For example, finitestate grammar LMs and FST-based LUMs achieve high accuracy in recognizing and understanding ingrammar utterances, whereas out-of-grammar utterances are covered by N-gram models and LUMs based on WFST and keyphrase-extractors.
it is more possible that the understanding results of MLMU will include the correct result than a case when a single understanding model is used.