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This paper describes the system submitted by ANA Team for the SemEval-2019Task 3: EmoContext. We propose a novel Hierarchical LSTMs for ContextualEmotion Detection (HRLCE) model. It classifies the emotion of an utterancegiven its conversational context. The results show that, in this task, ourHRCLE outperforms the most recent state-of-the-art text classificationframework: BERT. We combine the results generated by BERT and HRCLE to achievean overall score of 0.7709 which ranked 5th on the final leader board of thecompetition among 165 Teams.

ANA at SemEval-2019 Task 3: Contextual Emotion detection in Conversations through hierarchical LSTMs and BERT