Making large-scale support vector machine learning practical
Advances in kernel methods
A systematic comparison of various statistical alignment models
Computational Linguistics
BLEU: a method for automatic evaluation of machine translation
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Feature-rich statistical translation of noun phrases
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Design of a multi-lingual, parallel-processing statistical parsing engine
HLT '02 Proceedings of the second international conference on Human Language Technology Research
Automatic tagging of Arabic text: from raw text to base phrase chunks
HLT-NAACL-Short '04 Proceedings of HLT-NAACL 2004: Short Papers
N-gram posterior probabilities for statistical machine translation
StatMT '06 Proceedings of the Workshop on Statistical Machine Translation
Performance confidence estimation for automatic summarization
EACL '09 Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics
Active learning for statistical phrase-based machine translation
NAACL '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Example-based paraphrasing for improved phrase-based statistical machine translation
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
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This paper studies the impact that difficult-to-translate source-language phrases might have on the machine translation process. We formulate the notion of difficulty as a measurable quantity; we show that a classifier can be trained to predict whether a phrase might be difficult to translate; and we develop a framework that makes use of the classifier and external resources (such as human translators) to improve the overall translation quality. Through experimental work, we verify that by isolating difficult-to-translate phrases and processing them as special cases, their negative impact on the translation of the rest of the sentences can be reduced.