The encoder is to map the input utterance X into a compact vector that can capture its essential topics.
we use a bi-directional GRU (Cho et al., 2014) as the utterance encoder, and each word x i is firstly represented by its semantic representation e i mapped by semantic embedding  Figure 2: The overall architecture of SC-Seq2Seq model.