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2010

Tackling Sparse Data Issue in Machine Translation Evaluation

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Tackling Sparse Data Issue in Machine Translation Evaluation
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.
Ondrej Bojar, Kamil Kos, David Marecek
Added 10 Feb 2011
Updated 10 Feb 2011
Type Journal
Year 2010
Where ACL
Authors Ondrej Bojar, Kamil Kos, David Marecek
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