HiGRU: Hierarchical Gated Recurrent Units for Utterance-level Emotion Recognition

@article{Jiao2019HiGRUHG,
  title={HiGRU: Hierarchical Gated Recurrent Units for Utterance-level Emotion Recognition},
  author={Wenxiang Jiao and Haiqin Yang and Irwin King and Michael R. Lyu},
  journal={ArXiv},
  year={2019},
  volume={abs/1904.04446}
}
In this paper, we address three challenges in utterance-level emotion recognition in dialogue systems: (1) the same word can deliver different emotions in different contexts; (2) some emotions are rarely seen in general dialogues; (3) long-range contextual information is hard to be effectively captured. We therefore propose a hierarchical Gated Recurrent Unit (HiGRU) framework with a lower-level GRU to model the word-level inputs and an upper-level GRU to capture the contexts of utterance-level… Expand
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