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• W2168103496 abstract "We illustrate and explain problems of n-grams-based machine translation (MT) metrics (e.g. BLEU) when applied to morphologically rich languages such as Czech. A novel metric SemPOS based on the deep-syntactic representation of the sentence tackles the issue and retains the performance for translation to English as well." @default.
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• W2168103496 date "2010-07-11" @default.
• W2168103496 modified "2023-10-17" @default.
• W2168103496 title "Tackling Sparse Data Issue in Machine Translation Evaluation" @default.
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