Hierarchical Transformer Network for Utterance-level Emotion Recognition

18 Feb 2020QingBiao LiChunHua WuKangFeng ZhengZhe Wang

While there have been significant advances in de-tecting emotions in text, in the field of utter-ance-level emotion recognition (ULER), there are still many problems to be solved. In this paper, we address some challenges in ULER in dialog sys-tems... (read more)

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Results from the Paper


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK BENCHMARK
Emotion Recognition in Conversation EmoryNLP HiTransformer-s Macro-F1 33.04 # 1
Emotion Recognition in Conversation EmotionPush HiTransformer-s Weighted Accuracy 86.92 # 1
Unweighted Accuracy 63.03 # 1

Methods used in the Paper