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• W41626942 abstract "In this paper, we compare the rule-based and data-drivenapproaches in the context of Spanish-to-Basque Machine Translation. The rule-based system we consider has been developed specifically for Spanish-to-Basque machine translation, and is tuned to this language pair. On the contrary, the data-driven system we use is generic, and has not been specifically designed to deal with Basque. Spanish-to-Basque Machine Translation is a challenge for data-drivenapproaches for at least two reasons. First, there is lack ofbilingual data on which a data-driven MT system can be trained. Second, Basque is a morphologically-rich agglutinative language and translating to Basque requires a huge generation of morphological information, a difficult task for a generic system not specifically tuned to Basque. We present the results of a series of experiments, obtained on two different corpora, one being “in-domain” and theother one “out-of-domain” with respect to the data-drivensystem. We show that n-gram based automatic evaluation and edit-distance-based human evaluation yield two different sets of results. According to BLEU, the data-driven system outperforms the rule-based system on the in-domain data, while according to the human evaluation, the rule-basedapproach achieves higher scores for both corpora." @default.
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• W41626942 date "2007-09-10" @default.
• W41626942 modified "2023-09-23" @default.
• W41626942 title "Comparing rule-based and data-driven approaches to Spanish-to-Basque machine translation" @default.
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