Publication: Supervised OCR Error Detection and Correction Using Statistical and Neural Machine Translation Methods
Supervised OCR Error Detection and Correction Using Statistical and Neural Machine Translation Methods
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Amrhein, C., & Clematide, S. (2018). Supervised OCR Error Detection and Correction Using Statistical and Neural Machine Translation Methods. Journal for Language Technology and Computational Linguistics, 33(1), 49–76. https://jlcl.org/content/2-allissues/1-heft1-2018/jlcl_2018-1_3.pdf
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For indexing the content of digitized historical texts, optical character recognition (OCR) errors are a hampering problem. To explore the effectivity of new strategies for OCR post-correction, this article focuses on methods of character-based machine translation, specifically neural machine translation and statistical machine translation. Using the ICDAR 2017 data set on OCR post-correction for English and French, we experiment with different strategies for error detection and error correction. We analyze how OCR post-correction wit
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Amrhein, C., & Clematide, S. (2018). Supervised OCR Error Detection and Correction Using Statistical and Neural Machine Translation Methods. Journal for Language Technology and Computational Linguistics, 33(1), 49–76. https://jlcl.org/content/2-allissues/1-heft1-2018/jlcl_2018-1_3.pdf
