In fact, the best model exhaustively generates all candidate strings, where the first part is a prefix of C 1 and the second part is a suffix of C 2 and scores them to pick the best candidate while using a backward model learned to generate the components given the blend.
we propose a more straightforward model that explicitly incorporates inherent linguistic constraints entirely obviating the need for decoding using exhaustive candidate generation yet yielding competitive performance.