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Improving machine translation of educational content via crowdsourcing
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In: Behnke, Maximiliana, Miceli Barone, Antonio Valerio, Sennrich, Rico, Sosoni, Vilelmini, Naskos, Thanasis, Takoulidou, Eirini, Stasimioti, Maria, Menno, van Zaanen, Castilho, Sheila orcid:0000-0002-8416-6555 , Gaspari, Federico orcid:0000-0003-3808-8418 , Georgakopoulou, Panayota orcid:0000-0001-9780-1813 , Kordoni, Valia, Egg, Markus and Kermanidis, Katia Lida orcid:0000-0002-3270-5078 (2018) Improving machine translation of educational content via crowdsourcing. In: LREC 2018 - 11th International Conference on Language Resources and Evaluation, Miyazaki, Japan. ISBN 979-10-95546-19-1 (2018)
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Translation crowdsourcing: creating a multilingual corpus of online educational content
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In: Sosoni, Vilelmini orcid:0000-0002-9583-4651 , Kermanidis, Katia Lida orcid:0000-0002-3270-5078 , Stasimioti, Maria orcid:0000-0002-3270-5078 , Naskos, Thanasis, Takoulidou, Eirini, van Zaanen, Menno, Castilho, Sheila orcid:0000-0002-8416-6555 , Georgakopoulou, Panayota orcid:0000-0001-9780-1813 , Kordoni, Valia and Egg, Markus (2018) Translation crowdsourcing: creating a multilingual corpus of online educational content. In: 11th International Conference on Language Resources and Evaluation, 7-12 May 2018, Miyazaki, Japan. ISBN 979-10-95546-00-9 (2018)
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A comparative quality evaluation of PBSMT and NMT using professional translators
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Castilho, Sheila; Moorkens, Joss; Gaspari, Federico; Sennrich, Rico; Sosoni, Vilelmini; Georgakopoulou, Panayota; Lohar, Pintu; Way, Andy; Miceli Barone, Antonio Valerio; Gialama, Maria
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In: Castilho, Sheila orcid:0000-0002-8416-6555 , Moorkens, Joss, Gaspari, Federico, Sennrich, Rico, Sosoni, Vilelmini, Georgakopoulou, Panayota, Lohar, Pintu, Way, Andy orcid:0000-0001-5736-5930 , Miceli Barone, Antonio Valerio and Gialama, Maria (2017) A comparative quality evaluation of PBSMT and NMT using professional translators. In: MT Summit XVI, 18-22 Sept 2017, Nagoya, Japan. (2017)
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Abstract:
This paper reports on a comparative evaluation of phrase-based statistical machine translation (PBSMT) and neural machine translation (NMT) for four language pairs, using the PET interface to compare educational domain output from both systems using a variety of metrics, including automatic evaluation as well as human rankings of adequacy and fluency, error-type markup, and post-editing (technical and temporal) effort, performed by professional translators. Our results show a preference for NMT in side-by-side ranking for all language pairs, texts, and segment lengths. In addition, perceived fluency is improved and annotated errors are fewer in the NMT output. Results are mixed for perceived adequacy and for errors of omission, addition, and mistranslation. Despite far fewer segments requiring post-editing, document-level post-editing performance was not found to have significantly improved in NMT compared to PBSMT. This evaluation was conducted as part of the TraMOOC project, which aims to create a replicable semi-automated methodology for high-quality machine translation of educational data.
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Keyword:
Machine translating
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URL: http://doras.dcu.ie/23083/
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Enhancing access to online education: quality machine translation of MOOC content
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In: Kordoni, Valia, van den Bosch, Antal orcid:0000-0003-2493-656X , Kermanidis, Katia Lida orcid:0000-0002-3270-5078 , Sosoni, Vilelmini orcid:0000-0002-9583-4651 , Cholakov, Kostadin, Hendrickx, Iris, Huck, Matthias and Way, Andy orcid:0000-0001-5736-5930 (2016) Enhancing access to online education: quality machine translation of MOOC content. 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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