EmotionX-AR: CNN-DCNN autoencoder based Emotion Classifier

In this paper, we model emotions in Emo-tionLines dataset using a convolutionaldeconvolutional autoencoder (CNN-DCNN) framework. We show that adding a joint reconstruction loss improves performance. Quantitative evaluation with jointly trained network, augmented with linguistic features, reports best accuracies for emotion prediction; namely joy, sadness, anger, and neutral emotion in text.