandic, and Swedish. Three different normalisation methods are evaluated: a simplistic filtering model, a Levenshteinbased approach, and a character-based statistical machine translation approach. The evaluation shows that the machine translation approach often gives the best results, but also that all approaches improve over the baseline and that no single method works best for all languages.

Place, publisher, year, edition, pages
2014.
National Category
Language Technology (Computational Linguistics)
Research subject
Computational Linguistics
Identifiers
URN: urn:nbn:se:uu:diva-264781OAI: oai:DiVA.org:uu-264781DiVA: diva2:861521
Conference
European Association for Computational Linguistics, EACL 2014.
Available from: 2015-10-17 Created: 2015-10-17 Last updated: 2017-01-25

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Megyesi, Beata

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  • apa
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Output format
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  • asciidoc
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