Our proposed decoding objective constraints (topic and semantic) are complementary to the MMI objective, which encourages diversity and relevance to the source input.
in addition to comparing against the baselines described above, we evaluated three variants of our model: (1) maximum conditional likelihood combined with semantic and topic distributional constraints with a beam size of 10 (DC-10) (2) The same configuration with MMI-bidi re-ranking using a beam size of 10 DC-MMI10 and (3) MMI-bidi reranking with a beam size of 200 (DC-MMI200).