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While there have been significant advances in detecting emotions from speechand image recognition, emotion detection on text is still under-explored andremained as an active research field. This paper introduces a corpus fortext-based emotion detection on multiparty dialogue as well as deep neuralmodels that outperform the existing approaches for document classification. Wefirst present a new corpus that provides annotation of seven emotions onconsecutive utterances in dialogues extracted from the show, Friends. We thensuggest four types of sequence-based convolutional neural network models withattention that leverage the sequence information encapsulated in dialogue. Ourbest model shows the accuracies of 37.9% and 54% for fine- and coarse-grainedemotions, respectively. Given the difficulty of this task, this is promising.

Emotion Detection on TV Show Transcripts with Sequence-based Convolutional Neural Networks