The amount of training data in statistical machine translation critically affects translation quality. In this paper, we demonstrate how to increase translation quality for one language pair by introducing parallel data from a closely related language. Specifically, we improve English→Slovak translation using a large Czech-English parallel corpus and a shallow MT system for Czech→Slovak translation. Several options are explored to identify the best possible configuration.
We also present our two contributions to available data resources, namely the English-Slovak parallel corpus and the Slovak variant of the WMT 2011 test set.
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