Deep Reinforcement Learning For Modeling Chit-Chat Dialog With Discrete Attributes
Table 2: Dialog-acts prediction accuracy for classifiers trained on validation set of different datasets.
['Corpus', 'Num Acts', 'Acc(%)']
While we aim for better classifier performance, it is important to note here that the primary objective of such dialog attribute classifiers is to tag unannotated open-domain dialog datasets. As future work, we will study how the classification errors influence response generation.