Paper: Triplet Lexicon Models for Statistical Machine Translation

ACL ID D08-1039
Title Triplet Lexicon Models for Statistical Machine Translation
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2008
Authors

This paper describes a lexical trigger model for statistical machine translation. We present various methods using triplets incorporating long-distance dependencies that can go be- yond the local context of phrases or n-gram based language models. We evaluate the pre- sented methods on two translation tasks in a reranking framework and compare it to the re- lated IBM model 1. We show slightly im- proved translation quality in terms of BLEU and TER and address various constraints to speed up the training based on Expectation- Maximization and to lower the overall num- ber of triplets without loss in translation per- formance.