Tokenization scheme performance in Arabic-English MT depends on whether statistical or neural models are used and on data size, with hybrid system selection providing gains.
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Machine translation systems lose lexical richness relative to human translations and may thereby exacerbate biases such as gender bias.
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The Impact of Preprocessing on Arabic-English Statistical and Neural Machine Translation
Tokenization scheme performance in Arabic-English MT depends on whether statistical or neural models are used and on data size, with hybrid system selection providing gains.
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Lost in Translation: Loss and Decay of Linguistic Richness in Machine Translation
Machine translation systems lose lexical richness relative to human translations and may thereby exacerbate biases such as gender bias.