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
Triplet lexicon models for statistical machine translation
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
The RWTH system combination system for WMT 2009
StatMT '09 Proceedings of the Fourth Workshop on Statistical Machine Translation
N-gram posterior probabilities for statistical machine translation
StatMT '06 Proceedings of the Workshop on Statistical Machine Translation
Extending statistical machine translation with discriminative and trigger-based lexicon models
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 1 - Volume 1
System Combination for Machine Translation of Spoken and Written Language
IEEE Transactions on Audio, Speech, and Language Processing
WMT '10 Proceedings of the Joint Fifth Workshop on Statistical Machine Translation and MetricsMATR
The RWTH system combination system for WMT 2011
WMT '11 Proceedings of the Sixth Workshop on Statistical Machine Translation
| Hi-index | 0.00 |
RWTH participated in the System Combination task of the Fifth Workshop on Statistical Machine Translation (WMT 2010). For 7 of the 8 language pairs, we combine 5 to 13 systems into a single consensus translation, using additional n-best reranking techniques in two of these language pairs. Depending on the language pair, improvements versus the best single system are in the range of +0.5 and +1.7 on BLEU, and between -0.4 and -2.3 on TER. Novel techniques compared with RWTH's submission to WMT 2009 include the utilization of n-best reranking techniques, a consensus true casing approach, a different tuning algorithm, and the separate selection of input systems for CN construction, primary/skeleton hypotheses, HypLM, and true casing.