The mathematics of statistical machine translation: parameter estimation
Computational Linguistics - Special issue on using large corpora: II
Statistical phrase-based translation
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
Automatic evaluation of machine translation quality using n-gram co-occurrence statistics
HLT '02 Proceedings of the second international conference on Human Language Technology Research
Moses: open source toolkit for statistical machine translation
ACL '07 Proceedings of the 45th Annual Meeting of the ACL on Interactive Poster and Demonstration Sessions
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We propose a method to recover missing phrases dropped in the phrase extraction algorithm. Those phrases, therefore, are not translated even though we tested the system with the training data. On the other hand, in nativeto-foreign, or backward training, some missing phrases can be recovered. In this paper, we combined two phrase translation tables extracted by the source-to-target and target-to-source training for the sake of more complete phrase translation table. We re-estimated the lexical weights and phrase translation probabilities for each phrase pair. Additional combining weights were applied to both tables. We assessed our method on different combining weights by counting the missing phrases and calculating the BLEU scores and NIST scores. Approximately 7% of missing phrases are recovered and 1.3% of BLEU score is increased.