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Aliya Turganbayeva, Diana Rakhimova, Vladislav Karyukin, Aidana Karibayeva and Asem Turarbek
The problems of machine translation are constantly arising. While the most advanced translation platforms, such as Google and Yandex, allow for high-quality translations of languages with simple grammatical structures, more morphologically rich languages...
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Shailza Jolly, Pepa Atanasova and Isabelle Augenstein
Fact-checking systems have become important tools to verify fake and misguiding news. These systems become more trustworthy when human-readable explanations accompany the veracity labels. However, manual collection of these explanations is expensive and ...
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Hannah Béchara, Constantin Orasan, Carla Parra Escartín, Marcos Zampieri and William Lowe
As Machine Translation (MT) becomes increasingly ubiquitous, so does its use in professional translation workflows. However, its proliferation in the translation industry has brought about new challenges in the field of Post-Editing (PE). We are now face...
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Liliya Eugenevna Ziganshina, Ekaterina V. Yudina, Azat I. Gabdrakhmanov and Juliane Ried
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Lieve Macken, Daniel Prou and Arda Tezcan
This paper studies the impact of machine translation (MT) on the translation workflow at the Directorate-General for Translation (DGT), focusing on two language pairs and two MT paradigms: English-into-French with statistical MT and English-into-Finnish ...
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Jennifer Vardaro, Moritz Schaeffer and Silvia Hansen-Schirra
This study aims to analyse how translation experts from the German department of the European Commission?s Directorate-General for Translation (DGT) identify and correct different error categories in neural machine translated texts (NMT) and their post-e...
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Hanna Martikainen
The recent arrival on the market of high-performing neural MT engines will likely lead to a profound transformation of the translation profession. The purpose of this study is to explore how this paradigm change impacts the post-editing process, with a f...
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