Log-linear models for word alignment
Yang Liu, Qun Liu, Shouxun Lin · 2005
We present a framework for word alignment based on log-linear models.All knowledge sources are treated as feature functions, which depend on the source langauge sentence, the target language sentence and possible additional variables.Log-linear models allow statistical alignment models to be easily extended by incorporating syntactic information.In this paper, we use IBM Model 3 alignment probabilities, POS correspondence, and bilingual dictionary coverage as features.Our experiments show that log-linear models significantly outperform IBM translation models.