Corpus ID: 3526062

EmotionLines: An Emotion Corpus of Multi-Party Conversations

@article{Chen2018EmotionLinesAE,
  title={EmotionLines: An Emotion Corpus of Multi-Party Conversations},
  author={Sheng-Yeh Chen and Chao-Chun Hsu and Chuan-Chun Kuo and Ting-Hao Huang and Lun-Wei Ku},
  journal={ArXiv},
  year={2018},
  volume={abs/1802.08379}
}
  • Sheng-Yeh Chen, Chao-Chun Hsu, +2 authors Lun-Wei Ku
  • Published in LREC 2018
  • Computer Science
  • ArXiv
  • Feeling emotion is a critical characteristic to distinguish people from machines. [...] Key Method Dialogues in EmotionLines are collected from Friends TV scripts and private Facebook messenger dialogues. Then one of seven emotions, six Ekman's basic emotions plus the neutral emotion, is labeled on each utterance by 5 Amazon MTurkers. A total of 29,245 utterances from 2,000 dialogues are labeled in EmotionLines. We also provide several strong baselines for emotion detection models on EmotionLines in this paper.Expand Abstract

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    MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

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    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 14 REFERENCES

    Towards Empathetic Human-Robot Interactions

    VIEW 2 EXCERPTS

    Zero-shot learning of intent embeddings for expansion by convolutional deep structured semantic models

    VIEW 2 EXCERPTS

    Convolutional neural networks for sentence classification

    • Y. Kim
    • arXiv preprint arXiv:1408.5882
    • 2014
    VIEW 1 EXCERPT

    Towards Text-based Emotion Detection A Survey and Possible Improvements

    VIEW 1 EXCERPT

    IEMOCAP: interactive emotional dyadic motion capture database

    VIEW 1 EXCERPT