BLEU: a method for automatic evaluation of machine translation
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Minimum error rate training in statistical machine translation
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Meteor: an automatic metric for MT evaluation with high levels of correlation with human judgments
StatMT '07 Proceedings of the Second Workshop on Statistical Machine Translation
English-to-Czech factored machine translation
StatMT '07 Proceedings of the Second Workshop on Statistical Machine Translation
Further meta-evaluation of machine translation
StatMT '08 Proceedings of the Third Workshop on Statistical Machine Translation
StatMT '09 Proceedings of the Fourth Workshop on Statistical Machine Translation
WMT '10 Proceedings of the Joint Fifth Workshop on Statistical Machine Translation and MetricsMATR
Approximating a deep-syntactic metric for MT evaluation and tuning
WMT '11 Proceedings of the Sixth Workshop on Statistical Machine Translation
Two-step translation with grammatical post-processing
WMT '11 Proceedings of the Sixth Workshop on Statistical Machine Translation
Modeling inflection and word-formation in SMT
EACL '12 Proceedings of the 13th Conference of the European Chapter of the Association for Computational Linguistics
SSST-6 '12 Proceedings of the Sixth Workshop on Syntax, Semantics and Structure in Statistical Translation
Probes in a taxonomy of factored phrase-based models
WMT '12 Proceedings of the Seventh Workshop on Statistical Machine Translation
Selecting data for English-to-Czech machine translation
WMT '12 Proceedings of the Seventh Workshop on Statistical Machine Translation
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The paper describes our experiments with English-Czech machine translation for WMT10 in 2010. Focusing primarily on the translation to Czech, our additions to the standard Moses phrase-based MT pipeline include two-step translation to overcome target-side data sparseness and optimization towards SemPOS, a metric better suited for evaluating Czech. Unfortunately, none of the approaches bring a significant improvement over our standard setup.