A systematic comparison of various statistical alignment models
Computational Linguistics
The mathematics of statistical machine translation: parameter estimation
Computational Linguistics - Special issue on using large corpora: II
HMM-based word alignment in statistical translation
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 2
BLEU: a method for automatic evaluation of machine translation
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Symmetric word alignments for statistical machine translation
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
ORANGE: a method for evaluating automatic evaluation metrics for machine translation
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Lattice-based minimum error rate training for statistical machine translation
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
iROVER: improving system combination with classification
NAACL-Short '07 Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics; Companion Volume, Short Papers
The RWTH system combination system for WMT 2009
StatMT '09 Proceedings of the Fourth Workshop on Statistical Machine Translation
OpenFst: a general and efficient weighted finite-state transducer library
CIAA'07 Proceedings of the 12th international conference on Implementation and application of automata
The RWTH system combination system for WMT 2010
WMT '10 Proceedings of the Joint Fifth Workshop on Statistical Machine Translation and MetricsMATR
System Combination for Machine Translation of Spoken and Written Language
IEEE Transactions on Audio, Speech, and Language Processing
Findings of the 2011 Workshop on Statistical Machine Translation
WMT '11 Proceedings of the Sixth Workshop on Statistical Machine Translation
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RWTH participated in the System Combination task of the Sixth Workshop on Statistical Machine Translation (WMT 2011). For three language pairs, we combined 6 to 14 systems into a single consensus translation. A three-level meta-combination scheme combining six different system combination setups with three different engines was applied on the French--English language pair. Depending on the language pair, improvements versus the best single system are in the range of +1.9% and +2.5% abs. on BLEU, and between −1.8% and −2.4% abs. on TER. Novel techniques compared with RWTH's submission to WMT 2010 include two additional system combination engines, an additional word alignment technique, meta combination, and additional optimization techniques.