Hybrid Code Networks using a convolutional neural network as an input\n layer achieves higher turn accuracy

The dialogue management is a task of conversational artificial intelligence.\nThe goal of the dialogue manager is to select the appropriate response to the\nconversational partner conditioned by the input message and recent dialogue\nstate. Hybrid Code Networks is one of the models of dialogue managers, which\nuses an average of word embeddings and bag-of-words as input features. We\nperform experiments on Dialogue bAbI Task 6 and Alquist Conversational Dataset.\nThe experiments show that the convolutional neural network used as an input\nlayer of the Hybrid Code Network improves the model's turn accuracy.\n