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ACL
2007

Generating Complex Morphology for Machine Translation

9 years 1 months ago
Generating Complex Morphology for Machine Translation
We present a novel method for predicting inflected word forms for generating morphologically rich languages in machine translation. We utilize a rich set of syntactic and morphological knowledge sources from both source and target sentences in a probabilistic model, and evaluate their contribution in generating Russian and Arabic sentences. Our results show that the proposed model substantially outperforms the commonly used baseline of a trigram target language model; in particular, the use of morphological and syntactic features leads to large gains in prediction accuracy. We also show that the proposed method is effective with a relatively small amount of data.
Einat Minkov, Kristina Toutanova, Hisami Suzuki
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2007
Where ACL
Authors Einat Minkov, Kristina Toutanova, Hisami Suzuki
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