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The ADAPT bilingual document alignment system at WMT16
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In: Lohar, Pintu, Afli, Haithem orcid:0000-0002-7449-4707 , Liu, Chao-Hong orcid:0000-0002-1235-6026 and Way, Andy orcid:0000-0001-5736-5930 (2016) The ADAPT bilingual document alignment system at WMT16. In: First Conference on Machine Translation (WMT16), 11-12 Aug 2016, Berlin, Germany. (2016)
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FaDA: fast document aligner using word embedding
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In: Lohar, Pintu, Ganguly, Debasis orcid:0000-0003-0050-7138 , Afli, Haithem orcid:0000-0002-7449-4707 , Way, Andy orcid:0000-0001-5736-5930 and Jones, Gareth J.F. orcid:0000-0003-2923-8365 (2016) FaDA: fast document aligner using word embedding. Prague Bulletin of Mathematical Linguistics (106). pp. 169-179. ISSN 1804-0462 (2016)
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Using SMT for OCR error correction of historical texts
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In: Afli, Haithem orcid:0000-0002-7449-4707 , Qui, Zhengwei, Way, Andy orcid:0000-0001-5736-5930 and Sheridan, Páraic (2016) Using SMT for OCR error correction of historical texts. In: Tenth International Conference on Language Resources and Evaluation (LREC 2016), 23-28 May 2016, Portorož, Slovenia. ISBN 978-2-9517408-9-1 (2016)
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Integrating optical character recognition and machine translation of historical documents
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In: Afli, Haithem orcid:0000-0002-7449-4707 and Way, Andy orcid:0000-0001-5736-5930 (2016) Integrating optical character recognition and machine translation of historical documents. In: COLING, the 26th International Conference on Computational Linguistics, 13-16 Dec 2016, Osaka, Japan. (2016)
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Abstract:
Machine Translation (MT) plays a critical role in expanding capacity in the translation industry. However, many valuable documents, including digital documents, are encoded in non-accessible formats for machine processing (e.g., Historical or Legal documents). Such documents must be passed through a process of Optical Character Recognition (OCR) to render the text suitable for MT. No matter how good the OCR is, this process introduces recognition errors, which often renders MT ineffective. In this paper, we propose a new OCR to MT framework based on adding a new OCR error correction module to enhance the overall quality of translation. Experimentation shows that our new system correction based on the combination of Language Modeling and Translation methods outperforms the baseline system by nearly 30% relative improvement.
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Keyword:
Machine translating
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URL: http://doras.dcu.ie/23243/
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From Arabic user-generated content to machine translation: integrating automatic error correction
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In: Afli, Haithem orcid:0000-0002-7449-4707 , Aransa, Walid, Lohar, Pintu and Way, Andy orcid:0000-0001-5736-5930 (2016) From Arabic user-generated content to machine translation: integrating automatic error correction. In: 17th International Conference on Intelligent Text Processing and Computational Linguistics, 3–9 Apr 2016, Konya, Turkey. (2016)
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Dublin City University and partners’ participation in the INS and VTT tracks at TRECVid 2016
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In: Marsden, Mark, Mohedano, Eva, McGuinness, Kevin orcid:0000-0003-1336-6477 , Calafell, Andrea, Giró-i-Nieto, Xavier orcid:0000-0002-9935-5332 , O'Connor, Noel E. orcid:0000-0002-4033-9135 , Zhou, Jiang orcid:0000-0002-3067-8512 , Azevedo, Lucas, Daudert, Tobias, Davis, Brian, Hurlimann, Manuela, Afli, Haithem orcid:0000-0002-7449-4707 , Du, Jinhua, Ganguly, Debasis orcid:0000-0003-0050-7138 , Li, Wei B. orcid:0000-0001-7347-3501 , Way, Andy orcid:0000-0001-5736-5930 and Smeaton, Alan F. orcid:0000-0003-1028-8389 (2016) Dublin City University and partners’ participation in the INS and VTT tracks at TRECVid 2016. In: TRECVid Conference, 14-16 Nov 2016, Gaithersburg, Md., USA. (2016)
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Dublin City University and Partners' participation in the INS and VTT Tracks at TRECVid 2016
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FaDA: Fast Document Aligner using Word Embedding
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In: Prague Bulletin of Mathematical Linguistics , Vol 106, Iss 1, Pp 169-179 (2016) (2016)
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