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Models/COSMIC

COSMIC

Reported on 9 benchmarks across 1 task · 2 papers · 5 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Audio9 results

  • Emotion RecognitiononEmoWoz
    Macro F1· 2021-09-10
    61.12
    best: 65.33 (CD-ERC)
    SOTA
    EmoWOZ: A Large-Scale Corpus and Labelling Scheme for Emotion Recognition in Task-Oriented Dialogue SystemsarXiv:2109.04919
  • Emotion RecognitiononEmoWoz
    Macro F1 (w/o Neutral)· 2021-09-10
    56.34
    SOTA
    EmoWOZ: A Large-Scale Corpus and Labelling Scheme for Emotion Recognition in Task-Oriented Dialogue SystemsarXiv:2109.04919
  • Emotion RecognitiononEmoryNLP
    Weighted-F1· 2020-10-06
    38.11
    best: 42.08 (CKERC)
    SOTA
    COSMIC: COmmonSense knowledge for eMotion Identification in ConversationsarXiv:2010.02795
  • Emotion RecognitiononMELD
    Weighted-F1· 2020-10-06
    65.21
    best: 69.9 (ELR-GNN)
    SOTA
    COSMIC: COmmonSense knowledge for eMotion Identification in ConversationsarXiv:2010.02795
  • Emotion RecognitiononDailyDialog
    Macro F1· 2020-10-06
    51.05
    best: 55.84 (EmoOne-RoBERTa)
    SOTA
    COSMIC: COmmonSense knowledge for eMotion Identification in ConversationsarXiv:2010.02795
  • Emotion RecognitiononEmoWoz
    Weighted F1· 2021-09-10
    85.94
    best: 88.33 (ContextBERT)
    EmoWOZ: A Large-Scale Corpus and Labelling Scheme for Emotion Recognition in Task-Oriented Dialogue SystemsarXiv:2109.04919
  • Emotion RecognitiononEmoWoz
    Weighted F1 (w/o Neutral)· 2021-09-10
    77.09
    best: 79.67 (ContextBERT)
    EmoWOZ: A Large-Scale Corpus and Labelling Scheme for Emotion Recognition in Task-Oriented Dialogue SystemsarXiv:2109.04919
  • Emotion RecognitiononDailyDialog
    Micro-F1· 2020-10-06
    58.48
    best: 64.07 (S+PAGE)
    COSMIC: COmmonSense knowledge for eMotion Identification in ConversationsarXiv:2010.02795
  • Emotion RecognitiononIEMOCAP
    Weighted-F1· 2020-10-06
    65.3
    best: 74.08 (SDT)
    COSMIC: COmmonSense knowledge for eMotion Identification in ConversationsarXiv:2010.02795