Given that different Machine Translation (MT) evaluation metrics are useful for capturing different aspects of translation quality, it becomes desirable to create MT systems tuned with respect to each individual criterion.
the maximum likelihood techniques that underlie the decision processes of most current MT systems do not take into account these application specific goals.