@inproceedings{alswaidan-menai-2019-ksu,
    title = "{KSU} at {S}em{E}val-2019 Task 3: Hybrid Features for Emotion Recognition in Textual Conversation",
    author = "Alswaidan, Nourah  and
      Menai, Mohamed El Bachir",
    editor = "May, Jonathan  and
      Shutova, Ekaterina  and
      Herbelot, Aurelie  and
      Zhu, Xiaodan  and
      Apidianaki, Marianna  and
      Mohammad, Saif M.",
    booktitle = "Proceedings of the 13th International Workshop on Semantic Evaluation",
    month = jun,
    year = "2019",
    address = "Minneapolis, Minnesota, USA",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/S19-2041/",
    doi = "10.18653/v1/S19-2041",
    pages = "247--250",
    abstract = "We proposed a model to address emotion recognition in textual conversation based on using automatically extracted features and human engineered features. The proposed model utilizes a fast gated-recurrent-unit backed by CuDNN, and a convolutional neural network to automatically extract features. The human engineered features take the frequency-inverse document frequency of semantic meaning and mood tags extracted from SinticNet."
}