Sequence-to-Sequence

In this way the network architecture is able to respond to an utterance with an response. Last year this concept was generalized to including a dialog encoder layer on top of the standard encoder. This might further enhance the architecture to keep track of previous utterances in a full dialog. The Sequence-To-Sequence architectures as every machine learning system has to undergo a certain training process. Here, the encoder and the decoder are trained together by presenting corresponding sequence pairs to them.