Translation model pruning via usage statistics for statistical machine translation

We describe a new pruning approach to remove phrase pairs from translation mod-els of statistical machine translation sys-tems. The approach applies the original translation system to a large amount of text and calculates usage statistics for the phrase pairs. Using these statistics the rele-vance of each phrase pair can be estimated. The approach is tested against a strong baseline based on previous work and shows significant improvements.