  We present a DialGPT based model for generating creative dialog responses
that are conditioned based on one of the following emotions: anger, disgust,
fear, happiness, pain, sadness and surprise. Our model is capable of producing
a contextually apt response given an input sentence and a desired emotion
label. Our model is capable of expressing the desired emotion with an accuracy
of 0.6. The best performing emotions are neutral, fear and disgust. When
measuring the strength of the expressed emotion, we find that anger, fear and
disgust are expressed in the most strong fashion by the model.
