Unlike in most applications of HMMs in text processing, in which the representation of a token is simply its word or lemma identity, tokens in DSHMM are also associated with a vector representation of their meaning in context according to a distributional semantic model (Section 3.1).
the emissions can be decomposed into pairs H t = (lemma(H t ), sem(H t )) and A ta = (lemma(A ta ), sem(A ta )), where lemma and sem are functions that return the lemma identity and the semantic vector respectively.