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|Title:||Source language adaptation for resource-poor machine translation|
|Source:||Wang, P.,Nakov, P.,Ng, H.T. (2012). Source language adaptation for resource-poor machine translation. EMNLP-CoNLL 2012 - 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, Proceedings of the Conference : 286-296. ScholarBank@NUS Repository.|
|Abstract:||We propose a novel, language-independent approach for improving machine translation from a resource-poor language to X by adapting a large bi-text for a related resource-rich language and X (the same target language). We assume a small bi-text for the resource-poor language to X pair, which we use to learn word-level and phrase-level paraphrases and cross-lingual morphological variants between the resource-rich and the resource-poor language; we then adapt the former to get closer to the latter. Our experiments for Indonesian/Malay-English translation show that using the large adapted resource-rich bi-text yields 6.7 BLEU points of improvement over the unadapted one and 2.6 BLEU points over the original small bi-text. Moreover, combining the small bi-text with the adapted bi-text outperforms the corresponding combinations with the unadapted bi-text by 1.5-3 BLEU points. We also demonstrate applicability to other languages and domains. © 2012 Association for Computational Linguistics.|
|Source Title:||EMNLP-CoNLL 2012 - 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, Proceedings of the Conference|
|Appears in Collections:||Staff Publications|
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