One major drawback of phrase-based
translation is that it segments an input sentence
into continuous phrases. To support
linguistically informed source discontinuity,
in this paper we construct graphs
which combine bigram and dependency
relations and propose a graph-based translation
model. The model segments an
input graph into connected subgraphs,
each of which may cover a discontinuous
phrase. We use beam search to combine
translations of each subgraph left-to-right
to produce a complete translation. Experiments
on Chinese–English and German–
English tasks show that our system is
significantly better than the phrase-based
model by up to +1.5/+0.5 BLEU scores.
By explicitly modeling the graph segmentation,
our system obtains further improvement,
especially on German–English.