Of the two state-of-the-art approaches on dialog act recognition, one uses a deep stack of Recurrent Neural Networks (RNNs) (Schmidhuber, 1990) to capture long distance relations between tokens (Khanpour et al., 2016) , while the other uses multiple parallel temporal Convolutional Neural Networks (CNNs) (Fukushima, 1980) to capture relevant functional patterns with different length <cite>(Liu et al., 2017)</cite> .