As our task at hand deals with multi-party discourse that presumably involves temporal relations important for the learned representation, we opted for a state-of-theart self-attentive LSTM model.
we re-implemented the Structured Self-Attentive Embedding Neural Network (SSAE-NN) (Lin et al., 2017) which learns an embedding matrix representation of the input using attention weights.