A Generative Attentional Neural Network Model for Dialogue Act Classification
Quan Hung Tran, Gholamreza Haffari, Ingrid Zukerman · 2017
We propose a novel generative neural network architecture for Dialogue Act classification.Building upon the Recurrent Neural Network framework, our model incorporates a new attentional technique and a label-to-label connection for sequence learning, akin to Hidden Markov Models.Our experiments show that both of these innovations enable our model to outperform strong baselines for dialogue-act classification on the MapTask and Switchboard corpora.In addition, we analyse empirically the effectiveness of each of these innovations.