18. The system of claim 17 , wherein calculating the first aggregate error surface and the optimal model parameter for each feature function further comprises: for each feature function in the plurality of feature functions: for each source sentence in the plurality of source sentences: calculating a minimum cost surface as a function of feature function model parameter; calculating a source sentence error surface using the minimum cost surface; merging the source sentence error surfaces for each source sentence into the first aggregate error surface for the feature function; and identifying the optimal model parameter for the feature function that minimizes the first aggregate error surface for the feature function.
19. The system of claim 18 , wherein the minimum cost surface is calculated according to: f ⁡ ( f ; λ m ) = min e ∈ C ⁢ { K ⁡ ( e , f ) + λ m ⁢ h m ⁡ ( e , f ) } , where f(f;λ m )represents the minimum cost surface for a source sentence f and an optimal model parameter λ m ,C represents a group of candidate translations e, K represents a weighted feature function excluding a feature m that is being optimized, and h m (e,f) represents a slope of a line corresponding to a candidate translation e.