For example, it is possible to incorporate neural features into traditional SMT models to disambiguate hypotheses (Neubig et al., 2015;Stahlberg et al., 2016).
the search space of traditional SMT is usually limited by translation rule tables, reducing the ability of these models to generate hypotheses on the same level of fluency as NMT, even after reranking.