Translationese: Between Human and Machine Translation

By S. Winter. 2016

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TyDi QA: A Benchmark for Information-Seeking Question Answering in Typologically Diverse Languages (2020, background): “The result is that a corpus of so-called Translationese may be markedly different from purely native text (Lembersky et al., 2012; Volansky et al., 2013; Avner et al., 2014; Eetemadi and Toutanova, 2014; Rabinovich and Wintner, 2015; Wintner, 2016).”
MKQA: A Linguistically Diverse Benchmark for Multilingual Open Domain Question Answering (2020, unknown): “Recent investigations into cross-lingual modeling have revealed “translation artifacts” in datasets where either machine translation systems are used for data generation, or human translation tasks are not carefully curated (Artetxe et al., 2020; Wintner, 2016; Rabinovich and Wintner, 2015).”