The final matching degree is computed with the accumulation of the matching vectors.
for each utterance-response pair, the model constructs a word-word similarity matrix and a sequence-sequence similarity matrix by the word embeddings and the hidden states of a recurrent neural network with gated recurrent units (GRU) (Chung et al., 2014) respectively.