First, this is because the acoustic model used in these experiments was trained on a relatively small corpus (6,000 utterances), which introduces the possibility that the acoustic model was under-trained.
the error rates for both baseline and test systems may be greater here than if a larger training corpus had been used, so the performance gain due to the introduction of referential semantics may be overstated.